Results 41 to 50 of about 10,098 (246)

Mixed‐Metal Promotion in a Manganese‐Molybdenum Oxynitride as Catalyst to Integrate C─C and C─N Coupling Reactions for the Direct Synthesis of Acetonitrile from Syngas and Ammonia

open access: yesAdvanced Materials, EarlyView.
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje   +7 more
wiley   +1 more source

Polymorph‐Specific Electronic Transduction in WO3 during Molecular Sensing

open access: yesAdvanced Materials, EarlyView.
Metal‐oxide polymorphs with similar surface chemistry can nevertheless exhibit distinct sensing properties. In γ‐ and ε‐WO3, analyte adsorption appears comparable; yet, only ε‐WO3 induces a pronounced lattice electronic perturbation that accommodates charge in sub‐conduction band minimum states.
Matteo D'Andria   +6 more
wiley   +1 more source

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting [PDF]

open access: yes, 2017
It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this
Azad, Ariful   +2 more
core   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

open access: yesAdvanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam   +6 more
wiley   +1 more source

Guiding a Path Tracer with Local Radiance Estimates [PDF]

open access: yes, 2012
Path tracing is a basic, statistically unbiased method for calculating the global illumination in 3D scenes. For practical purposes, the algorithm is too slow, so it is used mainly for theoretical purposes or as a base for more advanced algorithms.
Berger, Martin
core  

Augmenting Navigation Systems for Near Real-Time Scenarios Using LiDAR

open access: yes, 2023
Global Navigation Satellite Systems (GNSS) are critical components of today's intelligent transport applications. They work in conjunction with Road Network Graphs (RNGs), real-world abstractions of transportation infrastructure, to provide services such
Azam, Muhammad
core  

Switchable Magnonic Crystals Based on Spin Crossover/CrSBr Heterostructures

open access: yesAdvanced Materials, EarlyView.
Multiscale modeling is employed to investigate the functionality of a light‐controlled, tunable magnonic crystal based on spin‐crossover Fe‐pz molecules integrated with a monolayer of CrSBr. Ab initio simulations confirm that the molecules remain functional on the CrSBr surface, while a semiclassical elastic model demonstrates that light‐induced ...
Andrei Shumilin   +4 more
wiley   +1 more source

Automatic detection of accommodation steps as an indicator of knowledge maturing [PDF]

open access: yes, 2011
Jointly working on shared digital artifacts – such as wikis – is a well-tried method of developing knowledge collectively within a group or organization.
Moskaliuk, Johannes   +13 more
core   +1 more source

Physical data embedding for memory efficient AI

open access: yesMachine Learning: Science and Technology
Deep neural networks have achieved exceptional performance across various fields by learning complex, nonlinear mappings from large-scale datasets. However, they face challenges such as high memory requirements and limited interpretability.
Callen MacPhee   +2 more
doaj   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

open access: yesAdvanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong   +11 more
wiley   +1 more source

Home - About - Disclaimer - Privacy