Inverse Design of Nanoparticulate Materials
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré +5 more
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Covert communications in a downlink time division multiple access system. [PDF]
Moon J, Kim T, Bang I.
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Multi-Objective Optimization for Through-Silicon via Structure Considering Thermomechanical Reliability and Electrical Performance. [PDF]
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A GCU-SAM Enhanced Transformer for Fault Diagnosis of Rotating Machinery. [PDF]
Li J, Hu L, Luo P.
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An improved human memory algorithm with multi-directional and chaotic approaches for global optimization and energy-efficient cluster head selection in WSNs. [PDF]
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Mechanical Properties and Energy Absorption Characteristics of Ring Lattice Sandwich Structures Under Compressive Load. [PDF]
Wang W, Jiang X, Liao Y, Tian Z.
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Optimizing Process Parameters in Laser Transmission Welding Solid PC/Porous-PET Using Prediction Models: Experimental Validation and Morphology Analysis. [PDF]
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A Tutorial and Review on Inter-Layer FEC Coded Layered Video Streaming
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