We studied the synchronization and stability of power grids with heterogeneous inertia and damping factors, and demonstrated power feasibility of operating a system consisting of only renewable generation technologies with enhanced stability.
How can a probabilistic generative model of data be learned in a neurobiologically-plausible fashion without the popular algorithm known as backpropagation of errors? This paper seeks to answer this question by developing a computational framework referred to as neural generative coding.
Story behind the paper: 'Photocatalytic degradation of steroid hormone micropollutants by TiO2-coated polyethersulfone membranes in a continuous flow-through process', scheduled for publication in Nature Nanotechnology on 31 March 2022
Topological Dirac semimetal, with its versatile symmetry-breaking operation, provides unprecedented opportunities to explore Dirac fermiology for low-energy spectroscopy beyond early landmarks of interband-engineering optoelectronics.
In this study, we propose an approach that achieves spatial control of the melt-front location of pure phase change materials using pressure-enhanced close contact melting, enhancing thermal management and storage to support a rapidly-electrifying energy infrastructure.
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