ChromSoc is organizing a two-day symposium, Data Analytics and Ai in Chromatography, from 10–11 May 2027 in the Green Park Conference Centre in Reading, UK. The Chromatographic Society (ChromSoc) is organizing a two-day symposium called Data Analytics and Ai in Chromatography running…
Electrocatalysis sits at the heart of clean hydrogen production, fuel cells, and carbon dioxide conversion, yet progress toward scalable, high-performance catalysts has remained frustratingly slow. A growing body of research now suggests that artificial intelligence (AI) may be key to…
A research team maps the key tasks that define modern enzyme engineering—function annotation, structure modeling, and property prediction—and explain how AI methods now accelerate each step, from mining candidate enzymes in massive sequence databases to generating new variants…
Considering these criteria, researchers from Tokyo University of Science (TUS) led by Associate Professor Takashi Ikuno have developed a flexible paper-based sensor that operates like the human brain. Their findings were published online in the journal Advanced Electronic Materialson 22 February…
A Tsinghua University team built OrgAIcat, a machine learning framework trained on more than 22,000 literature data points that predicts enantioselectivity in organocatalytic reactions and, combined with Bayesian optimization, raised a challenging Aldol reaction from 41% to 96% ee in only 12 experiments.
An international team of 69 researchers has proposed a physics-aware AI framework, published in ACS Energy Letters, designed to make AI-guided discovery of solid-state hydrogen storage materials more reliable through constrained models, transparent data, and continuous experimental feedback.
Intelligent design is fundamentally a theory of design detection. But in addition to helping us evaluate models that best explain past events, ID can also guide experiments that study the present-day… Download file | Play in new window | Duration: 00:40:49 | Recorded on…
A controlled lemon balm experiment linked fungal inoculation and 250 ppm TiO₂ nanoparticles to improved growth and reduced malondialdehyde under drought, while Bayesian Ridge regression predicted shoot fresh weight with an R² of 0.9194. In a controlled plant experiment, inoculation with the arbuscular mycorrhizal…
A new study shows a CatBoost machine learning model with only seven simple inputs predicts fluorinated gas solubility in ionic liquids with roughly three times the accuracy of earlier descriptor-heavy neural networks. Subject of Research: Interpretable ensemble machine learning for…
AI models can screen millions of potential materials, reducing computational searches from decades to hours and helping researchers focus on promising candidates for laboratory testing. Open databases such as the Materials Project provide large, curated datasets that support machine learning,…
Artificial intelligence for chemistry: machine learning for molecules, reactions and materials, generative design, chemistry foundation models and datasets.
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