Results 61 to 70 of about 1,280 (258)
Advanced Functional Materials, EarlyView.An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
The Geology, Sedimentology, And Stratigraphy Of The Ordovician Through Silurian Smith Formation, Northern Seward Peninsula, Alaska [PDF]
, 1989 Thesis (M.S.) University of Alaska Fairbanks, 1989The purpose of this study is to determine the stratigraphic relationships and depositional settings of three outcrops at Cape Deceit, northern Seward Peninsula, Alaska.
Ryherd, Timothy John
core
Counterion Dependent Side‐Chain Relaxation Stiffens a Chemically Doped Thienothiophene Copolymer
Advanced Functional Materials, EarlyView.Oxidation of a thienothiophene copolymer, p(g3TT‐T2), via different doping strategies and dopant molecules resulted in materials with similar oxidation levels and a high electrical conductivity of ≈100 S cm−1. However, mechanical properties varied significantly, with sub‐glass transition temperatures and elastic moduli spanning from –44°C to –3°C and ...
Mariavittoria Craighero +12 more
wiley +1 more source
EFFECT OF INTER-PLY SLIDING ON THE APPEARANCE OF DEFECTS FOR MULTILAYERED COMPOSITE SHAPING
, 2013 International audienceThe transport sector is one of the fastest growing consumer of energy and producer of greenhouse gases in the world. Consequently, transportation means with a low energy consumption, and thus global warming, are more and more ...
Hivet, G. +2 more
core +2 more sources
Advanced Functional Materials, EarlyView.Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
, 2012 Embedded CPUs typically use much less power than desktop or server CPUs but provide limited or no support for floating-point arithmetic. Hybrid reconfigurable CPUs combine fixed and reconfigurable computing fabrics to balance better execution performance
Mücke, Manfred +5 more
core +1 more source
Advanced Functional Materials, EarlyView.Oxygen‐tunnel (OT) indium tin oxide (ITO) vertical channel transistors (VCTs) enable reliable, high‐density gain‐cell memory for monolithic 3D integration. A sandwiched SiN/SiO2/SiN OT stack selectively regulates oxygen transport, suppressing parasitic electrode oxidation while stabilizing channel oxygen vacancies, thereby suppressing carrier injection
Hyeonho Gu +17 more
wiley +1 more source
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced 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
Titanium Suboxides Responsible for Electronic Anomaly Near Room Temperature in the Ti3C2Tx MXene
Advanced Functional Materials, EarlyView.Our multi‐technique study reveals that the near‐room‐temperature anomaly in Ti3C2Tx MXene is linked to titanium suboxide nanodomains, including Ti3O5, embedded within the MXene host. Their temperature‐driven transformation provides an alternative explanation to solvent‐ and swelling‐based models and offers new insight into the thermally activated ...
Bence G. Márkus +8 more
wiley +1 more source
Parallel Accurate Minifloat MACCs for Neural Network Inference on Versal FPGAs
Machine Learning (ML) is ubiquitous in contemporary applications. Its need for efficient acceleration has driven vast research efforts into the quantization of neural networks with low-precision numerical formats.
Hossfeld, Konstantin J. +3 more
core +1 more source