Results 121 to 130 of about 35,400 (266)
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
Laser‐Induced Graphene from Waste Almond Shells
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source
Modulating Electrochemical CO2 Reduction Pathways via Interfacial Electric Field
Engineering interfacial electric fields in Cu/ITO electrodes enables precise control of CO2 reduction pathways. Charge transfer from Cu to ITO generates positively charged Cu species that steer selectivity from ethylene toward methane. This work demonstrates how interfacial electric‐field modulation can direct reaction intermediates and transform ...
Mahdi Salehi +7 more
wiley +1 more source
Packing measure in general metric space
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Exploring the photocatalytic reverse water–gas shift (RWGS) reaction on doped SrTiO3 nanoparticle films, reveals that normalizing catalytic rates by the catalyst's specific surface area (SSA) disentangled surface area effects from the catalyst's intrinsic material properties.
Dikshita Bhattacharyya +6 more
wiley +1 more source
Entropy of a Quasi-de Sitter Spacetime and the Role of Specific Heat. [PDF]
Luongo O, Azizinia M, Boshkayev K.
europepmc +1 more source
Electroactive Metal–Organic Frameworks for Electrocatalysis
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska +7 more
wiley +1 more source
Ramifications of generalized Feller theory. [PDF]
Cuchiero C, Möllmann T, Teichmann J.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source

