Results 141 to 150 of about 381,026 (309)

CEG 720: Computer Architecture I

open access: yes, 2010
Review of sequential computer architecture and study of parallel computers. Topics include memory hierarchy, reduced instruction set computer, pipeline processing, multiprocessing, various parallel computers, and interconnection ...
Chung, Soon M.
core  

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

open access: yesAdvanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou   +5 more
wiley   +1 more source

Orbital Geometry‐Governed Response of Pressure‐Tunable Quantum Defects in hBN

open access: yesAdvanced Functional Materials, EarlyView.
Defects in hBN act as ultrasensitive quantum manometers when the energy of the intradefect optical transitions is modified by lattice compression. The orbital geometry of the electron wave functions governs how electron hopping and Coulomb interactions react uniquely to the reduction of the van der Waals gap and in‐plane compression, leading to robust ...
Magdalena Grzeszczyk   +6 more
wiley   +1 more source

CEG 7350-01: Computer Architecture

open access: yes, 2012
Review of sequential computer architecture and study of parallel computers.Topics include memory hierarchy, reduced instruction set computer, pipelineprocessing, multiprocessing, various parallel computers, and interconnection ...
Chung, Soon M.
core  

Performance Characteristics of OpenMP Language Constructs on a Many-core-on-a-chip Architecture

open access: yes, 2008
. Recent emerging many-core-on-a-chip architectures present massive on-chip parallelism through hardware support for multithreading. In order to achieve fast development of parallel applications that exploit this massive intrachip parallelism to achieve ...
Weirong Zhu   +2 more
core   +1 more source

Moving Beyond Oligoethers: Polar Side‐Chain Engineering for Aqueous Mixed Ionic–Electronic Conductors

open access: yesAdvanced Functional Materials, EarlyView.
We investigate how side‐chain chemistry and hydrogen bonding affect electrochemical doping in poly(propylenedioxythiophene) polymers. Replacing oligoether side chains with hydroxyl or carboxylic acid groups nearly triples electrochemical conductivity.
Joshua M. Rinehart   +5 more
wiley   +1 more source

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

open access: yesAdvanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone   +8 more
wiley   +1 more source

Implicit Unstructured Computational Aerodynamics on Many-Integrated Core Architecture

open access: yes, 2014
This research aims to understand the performance of PETSc-FUN3D, a fully nonlinear implicit unstructured grid incompressible or compressible Euler code with origins at NASA and the U.S.
Al Farhan, Mohammed, Keyes, David E.
core  

Ultrasensitive Anti‐Stokes Luminescence Thermometry in Transition Metal Dichalcogenide Monolayers

open access: yesAdvanced Functional Materials, EarlyView.
We demonstrate a highly sensitive nanothermometer using anti‐Stokes photoluminescence, also known as photoluminescence upconversion (UPL), in monolayer tungsten disulfide. A strong resonantly enhanced UPL is observed, confirming the central role of optical phonons in the PL upconversion mechanism.
Sharada Nagarkar   +6 more
wiley   +1 more source

PseudospectralNet: Toward Hybrid Atmospheric Models for Climate Simulations

open access: yesJournal of Advances in Modeling Earth Systems
Recent machine learning (ML) models have shown great success for weather prediction tasks, suggesting that atmospheric dynamics can in principle be learned from data.
Maximilian Gelbrecht   +2 more
doaj   +1 more source

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