DESC:FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:
METHOD AND SYSTEM FOR DESIGNING A TASK SPECIFIC SOLVENT EXTRACTANT COMBINATION

Applicant:
Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th Floor,
Nariman Point, Mumbai 400021,
Maharashtra, India

The following specification particularly describes the invention and the manner in which it is to be performed.
CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY

[01] The present application claims priority from Indian provisional patent application no. 201821026445, filed on July 16, 2018. The entire contents of the aforementioned application are incorporated herein by reference.

TECHNICAL FIELD

[02] The disclosure herein generally relates to field of solvent extraction system, more particularly, to methods and systems for designing a task specific solvent extractant combination.

BACKGROUND

[03] Extractants are the reagents used by solvent extractant system to extract or separate a target entity from a mixture containing multiple species. They are mainly used in solvent extraction and ion exchange processes. Conventionally, the design of these extractants for the solvent extractant system is based on a trial and error process, which follows certain rules of thumb gained from prior experience. Furthermore, any new extractant conceived must be synthesized prior to its use in a solvent extractant system, thus requiring expertise in chemical synthesis.
[04] Conventional methods design solvent extractant systems by performing experiments using a number of different solvent-extractant combinations to measure the selectivity and extraction efficiency of the said system for the target species. Conventional approaches provide a ‘semi-intelligent’ exhaustive search, thus requiring a huge amount of time and money for design and commercialization.
[05] The existing methods for designing the extractant solvent combinations are oblivious to the atomic scale details, which is necessary to design task specific solvent-extractant systems.

SUMMARY

[06] Embodiments of the present disclosure present technological improvements as solutions to one or more of the above-mentioned technical problems recognized by the inventors in conventional systems. For example, in one embodiment, a system for designing a task specific solvent-extractant combination is provided. The system comprises an input module, a user interface, at least one memory and a processor in communication with the memory. The input module provides a library of chemical entities as an input. The user interface selects a set of functional groups and a set of target metal ions from the library to design a set of extractants for the task, wherein the task is selective separation of the set of target metal ions. The processor is further configured to perform the steps of: performing an ab-initio electronic structure calculation to obtain optimal binding configuration of the set of functional groups to the set of target metal ions; designing a set of extractant from the obtained optimal binding configurations using host designer software; performing the ab-initio electronic structure calculation on each of the set of designed extractant to obtain binding free energies of the designed extractant with the target metal ions, wherein the differences in the binding free energy of an extractant with two different metal ions provides a measure of its selectivity to one ion over another ion; identifying one or more metal ion-extractant complexes based on the highest selectivity for a target metal ion out of the set of target metal ions; computing solvation free energy of the one or more metal ion-extractant complexes in water and a number of different solvents using thermodynamic integration (TI), wherein the solvation free energy is used to compute partition coefficient; computing an energy barrier for transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluents interface using umbrella sampling; and shortlisting the most promising task specific extractant-solvent combination for the selective separation of the set of target metal ions based on their selectivity, the partition coefficient and the energy barrier.
[07] In another embodiment a method for designing a task specific solvent-extractant combination has been provided. Initially a library of chemical entities is provided as an input. Further, a set of functional groups and a set of target metal ions are selected from the library to design a set of extractants for the task, wherein the task is selective separation of the set of target metal ions. In the next step, an ab-initio electronic structure calculation is performed to obtain optimal binding configuration of the set of functional groups to the set of target metal ions. Further a set of extractants are designed from the obtained optimal binding configurations using the host designer software. In the next step the ab-initio electronic structure calculation is performed on each of the set of designed extractants to obtain binding free energies of the designed extractant with the target metal ions, wherein the differences in the binding free energy of an extractant with two different metal ions provides a measure of its selectivity to one ion over another ion. In the next step, one or more metal ion-extractant complexes are identified based on the highest selectivity for a target metal ion out of the set of target metal ions. Further, the solvation free energy of the one or more metal ion-extractant complexes is computed in water and a number of different solvents using thermodynamic integration (TI), wherein the solvation free energy is used to compute partition coefficient. In the next step, an energy barrier is computed for transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluent interface using umbrella sampling. And finally, the most promising task specific extractant-solvent combination is shortlisted for the selective separation of the set of target metal ions based on their selectivity, the partition coefficient and the energy barrier.
[08] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

[09] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles:
[010] Fig. 1 illustrates a system diagram for designing a task specific solvent-extractant combination, in accordance with an embodiment of the present disclosure.
[011] FIG. 2 illustrates a schematic flow diagram for designing the task specific solvent extractant combination, in accordance with an embodiment of the present disclosure.
[012] Fig. 3A-3B illustrates the steps involved in designing a task specific solvent extractant combination, in accordance with an embodiment of the present disclosure.
[013] FIG. 4 illustrates structure of methyl hydroxamate anion, in accordance with an embodiment of the present disclosure.
[014] FIG. 5 illustrates optimized geometry of rare earth elements (REE) ion complex with hydroxamate ions, nitrate ion and water molecules, in accordance with an embodiment of the present disclosure.
[015] FIG. 6 illustrates linking sites for the host designer program, in accordance with an embodiment of the present disclosure.
[016] FIGS. 7A through 7F illustrate structures of six bis-hydroxamate extractants generated using host designer program by linking the two hydroxamate groups bound to the REE ion, in accordance with an embodiment of the present disclosure.
[017] FIGS. 8A and 8B illustrates structures of REE ion–D2EHPA complex solvated in water and heptane respectively, in accordance with an embodiment of the present disclosure.
[018] FIG. 9 illustrates a graph providing experimental validation of the simulation results for designing a solvent extractant system, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

[019] Exemplary embodiments are described with reference to the accompanying drawings. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments. It is intended that the following detailed description be considered as exemplary only, with the true scope being indicated by the following claims.
[020] The embodiments herein provide a system and method for designing a task specific solvent-extractant combination. The disclosure provides a generic framework that enables ‘rational design’ of a task specific solvent-extractant combination. The framework integrates various molecular simulation protocols to enable ‘rational design’ of solvent extractant combinations using a multi-scale modeling approach. Further, the present disclosure provides a molecular mechanism of solvent extraction in order to design better extractants for extraction. In an example, the task may involve selective separation of a set of target metal ions.
[021] Referring now to the drawings, and more particularly to FIG. 1 through FIG. 9, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments and these embodiments are described in the context of the following exemplary system and/or method.
[022] FIG. 1 illustrates a block diagram of a system 100 for designing a task specific solvent extractant combination, in accordance with an embodiment of the present disclosure. The system 100 includes an input module 102, a user interface 104, at least one memory 106 and one or more hardware processors 108 or a processor 108. The processor 108, the user interface 104, and the at least one memory 106, may be coupled by a system bus (not shown).
[023] The input module 102 and the user interface 104 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. In an example, the input module 102 and the user interface 104 may be one unit and serves the purpose of both. The input module 102 and the user interface 104 may include a variety of software and hardware interfaces, for example, interfaces for peripheral device(s), such as a keyboard, a mouse, an external memory, a camera device, and a printer. The interfaces 104 can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, local area network (LAN), cable, etc., and wireless networks, such as Wireless LAN (WLAN), cellular, or satellite.
[024] The hardware processor 108 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the hardware processor 108 is configured to fetch and execute computer-readable instructions stored in the memory 106.
[025] The memory 106 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.
[026] According to an embodiment of the disclosure, the processor 108 includes a plurality of modules. The plurality of modules may include routines, programs, objects, components, data structures, and so on, which perform particular tasks or implement particular abstract data types.
[027] According to an embodiment of the disclosure, the plurality of modules may include a simulator 110, a host designer software 112, a selectivity computing module 114, a partition coefficient calculation module 116, a transport property calculation module 118 and an extractant-solvent combination selection module 120.
[028] The system 100 also maintains a library of chemical entities 122 (interchangeably referred as library 122) of one or more chemical entities and a plurality of species comprising of a plurality of metal ions, a set of force field parameters for the plurality of metal ions and chemical entities, a plurality of functional groups, a plurality of diluents and a plurality of basis functions and electron exchange correlation potentials for ab-initio calculation. Further, the user interface 104 is configured to select a set of target metal ions and a set of functional groups from the library 122, wherein the selected target metal ions are to be selectively extracted.
[029] According to an embodiment of the disclosure the processor 108 comprises the simulator 110. The simulator 110 is configured to perform a first set of simulations. The first set of simulation includes ab-initio electronic structure calculations to obtain optimal binding configuration of the set of functional groups to the set of target metal ions. The ab-initio electronic structure calculation may be performed using either or a combination of density functional theory (DFT), Coupled Clusters with Single and Double excitation (CCSD), Moller plesset 2nd order perturbation theory (MP2). The ab-initio calculations are performed using either of NWChem or Gaussian 09 or GAMESS suite of programs.
[030] According to an embodiment of the disclosure the processor 108 also comprises the host designer software 112. The host designer software 112 is configured to design a set of extractant from the obtained optimal binding configurations. The set of extractants are a plurality of size specific extractants with a plurality of functional groups for each of the set of target metal ions.
[031] According to an embodiment of the disclosure the processor also comprises the selectivity computing module 114. The selectivity computing module 114 is configured to perform a second set of simulations. The second set of simulations include the ab-initio electronic structure calculation on each of the set of designed extractant to obtain binding free energies of the designed extractant with the target metal ions. The differences in the binding free energy of an extractant with two different metal ions provides a measure of its selectivity to one ion over another ion. The selectivity computing module 114 is further configured to identify one or more metal ion-extractant complexes based on the highest selectivity for a target metal ion out of the set of target metal ions.
[032] The designed size specific extractants showing the largest selectivity measure for a target metal ion are shortlisted. Furthermore, one or more dynamic properties of the plurality of designed size specific extractants, in aqueous and organic phases are computed. For characterization in organic phase, at least an organic phase comprising of one or more solvents from the repository of chemical entities and species is selected.
[033] According to an embodiment of the disclosure the processor 108 also comprises the partition coefficient calculation module 116. The partition coefficient calculation module 116 is configured to compute solvation free energy of the one or more metal ion-extractant complexes in water and a number of different solvents using thermodynamic integration (TI), wherein the solvation free energy is used to compute partition coefficient. The partition coefficient is a thermodynamic measure of the preference of the complex to remain in organic phase over aqueous phase. The partition coefficient may also be referred as Log P.
[034] According to an embodiment of the disclosure the processor 108 also comprises the transport property calculation module 118. The transport property calculation module 118 is configured to compute an energy barrier for transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluent interface using umbrella sampling. A potential of mean force (PMF) profile is the change in the energy as an entity is moved from one location to another location. The PMF profile provides the energy barrier for the transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluent interface. Further, the plurality of designed size specific extractants are ranked based aqueous selectivity measure, partition coefficient, and PMF profiles.
[035] According to an embodiment of the disclosure, the solvent extractant combination selection module 120 is configured to shortlist the most promising task specific extractant-solvent combination for the selective extraction of the target metal ions based on their selectivity, the partition coefficient and transport properties. In an embodiment, the extractant(s) and organic diluent(s) combinations showing the largest difference in aqueous – organic solvation free energies and the smallest energy barrier for transport across the aqueous – organic interface are considered as the solvent-extractant(s) combination with desired properties. According to an embodiment of the disclosure, the system 100 further comprises a module for validating the shortlisted solvent-extractant combination.
[036] In operation, a flowchart 200 illustrating the steps involved in designing a task specific solvent extractant combination in accordance with an embodiment of the present disclosure is shown in FIG. 3A-3B. In an embodiment, the method may include designing task specific solvent extractant systems based on the user requirements. In another embodiment, the method includes accelerating the discovery of task specific solvent extractant combinations for separation of one or more target chemical entities from a mixture of various species. Initially at step 202, the library of chemical entity 122 is provided as the input. In the next step 204, based on the user requirements, the set of target metal ions and a set of functional groups are selected from the library of chemical entities or species.
[037] In the next step 206, a first set of simulations are performed. In an example, the ab-initio electronic structure calculation are performed to obtain optimal binding configuration of the set of functional groups to the set of target metal ions. In the next step 208, the set of extractants are designed from the obtained optimal binding configurations using the host designer software.
[038] In the next step 210, the second set of simulations are performed. The ab-initio electronic structure calculations are performed on each of the set of designed extractant to obtain binding free energies of the designed extractant with the target metal ions. The differences in the binding free energy of an extractant with two different metal ions provides a measure of its selectivity to one ion over another ion. At step 212, one or more metal ion-extractant complexes are identified based on the highest selectivity for a target metal ion out of the set of target metal ions.
[039] In the next step 214, the solvation free energy of the one or more metal ion-extractant complexes is computed in water and in a number of different organic diluents using thermodynamic integration (TI). The computed solvation free energy is further used to compute partition coefficient.
[040] In the next step 216, the energy barrier is computed for the transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluents interface using umbrella sampling. The potential of mean force (PMF) profile is the change in the energy as an entity is moved from one location to another location across the water-organic interface. The PMF profile provides the energy barrier for the transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluent interface. And finally at step 218, the most promising task specific extractant-solvent combination is shortlisted for the selective extraction of the target metal ions based on their selectivity, the partition coefficient and transport properties.
[041] According to an embodiment of the disclosure, the system 100 can also be explained with the help of an example. In an embodiment, the method of FIG. 3 is explained with the help of a use case example in conjunction with FIGS. 3 through 8. For example, designing of extractants for the separation of two rare earth elements (REEs), namely Neodymium (Nd) and Dysprosium (Dy) from a mixture of the two, is illustrated. As depicted in FIG. 2, a plurality of functional groups from the repository of chemical entities are selected based on user requirements. For Example, for designing of bis-hydroxamate extractant for the size based separation of the two REEs, a simple hydroxamate anion containing atleast one alkyl group, namely methyl hydroxamate anion (C2H4NO2-) is selected. The structure of simplest hydroxamate anion containing at least one alkyl group, namely methyl hydroxamate anion (C2H4NO 2-) is shown in FIG. 4.
[042] Further, for designing size specific bis-hydroxamate extractants, the optimal binding geometry of two methyl hydroxamate anions to Nd3+ and Dy3+ ions is obtained using DFT calculations. Furthermore, since each hydroxamate anion carries a charge of -1, a weakly coordinating nitrate (NO3-) ion to balance the +3 charge of the REE ions is added. Each of the hydroxamate and nitrate anions are bidentate extractants, together providing a total of six donor groups. However, REE ions are known to have a 1st shell coordination number of nine. Thus, three water molecules (which are monodentate ligands, binding via the oxygen atom of the water molecule) are added in order to saturate the 1st shell coordination number of the REE ions.
[043] Further, a plurality of DFT calculations are performed using the NWChem quantum chemistry software in order to identify the optimal binding geometry of the hydroxamate anions to the REE ions. The plurality of DFT calculations utilize a B3LYP exchange correlation functional, stuttgart large core relativistic effective core potentials and associated 7s6p5d/5s4p3d basis set for the REE ions and a 6-31+G* basis set for C, H, N and O atoms. The optimized structure of the complex formed with the hydroxamate ions, nitrate ion and water molecules is shown in FIG. 5.
[044] Upon identifying the optimal binding geometry of the hydroxamate ions, the ions must bet linked together in order to create a bis-hydroxamate extractant. The step of linking ions together is performed using the host designer software. Specifically, the hydrogen atoms in the methyl groups of the two hydroxamate ions are selected as linking sites, as shown in FIG. 6. Arrows shown in FIG. 6 depict the hydrogen atoms of the methyl groups that are selected as the linking sites for host designer software. Host designer program then searches through the repository of various hydrocarbon groups in order to generate ‘linkers’ that conform to a predefined Root Mean Square Deviation (RMSD) criteria in order to connect the two hydroxamate ions. For the above mentioned example, host designer generates six new extractants by linking the two hydroxamate groups bound to the REE ion. The structure of the six extractants are shown in FIGS. 7A through 7F. After generation of the extractants, the geometry of the extractants is optimized and the aqueous binding free energy of extractants with the REE ions is computed using DFT. The aqueous binding free energy (?Gaq) is computed using equation 1, which is further represented as the thermodynamic cycle as shown in equation 2. The thermodynamic cycle computes the aqueous binding free energy (?Gaq) of an extractant (L) to an REE ion (Ln).

?Gaq= ?Go(g) + ??G*solv + (3+y-z) RTln(24.4) + 3RTln(55.34) ……... (1)

……………. (2)
As shown in equation 3, the aqueous binding free energy of an extractant to a metal ion is directly related to the equilibrium binding constant
?Gaq = -2.303RT(logK) ……………. (3)
[045] Where, R is the gas constant, T is the temperature and K is the equilibrium constant for the reaction. As shown in equation 4, the difference between the logK values of the extractant binding to Nd3+ and Dy3+ gives a measure of the selectivity of the extractant for Nd3+ over Dy3+, with larger values signifying higher selectivity.
Selectivity measure (Nd/Dy) = ?GNdaq – ?GDyaq …………… (4)
[046] In one embodiment, Nd3+/Dy3+ selectivity measure for each of the six newly designed extractants are provided in Table 1.
Aqueous selectivity computed using DFT
Extractant 1 1.96
Extractant 2 1.52
Extractant 3 2.04
Extractant 4 1.57
Extractant 5 1.55
Extractant 6 1.84
Table 1
As can be seen in Table 1, all the extractants show 100 times (2 log units) more selectivity for one REE ion over the other REE ion and amongst the six newly designed extractants, third extractant is the most selective extractant for Nd3+ over Dy3+, by a factor of 100 approximately.
[047] In an embodiment, the next step after design of an extractant and assessment of its aqueous selectivity is to characterize its dynamic properties in aqueous and organic phases and also evaluate the ease of transport of the metal-extractant complex across the aqueous organic interface (i.e., energy barrier for transport across the aqueous – organic interface). For performing the above step, a commercially available acidic extractant such as (Di-(2-ethylhexyl) phosphoric acid (D2EHPA)) and an organic solvent such as heptane are selected. Six D2EHPA molecules are known to bind to a single REE ion, three of them in their anionic form (formed upon deprotonation of D2EHPA) and the remaining three as neutral molecules. Further, a plurality of classical MD simulations are performed in vacuum to obtain the binding configuration of D2EHPA molecules to Nd3+ and Dy3+ ions. The simulations utilize OPLS all atom force field to describe the interactions between various atoms in the system. Subsequently, the complexes are solvated in water and heptane (organic solvent). The structure of the solvated systems are shown in FIGS. 8A and 8B. Each of the solvated systems is first equilibrated at room temperature (300 K). Next, TI calculations are performed to compute the solvation free energy of the complex in both aqueous and organic solvent phase as depicted in Table 2.

System\Solvent Water
(kcal/mol) Heptane (kcal/mol) logP
Nd-Complex -12.30 -48.91 26.49
Dy-Complex -7.27 -54.94 34.50
Table 2
[048] As can be seen in equation 5, the difference between the solvation free energy of the complex in the organic and aqueous phase is related to the partition coefficient.
logP(aq/org) = -?Gdiff/(2.303RT) ………….. (5)
[049] The partition coefficient is a thermodynamic measure of the preference of the complex to remain in organic solvent phase over aqueous phase. As can be seen in Table 2, Dy-D2EHPA complex has a logP value of 34.50 while Nd-D2EHPA complex has a logP value of 26.49, indicating that extraction of Dy3+ ions from aqueous to organic phase by D2EHPA extractant is thermodynamically much more favorable than extraction of Nd3+.
[050] FIG. 9 illustrates a graph providing experimental validation of the simulation results, in accordance with an example embodiment of the present subject. The simulation results have been validated by in house solvent extraction experiments in which a mixture Nd and Dy ions in 4:1 ratio was separated using D2EHPA as the extractant and heptane as the organic solvent. As depicted in FIG. 9, a full factorial Design of Experiments (DOE) is performed with pH, extractant concentration and A/O ratio as the variables, resulting in a total of 84 different solvent extraction experiments. The experiments show that D2EHPA is more selective for Dy3+ over Nd3+ ions at all conditions, thereby validating our simulation results and the proposed framework. Thus, the proposed framework can successfully design solvent-extractant combinations using software based simulations for the separation of target entities from a mixture of various species.
[051] The present disclosure includes replacing the laborious and expensive design approaches for solvent-extractant combinations with a chemistry driven software simulations based design framework. The present disclosure enables reduction in time and cost required for design of new task specific solvent extractant combination.
[052] The written description describes the subject matter herein to enable any person skilled in the art to make and use the embodiments. The scope of the subject matter embodiments is defined by the claims and may include other modifications that occur to those skilled in the art. Such other modifications are intended to be within the scope of the claims if they have similar elements that do not differ from the literal language of the claims or if they include equivalent elements with insubstantial differences from the literal language of the claims.
[053] It is to be understood that the scope of the protection is extended to such a program and in addition to a computer-readable means having a message therein; such computer-readable storage means contain program-code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The hardware device can be any kind of device which can be programmed including e.g. any kind of computer like a server or a personal computer, or the like, or any combination thereof. The device may also include means which could be e.g. hardware means like e.g. an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of hardware and software means, e.g. an ASIC and an FPGA, or at least one microprocessor and at least one memory with software modules located therein. Thus, the means can include both hardware means and software means. The method embodiments described herein could be implemented in hardware and software. The device may also include software means. Alternatively, the embodiments may be implemented on different hardware devices, e.g. using a plurality of CPUs.
[054] The embodiments herein can comprise hardware and software elements. The embodiments that are implemented in software include but are not limited to, firmware, resident software, microcode, etc. The functions performed by various modules described herein may be implemented in other modules or combinations of other modules. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can comprise, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
[055] The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
[056] Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
[057] It is intended that the disclosure and examples be considered as exemplary only, with a true scope of disclosed embodiments being indicated by the following claims.
,CLAIMS:1. A processor implemented method for designing a task specific solvent-extractant combination, the method comprising:

Providing, via an input module, a library of chemical entities as an input (202);
selecting a set of functional groups and a set of target metal ions from the library to design a set of extractants for the task, wherein the task is selective separation of the set of target metal ions (204);
performing, via one or more hardware processor, an ab-initio electronic structure calculation to obtain optimal binding configuration of the set of functional groups to the set of target metal ions (206);
designing, via one or more hardware processor, the set of extractants from the obtained optimal binding configurations using a host designer software (208);
performing, via one or more hardware processor, the ab-initio electronic structure calculation on each of the set of designed extractants to obtain binding free energies of the designed extractant with the target metal ions, wherein the differences in the binding free energy of an extractant with two different metal ions provides a measure of its selectivity to one ion over another ion (210);
identifying, via one or more hardware processor, one or more metal ion-extractant complexes based on the highest selectivity for a target metal ion out of the set of target metal ions (212);
computing, via one or more hardware processor, solvation free energy of the one or more metal ion-extractant complexes in water and a number of different solvents using thermodynamic integration (TI), wherein the solvation free energy is used to compute partition coefficient (214);
computing, via one or more hardware processor, an energy barrier for transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluent interface using umbrella sampling (216); and
shortlisting, via one or more hardware processor, the most promising task specific extractant-solvent combination for the selective separation of the set of target metal ions based on their selectivity, the partition coefficient and the energy barrier (218).

2. The method of claim 1, wherein the library of chemical entities include chemical composition, structures of functional groups, diluents, metal ions, their associated force field parameters and basis functions for ab-initio calculation.

3. The method of claim 1, wherein the ab-initio electronic structure calculation performed using either or combination of density functional theory (DFT), Coupled Clusters with Single and Double excitation (CCSD), Moller plesset 2nd order perturbation theory (MP2)

4. The method of claim 1, wherein the ab-initio calculations are performed using at least one of NWChem or Gaussian 09 or GAMESS codes.

5. The method of claim 1, wherein the extractant and organic diluents showing the largest difference in water-organic diluent solvation free energies and the smallest energy barrier for the transport across the water-organic interface is shortlisted.

6. The method of claim 1, further comprising the step of validating the shortlisted solvent-extractant combination.

7. A system (100) for designing a task specific solvent-extractant combination, the system comprises:

an input module (102) for providing a library of chemical entities (122) as an input;
a user interface (104) for selecting a set of functional groups and a set of target metal ions from the library to design a set of extractants for the task, wherein the task is selective separation of the set of target metal ions;
at least one memory (106); and
a processor (108) in communication with the at least one memory, wherein the processor is further configured to perform the steps of:
performing an ab-initio electronic structure calculation to obtain optimal binding configuration of the set of functional groups to the set of target metal ions;
designing a set of extractant from the obtained optimal binding configurations using host designer software;
performing the ab-initio electronic structure calculation on each of the set of designed extractant to obtain binding free energies of the designed extractant with the target metal ions, wherein the differences in the binding free energy of an extractant with two different metal ions provides a measure of its selectivity to one ion over another ion;
identifying one or more metal ion-extractant complexes based on the highest selectivity for a target metal ion out of the set of target metal ions;
computing solvation free energy of the one or more metal ion-extractant complexes in water and a number of different solvents using thermodynamic integration (TI), wherein the solvation free energy is used to compute partition coefficient;
computing an energy barrier for transport of the shortlisted one or more metal ion-extractant complexes across the water-organic diluents interface using umbrella sampling; and
shortlisting the most promising task specific extractant-solvent combination for the selective separation of the set of target metal ions based on their selectivity, the partition coefficient and the energy barrier.