Computational chemistry – Page 7
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WebinarImproving battery performance with cutting edge 3D chemistry modelling & simulation
Improve battery cell performance, reduce costs, cut waste and minimise risk
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ResearchInfinity shaped molecule displays unexpected aromaticity
New calculations uncover deeper understanding of the electron delocalisation behaviour in an unusual twisted polyarene
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ResearchThis computational chemist is experimentalists’ secret weapon in the hunt for new materials
Kim Jelfs discusses how software development feeds – and needs – collaboration
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ResearchMolecular counterfactuals method helps researchers explain AI predictions
Understanding machine learning predictions by exploring the road not travelled
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WebinarDriving the development of bio-based polymers with molecular simulation
Large-scale molecular simulations minimise costs and reduce the time it takes to develop bio-based polymer materials
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ResearchReal space alternative for magnetic spin-coupling models
Model for magnetic coupling moves past the orbital picture and overcomes its limitations
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ResearchComputational study predicts new high-pressure polymorph of Roy
Conformational energy-corrected DFT combined with crystal structure prediction leads to first crystal energy landscape for Roy that agrees with experimental evidence
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OpinionThe chemist’s gambit
If artificial intelligence can revolutionise chess, what might it do to chemistry?
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OpinionThe law of conservation of data
AI and machine learning are useful and powerful, but they need high quality data inputs that aren’t available yet for drug discovery
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ResearchAlgorithm out of Google’s DeepMind finesses DFT calculations
Machine learning creates algorithm that avoids large errors in solutions to certain problems
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ResearchUnsupervised machine-learning tool could accelerate catalyst discovery
The approach was able to identify phosphine ligands that may form dinuclear palladium(I) complexes using only five experimental data points
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ResearchMinority Report-esque AI predicts new designer drugs before they’re made
Machine learning program accurately predicts structure of unknown psychoactive substances from mass spectra alone
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ResearchTextbook electronegativity model fails when it comes to carbon–halogen bond strengths
Computational analysis finds that it’s size, not electronegativity differences, determining bond strength within periodic table groups
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WebinarEfficient modelling of polymers for industrial applications using molecular dynamics
Learn how simulations can elevate polymer modelling and enhance your workflow
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ResearchDouble aromaticity puts a hex on gallium
Planar hexacoordinate cluster isn’t stable when other group 13 elements replace gallium
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ResearchModel performs reality check on adsorbents for carbon capture
Tool could save researchers time by assessing new materials from a variety of angles
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ResearchAre organic chemists discovering fewer reactions than they were decades ago?
Analysis of millions of transformations reveals reliance on popular methods – and the rise of complex reactions
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OpinionWeininger’s Smiles
The man whose code – and attitude to life – brought much happiness to chemists
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BusinessPredicting and preventing production losses with AI
Seebo’s machine learning technology helps chemical manufacturers get deep insight into their processes
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WebinarOptimising protein stability using new computational design approaches for biologics
Learn how to use modern computational methods to optimise your approach to protein stability