Results 251 to 260 of about 1,100,569 (292)

Sequence-dependent conformational transitions of disordered proteins during condensation. [PDF]

open access: yesChem Sci
Wang J   +5 more
europepmc   +1 more source

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

Nanoparticle Shape Dictates Catalytic Performance in Selective Hydrogenation of Butadiene Over Au‐Pd Core‐Shell Nanoparticles

open access: yesAdvanced Functional Materials, EarlyView.
Controlling the exposed crystal facet of shape‐controlled Au‐Pd core‐shell catalysts though colloidal synthesis enhances their catalytic performance in the industrially relevant selective hydrogenation of butadiene. ABSTRACT Selective hydrogenation of butadiene is a critical step in purification of alkene feedstocks for polymer production and is ...
Marta Perxés Perich   +3 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

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

Historical Foundation and Practical Guideline for Ferroelectric Switching Kinetic Studies

open access: yesAdvanced Functional Materials, EarlyView.
The P and U pulses in the conventional PUND measurements are not identical because of the interplay between switching current and the measurement circuit components. This circuit effect can lead to a shift in polarization transients and misinterpreted physics in the switching kinetics.
Yi Liang, Pat Kezer, John T. Heron
wiley   +1 more source

Dual‐Inductive and Programmable Switching: A New Paradigm in Ionic Interface‐Controlled Perovskite Memory

open access: yesAdvanced Functional Materials, EarlyView.
A fully programmable, dual‐inductive switchable halide perovskite memristor is demonstrated through precise BDAI2‐mediated interface engineering. This ion‐modulating layer suppresses stochastic filamentary growth, enabling stable, non‐filamentary switching via dynamic barrier modulation.
So‐Yeon Kim, Juan Bisquert
wiley   +1 more source

Exciton Binding Energy of Phosphorescent Emitter Molecules in Organic Light‐Emitting Diodes

open access: yesAdvanced Functional Materials, EarlyView.
Energy level alignment is key to efficient OLED design, yet determining LUMO energies remains challenging. A methodology based on field‐induced dissociation and kinetic Monte Carlo simulations is presented to extract LUMO energies of iridium‐based phosphorescent emitters from their exciton binding energy.
Hiroki Tomita   +6 more
wiley   +1 more source

Speech probability distribution

IEEE Signal Processing Letters, 2003
It is demonstrated that the distribution of speech samples is well described by Laplacian distribution (LD). The widely known speech distributions, i.e., LD, Gaussian distribution (GD), generalized GD, and gamma distribution, are tested as four hypotheses, and it is proved that speech samples during voice activity intervals are Laplacian random ...
Saeed Gazor, Wei Zhang
openaire   +1 more source

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