13 papers · ranked by Valyu relevance
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With the rapid growth of chemical data and information, there is an increasing need for chemistry undergraduates to master Python tools for analyzing large chemical datasets and extracting key or feature information. Currently, more than 100,000 types of metal-organic frameworks (MOFs), as the material recently awarded…
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We present an open source collection of scripts and programs for the setup, management and evaluation of calculations with the Vienna ab-initio simulation package (VASP), called utils4VASP. It contains 20 independent Python scripts and Fortran programs, all with a unified and intuitive handling concept based on command…
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The analysis of molecular dynamics (MD) simulations is a critical but fragmented process, often requiring researchers to chain together multiple software tools and write bespoke scripts for routine structural and dynamic analyses. This workflow complexity creates a significant barrier to efficiency, standardization…
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TurtleMol is an open-source Python package that aims to help users generate large, complex molec- ular systems. In the current version, users can generate systems by filling volumes defined by basic geometric shapes (e.g. cube, sphere), or by shapes of arbitrary gemoetries defined meshes created in other software (such…
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Here, we present MolPic, an open-source Python-based software that can be used to generate high-resolution, publication-quality molecular figures directly from compound names or SMILES strings. MolPic supports single-molecule rendering, batch processing, and automated multi-panel 2D figure generation, which are…
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The materials-science literature is the richest reservoir of domain knowledge, yet converting its unstructured text—especially narrative passages and complex tables—into machine-readable data for analysis and ML model training remains challenging. To address this, we present KnowMat, an agentic, multi-stage pipeline…
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We provide an overview of core molSimplify functionality and recent updates that enhance its capabilities for automated molecular and materials modeling. We describe the mol3D and atom3D classes, which store atomic and bonding information for a wide range of functions, including reading, modifying, and characterizing…
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Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
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Mass spectrometry (MS) generates large datasets that are stored in increasingly optimized and complex file types, demanding technical expertise to extract information rapidly and easily. We wondered whether a simple structured query language (SQL) database could hold raw MS data and allow for easily readable queries…
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Large Language Models and Agentic Artificial Intelligence stand poised to completely overhaul our collective approach to science. Within chemical property prediction in particular, natural language-based workflows for modeling are already making serious inroads. To further this aim, in this white paper we introduce…
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Computational methods for predictive modeling have been increasingly utilized in the early stages of drug discovery to supplement high-throughput screening. The advent of highly efficient and complex machine learning architectures necessitates new methods of collating the plethora of topological, geometrical, and…
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Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
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For decades, molecular visualization software has been fundamental to education and research in chemistry, structural biology, and materials science. These tools have enabled the inspection of structures, dynamics, and interactions, yet their reliance on two-dimensional (2D) interfaces imposes persistent limitations.…