#  Historical Context and Key Features of
Digital Money Tokens

Shreepad Shukla Chief Technology Office Barclays

(August 25, 2020)

###### Abstract

Digital money tokens have attracted the attention of financial institutions,
central banks, regulators, international associations and fintechs. Their
research and experimentation with digital money tokens has included creating
innovative technical and operational frameworks. In this paper, we present a
‘money tree’ which places this recent concept of digital money tokens into a
historical context by illustrating their evolution from more traditional forms
of money. We then identify key features of digital money tokens with options
and examples. We hope this paper will be of interest to the financial services
industry and we look forward to feedback.

##  1 Introduction

Research and experimentation with digital money tokens is being conducted by
financial institutions [29], central banks [38, 34], regulators [12, 40],
international associations [17, 42] and fintechs [18, 30]. As an emerging
technology, the innovative technical and operational frameworks are often
bespoke. The terminology used to describe forms of digital money tokens is
also inconsistent across these frameworks.

It can therefore be difficult to identify and understand the key features that
distinguish different forms of digital money tokens, creating challenges in
specifying and communicating new products and also potentially creating
inappropriate opportunities for regulatory arbitrage across jurisdictions. To
address this, some industry bodies are exploring standard taxonomies for
digital money tokens. For example: (i) the Global Financial Markets
Association (GFMA) has proposed an initial starting point for a classification
of crypto-assets in their response [21] to a Basel Committee on Banking
Supervision (BCBS) consultation on the treatment of crypto-assets [4] and also
in their response [22] to an FSB consultation on challenges raised by global
stablecoins [17] and (ii) the Association for Financial Markets in Europe
(AFME) has recommended the publication of a more detailed taxonomy on the
classification of crypto-assets in their response [2] to the European
Commission consultation on a framework for crypto-asset markets [12].

This paper provides a historical context for digital money tokens by placing
them within a ‘money tree’ illustrating their evolution from more traditional
forms of money. We then identify key features of digital money tokens with
options and examples.

We hope this money tree and list of key features will be of interest to the
financial services industry. We look forward to feedback and continuing
industry collaboration on the classification of digital money tokens.

##  2 The Money Tree

Money is one of the fundamental inventions that support human societies and as
a result its history has been studied extensively [33, 28, 35, 37, 23], from
the first forms of account-based money and commodity money, through the
development of fiat money and on to new digital forms of money.

While the history of money has been documented in considerable detail, we
constructed a new summary visual representation to help us communicate the
evolution of digital money tokens. This covers fours eras: the ancient and
post-ancient eras (3000 BCE - 1300), the modern era (1300 - 1950), and the
digital era (1950 - present). This is presented as the ‘money tree’ in Figure
1 with the hope that others may also find it useful.

Figure 1: The ‘money tree’ depicts the evolution of forms of money from the
ancient era to the digital era. It branches out from the base into two
fundamental forms of money - tokens to the left and account claims to the
right. Examples are given in the era when they first appeared. Note some
examples (such as shells and some crypto-assets) are not currently broadly
accepted as money.

###  2.1 Introduction to Money

Money can be defined by the functions it serves in society [37], which [8]
describes as:

  * •

a _store of value_ with which to transfer purchasing power from today to some
future time;

  * •

a _medium of exchange_ with which to make payments for goods and services; and

  * •

a _unit of account_ with which to measure the value of a particular good,
service, saving or loan.

As money is a social convention [8], performing the above functions is not
sufficient for something to be considered money because it also needs to be
readily and easily accepted by others.

The money tree branches out from the base into two fundamental forms of money:
tokens111We use the term ‘token’ to refer to all forms of money that can be
transferred directly from one party to another without relying on an
intermediary. However, note there is currently no commonly agreed definition
for this term, e.g. some do not consider commodity money to be a token [33],
some consider the term ‘object’ to be more suitable than ‘token’ [1], and some
consider crypto-assets to be an account-based form of money [32]. and account
claims, or more simply, accounts [33]. Token-based money (e.g. cash) can be
transferred directly from one party to another without relying on an
intermediary, but account-based money (e.g. money in a bank account) cannot be
transferred directly from one party to another and instead depends on
intermediaries (e.g. the bank(s) where the accounts are held) to effect
transfers. Another key distinction between token-based money and account-based
money is the form of verification needed when it is transferred, as described
below (adapted from [11]):

  * •

Token-based money (or payment systems) rely critically on the ability of the
payee to verify the validity of the payment object. With cash a key risk is
counterfeiting, while in the digital world the key risk is whether the token
or ‘coin’ is genuine or not (electronic counterfeiting) and whether it has
already been spent.

  * •

By contrast, systems based on account money depend fundamentally on the
ability to verify the identity of the account holders. A key concern is
identity theft, which allows perpetrators to transfer or withdraw money from
accounts without permission. Identification is needed to correctly link payers
and payees and to ascertain their respective account histories.

###  2.2 Evolution of Account-based Money

Account-based money appears to pre-date token-based money, based on available
information on ancient civilisations [33, 35]. The evolution of account-based
money is tied closely to the evolution of account holding institutions.

The ‘Account’ side of the money tree depicts the following developments:

  * •

_Ancient and Post-Ancient Eras:_ Accounts in the ancient and post-ancient eras
were held at trusted institutions, such as temples in Mesopotamia and Greece,
where people could deposit precious metals or record credits in a currency.
These deposits and credits were recorded on, for example, clay and marble
tablets [35, 23].

  * •

_Modern Era:_ Depositories developed into dedicated financial institutions
during the Italian Renaissance, leading to the creation of official state
banks. Account holding institutions evolved into three main types over the
course of the modern era, partly in response to the growth of currencies:
central banks, regulated financial institutions, and unregulated or non-
financial institutions such as goldsmiths and early merchant banks [23]. Each
of these entities would hold accounts, usually denominated in a currency, with
differing levels of access and trust. Transactions were recorded on paper
ledgers using the ‘double-entry bookkeeping’ system. While currencies were
traditionally backed by commodity assets such as gold, towards the end of the
modern era this relationship was removed with the introduction of ‘fiat money’
i.e. money that is not convertible to gold or any other asset [3].

  * •

_Digital Era:_ The digital era has seen the development of digitised accounts
that are well understood and widely deployed. Transactions continue to be
recorded using the ‘double-entry bookkeeping’ system using digital
technologies. These have enabled account holders to have greater access to
their money through digital and physical channels [8]. While central banks and
regulated financial institutions have digitised accounts and introduced new
digital products (e.g. cards), the unregulated or non-financial institution
space has also seen a rapid evolution of new digital products (e.g. mobile
money, stored value digital wallets) from recent entrants such as
telecommunication and technology firms.

###  2.3 Evolution of Token-based Money

The ‘Token’ side of the money tree branches into two forms that have existed
from the ancient era to the digital era: ‘tokenised claims’ that represent a
claim on an entity or right on an underlying asset (e.g. currency notes) and
‘claimless tokens’ that don’t represent any such claim or right (e.g. coins).
For tokenised claims, note the nature of the entity or asset on which the
claim or right lies can be an important factor although, for simplicity, this
has not been elaborated in the money tree.

The ‘Token’ side of the money tree depicts the following developments:

  * •

_Ancient and Post-Ancient Eras:_ In the ancient and post-ancient eras,
claimless tokens took the form of shells, beads or metal coins. Tokenised
claims, such as paper promissory notes and currency notes issued in ancient
China, represented a claim on the issuing merchant or monarchy [35].

  * •

_Modern Era:_ The growth of currencies led to modern forms of money tokens
created by dedicated financial institutions, non-financial institutions,
central banks and governments. These entities issued metal coins and notes,
representing the modern forms of claimless tokens and tokens that represented
a claim or right [37]. Some tokens represented a claim on account-based forms
of money (e.g. negotiable instruments drawn on banks). Maintaining the value
of the currency against the value of the metal coins and honouring the claims
on notes issued were challenges for the issuers. This was due to variations in
the subjective value of the metals in the coins and poor management of the
relationship between notes issued and the underlying assets which backed them
[8]. With the introduction of fiat money towards the end of the modern era,
the nature of the entity issuing the tokens became vital to determining a
token’s ability to serve the three functions of money (i.e. store of value,
medium of exchange and unit of account).

  * •

_Digital Era:_ The digital era has seen the birth of new digital forms of
money tokens [8]. Similar to tokens in previous eras, digital money tokens can
either be tokenised claims (e.g. central bank digital tokens [11]) or
claimless tokens (e.g. some ‘cryptocurrencies’). Again, the nature of the
issuing entity remains critical to determining the token’s ability to serve
the three functions of money.

##  3 Key Features of Digital Money Tokens

The field of digital money tokens is evolving rapidly. The terminology used by
financial institutions, central banks, regulators, international associations
and fintechs to describe forms of digital money tokens is not always
consistent. This can make it challenging to understand the key features that
distinguish different forms of digital money tokens being developed and to
evaluate new product propositions. The current absence of a generally agreed
taxonomy may also lead to a fragmented regulatory approach [44] potentially
creating inappropriate opportunities for regulatory arbitrage [42].

The seminal work by Bech and Garratt [5] (that builds on earlier work [10, 6])
discusses and visually represents a taxonomy for money in the form of a ‘money
flower’, which is described in the next section. It has since been heavily
referenced (e.g [31, 43]) and also adapted (e.g. [11, 36]), becoming an key
contribution to the taxonomy of money. However, this high-level taxonomy does
not consider all of the key features of digital money tokens and so does not
fully distinguish between these forms of money.

Adrian and Mancini-Griffoli presented a visual taxonomy for money [1]
(coincidentally also named ‘money tree’) based on four features: type (claim
or object), value (redemption rate for claims, unit of account for objects),
the backstop for claims (government or private), and technology used
(centralised or decentralisaed). This taxonomy comprises five means of
payment: central bank money, crypto-currency, b-money (issued by banks),
e-money (offered by new private sector providers), and i-money (issued by
private investment funds). However, their use of ‘claim’ and ‘object’ as the
two distinct and fundamental types of money leads to listing cash and central
bank digital currencies as examples of ‘object’ money even though they are
claims on central banks.

The Token Taxonomy Framework (TTF) [27] is a taxonomy for digital tokens
developed by the InterWork Alliance, an industry association with members from
the technology and financial industries. The TTF is based on features such as
fungibility, unit of measure (fractional, whole or singleton), value
(intrinsic or referential), uniqueness and the nature of the supply (fixed,
capped-variable, gated or infinite) that are combined with behaviours (e.g.
transferable, mintable, divisible) to create a set of base token types. These
features, behaviours and base token types are generic and apply to money
tokens, securities tokens and utility tokens. This taxonomy does not appear to
include all of the key features of digital money tokens and is more focused on
token implementation mechanics.

Efforts by regulators and international associations to develop taxonomies for
digital tokens began in response to increasing consumer adoption of
‘cryptocurrencies’. This included a Financial Action Task Force (FATF) report
[15] defining ‘virtual currencies’ and presenting a taxonomy based on
convertibility and centralisation. These efforts to develop taxonomies
continued partly in response to an increasing number of Initial Coin Offerings
(ICOs). For example, guidelines by the Swiss Financial Market Supervisory
Authority (FINMA) [39] used the term ‘payment token’ and advice from the
European Banking Authority (EBA) to the European Commission [13] used the term
‘payment/exchange/currency token’. The UK’s Financial Conduct Authority (FCA)
took a different approach in its final guidance on crypto-assets [16] by
defining a taxonomy for tokens based on whether they are regulated. The two
main categories were ‘regulated tokens’ (including ‘security tokens’ and
‘e-money tokens’) and ‘unregulated tokens’ (including ‘exchange tokens’ and
‘utility tokens’).

Recent consultations by BCBS [4], the European Commission [12] and the FSB
[17], revised guidance from FINMA [40] and reports from BIS’ Committee on
Payments and Market Infrastructures (CPMI) [20] and the International
Organization of Securities Commissions (IOSCO) [42] in response to the rise of
‘stablecoins’ provided a more detailed view of features of digital money
tokens. These features included stabilisation mechanisms, nature of asset
linkage, type of asset linked, nature of the claim, accessibility, reach,
redemption mechanics, permissioning model, transaction record model, and
dependence on existing payments infrastructure. The IOSCO report states that
“…many so-called stablecoins are neither ‘stable’ nor ‘coins’ in the true
sense of either word. So, whilst stablecoin is a marketing term that has been
widely adopted by industry, more neutral terms, may be more accurate starting
points for regulatory analysis”.

The European Central Bank (ECB) has defined a visual taxonomy for stablecoins
[14] in the form of a ‘crypto-cube’ based on three features: the existence of
an issuer responsible for satisfying any attached claim, whether decision-
making responsibilities over the stablecoin initiative are centralised, and
what underpins the value of a stablecoin (currency, other off-chain assets,
on-chain assets or expectations). This taxonomy comprises four types of
stablecoins: tokenised funds, off-chain collateralised stablecoins, on-chain
collateralised stablecoins and algorithmic stablecoins. Although the ‘crypto-
cube’ is a useful visual tool for categorising stablecoins, it does not
include all of the key features of digital money tokens.

GFMA’s initial approach for a classification of crypto-assets [22] is based on
four features: issuer, mechanism or structure underlying the asset value (e.g.
pegged to an underlying asset or access to a service), rights conferred (e.g.
cash flows, redemption), and nature of the claim (e.g. claim on issuer or
claim on underlying asset). They propose a taxonomy comprising six types of
crypto-assets: ‘cryptocurrencies’, ‘value-stable crypto-assets’, ‘security
tokens’, ‘settlement tokens’, ‘utility tokens’, and ‘other crypto-assets’.

###  3.1 The Money Flower

Bech and Garratt created the money flower [5] to support a new taxonomy of
money by showing how forms and specific examples of money fit into the overall
monetary landscape. In this section, we reproduce CPMI’s adaption of the money
flower [11] in Figure 2 which depicts a taxonomy based on four features:
issuer (central bank or not), form (digital or physical), accessibility
(widely or restricted), and technology (account-based or token-based).

Figure 2: The Venn-diagram illustrates the four key properties of money. CB =
central bank, CBDC = central bank digital currency (excluding digital central
bank money already available to monetary counterparties and some non-monetary
counterparties). Private digital tokens (general purpose) include crypto-
assets and currencies, such as bitcoin and ethereum. Source: Central Bank
Digital Currencies, CPMI Papers. ©Bank for International Settlements 2018.

CPMI describes other properties of money that are not depicted on their money
flower, including 24x7 availability, anonymity, whether peer to peer transfers
are supported, whether interest is borne, and if any limits are imposed on
holdings.

Digital money tokens are represented on CPMI’s money flower as the
intersection of the ‘Digital’ and ‘Token-based’ ellipses, i.e. the four areas
labelled ‘CB digital tokens (wholesale only)’, ‘CB digital tokens (general
purpose)’, ‘Private digital tokens (wholesale only)’, and ‘Private digital
tokens (general purpose)’.

###  3.2 Identifying the Key Features

Mark Carney’s speech on ‘The Future of Money’ [8] explored the ability of
‘cryptocurrencies’ to serve the three functions of money, i.e. store of value,
medium of exchange and unit of account. In this section, we adopt a similar
approach in order to evaluate the significance of the features of digital
money tokens and identify the key features as follows:

  * •

_Issuer:_ An identifiable entity that controls the issuance of tokens, even if
issued via a decentralised ‘smart contract’ 222We use the term ‘smart
contract’ to refer to “ _…an automatable and enforceable agreement.
Automatable by computer, although some parts may require human input and
control. Enforceable either by legal enforcement of rights and obligations or
via tamper-proof execution of computer code_ ” [9] or an approved
intermediary. While some digital money token arrangements do not have a
specific issuer, in other arrangements an identifiable entity exercises
control over this process even if token issuance is handled by a decentralised
smart contract or an approved intermediary. The nature of this entity, its
decisions regarding other key features (nature of claim, asset linkage, type
of linked asset, redemption etc) and its ability to operate the token
arrangement appropriately determine whether the digital money tokens issued
can fulfill all three functions of money. As a result, this is likely to be
the most significant feature.

  * •

_Claim, Right or Interest:_ The nature of the claim, right or interest arising
from ownership or control of a token. Depending on the digital token
arrangement, the ownership of digital money tokens may or may not confer the
owner with a claim, right or interest. The nature of this claim, right or
interest can influence the token’s ability to serve as a store of value.

  * •

_Asset Linkage:_ The nature of the linkage, if any, between the value of the
token and an underlying asset or basket of assets. The linkage can be to part
or all of an underlying asset. The nature of this linkage can affect the
stability of the digital money tokens’ value and can thereby influence the
token’s ability to serve as a store of value.

  * •

_Type of Linked Asset:_ The type of asset linked to the token. The type of the
linked asset can influence the token’s ability to serve as a store of value
because volatility in the value of the asset will affect the value of the
tokens. In addition, some linked asset types (e.g. cash denominated in a fiat
currency) can also naturally serve as an underlying unit of account.

  * •

_Redemption Rate 333We use the term ‘redemption rate’ instead of ‘exchange
rate’ [20] because ‘exchanging’ the token is a more general term that includes
other actions such as buying other assets from any entity using a token:_ The
rate at which tokens are redeemed by the issuer or an approved intermediary
against a pre-determined asset or set of assets. If the digital money token
arrangement supports redemption of issued tokens, whether the redemption rate
is fixed or variable impacts the stability of the token’s value, which can
influence the token’s ability to serve as a store of value.

  * •

_Denomination:_ The unit of account used to quantify token ownership. The
denomination of a digital money token can affect its ability to serve as a
unit of account. For example, retailers that quote prices in
‘cryptocurrencies’ typically update them frequently due to their volatility.

  * •

_Accessibility:_ Accessibility distinguishes between tokens that are available
everywhere to everyone and tokens that are restricted to certain agents or
uses. This feature refers to restrictions, typically imposed by the issuer,
such as only specific types of entities that can participate (e.g. regulated
financial institutions) or only specific uses (e.g. wholesale banking
transactions). Accessibility can influence the extent to which digital money
tokens can serve as a medium of exchange.

As discussed previously, money is a social convention and it is therefore not
sufficient for a digital money token to have all the above key features to be
considered money because it also needs to be readily and easily accepted.

In addition to these key features, there are other features such as
availability, anonymity, whether interest is borne, holding limits, reach,
permissioning model, transaction record model, nature of supply, and
dependence on existing payments infrastructure. While these features represent
important design choices, they are likely to be of lesser significance because
they are either subsumed under the above key features or have a smaller impact
on whether a given digital money token can serve the three functions of money.

###  3.3 Options for the Key Features

In order to develop a robust taxonomy, a list of key features and options is
necessary. We now examine the potential options for each of the key features
of digital money tokens, as summarised in Figure 3.

Figure 3: Summary of key features and options for digital money tokens

Table LABEL:table:digitaltokenmoney-features-options below describes these
options for key features of digital money tokens, together with illustrative
examples.

Feature/Option |  Description |  Example(s)
---|---|---
_Issuer_
Central bank |  Financial institution with privileged control over the production and distribution of money |  e-Krona [38]
Regulated Financial Institution (FI) |  Banks, Financial Market Infrastructures (FMIs) and other regulated FIs |  USC [18], JPM Coin [29]
Other |  Unregulated or non-financial entity |  Tether [41]
None |  No specific entity controls the issuance of tokens, issuance is managed entirely algorithmically |  Bitcoin
_Claim, Right or Interest_
Claim on issuer |  Legal claim on the issuer or an approved intermediary, typically exercised via instruction to the issuer or an approved intermediary |  e-Krona, JPM Coin
Right or interest via issuer |  No legal claim on the issuer, but right or interest (e.g. share of underlying asset) exercised via instruction to the issuer or an approved intermediary e.g. to redeem share |  USC
No claim on, right or interest via issuer |  No legal claim on the issuer, no right or interest exercised via issuer or no specific issuer |  Bitcoin
_Asset Linkage_
Asset backed |  Tokens are fully backed by underlying assets that are typically held or controlled by the issuer or an approved intermediary |  USC, Single-currency Libra Coin [30]
Asset pegged |  Tokens are not fully backed by assets but their value is fixed against one or more assets, typically by leveraging the financial strength and stability of the issuer |  -
Asset referenced |  Tokens are not fully backed by or pegged to assets but refer to assets to determine value |  Dai [19]
No asset linkage |  Tokens are not fully backed by, pegged to or referenced to any assets |  Bitcoin
_Type of Linked Asset_ 444We use the terms ‘tangible assets’, ‘cash’,
‘financial assets’ and ‘intangible assets’ based on the International
Financial Reporting Standards (IFRS). The treatment of ‘crypto-assets’ is
based on guidance from the IFRS Interpretations Committee [24] and the
Institute of Singapore Chartered Accountants [26]. Linkage to an asset is
different from linkage to a basket of assets of the same type, but these
options are listed together for brevity
Cash |  Tokens are linked to cash denominated in a fiat currency |  USC
Non-cash financial asset(s) |  Tokens are linked to a non-cash financial asset or a basket of such financial assets (e.g. securities, contractual rights) |  ArCoin [7]
Non-financial crypto-asset(s) |  Tokens are linked to a crypto-asset or a basket of crypto-assets that do not represent cash or other financial assets (e.g. Ether) |  Dai
Other intangible asset(s) |  Tokens are linked to an intangible asset not covered by the above options (e.g. intellectual property, digital goods) or a basket of such assets |  -
Tangible asset(s) |  Tokens are linked to a tangible asset (e.g commodities, real estate) or a basket of tangible assets |  PMGT [25]
Hybrid |  Tokens are linked to a basket of two or more of the above asset types |  Single-currency Libra Coin
_Redemption Rate_
Fixed |  Tokens can be redeemed against pre-determined assets at a fixed rate |  USC, JPM Coin
Variable |  Tokens can be redeemed against pre-determined assets at a variable rate |  Multi-currency Libra Coin
Not applicable |  Tokens cannot be redeemed or there is no issuer |  Bitcoin
_Denomination_
Fiat currency |  Tokens are denominated in a fiat currency or are redeemable in a fiat currency at a fixed rate |  e-Krona, USC
Other |  Tokens have their own independent denomination |  Multi-currency Libra Coin
_Accessibility_
General purpose |  Tokens are intended for general use, including both retail and wholesale purposes |  e-Krona, Libra Coin
Wholesale |  Tokens where access is restricted, for example to FIs or selected clients of FIs |  USC, JPM Coin
|  |
Table 1: The options for each of the key features of digital money tokens,
with brief descriptions and illustrative examples.

##  4 Summary

In this paper, we presented a ‘money tree’ which placed the recent concept of
digital money tokens into a historical context by illustrating their evolution
from more traditional forms of money. We then identified the key features of
digital money tokens with options and examples. The money tree and the list of
key features and options contributes to the design space for the emerging
field of digital money tokens. We hope this paper will be of interest to the
financial services industry as it innovates with digital money tokens. We
welcome feedback and look forward to continuing industry collaboration on the
the classification of digital money tokens. In particular, international
collaboration between financial institutions, central banks, regulators,
associations and fintechs will enable the development of global standards.

## Acknowledgements

The author would like to thank Lee Braine (Barclays) for direction, input and
review of this paper. Thanks are also due to Nicole Sandler (Barclays), Vikram
Bakshi (Barclays), Richard Barnes (Barclays) and Simon Gleeson (Clifford
Chance) for their helpful feedback.

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[1] [1]

[1]

[cor1]Corresponding author at: Institute of High Energy Physics, Chinese
Academy of Sciences, Beijing 100049, China.

# Development of water extraction system for liquid scintillator purification
of JUNO

Jiaxuan Ye<EMAIL_ADDRESS>Jian Fang<EMAIL_ADDRESS>Tao Hu  Li Zhou  Wei Hu
Wanjin Liu  Yayun Ding  Meangchao Liu  Boxiang Yu  Xilei Sun  Lijun Sun
Yuguang Xie  Xiao Cai  Insitute of High Energy Physics, Chinese Academy of
Sciences (CAS), Beijing 100049, China  University of Chinese Academy of
Sciences, Beijing 100049, China  State Key Laboratory of Particle Detection
and Electronics, (Beijing 100049, HeFei 230026), China

###### Abstract

The Jiangmen Underground Neutrino Observatory (JUNO) uses 20k tons of liquid
scintillator (LS) to detect neutrinos. The content of radioactive substances
in the liquid scintillator will affect the experimental results. JUNO will use
counter current water extraction to reduce the radioactive metal ions inside
the LS. In this article, The factors that affect the final water extraction
like the partition coefficient and the factors that affect it, the optimal
mass transfer droplet size, the flow rate ratio, theoretical stage and
different working mode (LS as continuous phase or dispersed phase) have been
studied. We built counter current extraction prototype in the laboratory and a
pilot plant in Daya Bay. We not only study the factors above, but also get a
lot of engineering experience that worth sharing.

###### keywords:

liquid scintillator water extraction purification JUNO neutrino experiment

##  1 Introduction

The Jiangmen Underground Neutrino Observatory (JUNO) is a further exploration
of neutrino after the Daya Bay Reactor Neutrino Experiment [1]. JUNO is a
multi-purpose neutrino observatory. The main goal is to determine the neutrino
mass hierarchy as well as to precisely measure neutrino oscillation parameters
[2].

JUNO plans to use 20k tons liquid scintillator(LS) as sensitive medium with an
unprecedented target energy resolution of 3% at 1 MeV. The LS in JUNO is
compound organic liquid, containing linear alkyl benzene(LAB) as primary
solvent, 2,5-diphenyloxazole (PPO) as luminous matter, and tiny amount of
1,4-bis(2-methylstyryl)benzene (bis-MSB) as wavelength shifter [3]. LAB-based
LS has high flash point so is safe to handle. JUNO also has stringent
requirements on the radio-purity of the LS in order to reach different physics
potentials. For example, in order to study reactor neutrinos, the LS
background would be 238U and 232Th less than $1\times 10^{-15}$ g/g and 40K
less than $1\times 10^{-16}$ g/g. Besides, in order to study solar neutrinos,
the LS background would be 238U and 232Th less than $1\times 10^{-17}$ g/g and
40K less than $1\times 10^{-18}$ g/g [2]. Otherwise, these backgrounds will
affect the detector’s ability to distinguish neutrino events. Thus the
critical point is to reduce the radioactive background in the process of LS
production and purification.

Other large-scale underground neutrino experiments using LS as detection
medium, such as Borexino [4] in Italy, SNO+ [5] in Canada and KamLAND in Japan
[6], all have similar but different purification methods. Due to the enormous
amount of LS, it presents a specific challenge for JUNO to achieve similar
level of low background, but with $>$20 times higher LS to purify. JUNO plans
to use multiple methods to remove radioactive impurities from LS:
distillation, water extraction and gas stripping. Distillation can separate
low volatile impurities from LS raw materials [7]. Water extraction is the
method that using the solubility difference of metal ions between water and
LS, to absorb radioactive metal ions in LS. Gas stripping is to remove
radioactive gases in LS, like Ar, Kr, Rn, etc [7]. As an important
purification method, water extraction does not change the LS component, thus
can be applied as an online purification method during neutrino experiment
running.

##  2 Principle of water extraction

Water extraction is a type of liquid-liquid extraction, which is often used to
extract solute in one liquid between two immiscible liquids based on the
different solubility. In JUNO, Water extraction is used to remove radioactive
impurities, mainly 238U, 232Th and 40K, in organic LS. Polar heavy metal ions
have large solubility in polar water than non-polar LS [8].

Water has many advantages as an extractant. Water is compatible with JUNO LS,
besides, it is cheaper and can be used in large quantities since JUNO has 20k
tons’ LS. The waste water is easy to handle and has no impact on the
environment.

In JUNO, water extraction system will run in counter-current mode. Large
industrial system often employs column extraction with multiple theoretical
stages rather than single batch extraction to achieve more efficient
separation. There are many factors that will affect the extraction efficiency,
such as the height of the tower, additional energy (like stirring), the design
of the tower internals, the flow rate of water($F_{W}$) and the flow rate of
LS($F_{LS}$), and the temperature during extraction. These factors will affect
the theoretical stages of extraction. Theoretical stages is a mathematical
description, which means that the extraction reaches equilibrium.

The partition coefficient $K_{D}$ is a key parameter to determine the water
extraction efficiency of the system. It is defined as the ratio of the solute
concentration in water phase ($C_{w}$) divided by the concentration in LS
phase ($C_{LS}$) after reaching one theoretical stage. $K_{D}$ is a function
of multiple factors, such as temperature, pressure and ion species. In
addition, the choice of continuous phase and dispersed phase may also affect
the final efficiency in column extraction.

$K_{D}=\frac{C_{W}}{C_{LS}}$ (1)

Figure 1: absorption spectrum after four system

Fig. 1 is a schematic diagram of counter-current extraction. ${C_{W}^{0}}$ and
${C_{LS}^{0}}$ represents the concentration of solute in the initial water
phase and LS phase. The numbers 1, 2, …, N in the picture represent the
theoretical stages. ${C_{LS}^{N}}$ represents the concentration of solute
after Nth stages of extraction. For each theoretical stages, two formulas can
be listed according to material balance and definition of partition
coefficient. Add the formulas of N material balance together to get eq. (2):

$C_{LS}^{0}-C_{LS}^{N}=\frac{F_{W}\cdot{K_{D}}}{F_{LS}}\cdot\left(C_{LS}^{1}-\frac{C_{W}^{0}}{K_{D}}\right)$
(2)

After replacing the right side of each material balance formula with the
partition coefficient formula, N formulas iterate can be obtained eq. (3):

$C_{LS}^{0}-C_{LS}^{1}=\left(\frac{F_{W}\cdot
K_{D}}{F_{LS}}\right)^{N}\cdot\left(C_{LS}^{N}-\frac{C_{W}^{0}}{K_{D}}\right)$
(3)

Using formulas (2) and (3), the concentration of solute in the
LS(${C_{LS}^{N}}$) after N-stage counter-current extraction can be obtained as

$C_{LS}^{N}=\frac{\left(1-\frac{F_{LS}}{F_{W}\cdot
K_{D}}\right)\cdot\left(C_{LS}^{0}-\frac{C_{w}^{0}}{K_{D}}\right)}{\left(\frac{F_{W}\cdot
K_{D}}{F_{LS}}\right)^{N}-\frac{F_{LS}}{F_{W}\cdot
K_{D}}}+\frac{C_{W}^{0}}{K_{D}}$ (4)

The concentration of solute in the final LS (${C_{LS}^{N}}$) depends on the
number of theoretical stages, the partition coefficient, and the ratio of the
flow rate of LS to water. In addition, the initial solute concentration of
water also have effects.

The goal for this development program is to measure the factors above and gain
experience in order to guide the design of full-scale system for JUNO based on
the results after experiments.

##  3 Laboratory study

Much efforts have been put to understand the purification efficiency for JUNO
LS purification. As the input to water extraction is already distilled, the
content of various radioactive metal ions is expected to be at trace level,
and is far below the saturated solubility.

###  3.1 General method

The typical ${}^{238}\text{U}$/${}^{232}\text{Th}$ contamination in JUNO LS
are from ${10^{-13}}$ to ${10^{-14}}$ g/g. It is impractical to measure
${}^{238}\text{U}$/${}^{232}\text{Th}$ content less than $10^{-14}$ g/g at
laboratory level [9]. Instead of knowing the water extraction efficiency of
${}^{238}\text{U}$/${}^{232}\text{Th}$, we adopt the method of using
${}^{212}\text{Pb}$ an proxy to evaluate the water extraction efficiency [10].
The method for loading ${}^{212}\text{Pb}$ into LS and setup is descried
elsewhere [9]. Here we give a brief review.

Our initial goal is to study the extraction efficiency of
${}^{238}\text{U}$/${}^{232}\text{Th}$, and then obtain the factors like
partition coefficient of ${}^{238}\text{U}$/${}^{232}\text{Th}$ to guide the
final full scale water extraction system design, but a large detector is
needed for measurement, so a pilot plan is required. The design of the pilot
plant also requires partition coefficient. Since the solubility of uranium and
thorium salt compounds in water is higher than that of lead salt
compounds[11], it is assumed that the partition coefficient of uranium and
thorium is not lower than that of lead. Therefore, ${}^{212}\text{Pb}$
extraction efficiency can be used to guide the design of pilot plant. On the
other hand, ${}^{212}\text{Pb}$ has a short half life of 10.6 h, allowing it
to be measured easier than ${}^{238}\text{U}$/${}^{232}\text{Th}$ through
decay products. We use ${}^{220}\text{Rn}$ to load ${}^{212}\text{Pb}$ into
LS. ${}^{212}\text{Pb}$ is the longest lived daughter product through the
${}^{220}\text{Rn}$ decay chain. The number of ${}^{212}\text{Pb}$ decays can
be measured via the correlated $\beta-\alpha$ emission from
${}^{212}\text{Bi}$-${}^{212}\text{Po}$ cascade decay. The short
characteristic halflife of 300 ns is extremely useful to suppress background.
Because of the short half-life, ${}^{212}\text{Pb}$ loading at $10^{-18}$ g/g
level could still be measured through their decay products. To set the scale,
${}^{212}\text{Pb}$ loading at $10^{-17}$ g/g in 100 ml of LS gives a decay
rate of $\sim$40 Bq.

Continuously fed Rn220 into the LS bubble bottle to 74.2 hours(7 half-life of
${}^{212}\text{Pb}$), ${}^{212}\text{Pb}$ concentration in LS achieved
balance. In the experiments of this paper LS all had loaded
${}^{222}\text{Rn}$ for 74.2 hours in advance. The LS sample is placed in a
cylindrical quartz bottle, which is further placed into a dark box. Two 2-inch
PMTs (XP2020, HZC) were mounted on each side of quartz bottle. Quartz bottle
was 5 cm in diameter and 1 cm in thickness, containing 17.1 g LS. Around the
PMTs and LS bottle placed 5cm in thickness low-radioactivity lead bricks to
shield part of environment gamma and cosmic ray.

A CAEN Flash ADC DT5751 (10 bit, 1 GHz sampling rate) was used for data
acquisition. A coincidence between two PMTs is required for trigger. Once
triggered, event waveform with total length of 2000 ns is recorded. Offline
analysis select candidate events with two pulses separated within 5 ns. The
total background event rate is 0.26 Hz.

###  3.2 Benchtop test

To measure the partition coefficient of ${}^{212}\text{Pb}$ between water and
LS, we use magnetic stirrer, 100 ml Erlenmeyer flask and 3 cm PTFE coated
magnet to perform water extraction. ${}^{212}\text{Pb}$ loaded LS is mixed
with high-purity water in equal amount (30 ml). The magnetic stirring is to
make LS and water to fully mixed and speed up the equalibrium.
${}^{212}\text{Pb}$ rate is measured before ($R_{0}$) and after ($R_{t}$) the
extraction, with the method described in Sec: 3.1 . The purification
efficiency is

$\displaystyle\epsilon=1-\frac{R_{t}}{R_{0}e^{-\frac{\Delta
t}{\tau}}}=\frac{K_{D}}{K_{D}+1}$ (5)

where $\Delta T$ is the time difference between measurements, $\tau$ is the
lifetime of ${}^{212}\text{Pb}$. $K_{D}$ is the partition coefficient defined
in Eq. (1).

The measurement of $K_{D}$ replies heavily on how well the system are in
equilibrium. Equilibrium depends on the stirring speed and the total time.
With this magnetic stirring, the longer and the faster the stirring, the
easier the system reaches equilibrium. Fig. 2, the extraction efficiency
increases with stirring speed and time before reaching equilibrium. At higher
speed, less time are needed to reach equilibrium. It took at least 30 minutes
to reach equilibrium at 600 rpm, while only several minutes at 1200 rpm. The
single stage extraction efficiency can reach 85$\pm$2%, with the uncertainty
dominated by systematic variations in equilibrium values under different
stirring time/speed combinations. 2% is the systematic error estimated by
repeated measurements. This incidates that the partition coefficient of
${}^{212}\text{Pb}$ is from 4.88 to 6.69.

Figure 2: Single stage extraction efficiency with different stirring speed and
time.

Multi-stage extraction is also performed. Fig.3 shows the relation between
extraction efficiency and the number of extraction stages. In this test, each
stage consists of 3-min stirring at a speed of 1200 rpm. After 5 stages, the
extraction efficiency became steady, reaching 92%. This indicates part of the
${}^{212}\text{Pb}$ is in different form that can not be removed by water.

Figure 3: Efficiency and number of extraction stages. Each stage consists of
an operation of 3 min stirring at 1200 rpm.

The single stage extraction efficiency is also studied at different
temperatures. The Erlenmeyer flask is heated to the set temperature by water
bath heating, then it is taken out and placed on a magnetic stirrer with
heating function. The stirring bottle is equipped with thermal insulation
cotton to keep it warm, and the temperature is monitored with an infrared
thermometer. The stirring speed is 1200 rpm, and the time is 10 minutes. Fig.
4 shows the relation between extraction efficiency and temperature. The
extraction efficiency increases with temperature steadily. At 80 ∘C, the
efficiency reaches the level where the multi-stage extraction at room
temperature ended up with. If the form of 212Pb in LS is not significantly
different with increasing temperature, it indicates the single stage
extraction is very efficiency in removing polar form of 212Pb at 80 ∘C.

Figure 4: Efficiency vs working temperature.

###  3.3 Rotary disc contactor prototype

A small prototype water extraction plant is constructed in the lab to
understand larger system parameters. It is a rotating disk column (RDC),
designed and manufactured by Institute of Process Engineering, CAS (Fig. 5).
It is designed to be operated in counter-current mode. The column is 3 meters
high and 40 mm in diameter. It consists of 25 rotor stages with rotation speed
up to 700 rpm. The working temperature can reach 80 ∘C. The designed LS flow
is 1.5 L/h, flow ratio between LS and water is 1:1 to 1:6 and this prototype
can reach 3 theoretical stages in room temperature, 1 atm. The shaft of the
prototype is made of polished 316L stainless steel, and the tower shell is
made of acrylic.

During operation, the phase fed from the bottom flows upwards is referred to
as dispersed phase, while the one comes in from top of the tower and flows
downwards is referred to as continuous phase. The stirring paddle disperses
the dispersed phase into small droplets, and the small droplets travels
through the continuous phase, when the mass transfer process occurs between
two phases.

Figure 5: Picture of the RDC.

####  3.3.1 Performance

Rotation speed An optimal rotation speed to form proper droplet size is
crucial for good mass transfer. When the stirring speed is very low, the
liquid scintillator and water are not sufficiently mixed. On the other hand,
if the rotation speed is too high, the droplets will become smaller and fail
to move up, which leads to flooding. Flooding is the phenomenon that the
dispersed phase forms a continuous liquid column to prevent the extraction
process. The extraction efficiency could maintain 80% above while the rotation
speed is over 500 rpm. At this time, the LS droplet diameter is from 1 to 2
mm.

Figure 6: Purification efficiency of different flow ratios between water and
LS

flow ratio Based on Eq. (4), the flow rate ratio will affect the final
extraction efficiency. Fig. 6 is the purification efficiency of different flow
ratios between water and LS. The purification efficiency is studied at
different flow ratio at the same rotation speed (500 RPM). We found the
efficiency could maintain above 80% for different flow ratio. However when
flow ratio between water and LS is too small (i.e. smaller than 1:6), the
efficiency drops dramatically. This indicates at 1:5, the equilibrium is
already established, further increasing water does not improve the mass
transfer.

Different continuous phase The choice of whether LS or water should be used as
dispersed phase is also studied. Fig. 7 shows the purification efficiency
curve with different rotation speed. When liquid scintillator is used as
continuous phase, a relatively higher rotation speed is required to achieve an
extraction efficiency of more than 80%, and it is easier to flood with very
small droplets, so that the entire extraction process is stopped. Besides, the
entire extraction system is very unstable and flooding is easy to occur in LS
as continuous phase.

Figure 7: Purification efficiency of different continious phase

##  4 Daya Bay water extraction pilot plant

We built a larger scale water extraction pilot plant at the Daya Bay
experiment. The purpose of this pilot plant is that we use the 20 tons LS
detector of Daya Bay experiment to check the LS quality produced by designed
purify facilities, study the process parameters and gain engineering
experience. Daya Bay experiment detectors distributed in 3 experiment halls
(EH1, EH2 and EH3), we carried out pilot experiment using one of 20 tons LS
detectors (AD1) in EH1 [12]. The original Gd-doped LS in the AD1 is completely
pumped out and replaced with undoped LS coming out from the purification
facilities [13]. Daya Bay detector AD1 can detect ${}^{238}\text{U}$ at
1$\times{10^{-15}}$g/g level. ${}^{238}\text{U}$ content in the LS of AD1 is
detected by the ${}^{212}\text{Bi}$ and ${}^{212}\text{Po}$ cascade decay in
the ${}^{238}\text{U}$ chain. This detector can measure changes in
${}^{238}\text{U}$ before and after purifying in different systems. Water
extraction system is among one of them. The LS was self-circulated through
purify facilities by turn to test the purification effects of each system.

###  4.1 System description

The role of water extraction as a part of the purification system is mainly to
remove radioactive ions dissolved in liquid scintillator. The difference from
the prototype is turbine extraction tower was adopted in water extraction
pilot plant (Fig. 8). The extraction tower was designed and produced by Wuxi
Hexiang Biochemistry Equipment Ltd. The extraction tower is 4.5m high and
0.15m in diameter. The flow rate of LS is 100 L/h and the flow rate of water
is 30 L/h. Flow ratio of between LS and water is around 3:1. The working
temperature is room temperature, working pressure is micro positive pressure.
The paddle speed is 140 r/min. The droplet diameter is between 1 mm and 2 mm.
The pilot plant extraction tower uses a specially designed turbine instead of
the rotation disc of prototype to stir LS and water, which improves the
stirring efficiency, reduces inter-stage flooding, and greatly improves the
extraction efficiency. The number of theoretical stages that the extraction
tower can reach is greater than 5. The system also includes 2 tanks, overflow
tank and product tank. There are 100 nm PTFE filters before the LS entering
the two tanks.

Figure 8: Picture of the Pilot Plant.

In order to avoid that extraction plant polluting LS, tower, tanks and
pipeline is made of 316L stainless steel. Inner surface is mechanical polished
and electrochemical polished to roughness Ra$<$ 0.4 $\mu$ m. During
assembling, tower components and the whole system were cleaned by the Alconox
detergent to clean the grease and high pure water is used for flushing. Tower
body and tank is chemical pickled and passivated to enhance its corrosion
resistance. The same cleaning method and treatment method are also used for
the pipeline. Orbital welding is adopted to avoid welding polluting LS.

To prevent Rn penetration, several methods were taken. The whole system was
sealed and covered with high pure nitrogen. The dynamic shaft is sealed by
magnetic force. Double O-rings flanges was used and inlet nitrogen between
O-rings to get positive pressure. A liquid seal tank was set to prevent Rn
permeation back from the vent. To ensure the sealing, a leakage rate
requirement was that partial flange connectors and valves less than
1$\times$10-8 mbar$\cdot$ L/s, the whole system is less than 1$\times$10-6
mbar$\cdot$ L/s. Airtight boxes were used to protect a part of valves and flow
meters that could not meet our leakage rate requirement. During experiments,
sealing of the water extraction system had met the design demands for Rn
prevention.

Since the water radioactivity level determines the radioactivity level of the
final LS (eq. (4)), the water used in extraction is supposed to be ultra-pure
and have inherent radioactivity as less as possible. Fig. 9 is the pure water
system for pilot plant. We purified tap water by the quartz sand filter,
activated carbon, PP filter, two-stage RO membranes, ion exchange resin and
100nm filter in turn. Before the pure water enters the pilot plant, it will be
stored in a storage tank, and the UV lamp will be irradiated for
sterilization. The resistivity of final outlet water reached 18.2 $M\omega$.
To remove Rn in water, we set up a nitrogen stripping column (Fig. 10).
Nitrogen stripping column is packed column, 6 meters total height, 80mm
packing section diameter, the height of packed section was 3.5 m divided into
three parts and each part was filled with 1 m high bulk packing and separated
by Pall ring to avoid fluid short circuit. Packing is polypropylene bulk Pall
ring with specific surface area 150 m2/m3. Water flow rate of nitrogen
stripping system is 30 L/h and nitrogen flow rate is 2 m3/h.

Figure 9: Pure water system of pilot plant

Figure 10: Nitrogen stripping column and Pall ring

The radon contents of water before nitrogen stripping was 25 Bq/m3, measured
by RAD-7. Radon contents of that after nitrogen stripping was measured
indirectly by AD1. LS mixed with 30 L water per hour and we assumed that all
the Rn in water would dissolve into LS, on the factual basis that the
solubility of radon in LS is more than thirty times higher than that in water.
Then the Rn concentration increase in AD1 was taken by water. According to the
AD1 data, in the 5 days period of water extraction, Rn counts reduced slower
than that decayed naturally. Rn contents of water was 20.1 mBq/m3, and Rn
concentration was reduced 1200 times than before nitrogen stripping.

Fig. 11 is the water extraction pilot plant flow-process diagram. LS from AD1
fed from the bottom of extraction tower flows upwards, pure water flows
downwards. The self-circulation will be carried out before the formal
experiment. When the formal experiment is carried out, it will be as shown in
the figure.

Figure 11: Water extraction of pilot plant flow-process diagram

###  4.2 Operation and Performance

In pilot plant the water extraction system performed stable and some of the
results had preliminary satisfied design demand: LS and water were agitated
fully, droplet size 1$\sim$2 mm which was fit for mass transfer. In series
running with other systems, ${}^{238}\text{U}$ content was purified to
2$\times 10^{-15}$g$/$g. During the commissioning of the water extraction
pilot plant, after the LS was purified and flow into product tank, the 100 nm
filter was block. We had to change the filter a few times. We checked the
replaced filter and found that there was a lot of water inside. We suspected
that the water blocked the filter, making it unable to work normally under
high LS flow. Therefore, in future full-scale water extraction plant, we
decided to use nitrogen to bubbling in the LS to remove water. By contrasting
the attenuation length(A.L.) of LS before and after the water extraction (Tab.
1), the A.L. did not obviously get worse, and it was considered that water
extraction system did not pollute LS, and kept LS’s transparency.

We want to know the individual purification efficiency of the water extraction
system. When the water extraction system was operated alone, the uranium
radioactivity level of the LS in AD1 did not drop further, nor did it rise
significantly. The extraction efficiency did not meet expectations may be
caused by a variety of reasons, like sealing problems, cleaning problems and
high water radioactivity problems. If it is a sealing problem, it is easy to
observe a significant increase in radioactivity in the AD1, so this
probability is low. Cleaning problems, such as tiny amount of dust entering
the interior of the LS, will affect the radioactivity. Therefore, in the full-
scale system, we will have more detailed cleaning steps and monitoring
methods. Another likely problem is the radioactivity of the water. If the
distribution coefficient of uranium is 5, the concentration of uranium in the
water must be lower than 5$\times 10^{-15}$g$/$g in order to make the
concentration of uranium in the LS lower than 1$\times 10^{-15}$g$/$g after
extraction(eq. (4)). Therefore, in future JUNO, the water will be purified
separately to ensure that the water extraction can achieve the expected
results.

Table 1: Attenuation length of different purification system. The error is 2.5 m Sample name | A.L.(m)
---|---
LAB after Al2O3 | 23.3
LAB after distillation | 25.4
LAB after water extraction | 24.6
LAB after stream stipping | 24.4

##  5 Conclusion

This article explores and measures a series of factors that may affect the
final water extraction efficiency. The distribution coefficient of Pb with
different temperature is measured. Multi-stage extraction efficiency is also
measured in laboratory. Since the JUNO water extraction system will adopt
counter-current extraction in the future, we built a prototype and a pilot
plant to explore other factors. In the experiment of the prototype, we have
given the change of the extraction efficiency with the rotation speed, and
then determined the appropriate droplet diameter. The working mode of water as
the continuous phase and liquid scintillation as the dispersed phase is
determined. An appropriate flow rate ratio range is also studied. For the
pilot test part, we obtained and shared a lot of experience in sealing
protection(double O-rings, airtight boxes), cleaning, and filtering. Nitrogen
stipping of water were proved to be highly effective. All of these will be
valuable experience and references in the perspective of achieving low-
background and high extraction efficiency in the final JUNO water extraction
system.

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