AIMC Topic: Chemistry Techniques, Synthetic

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MlCOFSyn: A Machine Learning Framework To Facilitate the Synthesis of 2D Covalent Organic Frameworks.

Journal of chemical information and modeling Jun 5, 2025
Two-dimensional covalent organic frameworks (2D COFs) have been historically synthesized empirically, often resulting in uncontrolled crystallization and inferior crystal sizes, which limit their performance in various applications. Recently, crystal...
Chemistry Techniques, Synthetic Crystallization Machine Learning Metal-Organic Frameworks Models, Molecular
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Machine Learning for Predicting the Drug-to-Antibody Ratio (DAR) in the Synthesis of Antibody-Drug Conjugates (ADCs).

Journal of chemical information and modeling Apr 11, 2025
The pharmaceutical industry faces challenges in developing efficient and cost-effective drug delivery systems. Among various applications, antibody-drug conjugates (ADCs) stand out by combining cytotoxic or bioactive agents with monoclonal antibodies...
Machine Learning Chemistry Techniques, Synthetic Immunoconjugates Antibodies, Monoclonal Algorithms
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Investigations into the Efficiency of Computer-Aided Synthesis Planning.

Journal of chemical information and modeling Jan 31, 2025
The efficiency of machine learning (ML) models is crucial to minimize inference times and reduce the carbon footprints of models deployed in production environments. Current models employed in retrosynthesis to generate a synthesis route from a targe...
Machine Learning Chemistry Techniques, Synthetic Algorithms
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Chemoenzymatic Synthesis Planning Guided by Reaction Type Score.

Journal of chemical information and modeling Dec 8, 2024
Thanks to the growing interest in computer-aided synthesis planning (CASP), a wide variety of retrosynthesis and retrobiosynthesis tools have been developed in the past decades. However, synthesis planning tools for multistep chemoenzymatic reactions...
Neural Networks, Computer Chemistry Techniques, Synthetic
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Autonomous mobile robots for exploratory synthetic chemistry.

Nature Nov 6, 2024
Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making. Most autonomous laboratories involve bespoke automated equipment, and reaction outcomes are ofte...
Laboratories Chemistry Techniques, Synthetic Workflow Photochemistry Magnetic Resonance Spectroscopy Decision Making Robotics Chromatography, Liquid Reproducibility of Results Mass Spectrometry Algorithms
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RLSynC: Offline-Online Reinforcement Learning for Synthon Completion.

Journal of chemical information and modeling Aug 18, 2024
Retrosynthesis is the process of determining the set of reactant molecules that can react to form a desired product. Semitemplate-based retrosynthesis methods, which imitate the reverse logic of synthesis reactions, first predict the reaction centers...
Chemistry Techniques, Synthetic Machine Learning
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Computational prediction of complex cationic rearrangement outcomes.

Nature Nov 15, 2023
Recent years have seen revived interest in computer-assisted organic synthesis. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field, including examples leading to advanced natur...
Reproducibility of Results Cyclization Knowledge Bases Terpenes Cations Biological Products Neural Networks, Computer Algorithms Solutions Chemistry Techniques, Synthetic
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Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit.

Journal of chemical information and modeling Jun 14, 2023
Machine learning models are increasingly being utilized to predict outcomes of organic chemical reactions. A large amount of reaction data is used to train these models, which is in stark contrast to how expert chemists discover and develop new react...
Chemistry Techniques, Synthetic Machine Learning Prospective Studies
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Merging enzymatic and synthetic chemistry with computational synthesis planning.

Nature communications Dec 14, 2022
Synthesis planning programs trained on chemical reaction data can design efficient routes to new molecules of interest, but are limited in their ability to leverage rare chemical transformations. This challenge is acute for enzymatic reactions, which...
Neural Networks, Computer Stereoisomerism Dronabinol Algorithms Chemistry Techniques, Synthetic
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Chemistry-informed molecular graph as reaction descriptor for machine-learned retrosynthesis planning.

Proceedings of the National Academy of Sciences of the United States of America Oct 3, 2022
Infusing "chemical wisdom" should improve the data-driven approaches that rely exclusively on historical synthetic data for automatic retrosynthesis planning. For this purpose, we designed a chemistry-informed molecular graph (CIMG) to describe chemi...
Solvents Machine Learning Chemistry Techniques, Synthetic Neural Networks, Computer Catalysis Monte Carlo Method
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