# Design, production, burn-in and tests of the hybrid circuits of the Upstream
Tracker at the LHCb detector

M. Citterio  N. Conti  F. De Benedetti,11footnotetext: Corresponding author P.
Gandini  A. Merli  N. Neri  M. Petruzzo  and E. Spadaro Norella

###### Abstract

We present a description of the design process, prototyping and production of
the hybrid circuits for the front-end electronics of the Upstream Tracker at
LHCb. The multilayer polyamide-based printed circuit boards, or hybrids, are
designed to host the front-end ASICs. The ASICs require an optimized power
delivery network from 0 to 120MHz, with a maximum of $10^{-2}$ Ohms round-trip
resistance, and 100 Ohms differential traces. Hybrids are required to have
minimal radiation length, and to withstand the harsh environmental conditions
of the data taking through intrinsic radiation hardness characteristics.

##  1 Introduction

The LHCb detector is undergoing a major upgrade phase after Run2 [1]. The
upgraded LHCb detector will increase the luminosity of the previous runs by a
factor of five. All the trackers will be replaced by more performing detectors
maintaining the general geometry of the experiment, while a new read-out
electronics systems at 40MHz will be provided for all the sub-detectors [2].
The Upstream Tracker (UT) is the new silicon tracker in LHCb positioned before
the magnet and will substitute the previous TT (Tracker Turicensis) detector.
It consists of four detection layers organized in staves that are covered with
single-sided silicon strip sensors on both sides to avoid acceptance gaps. The
two internal layers provide stereo information thanks to a stave rotation of
±5°. The UT employs four different sensor types to cope with the different
occupancy, geometry, and radiation expected in the various regions of the
detector. A dedicated 128 channels Application Specific Integrated Circuit
(ASIC) called SALT (Silicon ASIC for LHCb Tracking) reads the incoming events
from each sensor [3][8]. A total of 4192 ASICs are mounted on flexible low
mass polyamide circuits, called hybrids, providing power and digital signal
routing. The first chapter shows the hybrid circuit design while the second
one discusses their production.

##  2 Hybrid circuit design

Figure 1:  On the right the 8-ASIC SUSI hybrid, on the left the 4-ASIC VERA
version.

The hybrid circuits, shown in figure 1, are divided into two different
versions. A 4-ASIC circuit (named VERA), designed for the outermost area of
the detector, and an 8-ASIC version (named SUSI) designed for the innermost
sector of the detector where the occupancy is the highest. The hybrids are
polyamide-based, multilayer printed circuit boards with four copper layers and
a final thickness of 320um for the 4 ASIC and 440um for the 8 ASIC version.

Figure 2:  The PDN response of the SUSI Hybrid is here detailed. In red, the
ASIC on-die capacitance and bonding wires inductance resonance. In blue is the
analogue domain behaviour and in black is the digital one.

The design is optimized to deliver 500mW of power per ASIC via the low voltage
power lines and it is paired with a 500VDC sensor biasing network. A dynamic
and static Power Delivery Network (PDN) analysis has been carried out to
ensure proper power integrity for the low-voltage lines. This analysis aims to
avoid excessive voltage drop areas and to minimize the PDN’s inductive
behavior, features that could lead to a loss of reliability in the ASIC [4]. A
maximum peak below 20mOhms achieved in the dynamic PDN impedance helped to
minimize baseline oscillations in the data stream and ensured that the ASICs
would perform without glitches. To reach this goal, the usage of high-density
wire bonding on the power pads, thin stack up dielectrics between the power
planes and careful optimization of the capacitor values and their position on
the PCB was mandatory [5]. The high voltage biasing network is optimized to
deliver a low pass filtering action to the sensor with a final -20dB
attenuation at 10kHz and a maximum attenuation point before the first
resonance at around 40 MHz (ASIC’s clock frequency), as seen in figure 3. The
filtering is also optimized to keep 6 nF of bulk capacitance next to the
bonding wires biasing the sensor while maintaining a high safety factor
regarding the dielectric isolation between high and low voltage lines (3x).
Both hybrid versions were tested to the same 3x safety factor, equivalent to
1500 VDC, for the dielectric strength between the positive and negative high
voltage lines.

Figure 3:  Amplitude response of the high voltage network from the high
voltage power supply to the sensor bonding pads.The attenuation is highlighted
for significant frequencies, such as 40MHz.

A 4-Layer stack up with 18um thick metal layers is used to keep the radiation
length low enough to meet the detector requirements [1]. The final radiation
length requirement is reached by minimizing the number of capacitors, the
exposed gold-plated pads and by reducing the thickness of the plane separation
dielectrics, which in turn improve, even more, the PDN inductance and peak
impedance. The VERA and SUSI hybrid prototypes have been manufactured and
tested to assess their electrical performance. Both hybrid versions exceed the
detector noise requirements, and achieve a noise level lower than 1 LSB, as
shown in figure 4. The pulse scan plot shows a residual digital pickup at 40
MHz.

Figure 4:  Electrical tests on hybrid prototype. The figure on the left shows
the noise plot, while the figure on the right shows the pulse scan plot.

##  3 Hybrid circuit production

The hybrid circuit production involves several assembling and testing steps.
Single hybrids are embedded into a panel to reduce production costs and
assembly time. Two different designs of hybrid panels, one per hybrid version,
have been manufactured, as shown in figure 5.

Figure 5:  Hybrid panels design. The right image shows the SUSI panel design
with six single hybrids. The left image shows the VERA panel design with eight
hybrids.

Their size of 350x235mm allows embedding several copies of a single hybrid
plus a dedicated connector for testing purposes. The panels inherit the same
stack up and material identified in the hybrid design. A dedicated FR4
stiffener, temporarily used during the assembly, is glued to the back of the
flex panel to improve its mechanical strength. The glue covers only the
outermost region of the panel, as shown in figure 6 (left), to allow cutting
and removing operations during the module construction. Many voids and bridges
are added on the edge of a single circuit to improve the hybrid removal, as
shown in figure 6 (right). Several hole patterns allow aligning the different
tools used during production and further processing. The flex production and
the passive component assembly are carried out by an external company.

Figure 6:  The left image shows the flex panel in brown, the FR4 stiffener in
green and the glue pattern in pink. The right image shows the bridges and
voids around a single hybrid.

The SALT chips, manufactured by TSMC, are organized in wafers. The electrical
performance is assessed through a wafer test, which generates a list of good
and bad ASICs and their positions. Only ASICs marked as good are extracted
from the wafers and used, as shown in figure 7 (left). Chips are then glued
with a bi-component silver-loaded resin, the Loctite Ablestik 2902, which has
been chosen for its thermal and electrical conductivity. A dedicated robot
guarantees to lay down the glue in the correct positions, following a precise
glue pattern that allows to maximize the coverage and reduce glue spills. The
glue has been tested for radiation hardness.

Figure 7: The left figure shows the chip extraction operation from the wafer.
The central figure shows the gluing operation with the robot. The right figure
shows the ASICs alignment on VERA panel.

The ASICs are finally aligned and mounted onto the hybrid panels. A custom
vacuum pick-up tool is employed for VERA panels assembly with a precision of
100um. An alignment surface hosts the ASICs that are then transferred to the
hybrid panel using the vacuum pick-up tool, as shown in figure 7 (right).
Further corrections are performed manually under a microscope when needed. For
SUSI panels, the stringent alignment constraints require to execute the
assembly with an automatic pick and place machine, that positions the ASICs to
10um of precision. When the ASIC alignment is over, the curing takes place at
ambient temperature for 24 hours. The next production step consists of the
wire bonding of the chips. Panels are bonded with a Delvotec 6400 G4 automatic
machine. We use a 25um diameter (99% Al + 1% Si) wire, commonly used for this
type of application. A custom vacuum plate allows holding the panels during
the operations. Pull tests performed during the production permit to assess
the quality of the process.

After wire bonding, a burn-in test is performed. Hybrid panels are powered and
driven in a climatic chamber, where the maximum temperature is set to 60°C to
prevent any damage to the capacitors mounted next to the ASICs, which can
withstand a maximum temperature of 80°C. The burn-in test time is set
accordingly to seven days to be effective [7]. A custom hardware was designed
and manufactured to provide the nominal voltage required, a 40 MHz clock, and
the register configurations via I2C to each hybrid. The electronic system can
measure the temperature and the humidity of the environment. A dedicated
online software checks the burn-in status and logs the events for offline
analysis. A final electrical test is performed on the single hybrid thanks to
a dedicated electronic system provided by CERN, composed of a VLDB [6] board
and an acquisition card, called PCie40. The hybrid’s performance is assessed
by measuring several ASIC parameters, generating the same plots shown in
figure 4. A script analyzes the data and creates a detailed report, used for
hybrid grading. Hybrids are grouped in four categories: A (<2 bad channels), B
(<5 bad channels), C (more than 5 bad channels), and F (hybrid failure). Only
A-graded hybrids are considered suitable for stave construction. Hybrids with
no problematic channels are the first to be selected for stave construction.

As a final step, each panel undergoes an optical inspection to detect
mechanical problems. Typical issues are related to wire bonding, ASIC damage,
or wire bond pad defects not spotted previously. The panels are then packed in
3D-printed custom made PLA transport boxes and shipped to the final assembly
facility. Each pack is sealed in a sealed bag to protect the electronics from
moisture.

##  4 Conclusion

Two versions of polyamide-based hybrids for the Upstream Tracker have been
designed and tested, corresponding to different sensor types. A total number
of 1080 (4-chip) VERA and 110 (8-chip) SUSI hybrids have been successfully
manufactured, assembled, tested, and delivered for module and stave assembly.
These numbers include the production of spare hybrids for future repairs. The
production of hybrids has been completed. A first stave test in the final
configuration is foreseen by the end of November 2021 at CERN, where 25 staves
out of 68 have been already delivered. After assembling and testing the UT in
the cleanroom, the aim is to install the detector underground by the end of
February 2022.

##  5 Acknowledgment

We acknowledge support from the ERC Consolidator Grant SELDOM G.A. 771642

## References

  * [1] LHCb collaboration, _LHCb Tracker Upgrade Technical Design Report,_ CERN-LHCC-2014-001
  * [2] K. Wyllie et al., _Electronics architecture of the LHCb Upgrade_ , _LHCb-PUB-2011-011_ , https://cds.cern.ch/record/1340939/, 2011
  * [3] S. Bugiel et al., _SALT, a dedicated readout chip for high precision tracking silicon strip detectors at the LHCb Upgrade_ , _JINST_ 11 (2016) 02, C02028.
  * [4] Larry D. Smith, E. Bogatin, _“Principles of Power Integrity for PDN Design–Simplified: Robust and Cost Effective Design for High Speed Digital Products”_ , Prentice Hall Modern Semiconductor Design, ISBN-13: 978-0132735551, 2017
  * [5] S. Sandler, _“Power Integrity: Measuring, Optimizing, and Troubleshooting Power Related Parameters in Electronics Systems”_ , McGraw-Hill Education, ISBN-13: 978-0071830997, 2014
  * [6] R. Martin Lesma et al., _The Versatile Link Demo Board (VLDB)_ , _JINST_ 12 (2017) 02, C02020
  * [7] Cheng-Lin W., Chao-Ton S., _Determination of the optimal burn-in time and cost using an environmental stress approach: a case study in switch mode rectifier_ , Elsevier Reliability Engineering and System Safety, 76, 53-61, 2002, https://doi.org/10.1016/S0951-8320(01)00142-9.
  * [8] Abellan Beteta et al.,_The SALT—Readout ASIC for Silicon Strip Sensors of Upstream Tracker in the Upgraded LHCb Experiment_ , Sensors, 22, no. 1: 107, 2022, https://www.mdpi.com/1424-8220/22/1/107


# LAMOST carbon star

J. Shejeelammal1, Aruna Goswami1, Jianrong Shi2,
1Indian Institute of Astrophysics, Koramangala, Bangalore 560034, India;
<EMAIL_ADDRESS>
2 CAS Key Laboratory of Optical Astronomy, National Astronomical
Observatories, Beijing 100101, China.

( Accepted —; Received —; in original form — )

# HCT/HESP study of two carbon stars from the LAMOST survey ††thanks: Based on
data collected using HCT/HESP

J. Shejeelammal1, Aruna Goswami1, Jianrong Shi2,
1Indian Institute of Astrophysics, Koramangala, Bangalore 560034, India;
<EMAIL_ADDRESS>
2 CAS Key Laboratory of Optical Astronomy, National Astronomical
Observatories, Beijing 100101, China.

( Accepted —; Received —; in original form — )

###### Abstract

Carbon stars, enhanced in carbon and neutron-capture elements, provide wealth
of information about the nucleosynthesis history of the Galaxy. In this work,
we present the first ever detailed abundance analysis of carbon star
LAMOSTJ091608.81+230734.6 and a detailed abundance analysis of neutron-capture
elements for the object LAMOSTJ151003.74+305407.3. Updates on the abundances
of elements C, O, Mg, Ca, Cr, Mn and Ni for LAMOSTJ151003.74+305407.3 are also
presented. Our analysis is based on high resolution spectra obtained using
Hanle Echelle Spectrograph (HESP) attached to the Himalayan Chandra Telescope
(HCT), IAO, Hanle. The stellar atmospheric parameters (Teff, logg, micro-
turbulance ${\zeta}$, metallicity [Fe/H]) are found to be (4820, 1.43, 1.62,
$-$0.89) and (4500, 1.55, 1.24, $-$1.57) for these two objects respectively.
The abundance estimates of several elements, C, N, O, Na, $\alpha$-elements,
Fe-peak elements and neutron-capture elements Rb, Sr, Y, Zr, Ba, La, Ce, Pr,
Nd, Sm and Eu are presented. Our analysis shows the star
LAMOSTJ151003.74+305407.3 to be a CEMP-r/s star, and LAMOSTJ091608.81+230734.6
a CH giant. We have examined if the i-process model yields ([X/Fe]) of heavy
elements could explain the observed abundances of the CEMP-r/s star based on a
parametric model based analysis. The negative values obtained for the neutron
density dependent [Rb/Zr] ratio confirm former low-mass AGB companions for
both the stars. Kinematic analysis shows that LAMOSTJ151003.74+305407.3
belongs to the Galactic halo population and LAMOSTJ091608.81+230734.6 to the
disc population.

###### keywords:

stars:individual - stars: Carbon - stars: Abundances - stars: nucleosynthesis

††pagerange: LABEL:firstpage–LABEL:lastpage††pubyear: 2014

##  1 Introduction

Allowing to measure carbon and neutron-capture elements, the atmospheres of
the less-evolved low-mass stars form a unique treasure trove of information
for the astrophysicists seeking the chemical evolution history of the Galaxy.
Thus, studies on the metal-poor stars such as CH stars (Keenan 1942) with
their more metal-poor counterparts, Carbon Enhanced Metal-Poor (CEMP) stars
offer the best means to constrain the neutron-capture nucleosynthesis
processes, especially the nucleosythesis occurring in the Asymptotic Giant
Branch (AGB) stars. The spectra of these peculiar stars show strong CH and C2
molecular bands and features due to enhanced neutron-capture elements compared
to the normal stars. They are characterized by C/O$>$ 1.

The CEMP stars are more metal-poor ([Fe/H]$<$$-$1) than the classical CH stars
(Lucatello et al. 2005, Aoki et al. 2007, Abate et al 2016, Hansen et al.
2016a, c) with [C/Fe]$>$1 (Beers & Christlieb 2005, Abate et al. 2016). They
were first identified among the Very Metal-Poor stars discovered in the
extensive spectroscopic survey to identify a large sample of most metal-poor
stars, HK survey (Beers et al. 1985, 1992, 2007 Beers 1999), and later in a
number of successive surveys like Hamburg/ESO Survey (HES; Christlieb et al.
2001a, 2001b, Christlieb 2003), Sloan Digital Sky Survey (SDSS; York et al.
2000), Sloan Extension for Galactic Understanding and Exploration (SEGUE;
Yanny et al. 2009) etc. A number of other large sky survey programs in the
past were also dedicated to identify the Galactic carbon stars, for instance,
the First Byurakan Spectral Sky Survey (Gigoyan et al. 1998), the Automatic
Plate Measuring survey (Totten & Irwin 1998, Ibata et al. 2001), infrared
objective-prism surveys (Alksnis et al. 2001), Large Sky Area Multi-Object
Fiber Spectroscopic Telescope (LAMOST) pilot survey (Cui et al. 2012, Deng et
al. 2012, Zhao et al. 2012).

Beers & Christlieb (2005) put forward the first classification scheme for CEMP
stars and classified them into different sub-classes, CEMP-s, CEMP-r, CEMP-r/s
and CEMP-no depending on the level of enrichment of neutron-capture elements
Ba and Eu. A slight deviation from the original classification schemes have
been adopted by several authors (Aoki et al. 2007, Abate et al. 2016, Frebel
2018, Hansen et al. 2019). High-resolution spectroscopic analyses have shown
that, at present, about 80% of the CEMP stars are CEMP-s stars (Aoki et al.
2007) and about half of the CEMP-s stars are CEMP-r/s stars (Sneden et al.
2008, Käppeler et al. 2011, Bisterzo et al. 2011).

CH stars and CEMP-s/(r/s) stars belong to the main-sequence or giant phase of
stellar evolution. Hence, the observed over abundances of the carbon and
neutron-capture elements are attributed to an extrinsic origin. In the case of
CH and CEMP-s stars, enriched in s-process elements, the most accepted
scenario involves binary mass-transfer from an AGB companion. There exist a
number of proposed scenarios for the simultaneous r- and s- process enrichment
observed in CEMP-r/s stars (Jonsell et al. 2006 and references therein);
however, none of them could successfully reproduce the observed frequency and
high [hs/ls] ratio of CEMP-r/s stars (Abate et al. 2016). An intermediate
neutron-capture process (i-process) that operates with neutron densities in
between s- and r-process neutron densities had been invoked to explain the
observed abundances of CEMP-r/s stars. Hampel et al. (2016, 2019) could
successfully reproduce the observed abundance trend of several CEMP-r/s stars
considering this production scenario. The i-process was originally proposed by
Cowan & Rose (1977). Among the proposed scenarios for the nucleosynthetic
sites of the i-process are, massive (5 - 10 M⊙) super-AGB stars (Doherty et
al. 2015; Jones et al. 2016), evolved low-mass stars (Herwig et al. 2011;
Hampel et al. 2019), low-mass, low-metallicity ([Fe/H] ${\leq}$ $-$3) stars
(Campbell & Lattanzio 2008; Campbell et al. 2010; Cruz et al. 2013; Cristallo
et al. 2016), and Rapidly Accreting White Dwarfs (Herwig et al. 2014;
Denissenkov et al. 2017). Clarkson et al. (2018) and Banerjee et al. (2018)
have suggested that massive (M ${\geq}$ 20 M⊙), metal-poor stars could also
play a role in the production of i-process elements. In spite of several
efforts, large uncertainties still exist regarding the i-process
nucleosynthesis and the possible astrophysical sites of its occurrence.(Frebel
2018; Koch et al. 2019).

It has been found from the long-term radial velocity monitoring studies that
vast majority of CH stars (McClure et al. 1980, McClure 1983, 1984, McClure &
Woodsworth 1990, Jorissen et al. 2016) and CEMP-s/rs stars (Lucatello et al.
2005, Starkenburg et al. 2014, Jorissen et al. 2016, Hansen et al. 2016c) are
most likely binaries, thus strongly favoring the binary mass transfer
scenario.

It has been identified that the fraction of CEMP stars in the Galactic halo
increases with decreasing metallicity; $\sim$20% for [Fe/H]$<$$-$2 (Norris et
al. 1997, Rossi et al. 1999, 2005, Christlieb 2003, Cohen et al. 2005,
Marsteller et al. 2005, Frebel et al. 2006, Lucatello et al. 2006, Carollo et
al. 2012, Lee et al. 2013), $\sim$40% for [Fe/H]$<$$-$3 (Aoki et al. 2013, Lee
et al. 2013, Yong et al. 2013b), $\sim$75% for [Fe/H]$<$$-$4 (Lee et al. 2013,
Placco et al. 2014, Frebel & Norris 2015), and thus making them important
tools for the studies of formation and evolution of early Galactic halo.

Ji et al. (2016) have identified 894 new carbon stars from the LAMOST DR2
which contains almost four million medium-resolution (R$\sim$1800) stellar
spectra, based on multiple line indices measurement. In this work, we have
carried out a detailed spectroscopic analysis of two carbon stars
LAMOSTJ091608.81+230734.6 and LAMOSTJ151003.74+305407.3 from Ji et al. (2016).

Observations and data reduction are presented in Section 2. Radial velocity of
the stars and the methodology used for the determination of stellar
atmospheric parameters are presented in section 3. The same section also
provides a brief discussion on the stellar mass determination. Section 4
provides a discussion on abundance uncertainties. Elemental abundance
determination is discussed in Section 5. In Section 6, we present the
kinematic analysis of the program stars, followed by the discussion on the
binary status of the stars in Section 7. Interpretations of abundance ratios
are presented in Section 8. A discussion on individual stars along with the
parametric model based analysis is also given in section 8. Conclusion are
drawn in Section 9.

##  2 OBSERVATIONS AND DATA REDUCTION

High-quality, high-resolution spectra of the objects LAMOSTJ091608.81+230734.6
and LAMOSTJ151003.74+305407.3 were obtained with the HESP (Hanle Echelle
SPectrograph) attached to the 2m Himalayan Chandra Telescope (HCT) operated by
Indian Astronomical Observatory, Hanle. The HESP spectra covers the wavelength
range 3530 - 9970 Å. The spectra of LAMOSTJ091608.81+230734.6 (Vmag = 10.4)
were obtained on April 4, 2018 at a spectral resolution
($\lambda/\delta\lambda$) $\sim$ 60,000, and the spectra of
LAMOSTJ151003.74+305407.3 (Vmag = 11.38) were obtained on May 23, 2018 at a
spectral resolution ($\lambda/\delta\lambda$) $\sim$ 30,000. For both the
objects we had acquired three frames; each frame was taken with 2700 seconds
exposure time. The three frames were added to enhance the S/N ratio, and the
co-added spectrum was used for further analysis. The data was reduced using
the standard procedures in IRAF111IRAF (Image Reduction and Analysis Facility)
is distributed by the National Optical Astronomical Observatories, which is
operated by the Association for Universities for Research in Astronomy, Inc.,
under contract to the National Science Foundation software. The basic
information of the program stars are given in Table 1. Two sample spectra of
the stars in the wavelength region 5160 - 5190 Å are shown in Figure 1.

Figure 1:  Sample spectra of the program stars in the wavelength region 5160
to 5190 Å. Table 1: Basic information of the program stars.

Star |  RA$(2000)$ |  Dec.$(2000)$ | B | V | J | H | K | Exposure | Date of obs. | S/N |
---|---|---|---|---|---|---|---|---|---|---|---
|  |  |  |  |  |  |  | (seconds) |  | 5500 Å | 7500 Å
LAMOSTJ091608.81+230734.6 | 09 16 8.82 | +23 07 34.86 | 11.44 | 10.40 | 8.654 | 8.141 | 8.022 | 2700(3) | 04/04/2018 | 37.15 | 42.38
LAMOSTJ151003.74+305407.3 | 15 10 3.30 | +30 54 7.36 | 13.50 | 11.38 | 9.33 | 8.737 | 8.539 | 2700(3) | 23/05/2018 | 33.67 | 70.17

The number of frames taken are indicated within the parenthesis with exposure.

##  3 ESTIMATION OF ATMOSPHERIC PARAMETERS AND RADIAL VELOCITY

A set of clean lines of several elements is used to calculate the radial
velocities of the program stars. While LAMOSTJ151003.74+305407.3 is found to
be a high velocity object with an estimated radial velocity of
$-$141.58$\pm$3.57 kms-1, the radial velocity of LAMOSTJ091608.81+230734.6 is
found to be 16.13$\pm$4.30 kms-1. The radial velocities of these two objects
are $-$145.2 and 17.3 kms-1 respectively, as noted from the SIMBAD
astronomical database (Gaia collaboration et al. 2018). For the star
LAMOSTJ151003.74+305407.3, our estimate shows a difference of $\sim$4 kms-1
from the SIMBAD value; this may be a clear indication that the star could be a
binary.

The equivalent width measurements of a set of Fe I and Fe II lines are used to
derive the atmospheric parameters of the stars. The lines are selected such
that the range of equivalent width and excitation potential are 20 - 180 mÅ
and 0.0 - 6.0 eV respectively. The photometric temperature estimates,
estimated using the temperature calibration equations of Alonso et al. (1999,
2001), had been used as an initial guess to derive the stellar atmospheric
parameters. The final model atmosphere is obtained through an iterative
process from the initial one taken from the Kurucz grid of model atmosphere
with no convective overshooting (http://cfaku5.cfa.hardvard.edu/). We made use
of the recent version MOOG2013 of the radiative transfer code MOOG (Sneden
1973) assuming Local Thermodynamic Equilibrium (LTE) for the analysis.

The temperature which gives nearly zero slope between the abundance and
excitation potential of Fe I lines is taken as the effective temperature. The
microturbulent velocity at this fixed effective temperature is then determined
such that there is no dependence of the Fe I abundance on equivalent width.
With this temperature and microturbulent velocity estimates, the surface
gravity is determined by demanding the abundances obtained from Fe I and Fe II
lines are to be nearly same. Figure 2 shows the abundances estimated from Fe I
and Fe II lines, as functions of excitation potential and equivalent widths.
The derived atmospheric parameters and the radial velocity estimates are given
in Table 2.

Figure 2: Iron abundances of the program stars derived from individual Fe I
and Fe II lines as function of (i) Excitation potential (lower panel), (ii)
equivalent width (upper panel). Solid circles correspond to Fe I and solid
triangles correspond to Fe II lines.  Table 2: Derived atmospheric parameters
of the program stars.

Star |  Teff | log g | $\zeta$ | [Fe I/H] | [Fe II/H] |  Vr |  Vr | Remarks
---|---|---|---|---|---|---|---|---
| (K) | cgs |  (km s-1) |  |  |  (km s-1) |  (km s-1) |
|  $\pm$100 |  $\pm$0.2 |  $\pm$0.2 |  |  | our estimates | SIMBAD |
LAMOSTJ091608.81+230734.6 | 4820 | 1.43 | 1.62 |  $-$0.89$\pm$0.14 |  $-$0.89$\pm$0.12 |  +16.13$\pm$4.30 |  +17.33$\pm$0.40 | 1
LAMOSTJ151003.74+305407.3 | 4500 | 1.55 | 1.24 |  $-$1.57$\pm$0.12 |  $-$1.57$\pm$0.12 |  $-$141.58$\pm$3.57 |  $-$145.25$\pm$0.003 | 1
| 4358.31 | 0.956 | 1.667 |  $-$1.346 | – | – | – | 2

Remarks: 1. Our work, 2. Hayes et al. (2018)

We have determined the mass of the star LAMOSTJ151003.74+305407.3 from its
position in the Hertzsprung-Russell diagram, generated using the evolutionary
tracks of Girardi et al. 2000, with the estimates of spectroscopic
temperature, Teff, and the luminosity, log$(L/L_{\odot})$. Then log g is
recalculated using this mass estimate as described in our previous work
Shejeelammal et al. (2020). For estimation of log$(L/L_{\odot})$, the required
visual magnitudes V and the parallaxes $\pi$ are taken from Simbad and Gaia
DR2 (Gaia collaboration et al. 2018, https://gea.esac.esa.int/archive/)
respectively. We have used z = 0.001 tracks for this star. The evolutionary
tracks for LAMOSTJ151003.74+305407.3 is shown in Figure 3. The estimated mass,
log g determined using parallax method are presented in Table 3. The mass
could not be determined for the other star using this method as the
evolutionary tracks corresponding to its temperature and luminosity are not
available.

Figure 3: The locations of LAMOSTJ151003.74+305407.3. The evolutionary tracks for 0.6, 0.7 and 0.8 M⊙ are shown from bottom to top for z = 0.001. Table 3: Mass and log g estimates by parallax method Star name | Parallax | $M_{bol}$ |  log(L/L⊙) |  Mass(M⊙) | log g | log g (spectroscopic)
---|---|---|---|---|---|---
| (mas) |  |  |  | (cgs) | (cgs)
LAMOSTJ091608.81+230734.6 |  1.0543$\pm$0.0517 |  0.105$\pm$0.107 |  1.854$\pm$0.043 | – | – | 1.43
LAMOSTJ151003.74+305407.3 |  0.2778$\pm$0.0346 |  1.891$\pm$0.271 |  2.653$\pm$0.109 |  0.70$\pm$0.10 |  1.20$\pm$0.05 | 1.55

##  4 ABUNDANCE UNCERTAINTIES

The main sources of uncertainty in the abundance are the errors in the
estimated stellar atmospheric parameters and the errors in the line
parameters. Total uncertainty in the elemental abundance, log $\epsilon$, is
given as;

$\sigma_{log\epsilon}^{2}$ = $\sigma_{ran}^{2}$ \+ $(\frac{\partial
log\epsilon}{\partial T})^{2}$ $\sigma_{T_{eff}}^{2}$ \+ $(\frac{\partial
log\epsilon}{\partial logg})^{2}$ $\sigma_{logg}^{2}$ \+

$(\frac{\partial log\epsilon}{\partial\zeta})^{2}$ $\sigma_{\zeta}^{2}$ \+
$(\frac{\partial log\epsilon}{\partial[Fe/H]})^{2}$ $\sigma_{[Fe/H]}^{2}$

where $\sigma_{ran}$ = $\frac{\sigma_{s}}{\sqrt{N}}$, $\sigma_{s}$ being the
standard deviation of the abundances derived from N lines of a particular
element considered. The other $\sigma$’s in the equation are the typical
uncertainties in the atmospheric parameters; $\Delta$Teff$\sim$ $\pm$100 K,
$\Delta$log g$\sim$ $\pm$0.2 dex, $\Delta$$\zeta$$\sim$ $\pm$0.2 km s-1 and
$\Delta$[Fe/H]$\sim$ $\pm$0.1 dex.

We have calculated the uncertainty in the abundance, [X/Fe], for each element
following a detailed procedure described in our earlier paper Shejeelammal et
al. (2020). As an example, these values for the star LAMOSTJ091608.81+230734.6
are given in Table 4.

Table 4: Differential Abundance ($\Delta$log$\epsilon$) of different elemental
species due to the variations in stellar atmospheric parameters for
LAMOSTJ091608.81+230734.6. The sixth column gives the computed rms uncertainty
of the second to fifth columns. The seventh column gives the total uncertainty
in the abundance ratio, [X/Fe], of each elemental species.

Element |  $\Delta$Teff |  $\Delta$log g |  $\Delta$$\zeta$ |  $\Delta$[Fe/H] |  ($\Sigma\sigma_{i}^{2}$)1/2 | $\sigma_{[X/Fe]}$
---|---|---|---|---|---|---
|  ($\pm$100 K) |  ($\pm$0.2 dex) |  ($\pm$0.2 kms-1) |  ($\pm$0.1 dex) |  |
C |  $\pm$0.10 | 0.00 | 0.00 |  $\mp$0.05 | 0.11 | 0.19
N |  $\pm$0.13 |  $\pm$0.03 | 0.00 |  $\pm$0.02 | 0.13 | 0.21
O | 0.00 |  $\pm$0.04 |  $\mp$0.02 | 0.00 | 0.04 | 0.16
Na I |  $\pm$0.08 |  $\mp$0.01 |  $\mp$0.05 |  $\mp$0.01 | 0.10 | 0.19
Mg I |  $\pm$0.09 |  $\mp$0.03 |  $\mp$0.08 |  $\mp$0.01 | 0.05 | 0.17
Si I |  $\pm$0.04 |  $\pm$0.01 |  $\mp$0.02 | 0.00 | 0.06 | 0.17
Ca I |  $\pm$0.10 |  $\mp$0.01 |  $\mp$0.08 |  $\mp$0.01 | 0.13 | 0.21
Sc II |  $\mp$0.02 |  $\pm$0.09 |  $\mp$0.06 |  $\pm$0.02 | 0.11 | 0.25
Ti I |  $\pm$0.14 |  $\mp$0.01 |  $\mp$0.07 |  $\mp$0.01 | 0.16 | 0.23
Ti II | 0.00 |  $\pm$0.09 |  $\mp$0.08 |  $\pm$0.03 | 0.12 | 0.26
V I |  $\pm$0.16 |  $\mp$0.01 |  $\mp$0.07 |  $\mp$0.01 | 0.18 | 0.24
Cr I |  $\pm$0.17 |  $\mp$0.02 |  $\mp$0.13 |  $\mp$0.03 | 0.22 | 0.27
Mn I |  $\pm$0.09 |  $\mp$0.02 |  $\mp$0.16 |  $\mp$0.01 | 0.18 | 0.24
Fe I |  $\pm$0.10 |  $\pm$0.01 |  $\mp$0.11 |  $\pm$0.05 | 0.16 | –
Fe II |  $\mp$0.06 |  $\pm$0.11 |  $\mp$0.10 |  $\mp$0.17 | 0.23 | –
Co I |  $\pm$0.07 |  $\pm$0.02 |  $\mp$0.06 |  $\pm$0.01 | 0.09 | 0.18
Ni I |  $\pm$0.09 | 0.00 |  $\mp$0.05 |  $\mp$0.01 | 0.10 | 0.19
Zn I |  $\mp$0.03 |  $\pm$0.05 |  $\mp$0.03 |  $\pm$0.02 | 0.07 | 0.17
Rb I |  $\pm$0.10 | 0.00 |  $\mp$0.03 | 0.00 | 0.10 | 0.19
Sr I |  $\pm$0.18 |  $\mp$0.02 |  $\mp$0.13 |  $\mp$0.02 | 0.22 | 0.27
Y I |  $\pm$0.17 |  $\mp$0.02 |  $\mp$0.04 |  $\mp$0.02 | 0.18 | 0.24
Y II | 0.00 |  $\pm$0.09 |  $\mp$0.11 |  $\pm$0.03 | 0.14 | 0.27
Zr I |  $\pm$0.17 |  $\mp$0.02 |  $\mp$0.07 |  $\mp$0.02 | 0.19 | 0.25
Zr II |  $\pm$0.01 |  $\pm$0.08 |  $\mp$0.06 |  $\pm$0.02 | 0.10 | 0.25
Ba II |  $\pm$0.02 |  $\pm$0.05 |  $\mp$0.15 |  $\pm$0.02 | 0.16 | 0.28
La II |  $\pm$0.01 |  $\pm$0.09 |  $\mp$0.06 |  $\pm$0.03 | 0.11 | 0.25
Ce II |  $\pm$0.02 |  $\pm$0.08 |  $\mp$0.13 |  $\pm$0.02 | 0.16 | 0.28
Pr II |  $\pm$0.02 |  $\pm$0.08 |  $\mp$0.07 |  $\pm$0.02 | 0.11 | 0.25
Nd II |  $\pm$0.03 |  $\pm$0.08 |  $\mp$0.16 |  $\pm$0.02 | 0.18 | 0.29
Sm II |  $\pm$0.04 |  $\pm$0.09 |  $\mp$0.08 |  $\pm$0.03 | 0.13 | 0.26
Eu II |  $\mp$0.02 |  $\pm$0.09 |  $\mp$0.03 |  $\pm$0.03 | 0.10 | 0.25

##  5 Abundance determination

Elemental abundances are derived from the measured equivalent widths and the
spectral synthesis calculation of spectral lines of neutral and ionized atoms.
Only clean unblended lines have been considered for the abundance
determination. Absorption lines due to each element is identified from the
close comparison of Doppler-corrected spectrum of the star Arcturus and the
program stars spectra. The line information such as log $gf$ and the lower
excitation potential are from the Kurucz database of atomic line lists. In
addition to the equivalent width method, spectral synthesis calculation is
also performed for the elements showing hyper-fine splitting. Also, the
abundances derived from the molecular bands are based on spectral synthesis
calculation. The hyper-fine components of Eu are taken from Worely et al.
(2013), Ba from Mcwilliam (1998), V, Co and Cu from Prochaska et al. (2000)
and Sc and Mn from Prochaska & Mcwilliam (2000). Solar abundance values are
taken from Asplund et al. (2009).

The abundance results are presented in Table 5. The lines used for the
estimation of abundances are given in Tables A1 and A2.

Table 5: Elemental abundances in LAMOSTJ091608.81+230734.6 and
LAMOSTJ151003.74+305407.3

|  |  |  | LAMOSTJ091608.81+230734.6 |  |  | LAMOSTJ151003.74+305407.3 |
---|---|---|---|---|---|---|---|---
| Z |  solar log$\epsilon^{\ast}$ |  log$\epsilon$ | [X/H] | [X/Fe] |  log$\epsilon$ | [X/H] | [X/Fe]
C (C2 band 5165 Å) | 6 | 8.43 | 7.90(syn) |  $-$0.53 | 0.36 | 8.60(syn) | 0.17 | 1.74
C (C2 band 5635 Å) | 6 | 8.43 | 7.90(syn) |  $-$0.53 | 0.36 | 8.60(syn) | 0.17 | 1.74
N | 7 | 7.83 | 7.79(syn) |  $-$0.04 | 0.85 | 7.53(syn) |  $-$0.30 | 1.27
O | 8 | 8.69 | 7.76(syn) |  $-$0.93 |  $-$0.04 | – | – | –
Na I | 11 | 6.24 |  6.03$\pm$0.15(4) |  $-$0.21 | 0.68 |  5.24$\pm$0.05(2) |  $-$1.00 | 0.57
Mg I | 12 | 7.60 |  7.12$\pm$0.15(2) |  $-$0.46 | 0.43 |  6.20$\pm$0.18(3) |  $-$1.58 |  $-$0.01
Si I | 14 | 7.51 |  6.59$\pm$0.18(3) |  $-$0.92 |  $-$0.03 | – | – | –
Ca I | 20 | 6.34 |  5.38$\pm$0.15(10) |  $-$0.96 |  $-$0.07 |  4.52$\pm$0.13(8) |  $-$1.82 |  $-$0.25
Sc II | 21 | 3.15 | 2.19(syn) |  $-$0.96 |  $-$0.07 | 1.85(syn) |  $-$1.30 | 0.27
Ti I | 22 | 4.95 |  4.07$\pm$0.17(12) |  $-$0.88 | 0.01 |  3.30$\pm$0.14(4) |  $-$1.65 |  $-$0.08
Ti II | 22 | 4.95 |  3.77$\pm$0.17(4) |  $-$1.18 |  $-$0.29 |  3.21$\pm$0.19(5) |  $-$1.74 |  $-$0.17
V I | 23 | 3.93 | 3.42(syn) |  $-$0.51 | 0.38 | 3.11(syn) |  $-$0.82 | 0.75
Cr I | 24 | 5.64 |  5.13$\pm$0.18(6) |  $-$0.51 | 0.38 |  3.59$\pm$0.10(5) |  $-$2.05 |  $-$0.48
Mn I | 25 | 5.43 | 4.70(syn) |  $-$0.73 | 0.16 | 3.43(syn) |  $-$2.00 |  $-$0.43
Fe I | 26 | 7.50 |  6.61$\pm$0.14(73) |  $-$0.89 | - |  5.93$\pm$0.12(35) |  $-$1.57 | -
Fe II | 26 | 7.50 |  6.61$\pm$0.12(6) |  $-$0.89 | - |  5.93$\pm$0.12(4) |  $-$1.57 | -
Co I | 27 | 4.99 | 3.89(syn) |  $-$1.10 |  $-$0.21 | – | – | –
Ni I | 28 | 6.22 |  5.63$\pm$0.11(11) |  $-$0.59 | 0.30 |  4.61$\pm$0.17(6) |  $-$1.61 |  $-$0.04
Zn I | 30 | 4.56 | 4.11(1) |  $-$0.49 | 0.40 |  2.56$\pm$0.14(2) |  $-$2.00 |  $-$0.43
Rb I | 37 | 2.52 | 2.10(syn) |  $-$0.42 | 0.47 | 1.00(syn) |  $-$1.52 | 0.05
Sr I | 38 | 2.87 | 2.95(syn) | 0.08 | 0.97 | – | – | –
Y I | 39 | 2.21 | 2.56(syn) | 0.35 | 1.24 | 2.20(syn) |  $-$0.01 | 1.56
Y II | 39 | 2.21 |  2.32$\pm$0.10(6) | 0.11 | 1.00 |  3.05$\pm$0.11(2) | 0.84 | 2.40
Zr I | 40 | 2.58 | 3.08(syn) | 0.50 | 1.39 | 2.05(syn) |  $-$0.53 | 1.04
Zr II | 40 | 2.58 | 2.73(syn) | 0.15 | 1.04 | 2.09(syn) |  $-$0.49 | 1.08
Ba II | 56 | 2.18 | 2.48(syn) | 0.30 | 1.19 | 2.00(syn) |  $-$0.18 | 1.39
La II | 57 | 1.10 | 2.00(syn) | 0.90 | 1.79 | 1.10(syn) | 0.00 | 1.57
Ce II | 58 | 1.58 |  2.34$\pm$0.11(7) | 0.76 | 1.65 |  1.32$\pm$0.13(7) |  $-$0.26 | 1.31
Pr II | 59 | 0.72 |  1.48$\pm$0.18(6) | 0.76 | 1.65 |  1.02$\pm$0.11(5) | 0.30 | 1.87
Nd II | 60 | 1.42 |  2.17$\pm$0.17(9) | 0.75 | 1.64 |  1.35$\pm$0.14(12) |  $-$0.07 | 1.50
Sm II | 62 | 0.96 |  1.41$\pm$0.11(10) | 0.45 | 1.34 |  1.03$\pm$0.08(6) | 0.07 | 1.64
Eu II | 63 | 0.52 | 0.33(syn) |  $-$0.19 | 0.70 | 0.09(syn) |  $-$0.43 | 1.14

$\ast$ Asplund (2009), The numbers within the parenthesis are the number of
lines used for abundance estimation.

###  5.1 Abundance analysis: C, N, O, 12C/13C, Na, $\alpha$\- and $Fe$-peak
elements

The abundance of oxygen is derived using the spectral synthesis calculation of
[O I] line at 6300.304 Å in LAMOSTJ091608.81+230734.6. The resonance O I
triplet lines at around 7770 Å and the [O I] 6363.776 Å line are blended and
could not be used for abundance determination. The estimated oxygen abundance
shows near solar value, with [O/Fe]$\sim$$-$0.04. We could not estimate the
abundance of oxygen for the star LAMOSTJ151003.74+305407.3 as no clean good
lines of oxygen could be detected in the spectrum of this object.

The carbon abundance is derived from the spectral synthesis calculation of the
C2 molecular bands at 5165 and 5635 Å (Figure 4). Both the bands gave the same
carbon abundance value in both the stars. Carbon is found to be enhanced in
LAMOSTJ151003.74+305407.3 with [C/Fe]$\sim$1.74 and mildly enhanced in the
other object with [C/Fe]$\sim$0.36.

Figure 4:  Synthesis of C2 band around 5165 Å (lower panel) and 5635 Å (upper
panel). Dotted and solid lines represent synthesized and observed spectra
respectively. Short dashed and long dashed lines represent the synthetic
spectra for $\Delta$ [C/Fe] = $-$0.3 and +0.3 respectively.

Once the carbon abundance is estimated, the abundance of nitrogen is derived
using the spectral synthesis calculation of 12CN lines at 8000 Å region. The
12CN molecular band at 4215 Å is not usable in both the stars. The CN and C2
molecular lines are taken from Ram et al. (2014), Sneden et al. (2014) and
Brooke et al. (2013). In both the stars nitrogen is enhanced with
[N/Fe]$\geq$0.85. The final C, N and O abundances are determined by an
iterative process. Using the first estimate of oxygen abundance derived from
the spectral synthesis calculation of 6300.304 Å [O I] line, the abundance of
carbon is estimated from the C2 molecular bands at 5165 and 5635 Å. The
abundance of nitrogen is then determined using these derived abundance
estimates of O and C. Once the nitrogen abundance is obtained, the oxygen and
carbon abundances are re-determined using this nitrogen abundance. This
iteration process is continued until a convergence is reached.

The carbon isotopic ratio, 12C/13C, is estimated from the spectral synthesis
calculation of 12CN lines at 8003.292, 8003.553, 8003.910 Å, and 13CN features
at 8004.554, 8004.728, 8004.781 Å. The spectrum synthesis fits for the program
stars in this region is shown in Figure 5. The values of this ratio are 8.67
and 13.33 in LAMOSTJ091608.81+230734.6 and LAMOSTJ151003.74+305407.3
respectively. These are typical values normally found in the case of giants
(Smith et al. 1993). For CEMP-s and CEMP-r/s stars, the values of 12C/13C
ratio are found in the range 2.5 - 40 (Bisterzo et al. 2011). We could
estimate the C/O ratio in the star LAMOSTJ091608.81+230734.6 which is found to
be greater than 1 as typically seen in CH stars.

Figure 5: Spectral synthesis of CN band around 8005 Å. Dotted and solid lines
represent synthesized and observed spectra respectively. Short dashed and long
dashed lines are the synthetic spectra for 12C/13C $\simeq$ 83 and 2.7
respectively.

The abundances of the elements Na, Mg, Si, Ca, Ti, Cr, Ni and Zn are derived
from the measured equivalent width of spectral lines listed in Table A2.
Scandium abundance is derived from the spectral synthesis calculation of Sc II
line at 6245.637 Å, vanadium abundance from the V I lines at 6251.827 and
4864.731 Å, manganese abundance from Mn I line at 6013.513 Å and the abundance
of cobalt from Co I line at 5342.695 Å.

A comparison of our estimated light element abundances for the star
LAMOSTJ151003.74+305407.3 with the literature values is given in Table 6.
Within the error limits, our estimates of Mg and Ni match with the estimates
of Hayes et al. (2018). However, our estimates are lower by $\sim$0.6 dex for
[Ca/Fe] and [Cr/Fe] and $\sim$0.3 dex for [Mn/Fe]. We have obtained
[C/Fe]$\sim$1.74, which is largely different from $\sim$0.81 of Hayes et al.
(2018).

Table 6: Comparison of the light element abundances of
LAMOSTJ151003.74+305407.3 with the literature values.

Star name | [C/Fe] | [Mg/Fe] | [Ca/Fe] | [Cr/Fe] | [Mn/Fe] | [Ni/Fe] | Ref
---|---|---|---|---|---|---|---
LAMOSTJ151003.74+305407.3 | 1.74 |  $-$0.01 |  $-$0.25 |  $-$0.48 |  $-$0.43 |  $-$0.04 | 1
| 0.81 | 0.21 | 0.36 | 0.11 |  $-$0.15 | 0.07 | 2

References: 1. Our work, 2. Hayes et al. 2018

###  5.2 Heavy element abundance analysis

####  5.2.1 The light s-process elements: Rb, Sr, Y, Zr

The spectral synthesis calculation of resonance line of Rb I at 7800.259 Å is
used to derive the Rb abundance in both the stars. The Rb I 7947.597 Å line
was not usable for the abundance estimation. The Rb hyperfine components are
taken from Lambert & Luck (1976). It is mildly enhanced in
LAMOSTJ091608.81+230734.6 with [Rb/Fe]$\sim$0.47, while it is near-solar in
LAMOSTJ151003.74+305407.3.

We could derive the strontium abundance only in LAMOSTJ091608.81+230734.6 as
no usable lines could be measured on the spectrum of the other star. The Sr I
4607.327 Å line in LAMOSTJ091608.81+230734.6 returned a value
[Sr/Fe]$\sim$0.97 from the spectral synthesis calculation.

The abundance of yttrium is derived using the spectral synthesis calculation
of Y I line at 6435.004 Å and equivalent width measurement of a few Y II lines
in both the stars. Both the species give a value [Y/Fe]$\geq$1\. The spectrum
synthesis fits for Y I of the program stars are shown in Figure 6.

The spectral synthesis calculation of Zr I line at 6134.585 Å and Zr II line
at 5112.297 Å are used to derive the zirconium abundance in the program stars.
In both the cases, Zr is found to be enhanced with [Zr/Fe]$>$1\. The spectrum
synthesis fits for Zr I of the program stars are shown in Figure 7.

In the case of LAMOSTJ091608.81+230734.6, neutral lines of Y and Zr give a
higher abundance than the singly ionized lines.

Figure 6:  Synthesis of Y I line at 6435.004 Å. Dotted and solid lines
represent synthesized and observed spectra respectively. Short dashed and long
dashed lines represent the synthetic spectra for $\Delta$[Y/Fe] = $-$0.3 and
+0.3 respectively. Figure 7:  Synthesis of Zr I line at 6134.585 Å. Dotted and
solid lines represent synthesized and observed spectra respectively. Short
dashed and long dashed lines represent the synthetic spectra for
$\Delta$[Zr/Fe] = $-$0.3 and +0.3 respectively.

####  5.2.2 The heavy s-process elements: Ba, La, Ce, Pr, Nd

The spectral synthesis calculation of Ba II line at 5853.668 Å in
LAMOSTJ091608.81+230734.6 and Ba II 6141.713 Å line in
LAMOSTJ151003.74+305407.3 are used to derive the barium abundances. La
abundance is derived from the spectral synthesis calculation of La II line at
5259.380 Å in both the stars. We could not detect any other useful lines due
to lanthanum in the program stars for the abundance determination. The
abundances of Ce, Pr and Nd are derived using the measured equivalent widths
of several spectral lines due to singly ionized species of the respective
elements. All these elements are found to be enhanced in both the stars with
[X/Fe]$>$1.

Finally, we have estimated the [ls/Fe], [hs/Fe] and [hs/ls] ratios in the
program stars. Here, ls and hs are light (Sr, Y and Zr) and heavy (Ba, La, Ce
and Nd) s-process elements respectively. Also, we have estimated the mean
abundance ratio of s-process elements (Sr, Y, Zr, Ba, La, Ce, Nd ), [s/Fe], to
find the s-process content.

####  5.2.3 The r-process elements: Sm, Eu

The Sm abundance is derived from the equivalent width measurement of Sm II
lines listed in Table A2. Both the stars show enhancement of Sm with
[Sm/Fe]$\sim$1.34 and 1.64 in LAMOSTJ091608.81+230734.6 and
LAMOSTJ151003.74+305407.3 respectively.

The abundance of europium is estimated from the spectral synthesis calculation
of Eu II 6645.064 Å. In LAMOSTJ091608.81+230734.6 Eu is enhanced with
[Eu/Fe]$\sim$0.70 while the other star shows a value 1.14.

##  6 Kinematic Analysis

The spatial velocity of a star in the solar neighborhood is measured with
respect to the Local Standard of Rest (LSR). The components of the spatial
velocity are $U_{LSR}$, $V_{LSR}$ and $W_{LSR}$; measured along the axes
pointing towards the Galactic center, the direction of Galactic rotation and
the North Galactic Pole respectively (Johnson & Soderblom 1987). Space
velocity of the programme stars are calculated following the procedures in
Bensby et al. (2003). Components of the spatial velocity of the star with
respect to LSR:

$(U,V,W)_{LSR}=(U,V,W)+(U,V,W)_{\odot}$ km/s.

where, $(U,V,W)_{\odot}$ is the solar motion with respect to LSR and its value
is (11.1, 12.2, 7.3) km/s (Schönrich et al., 2010) and

$\left[\begin{array}[]{c}U\\\ V\\\
W\end{array}\right]=B.\left[\begin{array}[]{c}V_{r}\\\ k.\mu_{\alpha}/\pi\\\
k.\mu_{\delta}/\pi\end{array}\right]$

where, $B=T.A$, T is the transformation matrix connecting the Galactic
coordinate system and equatorial coordinate system and A is a coordinate
matrix defined below

$T=\left[\begin{array}[]{ccc}-0.06699&-0.87276&-0.48354\\\
+0.49273&-0.45035&+0.74458\\\ -0.86760&-0.18837&0.46020\end{array}\right]$
$A=\left[\begin{array}[]{ccc}Cos\alpha.Cos\delta&-Sin\alpha&-Cos\alpha.Sin\delta\\\
Sin\alpha.Cos\delta&Cos\alpha&-Sin\alpha.Sin\delta\\\
Sin\delta&0&Cos\delta\end{array}\right]$

where $\alpha$ is the RA, $\delta$ the DEC, $V_{r}$ the radial velocity in
km/s, $k=4.74057km/s$ equivalent of 1 AU in one year, $\mu_{\alpha}$ and
$\mu_{\delta}$ respectively the proper motions in RA and DEC in arcsec/year
and $\pi$ the parallax in arcsec. The proper motion and parallax values are
taken from GAIA DR2 (Gaia collaboration et al. 2018,
https://gea.esac.esa.int/archive/) and SIMBAD astronomical database. The
spectroscopic velocity estimates have been used in this calculation.

The total spatial velocity of the star:
$V_{spa}^{2}=U_{LSR}^{2}+V_{LSR}^{2}+W_{LSR}^{2}$

Errors in the respective velocity components are calculated as follows:

$\left[\begin{array}[]{c}\sigma_{U}^{2}\\\ \sigma_{V}^{2}\\\
\sigma_{W}^{2}\end{array}\right]=C.\left[\begin{array}[]{c}\sigma_{V_{r}}^{2}\\\
(k/\pi)^{2}[\sigma_{\mu_{\alpha}}^{2}+(\mu_{\alpha}\sigma_{\pi}/\pi)^{2}]\\\
(k/\pi)^{2}[\sigma_{\mu_{\delta}}^{2}+(\mu_{\delta}\sigma_{\pi}/\pi)^{2}]\end{array}\right]+$
$\frac{2\mu_{\alpha}\mu_{\delta}k^{2}\sigma_{\pi}^{2}}{\pi^{4}}.\left[\begin{array}[]{c}b_{12}.b_{13}\\\
b_{22}.b_{23}\\\ b_{32}.b_{33}\end{array}\right]$

where $C_{ij}=b_{ij}^{2}$ and $\sigma^{\prime}_{s}$ the errors in respective
quantities.

The probability that a star belongs to the Galactic thin/thick disc or halo
population is calculated following the procedure described in Mishenina et al.
(2004), Bensby et al. (2003, 2004) and Reddy et al. (2006), with assumption
that the space velocities follow a Gaussian distribution.

$\begin{array}[]{c}P_{thin}=\frac{f_{1}.p_{1}}{P},P_{thick}=\frac{f_{2}.p_{2}}{P},P_{halo}=\frac{f_{3}.p_{3}}{P}\\\
\end{array}$

$P=\Sigma f_{i}.p_{i}$

$p_{i}=K_{i}.exp[\frac{-U_{LSR}^{2}}{2.\sigma_{U_{i}}^{2}}-\frac{(V_{LSR}-V_{ad})^{2}}{2.\sigma_{V_{i}}^{2}}-\frac{W_{LSR}^{2}}{2.\sigma_{W_{i}}^{2}}]$

$K_{i}=\frac{1}{(2.\pi)^{(3/2)}.\sigma_{U_{i}}.\sigma_{V_{i}}.\sigma_{W_{i}}}$;
$i=1,2,3$

where $\sigma^{\prime}_{s}$ are the dispersion in velocities, $V_{ad}$ the
mean galactic rotation velocity for each stellar population relative to LSR
and $f$ the fractional population. These values are taken from Reddy et al.
(2006).The estimates of the total spatial velocity and components of spatial
velocity along with the probability estimates are given in Table 7. Our
analysis shows that the star LAMOSTJ091608.81+230734.6 belongs to the thin
disc population and LAMOSTJ151003.74+305407.3 belongs to the Galactic halo
population.

Table 7: Spatial velocity and probability estimates for the program stars Star name |  ULSR |  VLSR |  WLSR |  Vspa |  pthin |  pthick |  phalo
---|---|---|---|---|---|---|---
|  (kms-1) |  (kms-1) |  (kms-1) |  (kms-1) |  |  |
LAMOSTJ091608.81+230734.6 |  $-$12.14$\pm$2.99 |  1.57$\pm$1.41 |  2.71$\pm$2.95 |  12.53$\pm$1.98 | 0.99 | 0.01 | 0.00
LAMOSTJ151003.74+305407.3 |  $-$16.38$\pm$2.84 |  $-$207.80$\pm$20.74 |  $-$49.68$\pm$8.67 |  214.25$\pm$22.33 | 0.00 | 0.29 | 0.71

##  7 Binary status of the program stars

For a precise identification of the source of carbon and heavy-element
enrichment in peculiar stars, it is very crucial to know their binary status.
A number of investigations dedicated to identify the binarity of the peculiar
stars have been carried out to date. The precise radial velocity monitoring
studies have shown that most of the Ba and CH stars (McClure et al. 1980,
McClure 1983, 1984, McClure & Woodsworth 1990, Udry et al. 1998a,b, Lucatello
et al. 2005, Jorissen et al. 2016) and a high fraction of CEMP-s/(r/s)
stars(Lucatello et al. 2005, Starkenburg et al. 2014, Jorissen et al. 2016)
are in binary systems. The compilation of Duquennoy & Mayor (1991) and
Starkenburg et al. (2014) have shown the binary fraction of CEMP-s/(r/s) stars
to be 100%. However, a few recent studies have reported a binary frequency of
82$\pm$10% for CEMP-s/(r/s) stars (Hansen et al. 2016c) and 17$\pm$9% for
CEMP-no stars (Hansen et al. 2016b).

All these conclusions are based on the data available to each study.
Information available in literature on the binary status of many CEMP stars is
still very limited. Yoon et al.(2016) (and references therein) have done a
compilation of the literature data for 305 CEMP stars that includes 147
CEMP-s/(r/s) stars and 127 CEMP-no stars. Out of these, 35 CEMP-s/rs stars and
22 CEMP-no stars have known binary status. Earlier to this, Spite et al.
(2013) observed for the first time the bimodality in the absolute carbon
abundances among the CEMP stars, with CEMP-s stars populating the high-carbon
region (A(C)$\sim$8.25) and CEMP-no stars populating the low-carbon region
(A(C)$\sim$6.5). Later, this bimodality is confirmed by Bonifacio et al (2015)
and Hansen et al (2015a) for an extended sample of CEMP stars. Yoon et al.
(2016) investigated anew the distribution of absolute carbon abundance, A(C),
in terms of the metallicity for these CEMP stars. Their analysis have shown
that the fiducial line at A(C)=7.1 in the [Fe/H] versus A(C) diagram could
well separate the binary nature of all the CEMP-s/(r/s) stars and majority of
CEMP-no stars. Despite of a few outliers, majority of the binary stars lie
above this line. Thus this diagram can be used as a tool to derive clues on
the binary status of the CEMP stars as well as the origin of their chemical
peculiarities. We have used such a figure to understand the binary nature of
our program stars. The distribution of absolute carbon abundance with
metallicity for different classes of chemically peculiar stars are shown in
figure 8. In this figure, both the program stars lie in the region occupied by
binary stars, indicating that our program stars are likely binaries. In
addition, the variation in radial velocity estimate for
LAMOSTJ151003.74+305407.3 by $\sim$4 kms-1 also suggests that this object
could be a binary star.

Figure 8: Distribution of A(C) as a function of [Fe/H] for known (and likely)
binary and single stars. Red nine-sided stars, magenta six-sided crosses, red
starred triangles, red filled circles and magenta five-sided stars represent
binary CEMP-s, single CEMP-s, binary CEMP-r/s, binary CEMP-no and single CEMP-
no stars respectively from literature (Yoon et al. 2016). All the red symbols
corresponds to the binary CEMP stars and magenta symbols to single CEMP stars.
Blue crosses represent the binary CH stars from literature (Purandardas et al.
2019, Karinkuzhi & Goswami 2014, 2015, Luck 2017). Binary Ba stars from
literature (Shejeelammal et al. 2020, Karinkuzhi et al. 2018) are represented
by green open hexagons. LAMOSTJ091608.81+230734.6 (filled triangle) and
LAMOSTJ151003.74+305407.3 (filled square). The dashed line indicate the
fiducial that separates binary and single stars.

##  8 Discussion

From the multiple line indices measured from the stellar spectra from LAMOST
DR2, Ji et al. (2016) have identified the objects LAMOSTJ091608.81+230734.6
and LAMOSTJ151003.74+305407.3 to be CH stars. Our detailed abundance analysis
confirms LAMOSTJ091608.81+230734.6 to be a CH star and
LAMOSTJ151003.74+305407.3 to be a CEMP -r/s star. The estimated abundances of
light elements from Na to Zn are quite similar to the normal giants following
the Galactic trend as shown in Figure 9. The estimated abundances of heavy
elements however show enhancement compared to their counterparts in other
normal stars (Figure 10).

The neutron density dependent [Rb/Zr] ratio has been estimated in order to see
the nature of companion star. For this ratio, the AGB models predict a
negative value in low-mass AGB stars (M$\leq$ 3 M⊙) and a positive value in
intermediate-mass AGB stars (M$\geq$ 4 M⊙) (Abia et al. 2001, van Raai et al.
2012, Karakas et al. 2012). This trend has been observed among the AGB stars
in the Galaxy and Magellanic Clouds (Plez et al. 1993, Lambert et al. 1995,
Abia et al. 2001, García-Hernández et al. 2006, 2007, 2009). The estimated
values of this ratio (Table 8) are shown in Figure 11. The range of Rb and Zr
observed in the Galactic and Magellanic Cloud low- and intermediate-mass AGB
stars (shaded regions) are also shown in the same figure.

Table 8: Estimates of [ls/Fe], [hs/Fe], [s/Fe], [hs/ls], [Rb/Zr], [Ba/Eu] and C/O Star name | [Fe/H] | [ls/Fe] | [hs/Fe] | [s/Fe] | [hs/ls] | [Rb/Zr] | [Ba/Eu] | C/O
---|---|---|---|---|---|---|---|---
LAMOSTJ091608.81+230734.6 |  $-$0.89 | 1.20 | 1.57 | 1.41 | 0.37 |  $-$0.92 | 0.49 | 1.38
LAMOSTJ151003.74+305407.3 |  $-$1.57 | 1.30 | 1.44 | 1.67 | 0.14 |  $-$0.99 | 0.25 | –

Figure 9: Observed [X/Fe] ratios of the light elements in the program stars
with respect to metallicity [Fe/H]. Red open circles correspond to normal
giants from literature (Honda et al. 2004, Venn et al. 2004, Aoki et al. 2005,
2007, Reddy et al. 2006, Luck & Heiter 2007, Hansen et al. 2016a, Yoon et al.
2016). Magenta nine-sided stars and blue starred triangles represent CEMP-s
and CEMP-r/s stars respectively from literature (Masseron et al. 2010). Cyan
crosses and green open squares represent giant and sub-giant CH stars
respectively from literature (Vanture 1992, Karinkuzhi & Goswami 2014, 2015,
Goswami et al. 2016). LAMOSTJ091608.81+230734.6 (filled triangle) and
LAMOSTJ151003.74+305407.3 (filled square).

Figure 10: Observed [X/Fe] ratios of the heavy elements in the program stars
with respect to metallicity [Fe/H]. Symbols have same meaning as in Figure 9.
Figure 11: The observed [Rb/Fe] and [Zr/Fe]. LAMOSTJ091608.81+230734.6 (filled
triangle) and LAMOSTJ151003.74+305407.3 (filled square). The shaded regions
represent the observed ranges of Zr and Rb in intermediate-mass (short-dashed
lines) and low-mass (dots) AGB stars of the Galaxy and the Magellanic Clouds
(van Raai et al. 2012). The Rb and Zr abundances in the program stars are
consistent with that of low-mass AGB stars.

LAMOSTJ091608.81+230734.6: The object is found to be metal-poor with a
metallicity of $-$0.89. Eventhough we could not find its position on HR
diagram, its estimated log g value suggests the star to be on RGB (Allen &
Barbuy 2006). The star shows a mild over abundance of carbon with
[C/Fe]$\sim$0.36. Similar values of carbon in CH stars have been reported in
literature (Purandardas et al. 2019, Goswami et al. 2016, Karinkuzhi & Goswami
2015, Vanture 1992). Nitrogen enhancement compared to carbon in the star,
along with the low 12C/13C ratio of $\sim$ 8.67, suggest the CN processing and
the First Dredge-Up (FDU) during the giant phase. Further, with its estimated
values of mean s-process abundance ratio, [s/Fe]$\sim$1.41, and C/O$\sim$1.38,
this star can be included in the CH giant category. The star shows negative
value for the [Rb/Zr], which indicates a low-mass companion AGB as expected
for the CH stars (Figure 11). The estimated [hs/ls] ratio is $\sim$0.37,
indicating the over abundance of second-peak s-process elements over the first
peak, as normally seen in most of the CH stars. Our kinematic analysis shows
that this star belongs to Galactic thin disc population.

Figure 12 compares the observed abundance ratios [Ba/Fe] and [Eu/Fe], the
representative s- and r- process elements respectively, in different classes
of chemically peculiar stars. The star LAMOSTJ091608.81+230734.6 falls in the
region occupied by other CH stars, Ba stars and CEMP-s stars. These three
classes of stars are known to have the same origin of s-process enhancement,
pollution from a binary low-mass AGB companion.

Figure 12: Observed [Eu/Fe] and [Ba/Fe] ratios for different classes of
chemically peculiar stars. Magenta nine-sided stars, blue starred triangles
and red six-sided crosses represent CEMP-s CEMP-r/s and r (including both
CEMP-r and rI/rII stars) stars respectively from literature (Masseron et al.
2010). Cyan crosses represent CH stars from literature (Vanture 1992,
Karinkuzhi & Goswami 2014, 2015, Goswami et al. 2016). Green open hexagons
represent the Ba stars from literature (Shejeelammal et al. 2020, Yang et al.
2016, Allen & Barbuy 2006). LAMOSTJ091608.81+230734.6 (filled triangle) and
LAMOSTJ151003.74+305407.3 (filled square). The dashed line is the least-square
fit to the observed abundances in r-stars.

LAMOSTJ151003.74+305407.3: This star is found to be metal-poor with a
metallicity [Fe/H] ${\sim}$ $-$1.57 and enhanced in carbon with [C/Fe]$>$1\.
With its estimated value of [Ba/Fe]$\sim$1.39 and [Ba/Eu]$\sim$0.25, along
with the enhanced carbon abundance, the star satisfies to be a CEMP-r/s star
(Beers & Christlieb, 2005, Abate et al. 2016). From the position of the star
on the HR diagram, it is found to be a giant. The abundances of heavy elements
in this star are well within the range observed in other CEMP-r/s stars
(Figure 10). In [C/N] versus log(12C/13C) space, this star occupies the same
region as the CEMP stars (Figure 13).

Figure 13: Observed [C/N] and log(12C/13C) ratios of the CEMP stars. Magenta
nine-sided stars, red six-sided crosses, blue starred triangles and green
filled pentagons represent CEMP-s, CEMP-r, CEMP-r/s and CEMP-no stars
respectively from literature (Masseron et al. 2010). LAMOSTJ151003.74+305407.3
(filled square).

From the study conducted by Aoki et al.(2007) for 22 metal-poor stars
($-$3.3$\leq$[Fe/H]$\leq$-1.0) exhibiting strong CH and/or C2 molecular band,
they came up with a new empirical definition for CEMP stars in terms of [C/Fe]
and log(L/L${}_{\odot})$. Based on this definition, there exist a clear
division between the CEMP stars and the carbon-normal metal-poor stars in the
log(L/L⊙) versus [C/Fe] plane. We have demonstrated this in Figure 14. The
star LAMOSTJ151003.74+305407.3 is also shown in the same figure. This star
falls in the region occupied by the CEMP stars.

Figure 14: Observed [C/Fe] ratios as a function of luminosity estimated from
the effective temperature. Red filled hexagons represent CEMP stars from
literature (Aoki et al. 2007 and references therein, Purandardas et al. 2019,
Goswami et al. 2016). Blue crosses represent carbon-normal metal-poor stars
from literature (Aoki et al. 2005, 2007, Cayrel et al. 2004, Honda et al.
2004). LAMOSTJ151003.74+305407.3 (filled square). The dashed line indicates
the dividing line between CEMP and the carbon-normal metal-poor stars.

The Figure 12 shows the position of the star LAMOSTJ151003.74+305407.3 in the
[Eu/Fe] - [Ba/Fe] space. The star is not placed in the bulk of the CEMP-r/s
stars, however, there are a few CEMP-r/s stars in the same region as
LAMOSTJ151003.74+305407.3.

With the knowledge that r-process and s-process are ascribed to different
astrophysical sites (Burbidge et al. 1957), several formation scenarios for
CEMP-r/s stars have been proposed in literature (Cohen et al. 2003, Qian &
Wasserburg 2003, Zijlstra 2004, Barbuy et al. 2005, Wanajo et al. 2006,
Jonsell et al. 2006, Bisterzo et al. 2011 and references therein), most of
them suggesting different independent processes for the r- and s- peculiarity.
One scenario describes that the CEMP-r/s star could have been a secondary in a
binary system formed out of r-process enriched ISM and its s-elements and
carbon enhancement is due to the later pollution from the AGB companion
through the mass-transfer mechanism (Hill et al. 2000, Cohen et al. 2003,
Ivans et al. 2005). But this could not successfully explain the observed
frequency of CEMP-r/s stars. The study by Barklem et al. (2005) have revealed
that an order of 1% of population II stars are CEMP-r/s stars. Cohen et al
(2003) have discussed another scenario that invokes a triple system in which
the star could have been a least massive tertiary, polluted first with the
r-elements from the massive primary exploded as supernova and later polluted
with s-elements by the secondary star evolved into an AGB . This hypothesis
had been discarded, as such a dynamically stable tertiary system is unlikely
to exist. Accretion Induced Collapse (AIC) in a binary system have been
suggested by Qian & Wasserburg (2003) and Cohen et al. (2003), but discarded
since it is physically uncertain with the existing neutrino theories (Qian &
Woosley 1996). Another scenario is a binary picture in which the primary star
evolved through AGB contributed the s-rich material to the secondary star, and
later explodes as Type 1.5 supernova (Zijlstra 2004, Wanajo et al. 2005)
depositing r-material on the surface of the secondary. Abate et al. (2016)
have calculated the frequency of CEMP-r/s stars among the CEMP-s stars for all
these formation scenarios. The theoretical frequency predicted in most of the
scenarios underestimate the observed frequency ($\sim$54% in their sample)
atleast by a factor of five. The simulation based on the hypothesis of
independent enrichment of s- and r- elements could predict a frequency
($\sim$22%) that approaches the observations, however, it fails to reproduce
the observed correlation of observed Ba and Eu abundances in CEMP-r/s stars.
The simulations of Jonsell et al. (2006) for a high neutron density s-process
in AGB star in a binary system also could not reproduce the observed abundance
pattern in CEMP-r/s stars.

Allen et al. (2012) have claimed from their analysis for a sample of CEMP
stars that both CEMP-s and CEMP-r/s stars have same astrophysical origin. A
modified neutron-capture process called intermediate neutron-capture process
(i-process) in AGB stars, first proposed by Cowan & Rose (1977), has been
invoked recently (Dardelet et al. 2014, Hampel et al 2016, 2019, Hansen et al.
2016c) to explain the observed abundance trend of CEMP-r/s stars in the
context of binary-mass transfer scenario. When a substantial amount of
hydrogen rich-material is mixed into the intershell region of the evolved red-
giant stars (Proton Ingestion Episodes, PIE) undergoing helium shell flash, a
significantly high neutron density of the order Nn $\sim$ 1015 \- 1017 cm-3
(intermediate between s- and r- processes) can be produced (Cowan & Rose
1977). A number of sites have been proposed for the PIEs in order for the
i-process nuclesynthesis to take place. Recent simulations have shown that the
neutron-densities of the order of 1012 \- 1015 cm-3 can be achieved in very
low-metallicity (z $\leq$ 10-4), low-mass (M $\leq$ 2M⊙) AGB stars (Fujimoto
et al. 2000, Campell & Lattanzio 2008, Lau et al. 2009, Cristallo et al. 2009,
Campbell et al. 2010, Stancliffe et al. 2011). A similar neutron density is
achieved during the dual core flash (H flash following the PIEs during the He
flash) in low-mass, extremely low-metallicity (z $\leq$ 10-5) stars (Fujimoto
et al. 1990, Hollowell et al. 1990, Lugaro et al. 2009); in the very-late
thermal pulses of post-AGB stars (Herwig et al. 2011, 2014 Bertolli et al.
2013, Woodward et al. 2015); during the thermal pulses of low-metallicity
super-AGB stars (Doherty et al. 2015, Jones et al. 2016); in Rapidly Accreting
White Dwarfs (RAWD) (Denissenkov et al. 2019). Dardelet et al. (2014), Hampel
et al. (2016) and Hampel et al. (2019) considered the possibility of i-process
in their simulation to see whether the CEMP-r/s phenomena could be explained
on the basis of s- and r- process elements produced at a single stellar site.
The i-process models could satisfactorily reproduce the abundance patterns of
twenty CEMP-r/s stars (Hampel et al. 2016) and seven low-Pb Magellanic post-
AGB stars (Hampel et al. 2019).

Hampel et al. (2016) used the single-zone nuclear network calculations to
simulate the properties of the intershell region of low-mass (1 M⊙), low-
metallicity (z = 10-4) AGB star and studied the neutron-capture
nucleosynthesis under the influence of different constant neutron densities
ranging from 107 to 1015 cm-3. The physical input conditions of intershell
region are adapted from Stancliffe et al. (2011) and the composition from
Abate et al. (2015b). The considered temperature and density of the intershell
region are 1.5 $\times$ 108 K and 1600 g cm-3 respectively. Compared to the
classical s-process, at i-process neutron densities, this simulation resulted
in an increased production of heavy s-process and r-process elements, while
similar abundances of light s-process elements, as typically observed for
CEMP-r/s stars (Abate et al. 2015a, Hollek et al. 2015). A range of
temperatures (1.0 $\times$ 108 \- 2.2 $\times$ 108 K) and densities (800 -
3200 g cm-3) have been tested in this simulation, which did not produce
significant changes in the result.

We have compared the observed heavy elemental abundance ratios of the star
LAMOSTJ151003.74+305407.3 with the model yields, [X/Fe], of Hampel et al.
(2016) for a range of neutron densities, n$\sim$109 \- 1015 cm-3. A further
dilution of the accreted material can occur on the surface of the CEMP-r/s
stars just like similarly formed CEMP-s stars (Stancliffe et al. 2007, 2013).
The neutron-density responsible for the observed abundance in this star is
derived by fitting the observed abundance with the dilution factor
incorporated parametric model function:

X = Xi . (1-d) + X⊙ . d

where X is the final abundance, Xi is the i-process abundance, X⊙ is the
solar-scaled abundance and d is the dilution factor. The best fit obtained
along with the neutron density and dilution factor is shown in Figure 15. The
neutron density responsible for the observed abundance of this star is found
to be n$\sim$1012 cm-3, if we assume a single stellar site for the production
of the observed neutron-capture abundance pattern.

Figure 15: The best fit obtained for the parametric model function is
represented by the solid line. The squares with error bars are the observed
abundances in LAMOSTJ151003.74+305407.3.

From the kinematic analysis, we find that this object belongs to the Galactic
halo with a probability of 71%. The spatial velocity estimate of the star is
similar to the typical velocity of halo objects, Vspa$>$180 kms-1 (Chen et al.
2004). Also it satisfies the criteria, [Fe/H]$<$$-$0.90 and VLSR$<$$-$120 km
s-1 (Eggen 1997) to be a halo object.

##  9 CONCLUSIONS

The results from a detailed high-resolution spectroscopic analysis of two
carbon stars identified from LAMOST DR2 are presented. Both the objects are
identified to be CH stars by Ji et al. (2016). Our analysis shows that the
object LAMOSTJ151003.74+305407.3 is a CEMP-r/s star, while the object
LAMOSTJ091608.81+230734.6 is a CH star.

Although, a few light element abundances are available in literature for
LAMOSTJ151003.74+305407.3, we have presented the first time detailed abundance
analysis for both the stars. We have estimated the abundances of 26 elements
along with the carbon isotopic ratio 12C/13C.

Our analysis based on the neutron-density dependent [Rb/Zr] ratio confirms
low-mass for the former AGB companion of the program stars. The kinematic
analysis shows, LAMOSTJ091608.81+230734.6 belongs to the Galactic disc, and
LAMOSTJ151003.74+305407.3 belongs to Galactic halo population.

An i-process parametric model based analysis performed for the CEMP-r/s star
LAMOSTJ151003.74+305407.3, yields a neutron density n$\sim$1012 cm-3 at the
neutron-capture nucleosynthesis site, may indicate that the i-process in the
companion AGB star be responsible for its observed abundance pattern.

##  10 ACKNOWLEDGMENT

We thank the staff at IAO and at the remote control station at CREST,
Hosakotte for assisting during the observations. Funding from the DST SERB
project No. EMR/2016/005283 is gratefully acknowledged. We are thankful to the
referee, Dr. Luca Sbordone, for useful comments and suggestions that have
considerably improved the paper. We are thankful to Melanie Hampel for
providing us with the i-process yields in the form of number fractions and
Partha Pratim Goswami for generating the model fits used in Figure 15. This
work made use of the SIMBAD astronomical database, operated at CDS,
Strasbourg, France, and the NASA ADS, USA. This work has made use of data from
the European Space Agency (ESA) mission Gaia
(https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and
Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Based on data collected
using HESP

Data Availability
The data underlying this article will be shared on reasonable request to the
corresponding author.

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## Appendix

Table A1 : Equivalent widths (in mÅ) of Fe lines used for deriving atmospheric
parameters Wavelength(Å) El $E_{low}$(eV) log gf LAMOSTJ091608.81+230734.6
LAMOSTJ151003.74+305407.3 Ref 4445.471 Fe I 0.087 -5.380 77.50(6.44) - 1
4484.220 3.603 -0.720 91.70(6.40) 88.1(5.72) 1 4489.739 0.121 -3.966
133.5(6.39 - 1 4619.288 3.603 -1.120 84.2(6.60) 76.7(5.95) 1 4635.846 2.845
-2.420 56.2(6.45) - 1 4637.503 3.283 -1.390 86.3(6.53) - 1 4643.464 3.654
-1.290 70.9(6.54) - 1 4690.138 3.686 -1.640 53.7(6.60) - 1 4882.143 3.417
-1.640 82.1(6.80) 55.7(5.94) 1 4907.732 3.430 -1.840 61.7(6.62) - 1 4908.031
4.217 -1.396 39.8(6.58) - 2 4917.229 4.191 -1.180 35.7(6.38) - 1 4924.770
2.278 -2.220 111(6.64) 112(5.85) 1 4939.687 0.859 -3.340 142(6.64) 173(6.02) 1
4967.890 4.191 -0.622 82.8(6.7) - 2 4969.917 4.216 -0.710 56.7(6.31) - 1
4985.253 3.930 -0.560 84.8(6.36) - 2 5022.236 3.984 -0.530 80.8(6.31) 96(6.05)
1 5028.126 3.573 -1.474 71.9(6.59) 42.6(5.78) 2 5049.819 2.278 -1.420
160.4(6.77) - 1 5109.652 4.302 -0.980 62.3(6.77) - 1 5127.359 0.915 -3.307
133.2(6.37) - 1 5159.058 4.283 -0.820 55.3(6.46) - 1 5187.915 4.143 -1.260
54.2(6.71) - 1 5215.179 3.266 -0.933 121(6.67) - 1 5242.491 3.634 -0.840
95.7(6.58) 84.2(5.87) 1 5247.050 0.087 -4.946 - 136.1(5.89) 1 5250.209 0.121
-4.938 120.4(6.63) 131.1(5.82) 1 5253.462 3.283 -1.670 92.1(6.8) 78.6(6.06) 1
5281.790 3.038 -1.020 - 150.6(5.94) 1 5322.040 2.280 -2.840 81.2(6.48)
76.4(5.88) 3 5339.930 3.270 -0.680 132.7(6.63) - 3 5364.858 4.445 0.2200
110.5(6.68) - 3 5365.399 3.573 -1.440 86.7(6.8) 55.7(5.9) 2 5367.479 4.415
0.3500 113.5(6.57) - 1 5369.961 4.370 0.3500 114.3(6.54) - 1 5383.369 4.312
0.5000 130(6.65) - 1 5543.936 4.217 -1.140 58.8(6.74) - 1 5569.620 3.420
-0.490 125.7(6.45) - 3 5576.090 3.430 -0.851 113.5(6.69) - 1 5586.756 3.368
-0.210 157.8(6.71) - 1 5618.631 4.209 -1.380 51.4(6.72) - 1 5701.544 2.559
-2.216 108.5(6.69) 90.7(5.79) 1 5741.848 4.256 -1.730 20.8(6.63) - 1 5753.120
4.260 -0.760 77.6(6.72) 58.6(6.08) 1 5856.088 4.294 -1.640 34(6.79) - 1
5859.586 4.549 -0.386 83.1(6.79) - 2 5862.357 4.549 -0.051 81.7(6.31) - 2
5956.692 0.859 -4.605 95.9(6.62) 81.6(5.81) 1 6003.010 3.881 -1.120 -
47.7(5.82) 1 6082.710 2.222 -3.573 55.2(6.66) 28.3(5.86) 1 6136.994 2.198
-2.950 84.5(6.47) 78.3(5.88) 1 6137.694 2.588 -1.403 157.5(6.76) - 1 6151.620
2.180 -3.290 79.8(6.71) 62.4(6.01) 3 6173.340 2.220 -2.880 101.7(6.72)
108.2(6.17) 3 6180.204 2.727 -2.780 64.8(6.64) 43.2(5.96) 1 6200.314 2.608
-2.437 - 85(5.96) 1 6213.429 2.222 -2.660 113(6.68) 102.7(5.88) 1 6219.279
2.198 -2.433 120.5(6.56) 140.4(6.08) 1 6240.646 2.222 -3.380 70.8(6.49)
54.1(5.84) 1 6252.554 2.404 -1.687 155.1(6.73) 152.2(5.76) 1 6254.258 2.279
-2.480 - 117.3(5.86) 1

The numbers within the parenthesis in columns 5-6 give the derived abundances
from the respective line.

Table A1 continues…
Wavelength(Å) El $E_{low}$(eV) log gf LAMOSTJ091608.81+230734.6
LAMOSTJ151003.74+305407.3 Ref 6280.617 0.859 -4.390 120.5(6.75) - 1 6297.800
2.222 -2.740 90.3(6.36) - 1 6301.500 3.654 -0.672 107.8(6.45) - 2 6322.690
2.588 -2.426 - 99.7(6.08) 2 6335.328 2.198 -2.230 128(6.46) - 1 6393.602 2.432
-1.620 158.3(6.71) - 1 6408.016 3.686 -1.048 93.5(6.52) - 2 6419.950 4.730
-0.090 81.3(6.77) 53.5(6.05) 3 6421.349 2.278 -2.027 - 153.1(5.91) 1 6430.850
2.180 -2.010 151.5(6.63) 160.5(5.84) 3 6481.870 2.278 -2.984 99.5(6.8) - 1
6574.227 0.990 -5.040 73.2(6.81) 69.5(6.23) 1 6575.019 2.588 -2.820 79.4(6.69)
- 1 6592.910 2.720 -1.470 131.8(6.53) - 3 6593.871 2.432 -2.422 107.1(6.55) -
1 6677.989 2.692 -1.470 148.4(6.64) 169(6.07) 1 6739.521 1.557 -4.950
28.6(6.59) - 1 6750.150 2.424 -2.621 113.7(6.82) - 1 4416.830 Fe II 2.778
-2.600 - 71.3(5.95) 1 4629.339 2.807 -2.280 108.3(6.55) - 1 4923.927 2.891
-1.320 159.8(6.68) - 1 5234.620 3.220 -2.240 99.2(6.48) 60.9(5.76) 3 6247.550
3.890 -2.340 57.1(6.6) 20.3(5.98) 3 6369.462 2.891 -4.253 29.7(6.81) - 2
6456.383 3.903 -2.075 67.3(6.56) 30.8(6.03) 1

The numbers within the parenthesis in columns 5-6 give the derived abundances
from the respective line.
References: 1. Führ et al. (1988), 2. Kurucz (1988), 3. Lambert et al. (1996)

Table A2 : Equivalent widths (in mÅ) of lines used for deriving elemental
abundances Wavelength(Å) El $E_{low}$(eV) log gf LAMOSTJ091608.81+230734.6
LAMOSTJ151003.74+305407.3 Ref 5682.633 Na I 2.102 -0.700 109.4(6.15) - 1
5688.205 2.100 -0.450 106.8(5.86) - 1 6154.226 2.102 -1.560 59.90(6.16)
23.10(5.27) 1 6160.747 2.104 -1.260 66.40(5.97) 35.20(5.20) 1 4702.991 Mg I
4.346 -0.666 - 116.9(5.85) 2 5528.405 4.346 -0.620 175.6(7.23) 138.9(6.00) 2
5711.088 4.346 -1.833 92.80(7.01) 64.30(6.20) 2 5690.425 Si I 4.929 -1.870
31.90(6.67) - 3 5948.541 5.083 -1.230 61.40(6.72) - 3 6145.016 5.616 -0.820
31.60(6.38) - 4 4435.679 Ca I 1.890 -0.520 - 119.2(4.77) 5 5349.465 2.709
-1.178 38.20(5.42) - 5 5512.980 2.932 -0.290 69.90(5.36) - 5 5581.965 2.523
-1.833 - 39.60(4.41) 5 5590.114 2.521 -0.710 89.50(5.67) 35.30(4.33) 5
5857.451 2.932 0.23 93.60(5.27) 76.20(4.47) 5 6102.723 1.879 -0.890
102.0(5.26) 103.5(4.59) 5 6166.439 2.521 -0.900 64.10(5.33) - 5 6169.042 2.523
-0.550 79.50(5.26) - 5 6169.563 2.523 -0.270 - 83.30(4.53) 5 6439.075 2.525
0.47 157.5(5.64) - 5 6449.808 2.523 -0.550 86.90(5.37) 70.30(4.61) 5 6471.662
2.525 -0.590 - 56.80(4.48) 5 6493.781 2.521 0.14 117.9(5.27) - 5

The numbers within the parenthesis in columns 5-6 give the derived abundances
from the respective line.

Table A2 continues…
Wavelength(Å) El $E_{low}$(eV) log gf LAMOSTJ091608.81+230734.6
LAMOSTJ151003.74+305407.3 Ref 4512.734 Ti I 0.836 -0.480 84.90(4.04) - 6
4617.269 1.749 0.389 87.00(4.29) - 6 4759.272 2.255 0.514 40.30(3.82) - 6
4840.874 0.899 -0.509 81.20(3.98) 78.00(3.19) 6 5007.210 0.820 0.1700
131.4(4.25) - 6 5024.842 0.818 -0.602 82.10(3.95) 90.20(3.30) 6 5210.386 0.047
-0.884 110.0(3.79) 143.9(3.23) 6 5460.499 0.050 -2.880 27.30(4.26) - 7
5918.535 1.070 -1.460 33.30(4.16) 25.70(3.50) 6 5922.110 1.046 -1.466
35.10(4.17) - 6 5941.751 1.050 -1.510 30.70(4.14) - 6 6303.757 1.443 -1.566
25.00(4.03) - 6 4568.314 Ti II 1.220 -2.650 69.10(3.98) 30.20(3.02) 6 4571.960
1.571 -0.530 - 140.4(3.16) 6 4764.526 1.236 -2.770 - 49.90(3.47) 6 4798.521
1.080 -2.430 72.10(3.62) - 6 4865.612 1.116 -2.610 71.30(3.82) - 6 5185.900
1.890 -1.350 82.10(3.66) 86.30(3.34) 6 5381.015 1.566 -2.080 - 46.00(3.07) 6
5247.565 Cr I 0.961 -1.640 - 81.80(3.60) 6 5296.691 0.982 -1.400 131.8(5.17) -
6 5300.744 0.982 -2.120 - 49.00(3.68) 6 5345.801 1.003 -0.980 150.1(5.12)
128.7(3.64) 6 5348.312 1.003 -1.290 121.6(4.86) 106.5(3.62) 6 5409.772 1.030
-0.720 156.1(4.98) 130.0(3.41) 6 5787.965 3.323 -0.083 67.70(5.30) - 6
6362.862 0.941 -3.623 33.00(5.33) - 5 4686.207 Ni I 3.597 -0.640 64.70(5.44) -
5 4752.415 3.658 -0.700 - 40.90(4.76) 8 4821.130 4.153 -0.850 37.40(5.73) - 8
4953.200 3.74 -0.670 59.80(5.51) 22.00(4.45) 5 4980.166 3.606 -0.110 -
72.90(4.55) 8 5082.350 3.657 -0.540 77.40(5.63) 36.50(4.49) 8 5102.960 1.676
-2.620 - 93.90(4.87) 8 6086.280 4.266 -0.530 53.50(5.79) - 8 6175.360 4.089
-0.530 52.30(5.55) - 8 6177.236 1.826 -3.500 38.40(5.56) - 8 6186.710 4.106
-0.777 41.80(5.62) - 8 6204.600 4.088 -1.130 32.40(5.76) - 8 6327.593 1.676
-3.150 79.10(5.72) - 8 6378.247 4.154 -0.890 31.40(5.57) - 5 6643.629 1.676
-2.300 - 106.6(4.53) 1 4722.150 Zn I 4.029 -0.370 - 34.80(2.66) 9 4810.530
4.080 -0.170 - 33.80(2.46) 9 6362.338 0.150 5.796 29.60(4.11) - 10 4607.327 Sr
I 0.000 -0.570 84.20(3.21) - 11 6435.004 Y I 0.066 -0.820 47.70(2.73)
55.20(2.19) 12 4883.684 Y II 1.084 0.07 145.4(2.37) - 12 5119.112 0.992 -1.360
- 172.7(3.13) 12 5289.815 1.033 -1.850 63.50(2.27) - 12 5402.774 1.839 -0.510
77.50(2.20) - 13 5544.611 1.738 -1.090 64.50(2.36) - 12 5546.009 1.748 -1.110
- 124.9(2.97) 12 5662.925 1.944 0.16 105.3(2.26) - 13 6613.733 1.748 -1.100
74.20(2.49) - 12

The numbers within the parenthesis in columns 5-6 give the derived abundances
from the respective line.

Table A2 continues…
Wavelength(Å) El $E_{low}$(eV) log gf LAMOSTJ091608.81+230734.6
LAMOSTJ151003.74+305407.3 Ref 4739.480 Zr I 0.651 0.230 84.30(3.30)
47.30(1.89) 14 4772.323 0.623 0.044 60.90(2.92) 63.90(2.27) 14 4805.889 0.687
-0.420 40.40(3.06) - 14 6134.585 0.000 -1.280 54.10(3.18) 32.50(2.15) 14
4257.120 Ce II 0.460 -1.116 - 36.80(1.15) 15 4336.244 0.704 -0.564 82.70(2.32)
- 15 4349.789 0.701 -0.107 - 65.90(1.34) 13 4407.273 0.701 -0.741 -
53.70(1.32) 15 4497.846 0.958 -0.349 - 67.00(1.44) 15 4508.079 0.621 -1.238
60.90(2.28) - 15 4628.161 0.516 0.008 120.8(2.43) - 15 4747.167 0.320 -1.246 -
50.80(1.25) 15 4873.999 1.107 -0.892 49.60(2.22) - 15 5187.458 1.211 -0.104
86.20(2.35) - 15 5274.229 1.044 -0.323 - 96.10(1.21) 6 5330.556 0.869 -0.760
72.30(2.23) 59.40(1.53) 15 6034.205 1.458 -1.019 42.10(2.52) - 15 5188.217 Pr
II 0.922 -1.145 26.00(1.59) 20.40(1.18) 15 5219.045 0.795 -0.240 - 77.20(1.02)
16 5259.728 0.633 -0.682 65.90(1.60) 61.90(1.04) 16 5292.619 0.648 -0.300
83.40(1.62) - 16 5322.772 0.482 -0.315 90.30(1.58) 98.00(0.98) 15 6165.891
0.923 -0.205 59.20(1.24) 63.00(0.87) 15 6278.676 1.196 -0.630 22.20(1.23) - 16
4446.384 Nd II 0.204 0.590 - 110.9(1.27) 17 4451.563 0.380 -0.040 115.1(2.04)
- 17 4556.133 0.064 -1.610 76.60(2.13) - 15 4811.342 0.064 -1.140 92.80(2.00)
- 15 4825.478 0.182 -0.860 112.4(2.37) - 15 4947.020 0.559 -1.250 -
58.00(1.42) 15 4961.387 0.631 -0.710 96.00(2.32) 98.20(1.56) 15 5212.361 0.204
-0.870 - 104.7(1.21) 15 5276.869 0.859 -0.440 - 71.80(1.15) 17 5287.133 0.744
-1.300 - 39.30(1.39) 15 5356.967 1.264 -0.250 - 68.20(1.42) 17 5361.510 0.680
-0.400 - 92.40(1.16) 17 5442.264 0.680 -0.910 84.40(2.19) 86.00(1.56) 17
5485.696 1.264 -0.120 77.70(1.96) 68.70(1.28) 17 5603.648 0.380 -1.830
71.70(2.43) - 15 5718.118 1.410 -0.340 - 48.90(1.39) 17 5825.857 1.080 -0.760
65.90(2.08) 50.00(1.40) 15 4458.509 Sm II 0.104 -1.110 76.30(1.45) - 15
4499.475 0.248 -1.413 52.10(1.34) 61.20(1.04) 15 4519.630 0.543 -0.751 -
81.70(1.07) 15 4566.210 0.330 -1.245 57.80(1.38) 63.70(1.01) 15 4615.444 0.544
-1.262 50.60(1.49) - 15 4642.228 0.379 -0.951 71.20(1.45) 88.90(1.15) 15
4674.593 0.184 -1.055 68.10(1.23) - 15 4676.902 0.040 -1.407 62.30(1.28) - 15
4704.400 0.000 -1.562 73.10(1.62) 65.00(0.89) 15 4726.026 0.333 -1.849
31.80(1.42) 27.70(1.02) 15 4854.368 0.379 -1.873 32.10(1.49) - 15

The numbers within the parenthesis in columns 5-6 give the derived abundances
from the respective line.
References: 1. Kurucz et al. (1975), 2. Lincke et al. (1971), 3. Garz (1973),
4\. Schulz-Gulde (1969), 5. Kurucz (1988), 6. Martin et al. (1988), 7. Smith
et al. (1978), 8. Führ et al. (1988), 9\. Warner (1968), 10. Lambert et al.
(1969), 11. Corliss et al. (1962), 12. Hannaford et al. (1982), 13. Cowley et
al. (1983), 14. Biemont et al. (1981), 15\. Meggers et al. (1975), 16.
Lagehaling et al. (1976), 17. Ward et al. (1985)