Results 161 to 170 of about 431 (222)

Numerical analysis of spray characterization of blends of hydrous ethanol with diesel and biodiesel. [PDF]

open access: yesSci Rep
Shanthan V   +5 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

An Improved Method and Device for Nucleic Acid Isolation Using a High-Salt Gel Electroelution Trap. [PDF]

open access: yesAnal Chem
Kalendar R   +6 more
europepmc   +1 more source

Polarization‐Enabled Piezoelectric Tellurium–Selenium (TexSe1–x) Thin Films for Memory Switching and Artificial Synaptic Functions

open access: yesAdvanced Science, EarlyView.
Here, we demonstrate and investigate polarization‐enabled electromechanical responses in cryogenic physical vapor deposition (cryogenic PVD)‐deposited TexSe1‐x thin films, a tellurium‐based compound with a tunable bandgap and enhanced non‐centrosymmetry.
Chia‐Chen Chung   +16 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

open access: yesAdvanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang   +5 more
wiley   +1 more source

Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices

open access: yesAdvanced Science, EarlyView.
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen   +9 more
wiley   +1 more source

Sustainable Synaptic Device with Two‐Dimensional Ferroelectric Materials for Neuromorphic Computing

open access: yesAdvanced Science, EarlyView.
α‐In2Se3 based FeSFETs can be utilized as sustainable devices through polarization switching governed by both out‐of‐plane and in‐plane polarizations. Upon reaching a fatigued state, current annealing enabled by conductance modulation can significantly enhance the endurance of FeSFETs.
Jaewook Yoo   +12 more
wiley   +1 more source

Home - About - Disclaimer - Privacy