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Showing 133 results for "programming languages" in Chemistry · Preprint
Chemistry Preprint PDF DOI

The Great Chicken-and-Egg of Chemistry: Bonding vs. Stability Revisited

Cherif F. Matta · 2026

The chemical bond is a central organizing concept in chemistry, yet it is absent from the molecular Hamiltonian and no "bond operator" exists. Bonding is therefore not a primitive physical entity but …

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Chemistry Preprint PDF DOI

Generative Chemical Language Models for Energetic Materials Discovery

Andrew Salij, R. Seaton Ullberg, Megan C. Davis, Marc J. Cawkwell, Christopher J. Snyder, Cristina Garcia Cardona, Ivana Matanovic, Wilton J. M. Kort-Kamp · 2026

The discovery of new energetic materials remains a pressing challenge hindered by limited availability of high-quality data. To address this, we have developed generative molecular language models tha…

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Chemistry Preprint PDF DOI

A unified variational framework for the inverse Kohn-Sham problem

Nan Sheng · 2026

The inverse Kohn-Sham (KS) problem seeks a local effective potential whose noninteracting ground state reproduces a prescribed electron density. Existing inversion formulations are often expressed in …

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Chemistry Preprint PDF DOI

Latent space design of interatomic potentials

Susan R. Atlas · 2026

The advent of neural-network-based deep learning techniques has led to the emergence of increasingly sophisticated numerical interatomic potentials, including graph neural networks and large language-…

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Chemistry Preprint PDF DOI

Escaping the Hydrolysis Trap: An Agentic Workflow for Inverse Design of Durable Photocatalytic Covalent Organic Frameworks

Iman Peivaste, Nicolas D. Boscher, Ahmed Makradi, Salim Belouettar · 2026

Covalent organic frameworks (COFs) are promising photocatalysts for solar hydrogen production, yet the most electronically favorable linkages, imines, hydrolyze rapidly in water, creating a stability-…

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Chemistry Preprint PDF DOI

Molecular Representations for AI in Chemistry and Materials Science: An NLP Perspective

Sanjanasri JP, Pratiti Bhadra, N. Sukumar, Soman KP · 2026

Deep learning, a subfield of machine learning, has gained importance in various application areas in recent years. Its growing popularity has led it to enter the natural sciences as well. This has cre…

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Chemistry Preprint PDF DOI

Direct Variational Calculation of Two-Electron Reduced Density Matrices via Semidefinite Machine Learning

Luis H. Delgado-Granados, David A. Mazziotti · 2026

We introduce a data-driven framework for approximating the convex set of $N$-representable two-electron reduced density matrices (2-RDMs). Traditional approaches characterize this set through linear m…

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Chemistry Preprint PDF DOI

AgentCAT: An LLM Agent for Extracting and Analyzing Catalytic Reaction Data from Chemical Engineering Literature

Wei Yang, Zihao Liu, Tao Tan, Xiao Hu, Hong Xie, Lulu Li Xin Li, Jianyu Han, Defu Lian, Mao Ye · 2026

This paper presents a large language model (LLM) agent named AgentCAT, which extracts and analyzes catalytic reaction data from chemical engineering papers, %and supports natural language based intera…

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Chemistry Preprint PDF DOI

NMRTrans: Structure Elucidation from Experimental NMR Spectra via Set Transformers

Liujia Yang, Zhuo Yang, Jiaqing Xie, Yubin Wang, Ben Gao, Tianfan Fu, Xingjian Wei, Jiaxing Sun, Jiang Wu, Conghui He, Yuqiang Li, Qinying Gu · 2026

Nuclear Magnetic Resonance (NMR) spectroscopy is fundamental for molecular structure elucidation, yet interpreting spectra at scale remains time-consuming and highly expertise-dependent. While recent …

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Chemistry Preprint PDF DOI

LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

Xinwu Ye, Yicheng Mao, Jia Zhang, Yimeng Liu, Li Hao, Fang Wu, Zhiwei Li, Yuxuan Liao, Zehong Wang, Yingcheng Wu, Zhiyuan Liu, Zhenfei Yin, Li Yuan, Philip Torr, Huan Sun, Xiangxiang Zeng, Mengdi Wang, Le Cong, Shenghua Gao, Xiangru Tang · 2026

Chemical large language models (LLMs) predominantly rely on explicit Chain-of-Thought (CoT) in natural language to perform complex reasoning. However, chemical reasoning is inherently continuous and s…

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Chemistry Preprint PDF DOI

El Agente Estructural: An Artificially Intelligent Molecular Editor

Changhyeok Choi, Yunheng Zou, Marcel Muller, Han Hao, Yeonghun Kang, Juan B. Perez-Sanchez, Ignacio Gustin, Hanyong Xu, Andrew Wang, Mohammad Ghazi Vakili, Chris Crebolder, Alan Aspuru-Guzik, Varinia Bernales · 2026

We present El Agente Estructural, a multimodal, natural-language-driven geometry-generation and manipulation agent for autonomous chemistry and molecular modelling. Unlike molecular generation or edit…

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Chemistry Preprint PDF DOI

Beyond Learning on Molecules by Weakly Supervising on Molecules

Gordan Prastalo, Kevin Maik Jablonka · 2026

Molecular representations are inherently task-dependent, yet most pre-trained molecular encoders are not. Task conditioning promises representations that reorganize based on task descriptions, but exi…

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Chemistry Preprint PDF DOI

cuGUGA: Operator-Direct Graphical Unitary Group Approach Accelerated with CUDA

Zihan Pengmei · 2026

We present cuGUGA, an operator-direct graphical unitary group approach (GUGA) configuration interaction (CI) solver in a spin-adapted configuration state function (CSF) basis. Dynamic-programming walk…

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Chemistry Preprint PDF DOI

ChemNavigator: Agentic AI Discovery of Design Rules for Organic Photocatalysts

Iman Peivaste, Ahmed Makradi, Salim Belouettar · 2026

The discovery of high-performance organic photocatalysts for hydrogen evolution remains limited by the vastness of chemical space and the reliance on human intuition for molecular design. Here we pres…

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Chemistry Preprint PDF DOI

Large Language Model Agent for User-friendly Chemical Process Simulations

Jingkang Liang, Niklas Groll, Gurkan Sin · 2026

Modern process simulators enable detailed process design, simulation, and optimization; however, constructing and interpreting simulations is time-consuming and requires expert knowledge. This limits …

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Chemistry Preprint PDF DOI

Bridging Visual Intuition and Chemical Expertise: An Autonomous Analysis Framework for Nonadiabatic Dynamics Simulations via Mentor-Engineer-Student Collaboration

Yifei Zhu, Jiahui Zhang, Binni Huang, Zhenggang Lan · 2025

Analyzing nonadiabatic molecular dynamics trajectories traditionally heavily relies on expert intuition and visual pattern recognition, a process that is difficult to formalize. We present VisU, a vis…

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Chemistry Preprint PDF DOI

Pushing the limits of one-dimensional NMR spectroscopy for automated structure elucidation using artificial intelligence

Frank Hu, Jonathan M. Tubb, Dimitris Argyropoulos, Sergey Golotvin, Mikhail Elyashberg, Grant M. Rotskoff, Matthew W. Kanan, Thomas E. Markland · 2025

One-dimensional NMR spectroscopy is one of the most widely used techniques for the characterization of organic compounds and natural products. For molecules with up to 36 non-hydrogen atoms, the numbe…

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Chemistry Preprint PDF DOI

DoNOF 2.0: A modern Open-Source Electronic Structure Program for Natural Orbital Functionals

Juan Felipe Huan Lew-Yee, Ion Mitxelena, Jorge M. del Campo, and Mario Piris · 2025

In this work, we present the second version of the Donostia Natural Orbital Functional Software, an open-source program for natural orbital functional calculations. The new release incorporates improv…

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Chemistry Preprint PDF DOI

Accelerated Machine Learning Force Field for Predicting Thermal Conductivity of Organic Liquids

Wei Feng, Siyuan Liu, Hongyi Wang, Zhenliang Mu, Zhichen Pu, Xu Han, Tianze Zheng, Zhenze Yang, Zhi Wang, Weihao Gao, Yidan Cao, Kuang Yu, Sheng Gong, Wen Yan · 2025

The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, and chemical processin…

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Chemistry Preprint PDF DOI

AtomDisc: An Atom-level Tokenizer that Boosts Molecular LLMs and Reveals Structure--Property Associations

Mingxu Zhang, Dazhong Shen, Ying Sun · 2025

Advances in large language models (LLMs) are accelerating discovery in molecular science. However, adapting molecular information to the serialized, token-based processing of LLMs remains a key challe…

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