Results 131 to 140 of about 493,090 (289)
Functional Encryption Against Probabilistic Queries: Definition, Construction and Applications
Geng Wang +3 more
openalex +1 more source
Epitaxial‐like growth of chalcogenide films on the wafer scale is essential to guarantee homogeneity, but remains challenging using magnetron sputtering, particularly for heterostructures. This work achieves highly textured TiTe2/Sb2Te3 heterostructures with atomically sharp interfaces on standard silicon substrates.
Chao Nie +10 more
wiley +1 more source
Deep Learning Analysis of Solid‐Electrolyte Interphase Microstructures in Lithium‐Ion Batteries
A transformer‐based deep learning model is developed for segmenting and analyzing high‐resolution TEM images of the solid‐electrolyte interphase (SEI) in lithium‐ion batteries. The model is trained on DFT‐based simulated images and predicts SEI grain and grain boundaries, revealing key microstructural features that govern ion transport and degradation.
Ishraque Zaman Borshon +4 more
wiley +1 more source
Explicit Randomness is not Necessary when Modeling Probabilistic Encryption
Véronique Cortier +2 more
openalex +2 more sources
Zn–Sn–O thin films synthesized via ultrasonic spray pyrolysis reveal tunable phase evolution and enhanced acetone selectivity. Integrating DFT insights with machine learning predictions uncovers the role of stoichiometric control and oxygen vacancies in VOC sensing.
Kevin Rueda‐Castellanos +6 more
wiley +1 more source
Benaloh's Dense Probabilistic Encryption Revisited
Laurent Fousse +2 more
openalex +2 more sources
A surface acoustic wave (SAW) launched in a two‐dimensional periodic array of magnetostrctive nanomagnets on a piezoelectric substrate excites spin waves in the nanomagnets which radiate electromagnetic waves in space. The polarization of the emitted beam in particular directions and at particular frequencies can be switched between horizontal and ...
Raisa Fabiha +2 more
wiley +1 more source
Applications of QSPR and Machine Learning in Molecular Photonics
Quantitative structureproperty relationships (QSPR) and machine learning (ML) are transforming photochemistry by enabling pre‐synthetic screening of photoactive molecules. This review outlines advances in data‐driven discovery of optical materials and functional dyes, identifies effective descriptors and models for photophysical processes, and provides
Andrey A. Buglak +2 more
wiley +1 more source
Illuminating Quantum Phenomena in 2D Materials: The Power of Optical Spectroscopy
Atomically thin 2D materials host quantum tunnelling, plasmonic and excitonic phenomena driven by reduced dimensionality and strong many‐body interactions. This review links these effects to state‐of‐the‐art optical probes—NSOM, pump–probe, CARS, TRR, and optical frequency comb spectroscopy—highlighting how their ultrahigh spatial–temporal resolution ...
Yuhui Zhou +4 more
wiley +1 more source

