Results 241 to 250 of about 14,778,232 (317)
Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh +3 more
wiley +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source
A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe +9 more
wiley +1 more source
HeaTrace: A Parametric Design‐to‐Fabrication Workflow for Thermally Programmable Soft Robots
A programmable thermal actuation workflow enables soft robots to be designed and fabricated with embedded heaters that drive multiple responses. By combining performance‐driven heater design with multimaterial fabrication, the system supports thermally triggered shape change, stiffness tuning, and thermochromic visual response, as demonstrated through ...
Naresh Kumar Thanigaivel +9 more
wiley +1 more source
An adaptive energy management and control framework for long-endurance UAV missions in dynamic environments: A reproducible simulation study. [PDF]
Wang J, Rajendran P, Li A, Wang S.
europepmc +1 more source
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Common Envelope Evolution, 2020
N. Ivanova, Stephen Justham, P. Ricker
semanticscholar +2 more sources
N. Ivanova, Stephen Justham, P. Ricker
semanticscholar +2 more sources
Science of the Total Environment, 2020
Accelerating CO2 emissions have driven physico-chemical changes in the world's oceans, such as ocean acidification and warming. How marine organisms adjust or succumb to such environmental changes may be determined by their ability to balance energy ...
Jonathan Y. S. Leung +2 more
semanticscholar +1 more source
Accelerating CO2 emissions have driven physico-chemical changes in the world's oceans, such as ocean acidification and warming. How marine organisms adjust or succumb to such environmental changes may be determined by their ability to balance energy ...
Jonathan Y. S. Leung +2 more
semanticscholar +1 more source

