chemistry

This paper presents a conditional catalyst generative model based on GPT architecture, pretrained on 133 million catalyst structures, achieving 98% structural validity and enabling controllable inverse design for targeted properties such as binding energy.

Introducing PhET Interactive Simulations, a free and ad-free interactive science simulation tool developed by the University of Colorado. It covers multiple subjects including physics, chemistry, and biology, with over 1.8 billion simulations completed. Suitable for students and teachers of all ages.

A researcher describes building a deep learning model with 270k parameters to predict melting points from topological indices, achieving R² 0.6399, and asks whether to publish the results.

A detailed account of how a mysterious contaminant, dimethylsilanediol, was discovered in the ISS's recycled water in 2010, nearly forcing a mission abort until Boeing identified the siloxane compound.

Anthropic's Claude, a general-purpose AI model without chemistry fine-tuning, outperformed specialized software like ChemDraw and MestReNova in NMR analysis, suggesting that the bottleneck in scientific AI has shifted from model capability to workflow design.

Showcases an AI-driven 3D chemistry learning app called Rebeldia, which uses Gemini 3.1 Pro and GPT Images 2 to build an explorable atomic universe, replacing the traditional periodic table with an interactive knowledge graph and real-time challenges.

Anthropic's new blog post details how Claude (Opus 4.7) can interpret NMR spectra, matching or beating dedicated software on some tasks, marking a step toward making AI useful for chemists.

This article explains in depth that electrolysis is not simply water splitting, but two separate reactions that produce acid and alkali at the positive and negative electrodes respectively. It also demonstrates methods to make hydrochloric acid and purify metals from ore using this principle, and introduces the key role of a homemade ion exchange membrane.

A detailed derivation of pancake chemistry from first principles, with an interactive calculator that adjusts ingredients based on available acids and desired texture.

Researchers used classical computers to solve a key chemistry problem involving the nitrogenase enzyme, which was previously thought to require quantum computers, demonstrating that classical methods can still handle complex quantum systems.

This paper introduces an expert-augmented, data-driven scoring framework that combines machine learning with chemists' domain knowledge to evaluate multi-step synthetic routes, achieving significant improvements in prediction accuracy over baselines.

MIT Associate Professor Connor Coley discusses his work developing AI models to understand chemical principles and accelerate drug discovery by predicting reaction pathways and analyzing vast numbers of potential compounds.

This paper reports the discovery of a molecule with a half-Möbius topology, a novel molecular structure that could have implications for materials science and synthetic chemistry.

This paper introduces ChemCost, a benchmark for evaluating how well LLM agents can estimate chemical procurement costs by grounding identities, retrieving quotes, and handling noise. It reveals that current agents struggle with robustness and precise arithmetic reasoning in scientific workflows.

ChemAmp introduces a tool amplification paradigm that dynamically coordinates specialized chemistry tools (UniMol2, Chemformer) as composable agents to enhance performance on molecular tasks. The framework outperforms chemistry-specialized models and reduces inference token costs by 94% compared to vanilla multi-agent systems.

Anthropic is collaborating with chemists to enhance Claude's chemistry capabilities, starting with a white paper on how Claude performs on NMR spectrum analysis compared to ChemDraw.