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Xu, Shuai

Publications and source records attributed to Xu, Shuai.

17 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

State Dependent Optimization with Quantum Circuit Cutting

Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate count by leveraging knowledge of the input quantum states. Surprisingly, we found that ISDO is broadly applicable to the downstream circuits produced by circuit cutting. Circuit cutting also requires measuring upstream qubits and has some flexibility of selection observables to do reconstruction. Therefore, we propose a state-dependent optimization (SDO) framework that incorporates ISDO, our newly proposed measure-state dependent optimization (MSDO), and a biased observable selection strategy. Building on the strengths of the SDO framework and recognizing the scalability challenges of circuit cutting, we propose nonseparate circuit cutting-a more flexible approach that enables optimizing gates without fully separating them. We validate our methods on noisy simulations of QAOA, QFT, and BV circuits. Results show that our approach consistently mitigates noise and improves overall circuit performance, demonstrating its promise for enhancing quantum algorithm execution on near-term hardware.

Li, Xinpeng↗
DOE OSTI2024

Coal-derived carbon anodes for lithium-ion batteries: Development, challenges, and prospects

Lithium-ion battery (LIB) development has increased rapidly, requiring low-cost anode materials with a high capacity, high-rate performance, and stable lifespan. Carbon-based anodes possess various exceptional morphologies and structures, making them promising candidates for meeting the technical demands; however, conventional synthetic carbon anode processes need expensive feedstocks that increase anode cost and limit commercialization. Coal, the most affordable and abundant carbon resource, has attracted increasing attention as the primary feedstock for producing high-value carbon anode materials. This article reviews the lithium storage mechanisms, characteristics, and productions of some high-valuable carbon anode materials for LIBs from coal and coal derivatives. The high-value carbon anode materials reviewed in this article are graphite, graphene, mesophase microbeads (MCMB), carbon fiber, and hard carbons. Furthermore, the remaining challenges and prospects of using coal-derived carbon materials to create high-performance and low-cost lithium-ion batteries are also discussed.

25 ENERGY STORAGE↗
DOE OSTI2024

Lignite-Derived Carbon Materials for Lithium-Ion Battery Anodes

This project involved collaboration between the University of North Dakota (UND) College of Engineering & Mines, Clean Republic, LLC (CR), and the North American Coal Corporation (NACoal) to develop advanced LIBs anodes from lignite-derived carbon materials. The overall goal of the project was to develop advanced anode materials for LIBs from lignite-derived carbon feedstocks.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Synthesis of hierarchical graphene coated porous Si anode for lithium-ion batteries

The ultra-high capacity and widespread availability of Si materials have resulted in them being the focus of extensive studies to replace the graphite anode. However, the main barriers preventing the Si anodes from large-scale applications are their huge volume change and severe interface reactions in the lithiation/delithiation process, which pulverizes its structure and subsequently deteriorates its cycle life. Here, micrometer-scale porous Si coated with graphene coating (mpSi@G) has been synthesized by using SiO 2 nanoparticles and novel coal-derived humic acid as feedstocks through a magnesiothermic reduction, followed by spray drying and calcination techniques. SEM, Raman, and X-ray absorption analysis demonstrate that the hierarchical graphene shell and micrometer-sized porous Si structure effectively release the Si anode's mechanical stress upon lithiation to achieve good structural stability. Here, the synthesized mpSi@G anode delivers a high initial lithiation capacity of 2974.9 mAh g –1 at 0.1 A g –1 with an initial coulombic efficiency of 70.2 %. Furthermore, the conductive hierarchical graphene network, along with the tight contacts of porous-Si and the graphene shell, contribute to a high capacity of 1109.5 mAh g –1 at a high current density of 5.0 A g –1 , showing excellent rate capability.

25 ENERGY STORAGE↗
DOE OSTI2024

Metal-to-insulator transition in oxide semimetals by anion doping

Dirac semimetals exhibiting nontrivial topological characteristics stand as exemplary parent compounds, offering great promise for the realization of novel electronic states. These materials also serve as a versatile platform for systematically investigating topological quantum phase transitions. In this study, we present compelling evidence of profound structural and transport phase shifts in a recently uncovered oxide Dirac semimetal, SrNbO3, achieved through effective in situ anion doping. Notably, a remarkable increase in resistivity of more than three orders of magnitude at room temperature is observed upon nitrogen-doping. The extent of electronic modulation in SrNbO3 is strongly correlated with the misfit strain, underscoring its phase instability to both chemical doping and crystallographic symmetry variations. Using first-principles calculations, we discern that elevating the level of nitrogen doping induces an upward shift in the conductive bands of SrNbO3-?N?. Consequently, a transition from a metallic state to an insulating state becomes apparent as the nitrogen concentration reaches a threshold of 1/3. This investigation sheds light on the potential of anion engineering in oxide Dirac semimetals, offering pathways for manipulating their physical properties. These insights hold promise for future applications that harness these materials for tailored functionalities.

Hong, Haitao↗
DOE OSTI2023

Towards Redefining the Reproducibility in Quantum Computing: A Data Analysis Approach on NISQ Devices

Although the building of quantum computers has kept making rapid progress in recent years, noise is still the main challenge for any application to leverage the power of quantum computing. Existing works addressing noise in quantum devices proposed noise reduction when deploying a quantum algorithm to a specified quantum computer. The reproducibility issue of quantum algorithms has been raised since the noise levels vary on different quantum computers. Importantly, existing works largely ignore the fact that the noise of quantum devices varies as time goes by. Therefore, reproducing the results on the same hardware will even become a problem. We analyze the reproducibility of quantum machine learning (QML) algorithms based on daily model training and execution data collection. Our analysis shows a correlation between our QML models’ test accuracy and quantum computer hardware’s calibration features. We also demonstrate that noisy simulators for quantum computers are not a reliable tool for quantum machine learning applications.

Senapati, Priyabrata↗
DOE OSTI2023

Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput

Undoubtedly, quantum computing offers valuable acceleration for solving intricate problems. One of the primary hurdles lies in executing large-scale quantum applications on backend machines. Qubit noise, among other factors, dramatically influences the execution process. Implementing effective scheduling techniques for quantum circuits is crucial for practical quantum computing and preventing excessive waiting times. The quantum realm is distinct from classical computing in terms of optimization, performance, utilization, and waiting periods. Consequently, the parameters and components of quantum circuit scheduling diverge from those of classical computing. This paper presents Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput, a straightforward yet effective scheduling framework and policy that enhances noise resilience, throughput, and the fidelity of quantum circuits. Drawing inspiration from classical methods, our scheduling approach incorporates additional constraints tailored for quantum logic. The outcome demonstrates a substantial improvement in fidelity and resource management, which is vital for real-world quantum applications.

Baheri, Betis↗
DOE OSTI2023

Insights into Chemical Prelithiation of SiO x /Graphite Composite Anodes through Scanning Electron Microscope Imaging

Initial Coulombic efficiency (ICE) is critical for determining the energy density of lithium-ion batteries (LIBs) used for practical applications; however, it is typically disregarded in anode research. We used SiO x and graphite composite anodes for commercial lithium-ion batteries in our preliminary research to achieve a balance between ICE, capacity, and cycling life. ICE reached 88%; however, it needs further improvement for commercial applications. Prelithiation is a process that involves the introduction of extra lithium ions into LIBs during their manufacturing to enhance the overall performance of the LIBs. We applied a chemical prelithiation method on our SiO x /graphite composite anodes, which comprised 95 wt % of the active material mass loading on the electrode. The ICE increased from 88% to 98% using an aryllithium reagent impregnation method within 2 min of prelithiation. The anode’s specific capacity density, rate, and cycle performance also significantly improved. Scanning electron microscopy (SEM) imaging enhanced by an osmium tetroxide staining method indicated that the P-anode contained a stable solid electrolyte interface (SEI) layer after the prelithiation process and cycling electrochemical test. The P-anode’s stable charge differential peak over 500 cycles also showcases a robust artificial SEI layer that was generated by the prelithiation procedure. Here, this prelithiation process has significant potential for adoption in the LIB industry’s current electrode manufacturing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling of plasma beta effects on the island divertor transport in the standard configuration of W7-X

The influence of plasma beta effects on the edge plasma transport in the Wendelstein 7-X standard configuration is studied systematically by using EMC3-EIRENE combined with a 3D equilibrium code named HINT. The magnetic topology changes induced by plasma beta effects are significantly reflected in plasma transport behaviors and heat flux patterns on divertor targets. After validating the modeling strategy by comparisons with experimental data, the extended simulations for high performance plasmas show that the threshold separatrix density for accessing the power detachment is reduced in higher beta plasmas. Compared with the vacuum field case, the impurity radiation distributions with finite beta effects are modified in the magnetic island region. The divertor heat flux is distributed more evenly along the toroidal direction on the strike line at the vertical target. The strike line on the horizontal target moves towards the pumping gap with an increase in the plasma beta. In addition, the different pressure profiles with the same central beta also result in a modified heat flux pattern on the divertor targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Insights into the Effect of Heat Treatment and Carbon Coating on the Electrochemical Behaviors of SiO Anodes for Li-Ion Batteries

The use of SiO as an anode material has attracted significant interest due to its high capacity and long cycling life. Many promising approaches, including structural design and carbon coating at high temperatures, effectively improve its intrinsic low electrical conductivity and poor Coulombic efficiency. However, the “heat treatment process-composition and microstructure-electrochemical properties” relationship of the SiO anode is not fundamentally understood. Here the structure and composition evolution in amorphous SiO and graphene-coated SiO is investigated using different heat-treatment conditions. X-ray absorption near-edge structure techniques are also employed to analyze the surface and bulk composition change during the initial lithiation process, supplemented by physical or chemical characterization and electrochemical testing. Here results reveal the structural transition of SiO during heat treatment, from amorphous to disproportionated hierarchical structure, where the as-formed dielectric exterior SiO 2 shell and interior SiO 2 matrix severely polarizes electrodes, hindering the lithiation process. Carbon coating on SiO effectively restricts the growth of the SiO 2 shell and facilitates charge transfer, leading to improved electrochemical performance. A schematic model is proposed to reveal the relationship between the treatments, the resultant structural evolutions, and corresponding electrochemical behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

QuGAN: A Quantum State Fidelity based Generative Adversarial Network

In the recent years, Generative Adversarial Networks (GANs) have been arguably one of the largest strides forward in Deep Learning. Many papers illustrate the use of GANs to accomplish extremely impressive goals, such as text-to-image or image augmentation. Specifically, GANs have seen this success in the computer vision domain. However, GANs are not without their own set of problems. GANs are computationally expensive, sometimes computationally prohibitive, and can suffer a multitude of convergence problems. As research on classical GANs continues to push the topic further, a branch of GANs, namely Quantum GANs, has seen research interest in the past years. In this work, we intend to push this research further with an illustration of a Quantum GAN architecture that provide stable convergence of the model and is extended onto real data sets. Furthermore, unlike many other Quantum GANs out there, our model's GAN architecture runs the discriminator and the generator primarily on Quantum hardware through the use of a Quantum-based similarity metric. When compared to the very few other Quantum GAN papers, our architecture leads to significantly better results in almost all aspects.

Stein, Samuel A.↗
DOE OSTI2021

Integrated ELM and divertor power flux control using RMPs with low input torque in EAST in support of the ITER research plan

Experiments have been carried out at the EAST tokamak to study ITER-relevant scenario integration issues, related to edge localized mode (ELM) control in H-mode plasmas by the application of three-dimensional (3D) resonant magnetic perturbations (RMPs), which have a large impact on the execution of the ITER research plan. The EAST experiments have successfully demonstrated ELM suppression at normalized torque inputs similar to ITER. The application of RMP fields with high toroidal mode number (n = 4) reduces the impact of ELM control on energy and particle confinement compared to those use lower n (n = 1, 2) RMPs. Injection of successive pellets is found to be effective in increasing the plasma density in ELM-suppressed H-modes and reducing the divertor power without triggering large ELMs at EAST. Access to high recycling and radiative divertor conditions while maintaining ELM suppression has been demonstrated in EAST by the use of gas fuelling and neon impurity seeding. Both approaches have been found to be effective in reducing power fluxes to the divertor strike points in near-separatrix lobes for both n = 2 and n = 4 RMPs. Furthermore, reduction of power fluxes in off-separatrix lobes is only effective for n = 4 RMP application, which is consistent with magnetic topology modelling (including plasma response) results showing a shallow penetration into the confined plasma region of field lines connected to these lobes compared to n = 2. The EAST results support the use of high n 3D fields for ELM suppression in ITER high Q DT scenarios since they provide optimum integration features regarding energy and particle confinement, pellet fuelling, radiative divertor operation while eliminating ELM transient power loads and being compatible with low torque input.

pellet fuelling↗
DOE OSTI2021

TQEA: Temporal Quantum Error Analysis

For the last few years quantum computers have captured researchers’ interest in solving complicated problems in finance, chemistry, machine learning, and many other NP problems. Quantum computing benefits from parallel computation, entanglement, and calculation speedup compared to classical computing. Even though the operations and number of qubits in quantum computers are limited, previous research showed that using quantum computers can be beneficial. These benefits gained researchers’ interest to work on the improvement of quantum computers and overcome the limitations by building more advanced quantum computers with fault tolerance capability, more physical qubits, and better operational gates. In practice, Quantum applications would be translated into Quantum Circuits and each circuit can contain one or many entanglements (s), single qubits operations, and readouts. The importance of running Quantum applications with controlled errors or without errors is critical to the desired result from Quantum readout. In this paper, we study the characteristics of superconducting quantum machines along with the previously proposed methods of Quantum error detection/correction and in order to build a better error model we propose a temporal method for analyzing the the behavior of qubits errors (T1 and T2), frequency of operation, entanglement errors, and readout errors. In order to detect and predict the behavior of each machine, we use simple exponential smoothing analysis on heuristic calibration data. Finally, based on observation, we show that based on frequency, qubits, readout and single operation errors we can build a temporal based model to study and predict the outcome of runs on each Quantum machine.

Baheri, Betis↗
DOE OSTI2021

In Situ Synthesis of Graphene-Coated Silicon Monoxide Anodes from Coa-Derived Humic Acid for High-Performance Lithium-Ion Batteries

Silicon monoxide (SiO) is attaining extensive interest amongst silicon-based materials due to its high capacity and long cycle life; however, its low intrinsic electrical conductivity and poor coulombic efficiency strictly limit its commercial applications. Here low-cost coal-derived humic acid (HA) is used as a feedstock to synthesize in-situ graphene-coated disproportionated SiO (D-SiO@G) anode with a facile method. HRTEM and XRD confirm the well-coated graphene layers on an SiO surface. Scanning Transmission X-ray Microscopy (STXM) and X-ray Absorption Near-Edge Structure (XANES) spectra analysis indicate that the graphene coating effectively hinders the side-reactions between the electrolyte and SiO particles . As a result, the D-SiO@G anode presents an initial discharge capacity of 1937.6 mAh g -1 at 0.1 A g -1 and an initial coulombic efficiency (ICE) of 78.2%. High reversible capacity (1023 mAh g -1 at 2.0 A g -1 ), excellent cycling performance ( 72.4% capacity retention after 500 cycles at 2.0 A g -1 ), and rate capability (774 mAh g -1 at 5 A g -1 ) results are substantial. Full coin cells assembled with LiFePO 4 electrodes and D-SiO@G electrodes display impressive rate performance. These results indicate a promising potential for practical use in high-performance lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Facile Synthesis of Micrometer-sized Hierarchical Porous Si@C Anodes for High-Performance Lithium-Ion Batteries

Extensive studies have been conducted to determine if replacing graphite anodes with silicon is feasible since silicon possesses a high capacity and is an abundant resource; however, Si anodes suffer significant volume changes during cycling, which pulverizes its structure and subsequently causes rapid capacity fading. We used SiO2 nanoparticles (nSiO2) and low-cost coal-derived humic acid as a feedstock to synthesize high performance Si-C anodes for Li-ion Batteries through spray drying, calcination, and magnesiothermic reductions. Our Si-C anodes features micrometer-sized porous Si coated with a graphitized carbon shell (mpSi@C). The hierarchical graphitized carbon shell and porous silicon structure relieve the mechanical stress of the Si phase upon cycling, which stabilizes the structure. This mpSi@C composite design allows for a high initial discharge capacity of 2199.9 mAh g-1 at 0.1 A g-1 and a cycling performance of 68% capacity retention after 100 cycles at 1.0 A g-1. The multipoint contact between the Si anode and C structure allows for a remarkable performance rate of 566.3 mAh g-1 at 5.0 A g-1.

01 COAL, LIGNITE, AND PEAT↗