Concept and modelling of memsensors as two terminal devices with enhanced capabilities in neuromorphic engineering. [PDF]
Vahl A +6 more
europepmc +1 more source
Understanding and Designing Phase Change Materials: Insights From Atom Probe Tomography
Atom probe tomography can distinguish metallic, covalent, and metavalent bonds based upon their bond rupture; in particular, the probability to form more than one ion (PME) in laser‐assisted field evaporation. These findings open new avenues in understanding and designing phase change materials (PCMs) since they allow quantification of bonds in solids ...
Jan Köttgen +3 more
wiley +1 more source
Retina‐Inspired Bi‐Based Terahertz Photonic Neuromorphic Devices
Combined with effective band alignment and substrate engineering, bismuth materials are introduced to form terahertz photonic bio‐inspired devices with picosecond short‐term plasticity to enable multi‐scene visual perception. Thus obtained hardware through the terahertz optical neural network (THz‐ONN) demonstrates high recognition accuracy, providing ...
Pujing Zhang +14 more
wiley +1 more source
Microfluidic Neurons, a New Way in Neuromorphic Engineering? [PDF]
Levi T, Fujii T.
europepmc +1 more source
Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley +1 more source
Neuromorphic engineering in wetware: the state of the art and its perspectives. [PDF]
Gentili PL, Zurlo MP, Stano P.
europepmc +1 more source
Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung +7 more
wiley +1 more source
Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh +8 more
wiley +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang +6 more
wiley +1 more source

