Results 131 to 140 of about 118,178 (316)
A model for learning strings is not a model of language
Proceedings of the National Academy of Sciences, 2022 Elliot Murphy, Evelina Leivada
openaire +2 more sources
Improved stiff string torque and drag prediction using a computationally efficient contact algorithm
Mathematical and Computer Modelling of Dynamical SystemsDue to the intermittent contact with the wellbore, determining torque and drag for deviated wells is difficult. Most models have ignored drill string stiffness and assumed continual contact to simplify derivation.
Sampath Liyanarachchi, Geoff Rideout
doaj +1 more source
Advanced Materials, EarlyView.ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald +7 more
wiley +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, EarlyView.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
Electroweak strings in the standard model
The European Physical Journal CAbstractWe argue that the existence of the electroweak monopole predicts the existence of the electroweak string in the standard model made of monopole–antimonopole pair separated infinitely apart, which carry the quantized magnetic flux $$4 \pi n/e$$ 4 π n
Liping Zou, Pengming Zhang, Y. M. Cho
openaire +3 more sources
Advanced Materials, EarlyView.We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
Constraining string theory models with cosmological inflation
, 2021 Inflation is a phase of accelerated expansion, taking place at very high energy in the early Universe. During this epoch, inhomogeneities are generated on cosmological scales from the amplification of quantum fluctuations of the gravitational and matter ...
Vennin, Vincent
core
Imaging the Holon string of the Hubbard model
Proceedings of the National Academy of Sciences, 2020 Significance A major direction in atomic physics today is to use neutral fermions in a lattice made of light to simulate electrons in crystals. It is hoped that such simulations will answer many long-standing questions in solid-state physics, among them the mechanism of charge transport of the 2D Hubbard model believed to capture
openaire +4 more sources
Advanced 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
Journal of High Energy PhysicsWe investigate canonically quantized open string solutions associated to the analytically continued action for the recently proposed tropical limit of topological A-type models, tropological sigma models, with various tropical versions of boundary ...
Emil Albrychiewicz +2 more
doaj +1 more source