Graph-based prediction of reaction barrier heights with on-the-fly prediction of transition states [0.03%]
基于图的反应能垒高度预测及过渡态的实时预测
Johannes Karwounopoulos,Jasper De Landsheere,Leonard Galustian et al.
Johannes Karwounopoulos et al.
The accurate prediction of reaction barrier heights is crucial for understanding chemical reactivity and guiding reaction design. Recent advances in machine learning (ML) models, particularly graph neural networks, have shown great promise ...
Federico Grasselli,Sanggyu Chong,Venkat Kapil et al.
Federico Grasselli et al.
The widespread adoption of machine learning surrogate models has significantly improved the scale and complexity of systems and processes that can be explored accurately and efficiently using atomistic modeling. However, the inherently data...
Coupling causality and interpretable machine learning to reveal the reaction coordinate of C-N coupling with a supramolecular Cu-calix[8]arene catalyst [0.03%]
利用因果关系和可解释的机器学习揭示超分子Cu-刚性八羟基冠醚催化剂促进的C-N偶联反应坐标
R A Talmazan,J Gamper,I Castillo et al.
R A Talmazan et al.
Supramolecular 3d transition-metal catalysts are large, flexible systems with intricate interactions, resulting in complex reaction coordinates. To capture their dynamic nature, we developed a broadly applicable, high-throughput workflow, t...
Going beyond SMILES enumeration for data augmentation in generative drug discovery [0.03%]
超越SMILES枚举，用于生成式药物发现中的数据增强
Helena Brinkmann,Antoine Argante,Hugo Ter Steege et al.
Helena Brinkmann et al.
Data augmentation can alleviate the limitations of small molecular datasets for generative deep learning by 'artificially inflating' the number of instances available for training. SMILES enumeration - wherein multiple valid SMILES strings ...
Comparative analysis of search approaches to discover donor molecules for organic solar cells [0.03%]
用于有机太阳能电池供体分子的搜索方法比较分析
Mohammed Azzouzi,Steven Bennett,Victor Posligua et al.
Mohammed Azzouzi et al.
Identifying organic molecules with desirable properties from the extensive chemical space can be challenging, particularly when property evaluation methods are time-consuming and resource-intensive. In this study, we illustrate this challen...
Accelerating optimization of halide perovskites: two blueprints for automation [0.03%]
卤素钙钛矿优化的加速：自动化蓝图
Hilal Aybike Can,Daniel Anthony Jacobs,Nicolas Fürst et al.
Hilal Aybike Can et al.
The fine-tuning of halide perovskite materials for both performance and stability calls for innovative tools that streamline high-throughput experimentation. Here, we present two complementary systems designed to accelerate the development ...
Development of synthetic chloride transporters using high-throughput screening and machine learning [0.03%]
基于高通量筛选和机器学习的合成氯离子转运蛋白的发展
Surid Mohammad Chowdhury,Nada J Daood,Katherine R Lewis et al.
Surid Mohammad Chowdhury et al.
The development of synthetic compounds capable of transporting chloride anions across biological membranes has become an intensive research field in the last two decades. Progress is driven by the desire to develop treatments for chloride t...
Alex M Ganose,Hrushikesh Sahasrabuddhe,Mark Asta et al.
Alex M Ganose et al.
[This corrects the article DOI: 10.1039/D5DD00019J.]. This journal is © The Royal Society of Chemistry.
Published Erratum
Digital discovery. 2025 Aug 18. DOI:10.1039/d5dd90036k 2025
Optimization of robotic liquid handling as a capacitated vehicle routing problem [0.03%]
带容量约束的车辆路由问题在机器人液体处理中的优化
Guangqi Wu,Runzhong Wang,Connor W Coley
Guangqi Wu
We present an optimization strategy to reduce the execution time of liquid handling operations in the context of an automated chemical laboratory. By formulating the task as a capacitated vehicle routing problem (CVRP), we leverage heuristi...
Laura van Weesep,Rıza Özçelik,Marloes Pennings et al.
Laura van Weesep et al.
Protein-protein interactions are at the heart of biological processes. Understanding how proteins interact is key for deciphering their roles in health and disease, and for therapeutic interventions. However, identifying protein interaction...