Research Articles
Iron-Biomass Catalysts for Fischer-Tropsch: LCA Insights on Sustainable Synthesis and Performance
This article provides a comprehensive analysis of iron-based catalysts supported on biomass-derived materials for Fischer-Tropsch synthesis (FTS), viewed through the critical lens of Life Cycle Assessment (LCA).
Accelerating Heterogeneous Catalyst Discovery: A Comprehensive Guide to Generative AI Models in 2024
This article provides researchers and material scientists with a detailed exploration of generative artificial intelligence (AI) for heterogeneous catalyst discovery.
Catalyst Discovery Revolution: Applying Hohenberg-Kohn Theorems for Drug Development
This article explores the transformative role of Density Functional Theory (DFT), founded on the Hohenberg-Kohn theorems, in modern catalyst design and drug discovery.
Mastering Stereochemical Control in Catalysis: A Practical Guide for Modern Drug Development
This comprehensive guide addresses the critical challenge of chirality and stereochemistry in catalyst design and application, a cornerstone of efficient and selective drug synthesis.
Mastering the d-Band Model: A Comprehensive Guide to Hammer and Nørskov's Catalysis Theory for Materials Research
This article provides a definitive guide to the Hammer and Nørskov d-band model, a cornerstone theory in heterogeneous catalysis and surface science.
H-ZSM-5 and H-Beta Zeolite Catalysis: Transforming Biomass Oxygenates into Valuable Platform Chemicals for Biomedical Research
This comprehensive review explores the catalytic cracking of biomass-derived oxygenates using H-ZSM-5 and H-Beta zeolites, focusing on their pivotal role in sustainable chemical synthesis with biomedical relevance.
Generative AI for Catalyst Discovery: A Comprehensive Guide to VAE, GAN, and Diffusion Models
This guide provides researchers, scientists, and drug development professionals with a comprehensive exploration of deep generative models—specifically Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Diffusion Models—for catalyst discovery and...
Revolutionizing Catalyst Discovery: How Equivariant Diffusion Models Generate Novel 3D Molecular Structures
This article explores the cutting-edge application of equivariant diffusion models for generating novel 3D catalyst structures.
Generative AI for Catalysts: How GANs Are Revolutionizing Novel Material Discovery for Researchers
This article provides a comprehensive guide to Generative Adversarial Network (GAN)-based workflows for the discovery and design of novel catalyst materials.
Fine-tuning LLMs for Catalyst Discovery: A Guide to CataLM and Domain-Specific AI in Chemistry
This article provides a comprehensive guide for researchers and drug development professionals on fine-tuning large language models (LLMs) like CataLM for catalyst domain knowledge.