Results 151 to 160 of about 931,753 (278)

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

open access: yesAdvanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +1 more source

Toward memristive in-memory computing: principles and applications. [PDF]

open access: yesFront Optoelectron, 2022
Bao H   +15 more
europepmc   +1 more source

Photoswitchable Conductive Metal–Organic Frameworks

open access: yesAdvanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu   +5 more
wiley   +1 more source

High-clockrate free-space optical in-memory computing. [PDF]

open access: yesLight Sci Appl
Liang Y   +14 more
europepmc   +1 more source

Intermolecular Interactions as Driving Force of Increasing Multiphoton Absorption in a Perylene Diimide‐Based Coordination Polymer

open access: yesAdvanced Functional Materials, EarlyView.
This study uncovers the unexplored role of intermolecular interactions in multiphoton absorption in coordination polymers. By analyzing [Zn2tpda(DMA)2(DMF)0.3], it shows how the electronic coupling of the chromophores and confinement in the MOF enhance two‐and three‐photon absorption.
Simon Nicolas Deger   +11 more
wiley   +1 more source

Achieving high precision in analog in-memory computing systems. [PDF]

open access: yesNpj Unconv Comput
Mannocci P   +3 more
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
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

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