Quintina Campbell,Jonathan Herington,Andrew D White
Quintina Campbell
Machine learning models have dual use potential, potentially serving both beneficial and malicious purposes. The development of open-source models in chemistry has specifically surfaced dual use concerns around toxicological data and chemic...
When chemistry is too colourful: gamut clipping in 8-bit sRGB risks misinterpretation of camera-based chemical analysis [0.03%]
当化学色彩过于丰富时：8位sRGB色域压缩会误读基于相机的化学分析结果
Calum Fyfe,Shengkai Yu,Marc Reid
Calum Fyfe
Digital cameras are increasingly utilised to capture visual changes in chemical processes. Monitoring colour with computer vision tools serves as a valuable proxy for monitoring bulk chemical changes. Most consumer-grade cameras digitise th...
Lukas Hörmann,Hemanadhan Myneni,Rwayda Kh S Al-Hamd et al.
Lukas Hörmann et al.
Open and reproducible research in materials science relies on the availability of data, code, and established metadata standards. Journal research data policies (RDPs) are a primary mechanism by which these community norms are enforced. We ...
Text-to-flowsheet: an LLM-assisted pipeline for expert-level digitization and automated simulation of chemical processes [0.03%]
文本到流程图：一种LLM辅助管道，用于化学过程的专家级数字化和自动化模拟
Jan-Frederic Laub,Luca Bosetti,André Bardow
Jan-Frederic Laub
Converting unstructured natural language descriptions into structured process flowsheets is a fundamental bottleneck in chemical engineering, traditionally requiring years of expert training. While large language models (LLMs) show promise ...
optimade-maker: automated generation of interoperable materials APIs from static datasets [0.03%]
优化材料API的自动化生成：基于静态数据集的互操作性材料/APIs
Kristjan Eimre,Matthew L Evans,Bud Macaulay et al.
Kristjan Eimre et al.
Atomistic structural data are central to materials science, condensed matter physics, and chemistry, and are increasingly digitised across diverse repositories and databases. Interoperable access to these heterogeneous data sources enables ...
Louis Longley,Francisco Munguia-Galeano,Yushu Han et al.
Louis Longley et al.
Fume hoods protect chemists and the environment from hazardous vapours and airborne substances produced during experiments. They are standard in chemistry laboratories worldwide. However, fume hoods were designed for manual chemistry, and t...
Molecular arms race classifier for decrypting venom peptide and ion channel interactions [0.03%]
用于解密毒液肽与离子通道相互作用的分子 arms race 分类器
Favour Achimba,Arezoo Bybordi,Mariam Gelashvili et al.
Favour Achimba et al.
Animal venoms comprise an astonishing number of peptides, proteins and small molecules. The diversity of venom compounds arises from evolutionary adaptations resulting in both offensive and defensive traits in predators and prey alike. This...
Identification of drug candidates against glioblastoma with machine learning and high-throughput screening of heterogeneous cellular models [0.03%]
基于机器学习和异质细胞模型高通量筛选的胶质母细胞瘤药物候选物鉴定研究
Vanessa Smer-Barreto,Richard J R Elliott,John C Dawson et al.
Vanessa Smer-Barreto et al.
Glioblastoma multiforme (GBM) is an aggressive primary brain tumour that presents significant treatment challenges due to its complex pathology and heterogeneity. The lack of validated molecular targets is a major obstacle for discovering n...
Accelerating discovery across scientific disciplines through reproducible workflows with AiiDAlab [0.03%]
基于可重复工作流的AiiDA实验加速各学科领域的发现
Aliaksandr V Yakutovich,Daniel Hollas,Edan Bainglass et al.
Aliaksandr V Yakutovich et al.
With ever-increasing computational capabilities, robust and automated research workflows have become essential for orchestrating large numbers of interdependent simulations. However, significant technical expertise is still required to conf...
Benchmarking physics-inspired machine learning models for transition metal complexes with diverse charge and spin states [0.03%]
基准测试物理启发的机器学习模型以求解不同电荷和自旋态的过渡金属配合物问题
Yuri Cho,Ksenia R Briling,Yannick Calvino Alonso et al.
Yuri Cho et al.
Physics-inspired machine learning (ML) models can be categorized into two classes: those relying solely on three-dimensional structure and those incorporating electronic information. In this work, we benchmark both classes for predicting qu...