Results 211 to 220 of about 42,575 (298)
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
Extrapolating Local Coupled Cluster Calculations toward CCSD(T)/CBS Binding Energies of Atmospheric Molecular Clusters. [PDF]
Knattrup Y, Elm J.
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Spectroscopic Supermassive Dark Star candidates. [PDF]
Ilie C, Mahmud SS, Paulin J, Freese K.
europepmc +1 more source
Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 more
wiley +1 more source
Topology across scales on heterogeneous cell data. [PDF]
Torras-Pérez M +6 more
europepmc +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
A visualizable and widely applicable steric repulsion descriptor for guiding experimental chemistry. [PDF]
Just GH +5 more
europepmc +1 more source
Among patients with acute ischemic stroke achieving successful large vessel recanalization (defined as expanded Thrombolysis in Cerebral Infarction [eTICI ≥2b]), incomplete tissue‐level reperfusion, distinct from visually identifiable distal occlusion on digital‐subtraction angiography, remains a significant challenge.
Yue Qiao +4 more
wiley +1 more source
Pore science and engineering: a new era of porous materials. [PDF]
Yu S, Chen LH, He MY, Su BL.
europepmc +1 more source

