High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning
We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang +6 more
wiley +1 more source
A Dynamic Physics-Guided Ensemble Model for Non-Intrusive Bond Wire Health Monitoring in IGBTs. [PDF]
Yang X, Hu Z, Bo Y, Shi T, Cui M.
europepmc +1 more source
Fluctuation-bias trade-off in portfolio optimization under Expected Shortfall with $\ell_2$ regularization [PDF]
Gábor Papp, Fabio Caccioli, Imre Kondor
openalex
Learned regularization for image reconstruction in sparse-view photoacoustic tomography
Tong Wang +4 more
openalex +1 more source
By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang +9 more
wiley +1 more source
HR-Mamba: Building Footprint Segmentation with Geometry-Driven Boundary Regularization. [PDF]
Su B +7 more
europepmc +1 more source
Tikhonov regularization in Hilbert scales under conditional stability assumptions [PDF]
H Egger, B Hofmann
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Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Divergence unveils further distinct phenotypic traits of human brain connectomics fingerprint. [PDF]
Uddin MK +4 more
europepmc +1 more source
Schematic illustration of SiNDs composite materials synthesis and its internal photophysical process mechanism. And an AI‐assisted dynamic information encryption process. ABSTRACT Persistent luminescence materials typically encounter an intrinsic trade‐off between high phosphorescence quantum yield (PhQY) and ultralong phosphorescence lifetime.
Yulu Liu +9 more
wiley +1 more source

