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Zhou, Jia

Publications and source records attributed to Zhou, Jia.

15 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗
DOE OSTI2025

NE-COST plug-in: Expanding ACCERT's Capabilities for Life-Cycle Cost Modeling

The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.

Zhou, Jia↗
DOE OSTI2024

Nuclear Energy Cost Estimates for Net Zero World Initiative – 2024 Update

This report provides recommended parameters for incorporating nuclear energy systems into decarbonization modeling scenarios. The values are primarily intended for the Net Zero World (NZW) Initiative but are expected to prove useful to other related efforts. Both costs and operational metrics are provided in the study for large reactors and small modular reactors (SMR).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Quantifying Capital Cost Reduction Pathways for Advanced Nuclear Reactors

The framework developed in this study is provided both as an excel sheet (https://inl.gov/content/uploads/2023/11/Nuclear-Reactor-Cost-Reduction-Pathway-Spreadsheet-Tool.xlsx) and a Python (Jupyter) Notebook (link: https://github.com/accert-dev/ACCERT/tree/main/Cost%20Reduction). Capital cost considerations are one of the primary inhibitors to the large-scale deployment of nuclear power plants. While it is widely accepted that first units will likely be expensive and relatively uncompetitive, it is reasonable to expect that subsequent units, built in relative quick succession, will be cheaper as they benefit from the so-called “learning effects”. However, the large degree of uncertainty associated with this parameter renders it challenging for first movers to invest in the first few expensive units. To resolve this impasse, the U.S. Department of Energy’s Advanced Nuclear Liftoff study advocated for the formation of large, committed order books of plants of the same technology to spread the costs across several units and kickstart the nuclear supply chain. The study also advocated best practices for avoiding overruns and keeping reactors on budget. This report builds on these key recommendations by attempting to quantify specific pathways toward cost reduction for nuclear energy. A capital cost estimation framework was built to untangle the effect of learning into a subset of key cost drivers, referred to as “levers”. Collectively, the choice of these levers is intended to reflect the decision-making of high-level stakeholders like plant owners and the government. In addition to the size of the firm orderbook, these levers included (a) cost drivers that are most often attributed to cost overruns such as architect/engineering (A/E) proficiency, construction proficiency, procurement service proficiency, design completion prior to the start of construction, and design maturity, and (b) cost reduction strategies such as modular construction, cross-site standardization, safety classification of the reactor building, and of the balance of plant. Two advanced reactor designs were leveraged as use cases and bottom-up cost estimates made with assumptions consistent with a well-executed first-of-a-kind project (WE-FOAK, i.e., almost no overruns) were used as baselines for the models. Cost correlations were surveyed from the literature to determine the impact of important variables on projected timelines and costs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Novobiocin blocks nucleic acid binding to Polθ and inhibits stimulation of its ATPase activity

Polymerase theta (Polθ) acts in DNA replication and repair, and its inhibition is synthetic lethal in BRCA1 and BRCA2-deficient tumor cells. Novobiocin (NVB) is a first-in-class inhibitor of the Polθ ATPase activity, and it is currently being tested in clinical trials as an anti-cancer drug. Here, we investigated the molecular mechanism of NVB-mediated Polθ inhibition. Using hydrogen deuterium exchange-mass spectrometry (HX-MS), biophysical, biochemical, computational and cellular assays, we found NVB is a non-competitive inhibitor of ATP hydrolysis. NVB sugar group deletion resulted in decreased potency and reduced HX-MS interactions, supporting a specific NVB binding orientation. Collective results revealed that NVB binds to an allosteric site to block DNA binding, both in vitro and in cells. Comparisons of The Cancer Genome Atlas (TCGA) tumors and matched controls implied that POLQ upregulation in tumors stems from its role in replication stress responses to increased cell proliferation: this can now be tested in fifteen tumor types by NVB blocking ssDNA-stimulation of ATPase activity, required for Polθ function at replication forks and DNA damage sites. Structural and functional insights provided in this study suggest a path for developing NVB derivatives with improved potency for Polθ inhibition by targeting ssDNA binding with entropically constrained small molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Demonstration of ACCERT Software for Nuclear Power Plant Techno-Economics

In the past few years, there has been a renewed interest in the deployment of nuclear power for decarbonizing the electricity grid as well as a range of industrial applications. As the demonstrations of advanced nuclear power plants start to begin, there will likely be a further increase in this interest. As nuclear is being considered as a part of the energy mix, understanding the cost of nuclear energy becomes increasingly important for all stakeholders including advanced reactor vendors (for making design decisions and marketing their designs), users of nuclear energy (e.g., to estimate the cost of decarbonization of other industries using nuclear), and government (e.g., in capacity expansion models that are used in framing policy). In this summary, we demonstrate a software tool called ACCERT that is currently being developed with funding from the Systems Analysis and Integration (SA&I) program under the Department of Energy’s Office of Nuclear Energy (DOE NE). ACCERT is a cost estimation and techno-economics tool for nuclear power plant applications that includes a database of (a) cost estimates of various ‘reference’ nuclear power plant designs gathered from existing literature, and (b) algorithms developed from these costs that can be used extrapolate the existing costs and perform a bottom-up cost estimation of other designs. A companion summary describes the software and its design in more detail and this summary presents a demonstration for four different nuclear power plant designs: a pressurized water reactor (PWR), high-temperature gas reactor (HTGR), sodium fast reactor (SFR), and a heat-pipe microreactor. The demonstrations include the reference cost estimates and the cost estimates of a modified design for each reference case.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Probing neutron-skin thickness with free spectator neutrons in ultracentral high-energy isobaric collisions

We show that the yield ratio of free spectator neutrons produced in high-energy 96 Zr+ 96 Zr to 96 Ru+ 96 Ru collisions is a clean probe of the neutron-skin thickness of colliding nuclei and the slope parameter L of the symmetry energy. The idea is demonstrated based on the proton and neutron density distributions via a state-of-the-art Skyrme-Hartree-Fock-Bogolyubov calculation. Among spectator nucleons given by the Glauber model, free spectator neutrons include those from direct production that survive from clusterization as well as those from deexcitation of heavy clusters described by the popular GEMINI model. More free neutrons are produced in collisions of 96 Zr nucleus due to its larger neutron skin, compared to those produced in collisions of 96 Ru nucleus with a smaller neutron skin. The difference of the free spectator neutron yield is further increased with the increasing difference of the neutron-skin thickness between 96 Zr and 96 Ru with a larger L value, and the increase in ultracentral collisions is particularly insensitive to model details and experimental uncertainties. Since the production of free spectator neutrons is not affected by the complicated dynamics in the mid-rapidity region, the ratio of their multiplicities in ultracentral isobaric collisions is a robust observable for constraining the neutron skin and L value.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Extreme Low-Temperature Stress Affects Nutritional Quality of Amino Acids in Rice

Global climate change has increased the frequency of extreme climate events, and their effects on the nutritional quality, especially on amino acids in rice, have not been quantified. The data from a 3-year low temperature stress (LTS) experiment including two rice varieties (Huaidao 5 and Nanjing 46), seven minimum/maximum temperature levels (one optimal 21/27°C and six LTS levels from 17/23 to 6/12°C), and three LTS durations (3, 6, and 9 days) after flowering, revealed significant interactive effects of LTS at different stages, durations, and temperature levels on the content and accumulation of amino acids. LTS increased rice total amino acid content, while decreasing its accumulation, with higher sensitivities to LTS at the flowering stage than at the grain filling stage. In most treatments, the lysine (the first limiting amino acid) and phenylalanine content were increased under LTS at early and peak flowering stages but decreased at the grain filling stage in both varieties, and only leucine content was increased at all three stages after flowering, while the content of other essential amino acids differed among the two varieties. With an increase of 1°C·d per day in the accumulated cold degree days, the relative content of the essential amino acids was increased by 0.01–0.41%, depending on the rice variety and growth stage. Our results suggest that LTS can improve nutritional quality of amino acids of rice grains in terms of amino acids content, especially at flowering stage. These results provide critical insights for assessing the potential impact of extreme climates on the nutrient quality of rice under future climate change.

Kang, Min↗
DOE OSTI2021

Probing extended scalar sectors with precision e + e - → Zh and Higgs diphoton studies

We compute the one-loop corrections to σ(e + e - → Zh) arising from representative extended Standard Model scalar sector scenarios. According to the new scalar SU(2)L representations, we consider the inert doublet, real and complex triplet, quintuplet, and septuplet models. With the sub-percent level precision expected for prospective future e + e - collider measurements of σ(e + e - → Zh), studies of the Higgsstrahlung process will probe extended scalar sector particle spectrum and interactions in a manner complementary to direct searches at the Large Hadron Collider and possible future pp colliders. We also compare with the sensitivity of future Higgs diphoton decay rate measurements. We find that the σ(e + e - → Zh) and Γ(h → γγ) complementarity is particularly pronounced for the complex triplet model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Hybrid Energy System Workflow for Energy Portfolio Optimization

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗