Research Articles
Catalyst Discovery Revolution: How CatDRX Outperforms Traditional Screening in Drug Development
This article provides a comprehensive comparison between the emerging Catalytic Dynamic Redox (CatDRX) platform and established catalyst screening methodologies.
Accelerating Catalysis Discovery: How Bayesian Optimization and In-Context Learning Transform Experimental Design
This article explores the transformative synergy between Bayesian optimization (BO) and in-context learning (ICL) for the autonomous design of catalytic experiments.
Accelerating Catalyst Discovery: A Comprehensive Guide to Bayesian Optimization for Drug Development Researchers
This article provides researchers, scientists, and drug development professionals with a complete framework for implementing Bayesian optimization (BO) to enhance catalyst performance.
Accelerating Discovery: How Bayesian Optimal Design is Revolutionizing Catalyst and Drug Development Research
This article explores the transformative role of Bayesian Optimal Experimental Design (BOED) in catalyst and pharmaceutical research.
The Catalyst AI Dilemma: Mastering Exploration vs. Exploitation for Next-Gen Drug Discovery
This article provides a comprehensive guide for researchers and drug development professionals on navigating the critical trade-off between exploration and exploitation within catalyst generative AI.
Bridging the Digital-to-Physical Gap: A Practical Guide to Assessing the Synthesizability of Generative AI-Designed Catalysts
This article provides a comprehensive framework for researchers and drug development professionals to evaluate the synthesizability of catalysts and molecular entities generated by AI models.
Property-Guided Generation: Revolutionizing Catalyst Design for Biomedical Applications
This article provides a comprehensive guide to property-guided generation for catalyst activity optimization, tailored for researchers and drug development professionals.
Overcoming Domain Shift: A Practical Guide for Applying Catalyst Generative AI in Drug Discovery
Catalyst generative models promise to revolutionize molecular design, but their real-world application is hampered by domain shift—the performance gap between training data and target domains.
Overcoming Data Scarcity in Chemical AI: Advanced Strategies for Reaction-Conditioned Generative Models
This article provides a comprehensive guide for researchers and drug development professionals tackling the critical bottleneck of data scarcity in reaction-conditioned generative models for chemistry.
Advanced ASPEN PLUS Modeling of Catalytic Biomass Gasification: A Complete Guide for Sustainable Fuel Researchers
This comprehensive article provides a detailed guide to modeling catalytic biomass gasification using ASPEN PLUS software, tailored for researchers and scientists in sustainable energy and biofuel development.