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AI-Guided Catalyst Discovery
Identify catalyst compositions and active-site descriptors for plasma environments using machine learning, DFT-informed data, and interpretable screening workflows.
Application · Plasma Catalysis
AI-powered plasma catalysis for next-generation chemical innovation.
DeepChemIQ helps partners design, model, and optimize plasma-catalytic processes across a broad range of chemical transformations. Our ammonia-to-hydrogen work serves as a model study demonstrating how AI, mechanistic modeling, experiments, and reactor analysis can work together.
Plasma
AI
AI
Platform Focus
Catalyst × plasma × reactor intelligence
We combine catalyst discovery, plasma chemistry, CFD, and process-level analysis to accelerate plasma-catalytic technology development.
View Nature Chemical Engineering Paper →View ACS Catalysis Paper →Model Study
Ammonia-to-hydrogen as a demonstration case.
In our published plasma catalysis study, ammonia decomposition to hydrogen was used as a representative system to demonstrate interpretable machine learning-guided catalyst discovery under nonthermal plasma conditions. The same strategy can be adapted to many other plasma-catalytic reactions where catalyst identity, plasma species, reactor design, and energy efficiency must be optimized together.
Interpretable AIPlasma kineticsCatalyst screeningReactor analysis
Capabilities
A flexible platform for different plasma-catalytic innovations.
DeepChemIQ is not limited to one chemistry. We help translate plasma-catalysis concepts into actionable catalyst, reactor, and process-development strategies.
02
Plasma Reaction Innovation
Explore plasma-catalytic pathways for hydrogen, ammonia, CO₂ conversion, nitrogen activation, methane activation, and other emerging chemical transformations.
03
Plasma CFD & Reactor Design
Model discharge behavior, flow fields, temperature profiles, residence time, energy density, and reactor geometry to support scale-up and optimization.
04
Mechanism & Scale-Up Strategy
Connect plasma chemistry, surface kinetics, reactor design, techno-economics, and carbon impact to guide practical development decisions.
Application Areas
Built for broad plasma-catalysis exploration.
We support early-stage discovery, mechanism development, reactor modeling, and scale-up evaluation for multiple plasma-enabled chemical processes.
Plasma-assisted hydrogen production
CO₂ activation and upgrading
Nitrogen fixation and ammonia chemistry
Methane and light hydrocarbon activation
Catalyst screening for nonthermal plasma reactors
Packed-bed and dielectric-barrier-discharge reactor optimization
Development Workflow
From reaction concept to scalable plasma-catalytic design.
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Define the target plasma-catalytic reaction and operating window
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Map plasma species, radicals, excited states, and surface pathways
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Screen catalyst candidates with interpretable AI and descriptor models
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Evaluate reactor geometry, flow, and discharge behavior with plasma CFD
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Prioritize candidates using performance, cost, scalability, and carbon impact
Collaborate with DeepChemIQ
Have a plasma-catalytic process you want to design or optimize?
We work with academic groups, startups, and industrial teams on AI-guided catalyst discovery, plasma CFD, mechanism development, reactor optimization, and techno-economic evaluation.
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