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At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model

The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. Although a plethora of experimental techniques, including but not limited to optical contrast, Raman spectroscopy, nonlinear optical spectroscopy, near-field optical imaging, and hyperspectral imaging, facilitate the measurement of 2D material thickness, comprehensive data for many materials remain elusive. Over the past decade, the exponential proliferation of 2D materials and their heterostructures has outstripped the capabilities of conventional experimental and computational approaches. In this evolving landscape, machine learning (ML) has emerged as an indispensable tool, offering a scalable approach to augment these traditional methodologies. Addressing the critical gap, we introduce THICK2D—Thickness Hierarchy Inference and Calculation Kit for 2D Materials. This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. To demonstrate the utility and robustness of THICK2D, we successfully used the toolkit to predict the thickness of more than 8000 2D-based materials, sourced from two extensive 2D materials databases. THICK2D is disseminated as an open-source utility, accessible on GitHub at https://github.com/gmp007/THICK2D, and archived on Zenodo at https://10.5281/zenodo.11216648.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗

DOE OSTI2024

Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Mean-field equation for phase-modulated optical parametric oscillator

The widely established techniques for the generation of ultrashort optical pulses rely on passive mode locking of lasers, with the output pulse duration and emission spectrum determined by the intrinsic lifetime of laser transition in the gain medium. Due to the instantaneous nature of nonlinear gain, optical parametric oscillators (OPOs) are capable of generating optical radiation in all timescales from continuous-wave (cw) to ultrashort femtosecond regime, if driven by laser pump sources in the corresponding time domain. In the ultrashort timescale, operation of OPOs conventionally relies on mode-locked pump lasers, with the concomitant disadvantages of large footprint and high cost. At the same time, the lack of gain storage mandates the use of synchronous pumping, resulting in increased complexity. In this paper, we present the concept of phase-modulated OPO driven by cw pump laser. The approach overcomes the traditional drawbacks of ultrafast OPOs, enabling femtosecond pulse generation without the need for synchronous pumping, resulting in a simplified, compact, and cost-effective architecture using cw input pump lasers. We derive a mean-field equation for a degenerate χ ( 2 ) OPO driven by a cw laser with intracavity electro-optic modulator (EOM), and also including dispersion compensation. The equation predicts the formation of stable femtosecond pulses ( < 200 fs ) , in both normal and anomalous dispersion regimes, with a controllable repetition rate determined by the frequency of the EOM. The remarkable functionality of the proposed scheme paves the way for the development of an alternative class of widely tunable coherent femtosecond light sources in both bulk and integrated format based on χ ( 2 ) OPOs using cw pump lasers. Published by the American Physical Society 2024

Sanchez, A. D. (ORCID:0000000327630339)↗

DOE OSTI2020

Proven Technologies for the Solidification of Complex Liquid Radioactive Waste (LRW): Global Case Studies of Applications and Disposal Options - 20424

Legacy radioactive waste streams from the Cold War still exist and newly generated waste streams from nuclear power plants and research institutes go untreated and expose environmental hazards at many nuclear sites. The nature of the waste is diverse, depending upon the source or the process from which it originated. The most problematic waste streams include complex liquids such as organic (tri-butyl-phosphate TBP) solutions contaminated with Pu and U isotopes, mixed sludge types, high acid radioactive waste, H-3 contaminated organic and aqueous streams, etc. Technological, environmental and economic challenges exist for the treatment and disposal of such waste streams. A proven technology that has been applied to LRW on a global basis provides one option as a low-cost solution to legacy streams and small volume, highly complex LRW frequently found during decommissioning at nuclear power plants and weapons sites. The engineered polymer technology from Nochar, USA, is capable of solidifying standard and highly complex LLW and ILW waste streams for interim or final storage, or for incineration. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Deep learning techniques to disentangle water use efficiency, climate change, and carbon sequestration across ecosystem scales

Focal Areas: We plan to use machine learning (ML) to disentangle the impact of climate change on plant water use efficiency (WUE) across the leaf level, structured canopy, and community ecosystem scales. Due to the complex behavior of modeling plant WUE’s connection to carbon storage (and hidden co-varying interactions) we suggest that physics-based deep learning must be utilized. The second topic we propose is, based on a better understanding of WUE response to climate change, there is a need to predict how WUE will limit or enhance the recycling of water from transpiration by vegetation back to the land surface worldwide, and thus impact water storage capacity (i.e., natural and reservoirs), using machine learning optimization techniques such as genetic algorithms.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Evaluation of Global Climate Models for Use in Energy Analysis

The interplay between energy, climate, and weather is becoming more complex due to increasing contributions of renewable energy generation, energy storage, electrified end uses, and the increasing frequency of extreme weather events. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and subjective process. In this work, we assess datasets from various global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We present evaluations of their skills with respect to the historical climate and comparisons of their future projections of climate change for two climate change scenarios. We present the results for different climatic and energy system regions and include interactive figures in the accompanying software repository. Previous work has presented similar GCM evaluations, but none have presented variables and metrics specifically intended for comprehensive energy systems analysis including impacts on energy demand, thermal cooling, hydropower, water availability, solar energy generation, and wind energy generation. We focus on GCM output meteorological variables that directly affect these energy system components including the representation of extreme values that can drive grid resilience events. The objective of this work is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and scenarios in subsequent work.

14 SOLAR ENERGY↗

DOE OSTI2024

Development and Implementation of a Bag Degradation Predictive Tool at Los Alamos National Laboratory

Nuclear material packaging involves many complex variables derived from the stored material's properties, the storage environment, and the synergistic interaction of said material and its environment on the containment boundary. In the Plutonium Facility (PF-4) at Los Alamos National Laboratory (LANL) the typical containment boundary found, starting from the stored material itself to the outermost containment layer, consists of the material contained within a stainless steel (typically 304) slip-lid (or other equivalent stainless steel packaging layer) wrapped in an sPVC bag-out bag contained within a facility approved outer container stored within the boundaries of an approved facility (i.e., a building designed and approved to store nuclear material). This packaging configuration, though occasionally deviated from in the past, represents the current procedurally enforced, expected containment structure for all interim nuclear material containment outside of an engineered control barrier (e.g., a glovebox). Over the life of containerization research at LANL, packaging engineers have become increasingly concerned with the degradation of the sPVC bag-out bag, which can cause corrosion to the outermost packaging layer as well as possible exposure to alpha contamination if the bag-out bag layer is degraded to the point of containment failure. A bag-out bag degradation predictive tool (BDT) is therefore needed to assess the current and future nuclear material inventory for possible bag degradation in order to continue to ensure safe operations for the facility and its workers to deliver on the vital national security mission of 30 PPY.

42 ENGINEERING↗

DOE OSTI2022

Phase Stability and Kinetics of Topotactic Dual Ca 2+ –Na + Ion Electrochemistry in NaSICON NaV 2 (PO 4 ) 3

Recent reports of reversible calcium plating and stripping have rekindled interest in the development of Ca-ion batteries (CIBs) as next-generation energy storage devices. This technology has the potential to overcome the limitations of conventional Li-ion batteries, but CIBs are plagued by a paucity of suitable cathode materials. To date, NaSICON-structured NaV 2 (PO 4 ) 3 has been demonstrated as a successful cathode candidate, exhibiting reversible (de)intercalation of 0.6 mol Ca 2+ along with stable cycling performance. However, a complex multiphase mixture forms on discharge so the Ca-ion charge storage mechanism in the NaSICON framework is poorly understood. Here in this work, we report on an investigation of the structure and/or Na + /Ca 2+ environment(s) of a variety of chemically prepared NaSICON Ca x Na y V 2 (PO 4 ) 3 phases which were characterized using synchrotron XRD, SEM-EDS, 23 Na NMR, and TEM. Highly calciated CaV 2 (PO 4 ) 3 , Ca 1.5 V 2 (PO 4 ) 3 , and CaNaV 2 (PO 4 ) 3 phases can be prepared at high temperature, but -unlike Ca 0.6 NaV 2 (PO 4 ) 3 -these materials are electrochemically inactive. To better understand the fundamental factors impacting successful Ca 2+ electrochemistry in this system, DFT was employed to examine the Ca x Na y V 2 (PO 4 ) 3 phase diagram and Ca 2+ diffusion mechanism. Theoretical insights show that phase separation into Na-rich and Ca-rich phases is a reason for the capacity limitation and demonstrate that Na + ions in the host materials assist the migration of neighboring Ca 2+ ions, enabling reversible electrochemistry in Ca x Na y V 2 (PO 4 ) 3 . This investigation of fundamental principles affecting reversible Ca 2+ (de)intercalation in Ca x Na y V 2 (PO 4 ) 3 allows for the development of design principles to enable the discovery of a variety of successful cathodes for CIBs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A simple and fast algorithm for estimating the capacity credit of solar and storage

Energy storage is a leading option to enhance the resource adequacy contribution of solar energy. Detailed analysis of the capacity credit of solar energy and energy storage is limited in part due to the data intensive and computationally complex nature of probabilistic resource adequacy assessments. This paper presents a simple algorithm for calculating the capacity credit of energy-limited resources that, due to the low computational and data needs, is well suited to exploratory analysis. Validation against benchmarks based on probabilistic techniques shows that it can yield similar insights. The method is used to evaluate the impact of different solar and storage configurations, particularly with respect to the strategy for coupling storage and solar photovoltaic systems. Furthermore, application of the method to a case study of utilities in Florida, where solar is rapidly growing and demand peaks in the winter and summer, demonstrates that it can improve on rules of thumb used in practice by some utilities. If storage is required to charge only from solar, periods of high demand driven by cold weather events accompanied by lower solar production can result in a capacity credit of solar and storage that is less than the capacity credit of storage alone.

14 SOLAR ENERGY↗

DOE OSTI2021

Hillsborough County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Hillsborough County used the Clear Sky Decision Support Toolkit to analyze solar + storage as an additional resiliency feature at its Brandon Support Operation Complex (BSOC). During normal operations, the BSOC houses water utility administration services and workspaces for water and wastewater engineers, facilities maintenance, and environmental management staff. During emergency management activation, the BSOC serves as an emergency hub for Emergency Support Function 3 (ESF-3), which includes public utilities, public works, and engineering staff support members. The BSOC is designated as a critical facility by the County.

14 SOLAR ENERGY↗

DOE OSTI2022

Simulated CO 2 storage efficiency factors for saline formations of various lithologies and depositional environments using new experimental relative permeability data

Saline formations are attractive geologic reservoirs for permanent carbon dioxide (CO 2 ) storage. Here, the U.S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) has worked to develop and refine methods and tools for the calculation of CO 2 storage potential in subsurface reservoirs. DOE-NETL's CO 2 -SCREEN provides an online tool for executing these storage methods. CO 2 storage efficiency terms are input parameters in DOE-NETL's methods and equations embedded in the CO 2 -SCREEN, which assesses pore space available for CO 2 storage. In this work, a modeling workflow was initiated to refine two CO 2 storage efficiency terms - volumetric displacement (E V ) and microscopic displacement (E d ). The models are based on new experimental relative permeability data that are specific to homogenous lithology and depositional environments of key subsurface saline formations targeted for CO 2 storage. In future work, heterogenous features will be added to this initial modeling effort to update efficiency factors as described in DOE-NETL's methods and CO 2 -SCREEN tool. E V accounts for the volume utilized in the reservoir under the areal plume, while E d accounts for saturation values in the plume to assess efficiency of CO 2 storage at the pore scale. The results of this work are significant in that prior values were based on a limited geologically non-specific relative permeability data set that were collected prior to 2009. Specifically, we applied numerical simulations using TOUGH3 models to update CO 2 storage efficiency values for supercritical CO 2 injection into brine-saturated reservoirs for three lithologies (clastics, limestone, dolomite) and six depositional environments (Marginal Marine, Strand Plain, Deltaic Complex Fluvial, Aeolian, Shallow Marine, and Reef) that have a high potential for geologic CO 2 storage. Experimental relative permeability data in cores from these environments were utilized in the models with corresponding rock type/sedimentary environment. Results of this study showed that dolomite followed by limestone generated higher ranges of storage efficiency compared to clastics. The updated values provided a tighter efficiency range for clastics, lower P 10 but higher P 90 range for limestone, and higher P 10 and P 90 for dolomite. In general, tighter reservoirs with relatively low permeability and porosity were associated with higher E V and E d , showing efficient reservoir and pore utilization in these scenarios. High reservoir pressure and temperature associated with increasing depth increased the E V , and high CO 2 injection rates resulted in increases in E V and E d , while the impact of permeability anisotropy was minimal after the 30-year injection period.

03 NATURAL GAS↗

DOE OSTI2023

On the Feasibility of Market Manipulation and Energy Storage Arbitrage via Load-Altering Attacks

Around the globe, electric power networks are transforming into complex cyber–physical energy systems (CPES) due to the accelerating integration of both information and communication technologies (ICT) and distributed energy resources. While this integration improves power grid operations, the growing number of Internet-of-Things (IoT) controllers and high-wattage appliances being connected to the electric grid is creating new attack vectors, largely inherited from the IoT ecosystem, that could lead to disruptions and potentially energy market manipulation via coordinated load-altering attacks (LAAs). In this article, we explore the feasibility and effects of a realistic LAA targeted at IoT high-wattage loads connected at the distribution system level, designed to manipulate local energy markets and perform energy storage (ES) arbitrage. Realistic integrated transmission and distribution (T&D) systems are used to demonstrate the effects that LAAs have on locational marginal prices at the transmission level and in distribution systems adjacent to the targeted network.

25 ENERGY STORAGE↗

DOE OSTI2025

Skyrmion-like Spin Textures Emerging in the Material Derived from Structural Frustration

Magnetic materials with complex spin textures present both fundamental and practical appeal. The complex patterns of magnetic moments emerging on underlying crystal lattices hold potential for robust information storage and processing, including the promise of topological quantum computing. The scope of materials that host such patterns, however, remains rather limited. Here, in this study, we report a discovery of a complex spin texture in a noncentrosymmetric material that emerges from the structural frustration at the boundary between centrosymmetric parent structures MnCoGe (the hexagonal Ni 2 In or the orthorhombic TiNiSi structure type) and MnCoAs (the TiNiSi structure type). Our findings demonstrate that such structural frustration provides a powerful handle for identifying compositional spaces where complex magnetic behavior and associated nontrivial magnetic structures are likely to emerge. Thus, the new phase MnCoGe 1/3 As 2/3 exhibits a modulated cycloidal antiferromagnetic arrangement of electron spins on a noncentrosymmetric lattice (of the hexagonal ZrNiAl type) that materializes in the space between centrosymmetric collinear ferromagnets. This work provides a pathway for discovering novel materials with exotic spin textures for next-generation spintronics and quantum technologies.

Wang, YiXu [Florida State University, Tallahassee,↗

DOE OSTI2021

Concurrent Optimization of Capital Cost and Expected O&M

Concentrating solar power (CSP) technologies can utilize heat from concentrated sunlight from a field of tracking mirrors to generate electricity, reform fuel, provide process heat, or augment fossil plant heat sources. Electricity-generating power tower systems focus light from thousands of independent heliostats onto a thermal receiver, which uses the focused light to warm a heat transfer fluid (HTF), typically, a molten nitrate salt. The HTF is then sent to a power generation cycle or diverted into thermal energy storage (TES) for later use. Thermal storage is – in principle – a straightforward proposition. However, optimal utilization of a TES resource is complex and multi-faceted: thermal energy may be dispatched to produce electricity immediately upon first availability, or thermal energy may be reserved for next-day peak periods at risk of filling storage and dumping energy, or a portion of the thermal energy can be reserved to maintain equipment temperatures, reducing power cycle startup time, etc. Many possible dispatch permutations variously emphasize producing peak power, operating through transients, expediting daily startup, etc. The best operation strategy can change day-to-day throughout the year, depending on the weather and market pricing forecasts. The project we describe in this report develops a software package that allows users to explore design optimization, operations decisions, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The software we develop is the first comprehensive design tool of its kind to incorporate all of these aspects while being deployed as open source.

14 SOLAR ENERGY↗

DOE OSTI2024

A Review of Coupled Geochemical–Geomechanical Impacts in Subsurface CO 2 , H 2 , and Air Storage Systems

Increased demand for decarbonization and renewable energy has led to increasing interest in engineered subsurface storage systems for large-scale carbon reduction and energy storage. In these applications, a working fluid (CO 2 , H 2 , air, etc.) is injected into a deep formation for permanent sequestration or seasonal energy storage. The heterogeneous nature of the porous formation and the fluid–rock interactions introduce complexity and uncertainty in the fate of the injected component and host formations in these applications. Interactions between the working gas, native brine, and formation mineralogy must be adequately assessed to evaluate the efficiency, risk, and viability of a particular storage site and operational regime. This study reviews the current state of knowledge about coupled geochemical–geomechanical impacts in geologic carbon sequestration (GCS), underground hydrogen storage (UHS), and compressed air energy storage (CAES) systems involving the injection of CO 2 , H 2 , and air. Specific review topics include (1) existing injection induced geochemical reactions in these systems; (2) the impact of these reactions on the porosity and permeability of host formation; (3) the impact of these reactions on the mechanical properties of host formation; and (4) the investigation of geochemical-geomechanical process in pilot scale GCS. This study helps to facilitate an understanding of the potential geochemical–geomechanical risks involved in different subsurface energy storage systems and highlights future research needs.

08 HYDROGEN↗

DOE OSTI2023

Balancing molecular level influences of intermolecular frustrated Lewis pairs (FLP) for successful design of FLP catalysts for hydrogen storage applications

The rise in energy demands and the deleterious environmental issues related to fossil fuels has led to a surge of interest in hydrogen as a "green" alternative. Hydrogen's extraordinary energy density makes it a potential energy and economic "power"-house. Significant research has been dedicated to materials-based hydrogen storage. One area, liquid organic hydrogen carriers (LOHC) is of substantial interest for the reversible transportation of hydrogen from production to end-use facilities. There are challenges associated with this technology including the dependency on precious metal-based catalysts. Recent work in frustrated Lewis pair (FLP) catalysis demonstrates promise for addressing these challenges. Here this review is focused on assessing recent literature on the utilization of intermolecular FLP main group catalysts for improved hydrogenation/dehydrogenation of various substrates including potential LOHC complexes. This review will present an overview of FLPs, highlight potential hydrogen storage applications, and propose areas where knowledge gaps exist that require further investigations.

08 HYDROGEN↗

DOE OSTI2025

Spatial and chemical heterogeneity in aqueous Zn/MnO 2 batteries: role of Zn and Mn containing complexes

Aqueous Zn/MnO 2 batteries are a promising, safe alternative for grid-scale energy storage, owing to their environmentally safe and low-cost nature. The dissolution–deposition reaction mechanism in a mild aqueous pH regime has recently gained significance due to its relevance in battery design. Comprehending both the specific locations and the way reaction progresses is crucial for efficient batteries. This study demonstrates that Zinc Hydroxy Sulfate (ZHS) formed during discharge primarily near the dissolved MnO2 particles. Acting as a host for charge reactants in subsequent cycles, the charge product morphology was visualized using operando X-ray fluorescence microscopy. After ∼400 hours of cycling, capacity fade was linked to the formation of a Zn–Mn core–shell phase which is attributed to an irreversible core phase in the electrode, visualized through three-dimensional chemical mapping. Altogether, this research underscores the importance of understanding local morphological evolution in designing electrodes and chemistries for advanced grid-scale energy storage technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Low Carbon Technology Strategies: Large Office

This document includes steps that building owners and operators can implement to achieve smart, healthy, and low-carbon large office buildings within their existing building portfolios. Large offices are typically over 50,000 square feet and often include complex heating and cooling systems.

analytics↗