Results 181 to 190 of about 5,888,750 (277)

Quantum‐Trained AI Enables Inverse Design of Organic Frontier Orbitals at Billion‐Scale

open access: yesAdvanced Science, EarlyView.
Quantum‐trained AI links molecular substructures to frontier‐orbital energetics and enables interpretable screening across nearly one billion GDB‐13 molecules. By combining fragment‐ and ring‐level insights with donor–acceptor energy alignment against ITIC, the framework narrows an immense chemical space to a small set of promising candidates and ...
Yeongnam Ko, Se Jin Kim, Ki Chul Kim
wiley   +1 more source

Atomistic Kinetics of Dislocation‐Mediated Grain Growth in Monolayer MoS2

open access: yesAdvanced Science, EarlyView.
Atomic‐resolution in‐situ heating microscopy directly visualizes dislocation‐mediated grain boundary migration and grain growth in monolayer MoS2. Mobile grain boundaries migrate through collective motion of Mo 5|7 dislocations, whereas S 5|7 defects remain largely immobile.
Chang‐Won Choi   +11 more
wiley   +1 more source

Exploring anticancer drug structures through vertex based resolving parameters. [PDF]

open access: yesSci Rep
Chaudhry F   +4 more
europepmc   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

open access: yesAdvanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia   +4 more
wiley   +1 more source

Sombor topological indices for different nanostructures. [PDF]

open access: yesHeliyon, 2023
Imran M   +4 more
europepmc   +1 more source

MXene‐Based Room‐Temperature NO2 Gas Sensors: A Meta‐Analysis

open access: yesAdvanced Science, EarlyView.
This study presents the first comprehensive meta‐analysis of MXene‐based NO2 sensors, decoding 32 study characteristics across 61 peer‐reviewed studies. By isolating materials chemistry as the primary performance driver over device‐level parameters, the authors establish a methodological blueprint and a predictive structure–function map to accelerate ...
Alexander Khort   +3 more
wiley   +1 more source

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