Flexibility in load demand and PHEV parameters for clean and economic microgrid operation. [PDF]
Dey B, Misra S, Pal A.
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It provides an overview of the synthesis of organic/inorganic nanocomposites, spanning from conventional methods to advanced 3D printing techniques. It summarizes key challenges in 3D‐printed nanocomposites and highlights emerging innovations, including 5D printing, AI‐assisted material design, nanoscale additive manufacturing, and sustainable closed ...
Liwen Zhang+8 more
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Two-layer energy scheduling of electrical and thermal smart grids with energy hubs including renewable and storage units considering energy markets. [PDF]
Aich W+9 more
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AI‐Driven Defect Engineering for Advanced Thermoelectric Materials
This review presents how AI accelerates the design of defect‐tuned thermoelectric materials. By integrating machine learning with high‐throughput data and physics‐informed representations, it enables efficient prediction of thermoelectric performance from complex defect landscapes.
Chu‐Liang Fu+9 more
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Capabilities of battery and compressed air storage in the economic energy scheduling and flexibility regulation of multi-microgrids including non-renewable/renewable units. [PDF]
Naghibi AF+4 more
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High‐entropy materials (HEMs), typically composed of five or more principal elements in near‐equimolar ratios, offer significant potential due to their unique properties. This review outlines the emergence and structural evolution of HEMs, followed by an in‐depth discussion of the elemental roles (active sites, promoters, or stabilizers) for water ...
Yufei Zhao+9 more
wiley +1 more source
Parameter inference for stochastic reaction models of ion channel gating from whole-cell voltage-clamp data. [PDF]
Del Core L, Mirams GR.
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Using multivariate analysis, a novel emulgel adjuvant is developed by combining key nanoemulsion formulation variables–hydrogel trapping, small globule size, and mannide monooleate surfactant–achieving 10× greater immunogenicity than MF59 in mice after a single shot.
Ahmed O. Shalash+9 more
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A comparative study of deterministic and stochastic computational modeling approaches for analyzing and optimizing COVID-19 control. [PDF]
Kadri A+5 more
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Hardware Implementation of On‐Chip Hebbian Learning Through Integrated Neuromorphic Architecture
This work presents a neuromorphic hardware platform that integrates presynaptic transistors, threshold switching neurons, and adaptive feedback synapses. The architecture enables on‐chip Hebbian learning through correlation‐based weight updates without external training circuits.
Seonkwon Kim+6 more
wiley +1 more source