Engineering topics

Zhou, Shiyu

Publications and source records attributed to Zhou, Shiyu.

6 records

DOE OSTI2024

A Scalable, High-Efficiency, Low-Energy-Spread Laser Wakefield Accelerator Using a Tri-Plateau Plasma Channel

The emergence of multi-petawatt laser facilities is expected to push forward the maximum energy gain that can be achieved in a single stage of a laser wakefield acceleration (LWFA) to tens of giga-electron volts, which begs the question—is it likely to impact particle physics by providing a truly compact particle collider? Colliders have very stringent requirements on beam energy, acceleration efficiency, and beam quality. In this article, we propose an LWFA scheme that can for the first time simultaneously achieve hitherto unrealized acceleration efficiency from the laser to the electron beam of >20% and a sub-1% energy spread using a stepwise plasma structure and a nonlinearly chirped laser pulse. Three-dimensional high-fidelity simulations show that the nonlinear chirp can effectively mitigate the laser waveform distortion and lengthen the acceleration distance. This, combined with an interstage rephasing process in the stepwise plasma, can triple the beam energy gain compared to that in a uniform plasma for a fixed laser energy, thereby dramatically increasing the efficiency. A dynamic beam loading effect can almost perfectly cancel the energy chirp that arises during the acceleration, leading to the sub-percent energy spread. This scheme is highly scalable and can be applied to petawatt LWFA scenarios. Scaling laws are obtained, which suggest that electron beams with parameters relevant for a Higgs factory could be reached with the proposed high-efficiency, low-energy-spread scheme.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Designed Spin‐Texture‐Lattice to Control Anisotropic Magnon Transport in Antiferromagnets

Abstract Spin waves in magnetic materials are promising information carriers for future computing technologies due to their ultra‐low energy dissipation and long coherence length. Antiferromagnets are strong candidate materials due, in part, to their stability to external fields and larger group velocities. Multiferroic antiferromagnets, such as BiFeO 3 (BFO), have an additional degree of freedom stemming from magnetoelectric coupling, allowing for control of the magnetic structure, and thus spin waves, with the electric field. Unfortunately, spin‐wave propagation in BFO is not well understood due to the complexity of the magnetic structure. In this work, long‐range spin transport is explored within an epitaxially engineered, electrically tunable, 1D magnonic crystal. A striking anisotropy is discovered in the spin transport parallel and perpendicular to the 1D crystal axis. Multiscale theory and simulation suggest that this preferential magnon conduction emerges from a combination of a population imbalance in its dispersion, as well as anisotropic structural scattering. This work provides a pathway to electrically reconfigurable magnonic crystals in antiferromagnets.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Non-volatile magnon transport in a single domain multiferroic

Antiferromagnets have attracted significant attention in the field of magnonics, as promising candidates for ultralow-energy carriers for information transfer for future computing. The role of crystalline orientation distribution on magnon transport has received very little attention. In multiferroics such as BiFeO 3 the coupling between antiferromagnetic and polar order imposes yet another boundary condition on spin transport. Thus, understanding the fundamentals of spin transport in such systems requires a single domain, a single crystal. We show that through Lanthanum (La) substitution, a single ferroelectric domain can be engineered with a stable, single-variant spin cycloid, controllable by an electric field. The spin transport in such a single domain displays a strong anisotropy, arising from the underlying spin cycloid lattice. Our work shows a pathway to understanding the fundamental origins of magnon transport in such a single domain multiferroic.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Probing fractional statistics in quantum simulators of spin liquid Hamiltonians

Recent advances in programmable quantum devices brought to the fore the intriguing possibility of using them to realise and investigate topological quantum spin liquid phases. This new and exciting direction brings about important research questions on how to probe and determine the presence of such exotic, highly entangled phases in a noisy quantum environment. One of the most promising tools is investigating the behaviour of the topological excitations, and in particular their fractional statistics. In this work we put forward a generic route to achieve this, and we illustrate it in the specific case of \mathbb{Z}_2 ℤ 2 topological spin liquids implemented with the aid of combinatorial gauge symmetry. We design a convenient architecture to study signatures of fractional statistics via quasiparticle interferometry, and we assess its robustness to diagonal and off-diagonal disorder, as well as to dephasing - effects that are generally pervasive in current quantum programmable devices. Interestingly, when turned on its head, our scheme provides a remarkably clear test of the “quantumness” of these devices, with robust signatures that crucially hinge on quantum coherence and quantum interference effects, and cannot be mimicked by classical stochastic processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Fully Inkjet‐Printed, 2D Materials‐Based Field‐Effect Transistor for Water Sensing

Abstract Despite significant progress in solution‐processing of 2D materials, it remains challenging to reliably print high‐performance semiconducting channels that can be efficiently modulated in a field‐effect transistor (FET). Herein, electrochemically exfoliated MoS 2 nanosheets are inkjet‐printed into ultrathin semiconducting channels, resulting in high on/off current ratios up to 10 3 . The reported printing strategy is reliable and general for thin film channel fabrication even in the presence of the ubiquitous coffee‐ring effect. Statistical modeling analysis on the printed pattern profiles suggests that a spaced parallel printing approach can overcome the coffee‐ring effect during inkjet printing, resulting in uniform 2D flake percolation networks. The uniformity of the printed features allows the MoS 2 channel to be hundreds of micrometers long, which easily accommodates the typical inkjet printing resolution of tens of micrometers, thereby enabling fully printed FETs. As a proof of concept, FET water sensors are demonstrated using printed MoS 2 as the FET channel, and printed graphene as the electrodes and the sensing area. After functionalization of the sensing area, the printed water sensor shows a selective response to Pb 2+ in water down to 2 ppb. This work paves the way for additive nanomanufacturing of FET‐based sensors and related devices using 2D nanomaterials.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization

In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.

42 ENGINEERING↗