Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “utility scale”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Revealing the coupled oxygen and hypochlorite chemistry in saltwater batteries through operando pH and oxygen monitoring

Saltwater batteries (SWBs) that utilize Na⁺ ions from seawater have emerged as promising candidates for low-cost and sustainable grid-scale energy storage. To date, the cathode reaction mechanism of SWBs has been predominantly described by oxygen evolution and reduction reactions (OER/ORR). However, this assumption is valid only under idealized ocean-like conditions with constant pH and continuous oxygen replenishment. In practical systems, SWBs operate in finite volumes of saltwater, where saltwater composition dynamically evolves during cycling. Here, in this work, we systematically investigate the cathode reaction mechanisms of SWBs under finite saltwater conditions using galvanostatic cycling combined with electrochemical diagnostics and operando monitoring of dissolved oxygen and pH. Our results reveal that the cathode chemistry during SWB operation is considerably more complex than previously assumed. In addition to OER and ORR, hypochlorite formation and consumption reactions, along with pH-dependent switching of dominant reaction pathways, play critical roles. We further identify the sequence and relative contributions of these reactions throughout charge–discharge cycling. These findings provide a comprehensive and mechanistically grounded understanding of SWB cathode processes under relatively realistic cell design and operation condition. The insights presented here establish a new framework for interpreting SWB electrochemistry and offer directions for future strategies aimed at improving performance, stability, and practical viability.

Hypochlorite redox reaction↗
DOE OSTI2026

DTLMod: A simulation framework for in situ workflow optimization

In situ processing workflows have become essential for coping with the explosion in data volume and velocity in large-scale scientific computing, providing domain scientists with early insights at runtime. Multiple frameworks implement this paradigm through a data transport layer (DTL), offering different data access modes and deployment schemes, but researchers currently lack the appropriate tools to assess design and deployment options before committing to costly real experiments. We introduce DTLMod, an open-source simulated DTL that enables performance evaluation of in situ workflow configurations at scale. Built on SimGrid, it links into any SimGrid-based simulator and is available in C++ and Python. We evaluate DTLMod along four axes: scalability (tens of thousands of simulated processes across interconnected clusters in seconds, with linear memory scaling), versatility (three implementation variants trading fidelity for speed), accuracy (simulated times faithfully reflecting real behavior), and practical utility (two use cases demonstrating evidence-based workflow design decisions).

Suter, Fred [ORNL] (ORCID:0000000319021955)↗
DOE OSTI2026

Hydrogen release from aqueous based LOHCs: The role of water in the potassium formate/bicarbonate cycle

Here, in this study, we evaluate the chemical and physical properties governing the potential round-trip efficiency of an aqueous formate/bicarbonate cycle for hydrogen storage, with a particular focus on potassium formate as a potential liquid hydrogen carrier. Using thermodynamic parameters, we predict the conversion of formate to bicarbonate across varying temperatures and pressures, revealing that hydrogen release is relatively insensitive to temperature but highly dependent on pressure. Our findings indicate that hydrogen uptake is highly efficient, whereas hydrogen release poses a greater challenge, necessitating detailed optimization to enhance round-trip efficiency. We calculate the solubility limits of bicarbonate salts influenced by the common ion effect to enable the prediction of target conversion ranges that prevent the precipitation of potassium bicarbonate in a reactor. Furthermore, the energy efficiency of hydrogen release was assessed based on the heating requirements of the aqueous solutions. This analysis maximizes the round-trip efficiency by balancing the solubility limits of bicarbonate, the heat capacity of aqueous formate solutions and conversion based on thermodynamic equilibria. Taking these factors into consideration we suggest reaction conditions that could be utilized in a systems analysis to calculate the levelized cost of storage using the bicarbonate/formate cycle at commercial scales.

common ion effect↗
DOE OSTI2022

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Efficient synthesis of high-sulfur-content cathodes for high-performance Li–S batteries based on solvothermal polysulfide chemistry

A novel solvothermal polysulfide (PS) chemistry enables a facile and highly efficient process for synthesizing sulfur-carbon (S–C) composite powders containing up to 90 wt% S for high-performance Li–S batteries. Molecular dynamics calculations and experimental analyses reveal the formation of PSs upon dissolution of elemental S in N-methyl-2-pyrrolidone (NMP) at elevated temperatures and efficient infiltration of the PSs into the carbon host driven by the strong coupling with the C surfaces. The coupling enables extensive contact between S and C in the composite, leading to promising electrochemical properties for Li–S battery applications. In the power-type configuration, the composite cathodes having medium-to-high S contents (55 and 75%) demonstrate stable capacity at high current densities up to 100C (1C = 1670 mA g -1 -S) and no capacity fade up to 1000 cycles at 2C. In the energy-type configuration, a high-S-content and high-loading (90%-S, 4.2 mAh cm -2 ) cathode shows a specific capacity of 1440 mAh g -1 (86% S utilization) and 90% capacity retention after 300 cycles. This synthesis method enables significant advancement in realizing large-scale applications of Li–S batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

A caloritronics-based Mott neuristor

Abstract Machine learning imitates the basic features of biological neural networks at a software level. A strong effort is currently being made to mimic neurons and synapses with hardware components, an approach known as neuromorphic computing. While recent advances in resistive switching have provided a path to emulate synapses at the 10 nm scale, a scalable neuron analogue is yet to be found. Here, we show how heat transfer can be utilized to mimic neuron functionalities in Mott nanodevices. We use the Joule heating created by current spikes to trigger the insulator-to-metal transition in a biased VO 2 nanogap. We show that thermal dynamics allow the implementation of the basic neuron functionalities: activity, leaky integrate-and-fire, volatility and rate coding. This approach could enable neuromorphic hardware to take full advantage of the rapid advances in memristive synapses, allowing for much denser and complex neural networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Dynamic Mode Decomposition of Random Pressure Fields over Bluff Bodies

Fluctuating surface pressures on a bluff body exposed to a boundary layer flow generally are characterized as a spatiotemporally varying random field. In this paper, a dynamic mode decomposition (DMD) was applied to extract dominant features embedded in these random pressure fields. Utilizing an unsupervised machine learning algorithm, spatial modes and their temporal variations were grouped into different clusters at scales, e.g., macro, meso, and micro. A proper orthogonal decomposition (POD) of the experimental data was carried out to observe commonalities and distinctive perspectives each decomposition offers. Here, a comprehensive examination of the DMD/POD for their convergence criteria, data sufficiency, and modal components analysis was conducted. The physical interpretation of the spatiotemporal pressure field based on these decomposition schemes was discussed. At different scales, the DMD modes can capture the evolution of aerodynamic features, e.g., convection of vortices (or vortex tubes) and other structures. The distribution of energy among these three broad scales also reflects an energy cascade in pressure fluctuations akin to turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.

Nweye, Kingsley↗
DOE OSTI2021

Overview of the results from divertor experiments with attached and detached plasmas at Wendelstein 7-X and their implications for steady-state operation

Abstract Wendelstein 7-X (W7-X), the largest advanced stellarator, is built to demonstrate high power, high performance quasi-continuous operation. Therefore, in the recent campaign, experiments were performed to prepare for long pulse operation, addressing three critical issues: the development of stable detachment, control of the heat and particle exhaust, and the impact of leading edges on plasma performance. The heat and particle exhaust in W7-X is realized with the help of an island divertor, which utilizes large magnetic islands at the plasma boundary. This concept shows very efficient heat flux spreading and favourable scaling with input power. Experiments performed to overload leading edges showed that the island divertor yields good impurity screening. A highlight of the recent campaign was a robust detachment scenario, which allowed reducing power loads even by a factor of ten. At the same time, neutral pressures at the pumping gap entrance yielded the particle removal rate close to the values required for stable density control in steady-state operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Magnetic multilayer edges in Bernal-stacked hexagonal boron nitride

Single-layer h-BN is known to have edges with unique magnetism; however, in the commonly fabricated multilayer AA'-h-BN, edge relaxations occur that create interlayer bonds and eliminate the unpaired electrons at the edge. Recently, a robust method of growing the unconventional Bernal-stacked h-BN (AB-h-BN) has been reported. Here, we use theoretical approaches to investigate the nitrogen-terminated zigzag edges in AB-h-BN that can be formed in a controlled fashion using a high-energy electron beam. We find that these "open"edges remain intact in bilayer and multilayer AB-h-BN, enabling researchers potentially to investigate these edge states experimentally. We also investigate the thermodynamics of the spin configurations at the edge by constructing a lattice model that is based on parameters extracted from a set of first-principles calculations. We find that the edge spins in neighboring layers interact very weakly, resulting in a sequence of independent spin chains in multilayer samples. By solving this model using Monte Carlo simulations, we can determine nm-scale correlation lengths at liquid-N 2 temperatures and lower. At low temperatures, these edges may be utilized in magnetoresistance and spintronics applications.

1-dimensional spin chains↗
DOE OSTI2024

Stochastic density functional theory combined with Langevin dynamics for warm dense matter

Here, this study overviews and extends a recently developed stochastic finite-temperature Kohn-Sham density functional theory to study warm dense matter using Langevin dynamics, specifically under periodic boundary conditions. The method's algorithmic complexity exhibits nearly linear scaling with system size and is inversely proportional to the temperature. Additionally, a linear-scaling stochastic approach is introduced to assess the Kubo-Greenwood conductivity, demonstrating exceptional stability for dc conductivity. Utilizing the developed tools, we investigate the equation of state, radial distribution, and electronic conductivity of hydrogen at a temperature of 30 000 K. As for the radial distribution functions, we reveal a transition of hydrogen from gaslike to liquidlike behavior as its density exceeds 4 g/cm 3 . As for the electronic conductivity as a function of the density, we identified a remarkable isosbestic point at frequencies around 7 eV, which may be an additional signature of a gas-liquid transition in hydrogen at 30 000 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ptychographic X-ray speckle tracking with multi-layer Laue lens systems

The ever-increasing brightness of synchrotron radiation sources demands improved X-ray optics to utilize their capability for imaging and probing biological cells, nano-devices and functional matter on the nanometre scale with chemical sensitivity. Hard X-rays are ideal for high-resolution imaging and spectroscopic applications owing to their short wavelength, high penetrating power and chemical sensitivity. The penetrating power that makes X-rays useful for imaging also makes focusing them technologically challenging. Recent developments in layer deposition techniques have enabled the fabrication of a series of highly focusing X-ray lenses, known as wedged multi-layer Laue lenses. Improvements to the lens design and fabrication technique demand an accurate, robust, in situ and at-wavelength characterization method. To this end, a modified form of the speckle tracking wavefront metrology method has been developed. The ptychographic X-ray speckle tracking method is capable of operating with highly divergent wavefields. A useful by-product of this method is that it also provides high-resolution and aberration-free projection images of extended specimens. Three separate experiments using this method are reported, where the ray path angles have been resolved to within 4 nrad with an imaging resolution of 45 nm (full period). This method does not require a high degree of coherence, making it suitable for laboratory-based X-ray sources. Likewise, it is robust to errors in the registered sample positions, making it suitable for X-ray free-electron laser facilities, where beam-pointing fluctuations can be problematic for wavefront metrology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Adaptive Generation of Training Data for ML Reduced Model Creation

Machine learning proxy models are often used to speed up or completely replace complex computational models. The greatly reduced and deterministic computational costs enable new use cases such as digital twin control systems and global optimization. The challenge of building these proxy models is generating the training data. A naive uniform sampling of the input space can result in a non-uniform sampling of the output space of a model. This can cause gaps in the training data coverage that can miss finer scale details resulting in poor accuracy. While larger and larger data sets could eventually fill in these gaps, the computational burden of full-scale simulation codes can make this prohibitive. In this paper, we present an adaptive data generation method that utilizes uncertainty estimation to identify regions where training data should be augmented. By targeting data generation to areas of need, representative data sets can be generated efficiently. The effectiveness of this method will be demonstrated on a simple one-dimensional function and a complex multidimensional physics model.

Cianciosa, Mark↗
DOE OSTI2025

MIC-DP: A Scalable Correlation-Aware Differential Privacy Framework for High-Dimensional Data

Conventional differential privacy (DP) assumes record independence, limiting effectiveness on real-world datasets with temporal, spatial, or structural correlations. These dependencies undermine privacy guarantees and degrade utility in domains like healthcare, IoT, and smart city analytics. We propose Maximum Information Correlated Differential Privacy (MIC-DP), a novel framework that dynamically calibrates noise based on statistical dependencies. MIC-DP uses the Maximum Information Coefficient (MIC) to capture both linear and nonlinear correlations without explicit modeling, enabling adaptive sensitivity adjustment and improved privacy–utility trade-offs. Evaluations on healthcare (MIMIC), demographic (ACI), and synthetic datasets show that MIC-DP reduces mean absolute error (MAE) by up to 5.2% under strict privacy budgets (ϵ≤1), with aggregate utility improvements reaching 18% across datasets and evaluation metrics. MIC-DP provides formal (ϵ,δ)-privacy guarantees, scales efficiently with feature count, and supports deployment in moderate-scale, privacy-sensitive applications. Its tunable performance and runtime efficiency make MIC-DP suitable for privacy-sensitive applications where low-latency analytics and strong privacy guarantees must coexist. These results demonstrate MIC-DP’s effectiveness as a correlation-aware solution for practical DP.

Yang, Wenjun [Univ. of Washington, Tacoma, WA (Uni↗
DOE OSTI2024

CORRLA-RS

The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.

Gurecky, William [Oak Ridge National Laboratory (O↗
DOE OSTI2020

The MFiX Particle-in-Cell Method (MFiX-PIC) Theory Guide

MFiX (Multiphase Flow with Interphase eXchanges) is an open-source multiphase flow solver developed at the National Energy Technology Laboratory. Within the code, users have access to a single phase or interpenetrating continua-based multiphase two-fluid model (TFM), a discrete element model (DEM), and a particle-in-cell model (PIC). TFM, DEM, and PIC can all be used to create multiphase simulations that include hydrodynamics, chemical reactions, and heat transfer.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Accelerating Low-Income Financing and Transactions (LIFT) for Solar Access Everywhere (Final Technical Report)

The Accelerating Low-Income Financing and Transactions (LIFT) for Solar Access Everywhere project’s goal was to expand Low-to-Moderate Income (LMI) solar access for homeowners and renters. The LIFT project researched and gathered data on 453 LMI community solar project across the country. Following three years of research, the project delivered three groundbreaking research papers in June 2022, focused on 1) customer experience, 2) the growth of community solar programs, and 3) project-level financial best practices for serving LMI communities. These were followed by a user-friendly web-based Toolkit allowing users to interact with project data and key findings in November 2022. The customer experience research examined community solar subscribers’ primary motivations to join and remain satisfied with projects. Our research identified 453 projects across the country that dedicated some portion of the system capacity to LMI households. Seventeen of these projects participated in the LIFT customer experience research, allowing the project team to survey their customers and gain insight into how LMI subscribers feel about community solar and the programs that serve them. Subscribers in our sample indicated that the most critical issue that motivated them to participate in their program, however, was not savings but helping the environment. This was true for both LMI and non-LMI subscribers. Helping the environment was also the most important issue for LMI subscribers to measure how well their program was working for them. LIFT also explored how rapidly community solar has grown since its inception in 2006, publishing results in the Growth of U.S. Community Solar Serving LMI Households report. The results showed that community solar projects serving LMI households are one of the fastest growing segments of the solar industry. The report identifies and recommends ways developers should overcome real or perceived risks to LMI customer acquisition and subscriber management. Through the analysis of community solar project finance research, LIFT showed that most community solar projects serving LMI households are financed in the same ways mainstream community solar projects are financed. The value stacks and financial returns are no different, although LMI inclusion and participation rate varied across programs in our sample, ranging from between 10% and 100%. Based on the findings from the LIFT research, the team built a web-based user-friendly Toolkit, consisting of case studies, project finance best practices, and several tools built around the national dataset of 453 community solar projects that serve LMI households. These allow users to engage with the dataset in multiple ways; to explore the landscape of LMI community solar in the U.S., and to design community solar projects to optimize LMI inclusion, equity, and savings levels. The Toolkit also includes a library of LIFT-generated and LIFT-curated resources for users to learn more about how to best serve LMI communities through community solar. LIFT officially published the Toolkit on October 31, 2022, followed by a launch event (public webinar) on November 17, 2022. The core LIFT partners continue to engage in outreach and dissemination efforts to promote the LIFT Toolkit and research publications. Our driving motivation is to continue enabling solar developers to leverage the findings of this three-year research effort. By implication, the LIFT Toolkit is designed for use by utilities, energy service providers, and financiers or investors as a learning and decision-making tool to rapidly scale project models that optimize LMI inclusion and maximize real household savings.

14 SOLAR ENERGY↗
DOE OSTI2023

Development of quantum dot materials for infrared cameras (Final CRADA Report)

The aim of this project was to develop scalable methods to produce infrared (IR) mercury telluride (HgTe) colloidal quantum dot (CQD) thin films and demonstrate their utility in a proof-of-concept monolithic SWIR focal plane array (FPA). These objectives were accomplished by scaling up the HgTe CQD synthesis, characterizing physical and electrical properties of HgTe CQDs, evaluating solution-processed coating methods for quality and efficiency, and developing a process flow to integrate HgTe CQDs with commercial-off-the-shelf silicon CMOS readout circuits by solution-processed coating to produce monolithic FPAs. The FPA is the image sensor in an infrared imaging system responsible for detecting and processing reflected or emitted light into an infrared image of the scene under observation. The quality of the image is determined by the sensitivity and resolution of the image sensor in the system. Higher resolution IR FPAs enable higher throughput in manufacturing quality assurance, wider field of view for autonomous navigation, and longer range surveillance for defense.

77 NANOSCIENCE AND NANOTECHNOLOGY↗