| Autor: |
Wei, Xingfei, Zhao, Yinong, Zhuang, Yi, Hernandez, Rigoberto |
| Předmět: |
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| Zdroj: |
Journal of Chemical Physics; 6/7/2021, Vol. 154 Issue 21, p1-10, 10p |
| Abstrakt: |
Materials that exhibit synaptic properties are a key target for our effort to develop computing devices that mimic the brain intrinsically. If successful, they could lead to high performance, low energy consumption, and huge data storage. A 2D square array of engineered nanoparticles (ENPs) interconnected by an emergent polymer network is a possible candidate. Its behavior has been observed and characterized using coarse-grained molecular dynamics (CGMD) simulations and analytical lattice network models. Both models are consistent in predicting network links at varying temperatures, free volumes, and E-field ( E ⃗ ) strengths. Hysteretic behavior, synaptic short-term plasticity and long-term plasticity—necessary for brain-like data storage and computing—have been observed in CGMD simulations of the ENP networks in response to E-fields. Non-volatility properties of the ENP networks were also confirmed to be robust to perturbations in the dielectric constant, temperature, and affine geometry. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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