Engineering topics

Huang, Ru

Publications and source records attributed to Huang, Ru.

5 records

DOE OSTI2026

Memsensing by surface ion migration within Debye length

Integration between electronics and biology is often facilitated by iontronics, where ion migration in aqueous media governs sensing and memory. However, the Debye screening effect limits electric fields to the Debye length, the distance over which mobile ions screen electrostatic interactions, necessitating external voltages that constrain the operation speed and device design. Here we report a high-speed in-memory sensor based on vanadium dioxide (VO2) that operates without an external voltage by leveraging built-in electric fields within the Debye length. When VO2 contacts a low-work-function metal (for example, indium) in a salt solution, electrochemical reactions generate indium ions that migrate into the VO2 surface under the native electric field, inducing a surface insulator-to-metal phase transition of VO2. The VO2 conductance increase rate reflects the salt concentration, enabling in-memory sensing, or memsensing of the solution. The memsensor mimics Caenorhabditis elegans chemosensory plasticity to guide a miniature boat for adaptive chemotaxis, illustrating low-power aquatic neurorobotics with fewer memory units.

Guo, Ruihan↗

DOE OSTI2024

Reducing Operator Complexity of Galerkin Coarse-grid Operators with Machine Learning

Here, we propose a data-driven and machine-learning-based approach to compute non-Galerkin coarse-grid operators in multigrid (MG) methods, addressing the well-known issue of increasing operator complexity. Guided by the MG theory on spectrally equivalent coarse-grid operators, we have developed novel machine learning algorithms that utilize neural networks combined with smooth test vectors from multigrid eigenvalue problems. The proposed method demonstrates promise in reducing the complexity of coarse-grid operators while maintaining overall MG convergence for solving parametric partial differential equation problems. Numerical experiments on anisotropic rotated Laplacian and linear elasticity problems are provided to showcase the performance and comparison with existing methods for computing non-Galerkin coarse-grid operators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Learning Optimal Multigrid Smoothers via Neural Networks

Multigrid methods are one of the most efficient techniques for solving large sparse linear systems arising from partial differential equations (PDEs) and graph Laplacians from machine learning applications. One of the key components of multigrid is smoothing, which aims at reducing high-frequency errors on each grid level. However, finding optimal smoothing algorithms is problem-dependent and can impose challenges for many problems. In this paper, we propose an efficient adaptive framework for learning optimized smoothers from operator stencils in the form of convolutional neural networks (CNNs). Here, the CNNs are trained on small-scale problems from a given type of PDEs based on a supervised loss function derived from multigrid convergence theories and can be applied to large-scale problems of the same class of PDEs. Numerical results on anisotropic rotated Laplacian problems and variable coefficient diffusion problems demonstrate improved convergence rates and solution time compared with classical hand-crafted relaxation methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Electronically induced defect creation at semiconductor/oxide interface revealed by time-dependent density functional theory

Carrier induced defect creation at the semiconductor-oxide interface has been known as the origin of electronic device degradation for a long time, but how exactly the interface lattice can be damaged by carriers (especially low-energy ones) remains unclear. Here we carry out real-time time-dependent density functional theory simulations on concrete Si/SiO 2 interfaces to study the interaction between excited electrons and interface bonds. We show that the normal interface Si-H bonds are generally resistant to electrons due to the delocalized nature and high energy level of the Si-H antibonding states, and due to the high-energy barrier to break the Si-H bond. However, if an additional hydrogen atom exists by attaching to a nearby oxygen atom (forming a “Si-H···H-O” complex), the Si-H bond will be greatly weakened, including the reduction of energy barrier for bond breaking, and the lowering of the antibonding state energy level which favors electron injection. Together with the multiple vibrational excitation process, the corresponding Si-H bond can be broken much more easily. Thus we propose that the Si-H···H-O complex will be the center for defect creation and device degradation. Finally, we also explain why such a center might be relatively easy to form during the hydrogen annealing process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

A native oxide high-κ gate dielectric for two-dimensional electronics

Silicon-based transistors are approaching their physical limits and thus new high-mobility semiconductors are sought to replace silicon in the microelectronics industry. Both bulk materials (such as silicon-germanium and III–V semiconductors) and low-dimensional nanomaterials (such as one-dimensional carbon nanotubes and two-dimensional transition metal dichalcogenides) have been explored, but, unlike silicon, which uses silicon dioxide (SiO 2 ) as its gate dielectric, these materials suffer from the absence of a high-quality native oxide as a dielectric counterpart. This can lead to compatibility problems in practical devices. Here, we show that an atomically thin gate dielectric of bismuth selenite (Bi 2 SeO 5 ) can be conformally formed via layer-by-layer oxidization of an underlying high-mobility two-dimensional semiconductor, Bi 2 O 2 Se. Using this native oxide dielectric, high-performance Bi 2 O 2 Se field-effect transistors can be created, as well as inverter circuits that exhibit a large voltage gain (as high as 150). The high dielectric constant (~21) of Bi 2 SeO 5 allows its equivalent oxide thickness to be reduced to 0.9 nm while maintaining a gate leakage lower than thermal SiO 2 . The Bi 2 SeO 5 can also be selectively etched away by a wet chemical method that leaves the mobility of the underlying Bi 2 O 2 Se semiconductor almost unchanged.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗