AIMC Topic: Chemistry Techniques, Synthetic

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Organic synthesis in a modular robotic system driven by a chemical programming language.

Science (New York, N.Y.) Nov 29, 2018
The synthesis of complex organic compounds is largely a manual process that is often incompletely documented. To address these shortcomings, we developed an abstraction that maps commonly reported methodological instructions into discrete steps amena...
Software Automation Sildenafil Citrate Technology, Pharmaceutical Diphenhydramine Chemistry Techniques, Synthetic Programming Languages Triazoles Robotics
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Controlling an organic synthesis robot with machine learning to search for new reactivity.

Nature Jul 18, 2018
The discovery of chemical reactions is an inherently unpredictable and time-consuming process. An attractive alternative is to predict reactivity, although relevant approaches, such as computer-aided reaction design, are still in their infancy. React...
Robotics Chemistry Techniques, Synthetic Decision Making Spectrophotometry, Infrared Magnetic Resonance Spectroscopy Indicators and Reagents Machine Learning Time Factors
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Sonochemical-solvothermal synthesis of guanine embedded copper based metal-organic framework (MOF) and its effect on oprD gene expression in clinical and standard strains of Pseudomonas aeruginosa.

Ultrasonics sonochemistry Nov 26, 2017
The guanine incropped Cu based metal-organic framework (Guanine-Cu-MOF) was synthesized by facile one-step sonochemical method by simply mixing of 4-4, biphenyldicarboxylic, guanine and copper nitrate (Bio-Cu-Hbpdc-Gu). The prepared guanine-MOF was c...
Chemistry Techniques, Synthetic Guanine Carboxylic Acids Porins Metal-Organic Frameworks Ultrasonic Waves Pseudomonas aeruginosa Microbial Sensitivity Tests Humans Gene Expression Regulation Copper
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Syntheses and antibacterial activity of soluble 9-bromo substituted indolizinoquinoline-5,12-dione derivatives.

European journal of medicinal chemistry Dec 27, 2016
In our previous research, 9-bromo indolizinoquinoline-5,12-dione 1 has been found to be a good anti-MRSA agent. However, it had very low bioavailability in vivo possibly due to its low solubility in water. In order to obtain the derivatives with high...
Quinolines Chemistry Techniques, Synthetic Bacteria Solubility Water Anti-Bacterial Agents Humans Microbial Sensitivity Tests
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Enhancing Monte Carlo Tree Search for Retrosynthesis.

Journal of chemical information and modeling Jul 14, 2025
Computer-Assisted Synthesis Programs are increasingly employed by organic chemists. Often, these tools combine neural networks for policy prediction with heuristic search algorithms. We propose two novel enhancements, which we call eUCT and dUCT, to ...
Monte Carlo Method Chemistry Techniques, Synthetic Neural Networks, Computer Algorithms
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Exploring BERT for Reaction Yield Prediction: Evaluating the Impact of Tokenization, Molecular Representation, and Pretraining Data Augmentation.

Journal of chemical information and modeling May 12, 2025
Predicting reaction yields in synthetic chemistry remains a significant challenge. This study systematically evaluates the impact of tokenization, molecular representation, pretraining data, and adversarial training on a BERT-based model for yield pr...
Machine Learning Chemistry Techniques, Synthetic
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For chemists, the AI revolution has yet to happen.

Nature May 1, 2023
Chemistry Techniques, Synthetic Chemistry Artificial Intelligence
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Planning chemical syntheses with deep neural networks and symbolic AI.

Nature Mar 28, 2018
To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable t...
Chemistry Techniques, Synthetic Chemistry, Organic Artificial Intelligence Monte Carlo Method Neural Networks, Computer
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Perturbation Theory Machine Learning Models: Theory, Regulatory Issues, and Applications to Organic Synthesis, Medicinal Chemistry, Protein Research, and Technology.

Current topics in medicinal chemistry Jan 1, 2018
Machine Learning (ML) models are very useful to predict physicochemical properties of small organic molecules, proteins, proteomes, and complex systems. These methods may be useful to reduce the cost of research in terms of materials resources, time,...
Proteins Models, Chemical Chemistry, Pharmaceutical Chemistry Techniques, Synthetic Computer Simulation Humans Animals Machine Learning
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