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The specificity and structure of DNA cross-linking by the gut bacterial genotoxin colibactin
Colibactin is a chemically unstable genotoxic gut bacterial natural product that is linked to colorectal cancer (CRC). Though it has …
PDF Cite DOI bioRxiv
The specificity and structure of DNA cross-linking by the gut bacterial genotoxin colibactin
Reimagining Polymer Networks from Molecule to Material
Active Site Dynamics in Molybdenum-Based Silica-Supported Olefin Metathesis Catalysts: Site Renewal and Decay Beyond the Chauvin Cycle
Heterogeneous olefin metathesis catalysts exhibit low active site densities and unpredictable kinetics due to dynamic active site …
PDF Cite DOI ChemRxiv
Active Site Dynamics in Molybdenum-Based Silica-Supported Olefin Metathesis Catalysts: Site Renewal and Decay Beyond the Chauvin Cycle
Excitonic Anisotropy in Single-Crystalline 2D Silver Phenylchalcogenides
2D materials exhibiting in-plane anisotropy enable new applications in directional energy transport and polarized optical response. …
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Excitonic Anisotropy in Single-Crystalline 2D Silver Phenylchalcogenides
Tetrafunctional cyclobutanes tune toughness via network strand continuity
Customizing the toughness of polymer networks independently of their chemical composition and topology remains an unsolved challenge. …
PDF Cite DOI ChemRxiv
Tetrafunctional cyclobutanes tune toughness via network strand continuity
High-Throughput Discovery of Ferrocene Mechanophores with Enhanced Reactivity and Network Toughening
Mechanophores are molecules that undergo chemical changes in response to mechanical force, offering unique opportunities in chemistry, …
PDF Cite DOI ChemRxiv MIT News
High-Throughput Discovery of Ferrocene Mechanophores with Enhanced Reactivity and Network Toughening
Turning 2D MOFs into Mixed Ionic-Electronic Conductors via Side Chain Engineering
Despite the wide-ranging use of metal–organic frameworks (MOFs) as either electronic or ionic conductors, mixed electron–ion …
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Turning 2D MOFs into Mixed Ionic-Electronic Conductors via Side Chain Engineering
Are we there yet? Adventures on a road trip through machine learning as a computational chemist
Over the past two decades, the integration of machine learning (ML) into theoretical and computational chemistry has transformed the …
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Are we there yet? Adventures on a road trip through machine learning as a computational chemist
Graph neural networks for predicting metal–ligand coordination of transition metal complexes
High-throughput virtual screening campaigns are invaluable for surveying the combinatorial space of possible transition metal complexes …
PDF Cite DOI ChemRxiv
Graph neural networks for predicting metal–ligand coordination of transition metal complexes
Exploring beyond experiment: generating high-quality datasets of transition metal complexes with quantum chemistry and machine learning
Machine learning (ML) approaches enable screening of the vast chemical space of transition metal complexes (TMCs) at faster speeds than …
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Exploring beyond experiment: generating high-quality datasets of transition metal complexes with quantum chemistry and machine learning