<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fu, Tianda</style></author><author><style face="normal" font="default" size="100%">Liu, Xiaomeng</style></author><author><style face="normal" font="default" size="100%">Fu, Shuai</style></author><author><style face="normal" font="default" size="100%">Woodard, Trevor</style></author><author><style face="normal" font="default" size="100%">Gao, Hongyan</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Yao, Jun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Self-sustained green neuromorphic interfaces.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biocompatible Materials</style></keyword><keyword><style  face="normal" font="default" size="100%">Electronics</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanotechnology</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanowires</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Networks, Computer</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Synapses</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Jun 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">3351</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Incorporating neuromorphic electronics in bioelectronic interfaces can provide intelligent responsiveness to environments. However, the signal mismatch between the environmental stimuli and driving amplitude in neuromorphic devices has limited the functional versatility and energy sustainability. Here we demonstrate multifunctional, self-sustained neuromorphic interfaces by achieving signal matching at the biological level. The advances rely on the unique properties of microbially produced protein nanowires, which enable both bio-amplitude (e.g., &lt;100 mV) signal processing and energy harvesting from ambient humidity. Integrating protein nanowire-based sensors, energy devices and memristors of bio-amplitude functions yields flexible, self-powered neuromorphic interfaces that can intelligently interpret biologically relevant stimuli for smart responses. These features, coupled with the fact that protein nanowires are a green biomaterial of potential diverse functionalities, take the interfaces a step closer to biological integration.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/34099691?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fu, Tianda</style></author><author><style face="normal" font="default" size="100%">Liu, Xiaomeng</style></author><author><style face="normal" font="default" size="100%">Gao, Hongyan</style></author><author><style face="normal" font="default" size="100%">Ward, Joy E</style></author><author><style face="normal" font="default" size="100%">Liu, Xiaorong</style></author><author><style face="normal" font="default" size="100%">Yin, Bing</style></author><author><style face="normal" font="default" size="100%">Wang, Zhongrui</style></author><author><style face="normal" font="default" size="100%">Zhuo, Ye</style></author><author><style face="normal" font="default" size="100%">Walker, David J F</style></author><author><style face="normal" font="default" size="100%">Joshua Yang, J</style></author><author><style face="normal" font="default" size="100%">Chen, Jianhan</style></author><author><style face="normal" font="default" size="100%">Lovley, Derek R</style></author><author><style face="normal" font="default" size="100%">Yao, Jun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bioinspired bio-voltage memristors.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Action Potentials</style></keyword><keyword><style  face="normal" font="default" size="100%">Biosensing Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Electricity</style></keyword><keyword><style  face="normal" font="default" size="100%">Electronics</style></keyword><keyword><style  face="normal" font="default" size="100%">Equipment Design</style></keyword><keyword><style  face="normal" font="default" size="100%">Geobacter</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Dynamics Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanotechnology</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanowires</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Networks, Computer</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurons</style></keyword><keyword><style  face="normal" font="default" size="100%">Synapses</style></keyword><keyword><style  face="normal" font="default" size="100%">Wearable Electronic Devices</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 Apr 20</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">1861</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Memristive devices are promising candidates to emulate biological computing. However, the typical switching voltages (0.2-2 V) in previously described devices are much higher than the amplitude in biological counterparts. Here we demonstrate a type of diffusive memristor, fabricated from the protein nanowires harvested from the bacterium Geobacter sulfurreducens, that functions at the biological voltages of 40-100 mV. Memristive function at biological voltages is possible because the protein nanowires catalyze metallization. Artificial neurons built from these memristors not only function at biological action potentials (e.g., 100 mV, 1 ms) but also exhibit temporal integration close to that in biological neurons. The potential of using the memristor to directly process biosensing signals is also demonstrated.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32313096?dopt=Abstract</style></custom1></record></records></xml>