AI for Materials

AI for Carbon Capture and Molecular Separation

Identify adsorbents and operating conditions that separate the right molecule under realistic process constraints. CD ComputaBio combines molecular simulation, AI-guided materials screening, adsorption analysis, and regeneration-aware ranking for carbon capture, gas purification, hydrocarbon separation, pollutant removal, and adsorbent lifecycle studies.

Discuss Your Separation Challenge Explore Separation Services

Applicable to MOFs, COFs, zeolites, activated carbons, porous polymers, membranes, and hybrid adsorbent systems.

Separation stream Material-to-process logic

Mixed Feed Gas, vapor, water, or contaminant mixture

Selective Material Pore chemistry + operating conditions

Target Product Purity, recovery, capacity, or removal

Capture → Release or recovery → Regenerate → Repeat

The Separation Trade-Off

The highest uptake material is not necessarily the best separator

Separation performance emerges from several coupled properties. Stronger adsorption can increase capacity but make regeneration harder. Narrow pores can improve selectivity while slowing diffusion. A promising dry-gas material may lose performance in humid or contaminated streams.

Our screening logic therefore ranks materials against the complete operating objective rather than a single adsorption value.

01 · HOW MUCH

Working Capacity

Usable loading difference across adsorption and desorption conditions, not only maximum uptake.

02 · WHICH MOLECULE

Selectivity

Preference for the target component in a mixture at relevant composition, pressure, and temperature.

03 · HOW FAST

Transport and Kinetics

Diffusion, pore accessibility, particle effects, and the time required to approach useful separation.

04 · AT WHAT COST

Regeneration Burden

Energy, vacuum, purge, temperature, solvent, or pressure change required to restore capacity.

Decision target: useful separation performance over repeated operating cycles

Separation Application Lanes

Five research routes defined by feed stream and process objective

Select the route that matches the molecules being separated, the required product specification, and the conditions the material must withstand.

Carbon Capture Materials

Screen and optimize materials for post-combustion, pre-combustion, biogas, natural-gas, or direct-air capture scenarios.

Feeds CO₂/N₂, CO₂/CH₄, CO₂/H₂, dilute CO₂ Priorities Humidity tolerance, working capacity, selectivity, regeneration

View service → 02

Hydrogen Purification and Storage

Evaluate porous materials for hydrogen recovery, impurity removal, pressure-swing purification, and reversible storage.

Feeds H₂ with CO₂, CO, CH₄, N₂, or water Priorities Purity, recovery, volumetric capacity, adsorption reversibility

View service → 03

Light Hydrocarbon Separation

Target difficult mixtures whose components have similar sizes, boiling points, or physicochemical properties.

Feeds C₂/C₃/C₄ alkanes, alkenes, alkynes, isomers Priorities Molecular recognition, diffusion, purity, productivity

View service → 04

PFAS and Pollutant Removal

Prioritize adsorbents for trace contaminant capture in water or complex environmental matrices.

Targets PFAS, organics, dyes, metals, and emerging pollutants Priorities Trace affinity, competition, water stability, disposal or regeneration

View service → 05

Adsorbent Stability and Regeneration

Examine how water, impurities, temperature, cycling, and regeneration conditions change structure and performance.

Stressors Humidity, acid gases, oxidation, heat, solvent, cycling Priorities Capacity retention, structural integrity, energy, lifetime

View service →

Materials-to-Process Bridge

Evaluate performance at three connected scales

A material can rank highly at the molecular level yet fail after shaping, under mixed feeds, or during repeated regeneration. The workflow connects these scales before final prioritization.

Molecular Recognition

How pore size, topology, charge, functional groups, and guest interactions control adsorption and selectivity.

Binding sites · isotherms · diffusion

Material Performance

How defects, flexibility, moisture, mixture competition, particle form, and shaping affect usable behavior.

Working capacity · kinetics · stability

Process Relevance

How pressure, temperature, cycle design, purity, recovery, productivity, and regeneration change the ranking.

PSA · TSA · VSA · cyclic operation

Operating Envelope

Screen the material under the stream it will actually see

Idealized single-component data are useful for interpretation, but material selection should reflect mixture composition, trace contaminants, humidity, pressure, temperature, and regeneration conditions.

Process variable

Why it changes performance

What the project evaluates

Mixture composition

Components compete for pore volume and binding sites

Mixture selectivity and displacement risk

Humidity

Water may block sites, alter structure, or change affinity

Water competition and hydrolytic stability

Pressure

Loading and working capacity depend on adsorption range

Process-relevant uptake and pressure-swing window

Temperature

Adsorption strength and diffusion respond differently to heat

Capture efficiency and thermal regeneration trade-off

Trace impurities

Strongly adsorbed contaminants may poison active sites

Competitive binding and irreversible capacity loss

Cycling

Repeated adsorption and release can accumulate damage

Capacity retention and regeneration robustness

Search the material space Databases, hypothetical structures, functionalization, and client-provided candidates

Remove infeasible candidates Pore accessibility, chemistry, stability flags, synthesis or shaping constraints

Evaluate realistic separation Mixtures, humidity, temperature, pressure, diffusion, and working capacity

Prioritize validation Shortlist, uncertainty, differentiating experiments, and operating window

Screening Cascade

Spend high-fidelity calculations on the candidates that survive

The first screening layer removes obvious mismatches quickly. More demanding simulations and mechanistic analyses are then focused on candidates with credible pore accessibility, material stability, and process relevance.

Final output: a smaller, better-justified experimental shortlist—not simply a longer ranking table.

Separation Decision Dashboard

Deliverables built for material selection and validation planning

The final package connects performance metrics with operating assumptions, stability risks, and the experiments required to distinguish leading candidates.

Decision-ready output

Material and Process Shortlist

Candidate recommendations, operating conditions, mechanistic interpretation, and remaining uncertainty in one package.

01 Ranked adsorbents

Candidate materials compared across capacity, selectivity, kinetics, stability, and regeneration.

02 Operating-window analysis

Pressure, temperature, mixture, humidity, and cycle assumptions tied to each ranking.

03 Mechanistic evidence

Binding sites, pore occupancy, molecular orientation, diffusion, and competitive adsorption.

04 Validation priorities

Recommended isotherms, mixture tests, breakthrough, cycling, stability, and regeneration studies.

Frequently Asked Questions

Planning a molecular separation project

What information is needed to begin a separation-materials project?

Useful inputs include the feed composition, target product or contaminant, pressure and temperature range, humidity, required purity or removal level, regeneration method, known materials, and available adsorption or cycling data. The study can also begin from a target mixture and an open materials search.

Can MOFs, COFs, zeolites, activated carbons, and porous polymers be compared together?

Yes, provided the comparison uses consistent process-relevant metrics and acknowledges differences in stability, shaping, density, pore accessibility, cost-related constraints, and data quality. The goal is to identify credible material classes and candidates rather than force unlike materials into one simplistic score.

Can the model account for humidity and mixed-gas competition?

Yes. Depending on available structures, force fields, data, and project scope, humidity and mixture effects can be addressed using competitive adsorption models, molecular simulation, data-driven corrections, or targeted experimental-data integration.

How is regeneration included in material ranking?

Ranking can include working capacity, adsorption strength, desorption conditions, heat of adsorption, pressure or temperature swing, irreversible binding risk, and predicted capacity retention. The appropriate regeneration metric depends on the intended process.

Can proprietary adsorption isotherms or breakthrough data be used?

Yes. Client-provided isotherms, kinetic measurements, breakthrough curves, cycling results, stability data, and negative findings can be incorporated into project-specific models and candidate comparisons under the agreed confidentiality framework.

Define the separation before selecting the material

Share the feed mixture, target purity or removal goal, operating conditions, candidate material space, and available data. Our scientists will help design a screening and validation strategy around the real process decision.

Request a Separation Assessment

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