Ionic Liquids and Deep Eutectic Solvents
Design tunable ionic media around molecular interactions, transport, phase behavior, safety, recovery, and the realities of the target process.
Start Your ProjectComposition-aware design from ion pairs and eutectic networks to unit operations
Ionic liquids (ILs) offer combinatorial cation–anion design; deep eutectic solvents (DESs) derive behavior from component identity, ratio, non-ideal interactions, and melting-point depression. Neither class is defined by one property, and low vapor pressure alone does not establish safety or sustainability. We build application-specific design spaces that retain composition, water content, temperature, purity, preparation history, and measurement conditions. The result is a ranked and validation-ready solvent system—not a generic list of fashionable liquids.
Predictive design across chemistry, microstructure, transport, and process fit
IL and DES design-space construction
Enumerate cations, anions, H-bond acceptors/donors, molar ratios, co-solvents, water levels, functional groups, and synthesis or sourcing constraints.
Thermodynamic screening
Estimate activity coefficients, solubility, selectivity, partitioning, gas absorption, liquid–liquid equilibrium, and solid–liquid behavior using fit-for-purpose models.
Transport and microstructure
Model viscosity, diffusivity, density, conductivity, ion association, hydrogen-bond networks, nanosegregation, and their response to temperature and water.
Data-driven property prediction
Train or apply QSPR/ML models with explicit composition encoding, condition variables, cross-validation, applicability domains, and calibrated uncertainty.
Safety and sustainability gating
Screen toxicity evidence, biodegradability, persistence, synthesis burden, impurities, thermal stability, corrosion, emissions, recovery, and life-cycle data gaps.
Process integration and validation
Connect solvent candidates to mass transfer, regeneration, phase separation, electrochemical windows, materials compatibility, recycle quality, and scale-relevant tests.
Six stages from molecular building blocks to a validated formulation
| Stage | Key Activities | Decision Output |
|---|---|---|
| 1. System Scoping | Define solute/feed, target function, composition family, operating temperature, water exposure, impurities, equipment, regeneration, and acceptance criteria. | Application envelope and hard exclusions |
| 2. Evidence & Data Audit | Curate structures, component ratios, preparation history, purity, water content, measurement methods, conditions, EHS evidence, and process data. | Condition-resolved dataset and gap map |
| 3. Candidate Generation | Enumerate feasible ion pairs or HBA/HBD systems; constrain availability, synthesis, melting state, stability, corrosivity, and component compatibility. | Buildable composition space |
| 4. Multiscale Modeling | Combine descriptors/ML, quantum chemistry or COSMO-RS, targeted MD, phase-equilibrium calculations, and uncertainty-aware ranking. | Pareto-ranked candidates and sensitivity |
| 5. Process Robustness | Challenge water uptake, viscosity, transfer rates, phase split, impurity accumulation, decomposition, corrosion, regeneration, and recycle drift. | Operating window and failure-mode register |
| 6. Validation & Down-Selection | Design property confirmation and application tests, benchmark against conventional media, and define quantitative go/no-go gates. | Validated shortlist and scale-up path |
Traceable outputs for formulation, experimental, and process decisions
Composition Design Space
Structures, component identities, molar ratios, co-solvent/water windows, feasibility rules, and provenance.
Condition-Resolved Property Dataset
Measured and predicted thermodynamic, transport, electrochemical, thermal, and interfacial properties with uncertainty.
Ranked IL/DES Shortlist
Application-specific scores, Pareto fronts, exclusion reasons, applicability-domain flags, and benchmark comparisons.
Microstructure & Mechanism Analysis
Ion association, H-bond networks, water effects, diffusional limitations, and molecular drivers of selectivity or conductivity.
Process Window & Risk Register
Viscosity and transfer limits, phase behavior, regeneration, corrosion, decomposition, impurity, recycle, and scale-up risks.
Validation & Implementation Plan
Formulation protocol, water/purity control, test matrix, analytics, comparators, recycle challenge, and go/no-go criteria.
Ionic media engineered for distinct operating environments
Gas capture and separations
Balance gas solubility/selectivity with viscosity, mass transfer, water tolerance, regeneration energy, stability, and solvent loss.
Liquid–liquid extraction
Design partitioning and selectivity while managing mutual solubility, phase disengagement, product back-extraction, and recycle.
Electrochemistry and energy
Optimize conductivity, electrochemical window, electrode wetting, impurity sensitivity, thermal behavior, and long-duration cycling.
Biomass and polymer processing
Target cellulose, lignin, polymer, or additive interactions while controlling viscosity, degradation, precipitation, washing, and solvent recovery.
Catalysis and reaction media
Coordinate solvation and catalytic microenvironments with reaction rate, selectivity, catalyst retention, workup, and reuse.
Natural-product extraction and formulation
Evaluate solute recovery, matrix selectivity, water content, stability, toxicity evidence, downstream compatibility, and purification.
Composition and conditions control performance—and must remain visible in the model
Industrial relevance extends beyond low volatility
ILs have reached industrial use in separations, electrochemistry, catalysis, coatings, and processing. Implementation still depends on stability, impurity control, product isolation, recycle, equipment compatibility, and economics.1
Water can restructure a DES
DES density, viscosity, and hydrogen-bond organization are coupled to component ratio and water content. Dilution can improve transport, but sufficient water may disrupt the interaction network that defines the original mixture.2
Viscosity data require complete metadata
Aqueous DES viscosity depends on salt-to-HBD ratio, water fraction, and temperature, while literature measurements may vary across methods. Condition-resolved, traceable data are therefore essential for modeling and scale-up.3
1 Greer, A. J.; Jacquemin, J.; Hardacre, C. Industrial Applications of Ionic Liquids. Molecules 2020, 25, 5207. https://doi.org/10.3390/molecules25215207. Distributed under Open Access license CC BY 4.0.
2 Ijardar, S. P.; Deepa; Singh, V. Revisiting the Physicochemical Properties and Applications of Deep Eutectic Solvents. Molecules 2022, 27, 1368. https://doi.org/10.3390/molecules27041368. Distributed under Open Access license CC BY 4.0.
3 Gygli, G.; Xu, X.; Pleiss, J. Meta-analysis of viscosity of aqueous deep eutectic solvents and their components. Scientific Reports 2020, 10, 21395. https://doi.org/10.1038/s41598-020-78101-y. Distributed under Open Access license CC BY 4.0.
Evidence-linked design without assuming every ionic medium is benign
Each result remains linked to chemical identity, component ratio, batch purity, halide or metal content, water measurement, preparation history, temperature, method, model version, and process assumption. Predictions are reported within their applicability domain, while safety and sustainability data gaps remain explicit. High-value candidates require application-specific property, toxicity where relevant, compatibility, regeneration, and recycle validation. To discuss an ionic liquid, DES formulation, separation, electrochemical system, or internal dataset, please Contact Us or submit the Online Inquiry below.