Junction temperature and luminous flux prediction for white LED array based on electrical-photo-thermal modeling

HAS-RL: A Hierarchical Approximate Scheme Optimized With Reinforcement Learning for NoC-Based NN Accelerators

Warpage deformation analysis of AMB ceramic substrates in power modules

Double-sided heat dissipation numerical modeling of an embedded half-bridge power module with multiple chips

Investigating the Sintering Process and Mechanical Properties of Nano-copper Particles Coupling Particle Packing Modeling with Molecular Dynamics Simulation

Signal-dependent reactivity of host-guest complexes controls supramolecular aggregate formation

Microwave-Optics Entanglement Via Cavity Optomagnomechanics

Double-sided numerical thermal modeling of fan-out panel-level MOSFET power modules

Machine learning assisted early anomaly detection of LEDs with spectral power distribution modeling

Research on the optimal dosage of bio-oil/lignin composite modified asphalt based on rheological and anti-aging properties

Chemical signal regulated injectable coacervate hydrogels

Nanoindentation characterization of sintered porous Cu nanoparticles used in power electronics packaging – A molecular dynamic simulation study

Prediction of mechanical solutions for a laminated LCEs system fusing an analytical model and neural networks

Sintering mechanism of Ag nanoparticle-nanoflake: a molecular dynamics simulation

A neural network-assisted 3D theoretical thermoelastic solution for laminated liquid crystal elastomer plate used in restoring cardiac mechanical function

Conductive Co-based metal organic framework nanostructures for excellent potassium- and lithium-ion storage: Kinetics and mechanism studies

A Comprehensive Study on the Rejuvenation Efficiency of Compound Rejuvenators for the Characterization of the Bituminous Binder, Mortar, and Mixture

Research on Thermal-Mechanical Properties of GaN Power Module Based on QFN Package by Using Nano Copper/Silver Sinter Paste

Advances on methane reforming in solid oxide fuel cells

基于Lambert-Beer理论与人工神经网络的混合荧光粉发射光谱预测