arXiv subjects

Zhiming M. Wang

Publications and source records attributed to Zhiming M. Wang.

4 recordsLinked to original sources

arXiv2021

Self-repairing high entropy oxides

All biological organisms, from plants to living creatures, can heal minor wounds and damage. The realization of a similar self-healing capacity in inorganic materials has been a design target for many decades. This would represent a breakthrough in materials engineering, enabling many novel technological applications, since such materials would be able to resist damage caused by electromagnetic irradiation and/or mechanical impact. Here we demonstrate that a high-entropy oxide is intrinsically capable of undergoing an autonomous self-repairing process. Transmission electron microscopy revealed that the spinel structure of (AlCoCrCu0.5FeNi)3O4 can regrow and repair itself at the atomic level when damaged. Density functional theory calculations reveal that the extra enthalpy stored in the high entropy material during fabrication can be released to effectively heal macroscopic defects by regrowing into a partially ordered state. This extraordinary self-repairing phenomenon makes this new material highly desirable as a coating, enabling structures used in harsh environments to better withstand damage, such as cosmic irradiation in space, nuclear irradiation in nuclear power facilities, or tribological damage. Most importantly, our results set the general design principles for the synthesis of self-repairing materials.

cond-mat.mtrl-sci↗

arXiv2020

Backpropagation through nonlinear units for all-optical training of neural networks

Backpropagation through nonlinear neurons is an outstanding challenge to the field of optical neural networks and the major conceptual barrier to all-optical training schemes. Each neuron is required to exhibit a directionally dependent response to propagating optical signals, with the backwards response conditioned on the forward signal, which is highly non-trivial to implement optically. We propose a practical and surprisingly simple solution that uses saturable absorption to provide the network nonlinearity. We find that the backward propagating gradients required to train the network can be approximated in a pump-probe scheme that requires only passive optical elements. Simulations show that, with readily obtainable optical depths, our approach can achieve equivalent performance to state-of-the-art computational networks on image classification benchmarks, even in deep networks with multiple sequential gradient approximations. This scheme is compatible with leading optical neural network proposals and therefore provides a feasible path towards end-to-end optical training.

cs.ET↗

arXiv2020

Long-Lived Charge Separation Following Pump-Energy Dependent Ultrafast Charge Transfer in Graphene/WS$_2$ Heterostructures

Van der Waals heterostructures consisting of graphene and transition metal dichalcogenides (TMDCs) have recently shown great promise for high-performance optoelectronic applications. However, an in-depth understanding of the critical processes for device operation, namely interfacial charge transfer (CT) and recombination, has so far remained elusive. Here, we investigate these processes in graphene-WS$_2$ heterostructures, by complementarily probing the ultrafast terahertz photoconductivity in graphene and the transient absorption dynamics in WS$_2$ following photoexcitation. We find that CT across graphene-WS$_2$ interfaces occurs via photo-thermionic emission for sub-A-exciton excitation, and direct hole transfer from WS$_2$ to the valence band of graphene for above-A-exciton excitation. Remarkably, we observe that separated charges in the heterostructure following CT live extremely long: beyond 1 ns, in contrast to ~1 ps charge separation reported in previous studies. This leads to efficient photogating of graphene. These findings provide relevant insights to optimize further the performance of optoelectronic devices, in particular photodetection.

cond-mat.mtrl-sci↗

arXiv2013

Molecular Beam Epitaxial Growth of Bi2Te3 and Sb2Te3 Topological Insulators on GaAs (111) Substrates: A Potential Route to Fabricate Topological Insulator p-n Junction

High quality Bi2Te3 and Sb2Te3 topological insulators films were epitaxially grown on GaAs (111) substrate using solid source molecular beam epitaxy. Their growth and behavior on both vicinal and non-vicinal GaAs (111) substrates were investigated by reflection high-energy electron diffraction, atomic force microscopy, x-ray diffraction, and high resolution transmission electron microscopy. It is found that non-vicinal GaAs (111) substrate is better than a vicinal substrate to provide high quality Bi2Te3 and Sb2Te3 films. Hall and magnetoresistance measurements indicate that p type Sb2Te3 and n type Bi2Te3 topological insulator films can be directly grown on a GaAs (111) substrate, which may pave a way to fabricate topological insulator p-n junction on the same substrate, compatible with the fabrication process of present semiconductor optoelectronic devices.

cond-mat.mtrl-sci↗