"Explainable AI: Understanding, Prediction and Trust", lecture by Prof. Jan Jensen

YouTube video by AiChemist-MSCA-DN

youtu.be

Axel Dieter Becke: Not just the "B" in "B3LYP"

There is hardly anyone doing electronic structure calculations on molecules who has not used the famous B3LYP functional. Many will even know that the "B" in B3LYP stands for Becke, but how many know ...

arxiv.org

SmartReact: An Open-Source Python Package for Scalable Forward Synthesis Enumeration Built on Interpretable SMARTS Templates | ChemRxiv

Predicting which products can be made from a set of building blocks underpins library design, analogue generation, and synthesis-constrained generative modelling. Reaction templates encoded as SMARTS patterns are the standard tool for this forward ...

chemrxiv.org

ROBUST TRANSFER LEARNING FOR BAYESIAN OPTIMIZATION OF CHEMICAL REACTIONS | ChemRxiv

Transfer learning offers a promising route to accelerate Bayesian optimization (BO) by reusing knowledge acquired during related optimization tasks. In chemical reaction optimization, this most natura...

chemrxiv.org

Position: The Inevitable Transition to Machine Learning in Quantum Chemistry

Finding exact solutions to the quantum many-body problem is computationally intractable (QMA-hard). Traditional approximations for electrons in an atom or molecule -- density functional theory and wav...

arxiv.org

chemrxiv.org

MLIP-Enhanced Thermochemistry Predictions across Organic Chemical Space | ChemRxiv

This work presents thermoMLIP, a machine-learning-interatomic-potential-based workflow for efficient conformer optimization and thermochemistry prediction across organic chemical space. By combining M...

chemrxiv.org

Lectures and Seminars | AiChemist MSCA-DN

aichemist.eu

Systematic Expansion of Chemical Reaction Space from Graph-Based Model Reactions | ChemRxiv

Computational kinetic modeling relies on accurate transition-state geometries and activation barriers. While machine learning models trained on ab initio data have shown promise for transition-state s...

chemrxiv.org

Chemically Interpretable Explanations for Molecular Property Prediction via Fragment-Level Shapley Values | ChemRxiv

Machine learning has emerged as a powerful approach for molecular property prediction and drug discovery. However, the black-box nature of many machine learning models limits their interpretability, trustworthiness, and adoption in interdisciplinary ...

chemrxiv.org

Solitarius: An Agentic Architecture for Computer-aided Molecular Inverse Design | ChemRxiv

Applying generative molecular design requires both chemical knowledge to turn a scientific aim into a computable objective and technical skill to configure and run the workflow that pursues it. Here, ...

chemrxiv.org

My Best Senior Engineer Quit Last Month. Her Exit Interview Was Scheduled for Forty Minutes.

She was not burned out from writing code. She had barely written any in eight months. She was burned out from reading it. From being the…

blog.stackademic.com

Tenure-track Assistant Professor or Associate Professor of De novo Protein Design

The Novo Nordisk Foundation Center for Protein Design at the University of Copenhagen seeks to appoint two new group leaders in de novo protein design from 1 February 2027 or as soon as possible thereafter. These positions will be at the Assistant or Associate Professor level and associated with the Department of Biology (Faculty of Science) or the Department of Drug Design and Pharmacology (Faculty of Health and Medical Sciences).

employment.ku.dk

After Automation

AI progress creates more work for humans, not less

every.to

Harnessing AtomisticSkills for Agentic Atomistic Research

Bowen Deng, Bohan Li, Matthew Cox, Hoje Chun, Juno Nam, Artur Lyssenko, Sathya Edamadaka, Jurgis Ruza, Xiaochen Du, Nofit Segal, Jesus Diaz ...

compchemhighlights.org

A unified framework for automated transition state generation to accelerate mechanistic exploration in organic synthesis | ChemRxiv

Accurate generation of intricate 3D molecular structures is a fundamental challenge in computational chemistry. Transition states (TS), the transient structures that dictate reaction kinetics, exempli...

chemrxiv.org

Benchmark of double-ended transition state search methods for metal-catalysed reactions | ChemRxiv

Efficient and reliable identification of transition states (TS) is critical for reaction modelling. Among the available approaches, the combination of double-ended TS search with eigenvector-following...

chemrxiv.org

Data-driven complete basis set limit estimates from a minimal auxiliary basis

Quantum chemistry calculations are often performed using atom-centered basis sets which are chosen to balance accuracy and cost. While they are systematically improvable, the total energy converges sl...

arxiv.org