Accelerate Porous Sorbent Discovery

Transform months of experimental work into days of computational screening. Our bespoke machine learning models guide material design for environmental, industrial, and defence applications.

10 weeks

From idea to deployment

70%

Reduction in experimental loops

100%

Data-Driven models

Our Services

Comprehensive solutions for porous sorbent screening and material design

Screening-as-a-Service

Screening using foundational models across known porous sorbent classes for your specified target gas or gas mixture.

Deliverables

Top-performing candidate materials
Suggested operating conditions
Feasibility score for rapid triage

Tailored Model Development

Application-specific machine learning models tuned to your desired sorbent class and operating conditions.

Deliverables

Structure–property relationships
Capacity and selectivity analysis
Pathway exploration

Targeted Simulations

Advanced simulations under specified conditions, including impurities, to transform shortlists into actionable decisions.

Deliverables

Multicomponent isotherms
Heats of adsorption
Stability and regeneration insights
Ranked test plan with operating windows

Porous Material Consulting

Expert guidance on porous material selection, optimization, and application strategies tailored to your specific needs.

Deliverables

Material selection recommendations
Structural and adsorption characterization
Process optimization strategies
Experimental and computational training

About Stratsorb

Founded by three PhD colleagues with complementary expertise. Our collective research focuses on environmental and catalytic applications of porous sorbents, with more than 10 years of experience combined.

We develop bespoke machine learning models to screen porous sorbents and guide the design of materials for environmental applications, industrial processes, and defence technologies.

Synthesis

Synthesis & scale-up of porous materials

Characterization

Comprehensive material characterization methods

Computational Simulations

State-of-the-art computational modeling and ML

Our Team

Three PhD founders with complementary expertise

Daniel Pereira

Synthesis & Characterization

Co-Founder & PhD candidate

Expert in advanced synthesis and characterization techniques for porous materials.

Carlos Bornes

AI Lead

Co-Founder & PhD

Specialist in catalysis and machine learning interatomic potential development.

Márcio Soares

Computational Simulations

Co-Founder & PhD candidate

Expert in computational modeling and machine learning for material discovery and optimization.

Why Stratsorb

Traditional trial-and-error approaches are slow and resource-intensive. From synthesis bench to simulation, we bridge experimental and computational expertise to accelerate discovery and turn virtual insights into real-world solutions.

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