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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Selecting and Implementing Resilience Metrics in Existing Energy Sector Models [Slides]

Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result of the growing interest in energy sector resilience, research communities have proposed a plethora of candidate resilience indicators and metrics, most of which remain immature at different scales and segments within the energy system. A necessary focus of the research community lies in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing these challenges that need to be addressed, we explore how to effectively integrate resilience considerations into energy sector models and tools. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes - including consequences and/or changes in investment or operational decisions due to avoided consequences - based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches. To demonstrate the importance of perspective, we selected models that represent different segments of the energy sector, geographic scales, and modeling approaches. A second important aspect of our effort was the development of generalized power interruption scenarios. These scenarios were intended to help establish a framework for simulating the effects of real-world threats in terms of their impacts on system components and, in turn, power interruption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Innovation

Innovation is a highly overused buzzword in government offices and corporate America. Just like leadership, innovation is something that organizations realize they need, but often are frustrated in their efforts to achieve. Making matters worse, the definition of innovation changes with the user and the context. Simply put, innovation is change and change for any organization is difficult. This study examines the topic of innovation and pays special attention to what works, what does not work, and the basic principles governing how one might go about innovating. As leadership is critical to any successful innovation effort, special attention is given to leading change and leading innovation. ''The reasonable man adapts himself to the world; the unreasonable one persists to adapt the world to himself. Therefore, all progress depends on the unreasonable man.'' - George Bernard Shaw

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Leveraging the bioeconomy for carbon drawdown

Stringent climate change mitigation scenarios rely on large-scale drawdown of carbon dioxide from the atmosphere. Amongst drawdown technologies, bioenergy with carbon capture and sequestration (BECCS) has received considerable attention in the climate mitigation literature. Recently, attention has shifted further from a relatively narrow focus on BECCS to a broader focus on Biomass Carbon Removal and Storage (BiCRS). The concept of BiCRS has the potential to enable a future where the climate mitigation value of biomass resources is more valuable than the energy value, due to the potential to remove and sequester large quantities atmospheric CO 2 . This article provides a qualitative overview of prominent BiCRS technologies from which a set of the most promising technologies are assessed quantitively through life cycle assessment. There are numerous opportunities to incorporate carbon removal and management within the bioeconomy, but the majority of immediate carbon removal potential exists in four bioproducts: bioenergy, bioplastics, biochar, and wood products. We analyze the life cycle greenhouse gas emissions and disposition of sequestered carbon over 10,000 years for four bioproducts representative of each broader category: an advanced BECCS pathway, biopolyethylene, oriented strand board, and biochar soil amendment. We find that the BECCS pathway has the greatest magnitude and durability of CO 2 storage over all time horizons. However, non-BECCS pathways achieve 34–64% of the drawdown magnitude relative to BECCS and retain 55–67% of their initial drawdown over 100 years (central estimate). We identify three engineering strategies for enhancing carbon drawdown: reducing biomass supply chain emissions, maximizing carbon stored in long lived products, and extending the term of carbon storage. Finally, we highlight the need to characterize both the magnitude and permanence of carbon drawdown as a means for policymakers and technology develo pers to deploy limited biomass resources to maximize mitigation benefits.

09 BIOMASS FUELS↗
DOE OSTI2022

Less Common Topological Phenomena in Bulk Materials

"Prediction and subsequent discovery of topological insulators is considered to be one of the main results in condensed matter physics in the last decades. Not surprisingly, it has received major attention of both researchers and funding agencies. This attention is well-deserved; yet, one cannot but note that nearly all this research revolves about essentially the same concept: electronic excitations with linear dispersion, covering, of course, such diverse and intriguing phenomena as topological insulator, bulk Dirac states (or Weyl, if not spin degenerate), Mayorana fermions. In this project, we will address, mainly, other topological phenomena, such as topologically nontrivial magnetic patterns (as, for instance, topological Hall and related phenomena). Specifically, we propose three interrelated trusts: (1) Time-reversal symmetry breaking nonrelativistic antiferromagnets, called altermagnets. These are materials that break Kramers degeneracy of electronic bands, despite having zero net magnetization by symmetry and being fully collinear, and not necessarily non-centrosymmetric. The corresponding band structure is very similar to the band structure in non-centrosymmetric spin-orbital materials, but materials that we propose to study are distinctly different, first and foremost in the sense that despite sharing many aspects of their electronic properties with the latter, they break the time-reversal symmetry without either spin-orbit coupling or lack of inversion symmetry. (2) Topologically nontrivial magnetic spirals. The PI has been engaged with the experimental group of Dr. Ghimire at GMU investigating Dirac materials with helical magnetism, based on stacked magnetic Kagome layers, with a generic formula of RMn6Sn6. In particular, Y Mn6Sn6 demonstrates a component of the Hall effect that is naturally interpreted in terms of a topological spin texture, as well as linear magnetoresistance. Our calculation identify Dirac states that are robust with respect to the spiral formation, and let us derive an advance mean-field model explaining the observed phase diagram. This model predicted four distinct phases, with very distinct properties, which have now been seen in neutron experiments. The same compound is known to demonstrate topological Hall effect in a particular magnetic phase, and only at elevated temperature. Based on our understanding of the phase diagram, we have worked out a phenomenological theory of a chiral (skyrmionic) response to an external magnetic field, similar to the nematic response to external strain in Fe-based superconductors, which is possible in a centrosymmetric lattice and without interplanar Dzyaloshinskii-Moriya interaction. This phenomenological theory agrees quantitatively with the experiment. It is in our plans to research other similar materials for this effect. (3) Search for 3D analogues of Fe-based superconductors. We want to investigate materials that can be viewed as 3D analogues of FeSe. Specifically, we want materials that are good metals and host antiferromagnetism, which can be suppressed by pressure and generate an s-wave superconductivity, as in Fe-based superconductors. We have in mind some candidates already. This work will proceed in close collaboration with the experimental group of Prof. Nirmal Ghimire in the same department, whose expertise lies in sample making, magnetometry and transport measurements of materials with complex magnetic structures."

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Advanced Guide to Understanding Power System Model Results for Long-Term Resource Plans

This guide is for public utility commission staff, state energy office staff, and other stakeholders who review model results for utility integrated resource plans (IRPs). It builds on the "Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans," and delves into more advanced topics that were not included or not fully covered in the beginner's guide. The topics included here are evolving and may or may not be important to the resource plan you are evaluating. Due to limitations in resources, it's also not possible to give the highest level of detail or attention to every topic within a plan. An important part of planning for an uncertain future involves deciding which topics deserve the most focus and resources. It's all about prioritizing efforts where they will have the most impact or be most beneficial despite uncertainties ahead. As with the beginner's guide, we intend for this guide to help improve decision-making in the electricity planning process by strengthening understanding and dialogue between electricity system planners and relevant stakeholders. The following information is designed to allow you to better engage in the planning process by evaluating results, asking questions, and thinking through what is most important. We allocate significant discussion in the guide to electricity demand evolution, demand-side resources, and resource adequacy. These topics have garnered increasing attention, hence their prominence in this guide. Other topics are also presented, but their incorporation into the planning process might vary based on interest and relevance. The absence of certain topics doesn't diminish their importance; rather, it reflects the reality that in planning, trade-offs necessitate prioritizing certain aspects over others.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Lower-length-scale modeling of chemical additions, corrosion and fission products in select MSR base salts

Molten salts play a crucial role in advancing Generation IV nuclear energy technology, with chloride-based salts like NaCl-UCl 3 garnering significant attention due to their distinctive properties. However, the corrosive nature of molten salts causes the dissolution of chromium (Cr), leading to the formation of CrCl 2 and CrCl 3 species in molten chlorides. Moreover, the radioactive decay of nuclear fuel gives rise to fission products, including Cs, Sr, and I chlorides. The first part of this report presents a comprehensive study utilizing ab initio molecular dynamics (AIMD) simulations to investigate the properties of eutectic NaCl-UCl 3 molten salt in the presence of corrosion products (CrCl 2 and CrCl 3 ) and fission product (CsCl). The study focuses on essential structural and thermophysical properties such as density, mixing energy, coordination numbers (CN), and Radial Distribution Functions (RDF) of the salts with varying compositions of corrosion products and fission product, covering a range from 0% to 13.5%. The results offer valuable insights into the behavior of corrosion and fission products in uranium-based molten salts, providing essential data that can be used as input to the MTDB-TC and MSTDB-TP property databases being developed by the NEAMS program. Due to their favorable characteristics such as low melting points, high boiling points, and low costs, MgCl 2 +NaCl+KCl (MNK) eutectic salts have recently attracted attention as high-temperature heat transfer fluids. The incorporation of LiCl into MNK salts can further reduce their melting points and increase their specific heat capacities, which is de- sirable for high-temperature heat transfer applications. The second part of this report presents the development and validation of a new shell-model potential for the MgCl 2 +NaCl+KCl+LiCl system, which captures the polarization of Cl anions. The extensive comparison with experimental data and AIMD simulations demonstrates the accuracy and reliability of the potential. Furthermore, using this potential, we elucidate the intricate network structure in MNK eutectic salts that is formed through polyhedron sharing. This research contributes to a fundamental understanding of the atomic structures and thermophysical properties of multi-component molten salts, which is crucial for future development of heat transfer fluids for applications in molten salt reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improving and Assessing the Quality of Uncertainty Quantification in Deep Learning

Deep learning (DL) models have enjoyed increased attention in recent years because of their powerful predictive capabilities. While many successes have been achieved, standard deep learning methods suffer from a lack of uncertainty quantification (UQ). While the development of methods for producing UQ from DL models is an active area of current research, little attention has been given to the quality of the UQ produced by such methods. In order to deploy DL models to high-consequence applications, high-quality UQ is necessary. This report details the research and development conducted as part of a Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. The focus of this project is to develop a framework of methods and metrics for the principled assessment of UQ quality in DL models. This report presents an overview of UQ quality assessment in traditional statistical modeling and describes why this approach is difficult to apply in DL contexts. An assessment on relatively simple simulated data is presented to demonstrate that UQ quality can differ greatly between DL models trained on the same data. A method for simulating image data that can then be used for UQ quality assessment is described. A general method for simulating realistic data for the purpose of assessing a model’s UQ quality is also presented. A Bayesian uncertainty framework for understanding uncertainty and existing metrics is described. Research that came out of collaborations with two university partners are discussed along with a software toolkit that is currently being developed to implement the UQ quality assessment framework as well as serve as a general guide to incorporating UQ into DL applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Jurassic deserts and CO2 sequestration: the Glen Canyon Group in Utah, western USA

The Early Jurassic in the Western Interior of USA consisted of an extensive desert environment, including one of the largest ergs in geologic history. The Navajo erg has been estimated to extend as much as 2.2 million square kilometers, though the preserved extent is somewhat smaller. The Mesozoic was a global greenhouse phase, and during the Jurassic this region experienced fluctuations in climate aridity, reflected in the depositional environment. In addition to extensive dunefields, interdune deposits (lakes and oases) and fluvial systems are also documented within formations of the Glen Canyon Group. The Navajo Sandstone has received much attention as a potential CO2 injection target in recent years. It consists of thick, aeolian sandstones with high porosity and permeability, occurs in both outcrop and subcrop, and has industry data. Mapping of stratigraphic and sedimentologic changes within the Navajo Sandstone has been undertaken in localized areas, however piecing together these studies and developing regional models for CO2 potential has not received as much attention. There is significant industry data across Utah, and utilizing this data to pivot from a focus on hydrocarbon extraction to CO2 injection is an effective way to move forward with green energy, and to meet carbon neutral emission goals. Using legacy well data, we are developing a more comprehensive study of the Navajo Sandstone as a potential CO2 reservoir, in addition to identifying other zones of interest within the Glen Canyon Group, and improving understanding of stratigraphic complexity within one of the most significant aeolian systems in the world.

Mahon, Elizabeth↗
DOE OSTI2025

Probing the Sustainable Reduction of CO 2 , N 2 and NO 3 to Fuels and Chemicals using Non-Traditional Porphyrinoid Catalysts

For the last several decades, numerous strategies have been proposed to be able to interconvert electricity and commodity fuels for transportation and other applications. Even as solar and wind energy become more widely available, these renewable energy sources are not always available where the population is most dense or during peak times of energy demand. One plausible solution to the issue of electricity storage and transport is to use electricity to drive the formation of high-energy compounds and chemical fuels. As a result, the electrochemical conversion of CO 2 into chemical fuels has received major attention as a multi-pronged approach for electricity coversion, storage, and transport. Similar strategies are also attractive for conversion of N 2 and NO x into value added compounds such as ammonia. Metalloporphyrin and metallocorrole complexes are comprised of aromatic tetrapyrrole scaffolds and have been extensively studied as homogeneous catalysts for critical catalytic processes like the electrochemical CO 2 reduction reaction (eCO 2 RR) to generate CO as feedstock for the Fischer–Tropsch process to generate a variety of hydrocarbons as chemical fuels. Despite their significance and impact, efficiently driving such catalytic reduction processes is challenging for multiple reasons. Such processes require multiple-electron transfer events, as opposed to single-electron redox chemistry that forms high-energy singly-reduced intermediates. In addition, these electron transfer events must be coupled to proton-transfer steps and avoid application of high overpotentials where proton (H + ) reduction to generate H 2 (as well as other side-reactions) can lower the selectivity and energy efficiency of the eCO 2 RR process. Certain Fe(III) aromatic tetrapyrroles (e.g., porphyrins and corroles) have been reported to overcome these challenges, but are often difficult to synthesize and modify, and have a tendency to support single-electron redox chemistry at the metal as opposed to multielectron redox involving the ligand and metal in concert. Other families of tetrapyrroles in which all four meso-carbons are reduced (i.e., sp 3 -hybridized) are also known in the literature. These non-aromatic tetrapyrroles are known as porphyrinogens and support multi-electron redox chemistry which has been elaborated by several groups, prompting researchers to consider whether these scaffolds may improve the kinetics and efficiencies of multi-electron steps attendant to activation of thermodynamically stable small-molecule substrates such as CO 2 , N 2 , NO 3 − , and NO 2 − . Although porphyrinogens support multi-electron redox properties, the four sp 3 -hybridized meso-carbons inherent to the tetrapyrrole core completely disrupt π-conjugation between pyrrolic units, which compromises the photochemical properties of porphyrinogens in comparison to that of traditional porphyrinoids. Moreover, the highly reducing nature of porphyrinogens predisposes these platforms to extreme air and water sensitivity. Accordingly, such metalated porphyrinogens are often pyrophoric and/or incompatible with many common organic solvents (CH 2 Cl 2 , CHCl 3 , CH 3 CN, EtOAc, etc.). Hence, reports of efficient small-molecule activation or catalysis supported by porphyrinogens have been limited. To overcome the instability of porphyrinogens while retaining the scaffold’s attractive multi-electron redox properties, we have directed attention to establishing less-well studied groups of non-aromatic tetrapyrroles (i.e., phlorins, biladienes, and isocorroles). These non-traditional tetrapyrroles each contain just a single sp 3 -hybridized meso-carbon, which ablates the platforms aromaticity but still provides an extended π-framework. In addition to developing innovative platforms that may be used to sustainably generate value-added chemicals, fuels, and ammonia via either photo- or electrocatalytic approaches our work also has significantly broadened our understanding of how to prepare and modulate the properties of non-aromatic tetrapyrroles for other applications. Our efforts entailed a synergistic partnership and active collaborations with Drs. David C. Grills and Mehmed Z. Ertem (both of Brookhaven National Lab) to better characterize isocorroles (and related non-aromatic tetrapyrroles) using a variety of advanced spectroscopic and theoretical methods. Our combined efforts have shown that the combination of properties that isocorroles (and related tetrapyrroles) provide results in good chemical stability paired with unique redox and photochemical characteristics that are not typically supported by simple and/or unadorned aromatic tetrapyrroles. Beside redox chemistry, the photochemistry of isocorroles and other non-aromatic tetrapyrroles containing one sp 3 -hybridized meso-carbon is also appealing due to their absorption in the long-visible to near-IR regions, which are essential for photocatalysis and related applications that benefit from direct excitation at these wavelengths. The results reported vastly improve our understanding of non-aromatic tetrapyrrole synthesis, properties and utility for activation of small molecule substrates such as O 2 and CO 2 in the presence of weak cationic organic acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Quantifying and Optimizing the Energy Benefits of Mass Timber Construction

The International Mass Timber Alliance (IMTA) is a global organization of industry leaders, engineers, scientists, and associations dedicated to advancing mass timber construction. Its mission is to generate and disseminate scientific data supporting the development of standardized construction and energy efficient practices that promote the adoption of mass timber worldwide. IMTA collaborated with Oak Ridge National Laboratory (ORNL) to leverage ORNL’s expertise in building envelope modeling and testing to evaluate how mass timber construction can reduce peak heating and cooling demand, lower overall energy use, and improve resilience during power outages. A previous study of 80 mass timber buildings in Finland found measured energy use up to 50% lower than predicted by simulation. This project aimed to validate and extend those findings for U.S. buildings through analytical modeling, laboratory testing, and full-scale building evaluations. The research focused on the thermal performance of low-embodied-energy wall assemblies, such as cross-laminated timber (CLT) panels and log walls, with particular attention to the effects of thermal inertia on indoor comfort and energy performance. While mass timber’s structural and fire-resistance properties are well documented, its whole-building thermal behavior has received limited attention. Field data, simulation results, and resilience testing from this study will inform future modeling practices, design guidelines, and construction practices by quantifying the unique thermal and demand-flexibility benefits of mass timber construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Qualitative Risk Assessment of Legacy Wells within the Estimated Prairie State Generating Company Area of Review

This report details the digitization of a legacy wellbore database, including data processing assumptions, parameter estimation, and risk assessment methodology. The database, comprising 6,454 documents, was provided by ISGS. It includes valuable data from the Prairie State Generating Company (PSGC) and One Earth Energy (OEE) sites of the CarbonSAFE Phase III – Illinois Storage Corridor project. The report focuses on wells within a 15-mile radius from the Lively Grove #1 (LG#1) well at PSGC site, evaluating subsurface conditions and potential risks. A total of 4,386 wellbores within 15 miles of the LG#1 well were filtered based on depth and formation codes. LG#1 is the stratigraphic well at the PSGC site drilled in 2021. Ninety-four (94) wells penetrating the Maquoketa Shale Group (the primary confining unit) within the estimated area-of-review (AoR) for the PSGC site were evaluated using a qualitative risk assessment (QRA) methodology. The QRA developed by Arbad et al. 2022 focuses on legacy wells within the AoR and categorizes them based on well construction details. The QRA identifies wells that need immediate attention by categorizing them based on penetration depth and protection. Wells within the AoR were categorized into nine groups based on penetrations and protections. These categories range from Type 1 wells, with no documentation, to Type 9 wells, which do not penetrate the primary confining unit or storage reservoir (unit). Well accessibility within the AoR varies based on well status, including Dry & Abandoned (DA), Plugged & Abandoned (PA), Injection (INJ), Oil/Gas Producing (PROD), and Observation (Obs) wells. Accessibility levels were determined by well construction, with DA wells being the least accessible and Observation wells the most accessible, impacting gas leakage detection possibilities. Remedial action priority of wells decreases from Type 1 to Type 9 wells. Type 1 to Type 6 wells with status DA and PA require immediate attention, while Type 7 and Type 8 wells are low priority. A risk matrix used to prioritize corrective actions for legacy wells is proposed to categorize wells within an AoR based on penetrations, protections, and accessibility. The methodology involves data acquisition, well categorization into nine types, and determining CO 2 leakage pathways using well schematics and geospatial mapping. This approach is particularly useful for managing the integrity of legacy wells throughout the lifecycle of a Carbon Capture and Storage (CCS) project. A qualitative risk assessment of 94 wells within the AoR of the PSGC site identified 54 wells with high priority for corrective action due to penetration of the primary containment seal. The assessment utilizes color-coded maps to categorize well types and prioritize corrective actions, providing a comprehensive analysis. Schematics of wells penetrating the primary confining unit were drawn, and leakage pathways were identified. Details of all wells penetrating the confining zone are provided in the appendix, including information on well types, plugging, and casing status.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Cross-Feature Transfer Learning for Efficient Tensor Program Generation

Tuning tensor program generation involves navigating a vast search space to find optimal program transformations and measurements for a program on the target hardware. The complexity of this process is further amplified by the exponential combinations of transformations, especially in heterogeneous environments. This research addresses these challenges by introducing a novel approach that learns the joint neural network and hardware features space, facilitating knowledge transfer to new, unseen target hardware. A comprehensive analysis is conducted on the existing state-of-the-art dataset, TenSet, including a thorough examination of test split strategies and the proposal of methodologies for dataset pruning. Leveraging an attention-inspired technique, we tailor the tuning of tensor programs to embed both neural network and hardware-specific features. Notably, our approach substantially reduces the dataset size by up to 53% compared to the baseline without compromising Pairwise Comparison Accuracy (PCA). Furthermore, our proposed methodology demonstrates competitive or improved mean inference times with only 25–40% of the baseline tuning time across various networks and target hardware. The attention-based tuner can effectively utilize schedules learned from previous hardware program measurements to optimize tensor program tuning on previously unseen hardware, achieving a top-5 accuracy exceeding 90%. This research introduces a significant advancement in autotuning tensor program generation, addressing the complexities associated with heterogeneous environments and showcasing promising results regarding efficiency and accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Effectiveness and Long-Term Effects of SER+ FELIZ(mente): A School-Based Mindfulness Program for Portuguese Elementary Students

School-based mindfulness programs (SBMPs) have gained global popularity. Yet, there is a need for more rigorous procedures to develop and assess them. This study aimed to address these limitations by examining the effectiveness of a Portuguese SBMP, called SER + FELIZ(mente). The final sample included 190 third and fourth-graders: 99 in the SBMP group and 91 in a wait-list group. Effects on attentional control, emotional regulation and wellbeing were examined in the short term (T2) and 6 months later (T3). We also tested the moderating role of age, gender, and baseline scores. Using a multilevel modeling approach, results showed a clear benefit of SBMP on emotional wellbeing at T2 but not T3. Despite SBMP students surpassing wait-list students in attentional control, cognitive reappraisal, and social wellbeing at T2, these effects were due to a levelling off among SBMP students, coupled with a decline among wait-list students from T1 to T2. These effects were moderated by age at T3. While universal improvements were limited, our SBMP seemed to have acted as a shield against school stressors (i.e., likely, test anxiety at T2). This opens a new avenue for research concerning the role of SBMPs in preventing (rather than repairing) mental-health issues in elementary students.

Magalhães, Sofia↗
DOE OSTI2022

Recent Developments of Tin (II) Sulfide/Carbon Composites for Achieving High-Performance Lithium Ion Batteries: A Critical Review

The ever-increasing worldwide energy demand and the limited resources of fossil have forced the urgent adoption of renewable energy sources. Additionally, concerns over CO 2 emissions and potential increases in fuel prices have boosted technical efforts to make hybrid and electric vehicles more accessible to the public. Rechargeable batteries are undoubtedly a key player in this regard, especially lithium ion batteries (LIBs), which have high power capacity, a fast charge/discharge rate, and good cycle stability, while their further energy density improvement has been severely limited, because of the relatively low theoretical capacity of the graphite anode material which is mostly used. Among various high-capacity anode candidates, tin (II) sulfide (SnS 2 ) has been attracted remarkable attention for high-energy LIBs due to its enormous resource and simplicity of synthesis, in addition to its high theoretical capacity. However, SnS 2 has poor intrinsic conductivity, a big volume transition, and a low initial Coulombic efficiency, resulting in a short lifespan. SnS 2 /carbon composites have been considered to be a most promising approach to addressing the abovementioned issues. Therefore, this review summarizes the current progress in the synthesis of SnS 2 /carbon anode materials and their Li-ion storage properties, with special attention to the developments in Li-based technology, attributed to its immense current importance and promising prospects. Finally, the existing challenges within this field are presented, and potential opportunities are discussed.

25 ENERGY STORAGE↗
DOE OSTI2021

Adapting Existing Energy Models for Resilience Analysis

Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result of the growing interest in energy sector resilience, research communities have proposed a plethora of candidate resilience indicators and metrics, most of which remain immature at different scales and segments within the energy system. A necessary focus of the research community lies in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing these challenges that need to be addressed, we explore how to effectively integrate resilience considerations into energy sector models and tools. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes—including consequences and/or changes in investment or operational decisions due to avoided consequences—based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches. To demonstrate the importance of perspective, we selected models that represent different segments of the energy sector, geographic scales, and modeling approaches. A second important aspect of our effort was the development of generalized power interruption scenarios. These scenarios were intended to help establish a framework for simulating the effects of real-world threats in terms of their impacts on system components and, in turn, power interruption.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Evaluating and Countering the Insider Threat to the Radioactive Source Supply Chain

The modern supply chain is a global enterprise and little drove this home more than the global COVID-19 pandemic which sent economic shockwaves throughout the world. Many goods became scarce, as products were delayed, in limited supply, or simply not available. The suddenly diminished supply collided with still high demand and led to greatly increased costs. This was particularly true for the radioactive source supply chain. The pandemic introduced extensive delays for construction projects, slowed the transport of radiological materials to facilities, interrupted treatment deliveries, and impaired the mobility of contractors across the industry. All of these concerns not only adversely affected the economy, but also impacted the safety and security of radiological material, potentially raising national security concerns. The vulnerability of the supply chain, a critical element in an increasingly interconnected world, was exposed. One example that challenged the adaptive capacity of the overall supply chain is the Ever Given container ship, which became stuck in the Suez Canal in 2020. This accident immediately shut down shipments that accounted for 12% of global trade, with long-term impacts estimated to be much larger. Developing the ability to anticipate and react in real-time to sudden changes has quickly become a necessity, particularly in industries that deal with the transport of hazardous material. The reaction to these dramatic incidents was to largely focus attention and resources on protecting the supply chain from external threats. However, the threat to the radioactive material supply chain from insiders intimately involved in the process may be even greater and remains a blind spot that requires increased attention. Recent events revealed the blueprint for targeting and disrupting that supply chain, so the potential for a malicious insider—or a manipulated, unwitting insider—to take advantage of this vulnerability is elevated, creating security concerns for radiological industries. This paper examines and analyzes the potential insider threat to the radioactive source supply chain and recommends steps to take to counter this possibility.

Kinney, Justin↗
DOE OSTI2023

Impact of the Electronic Properties of Chalcogenide Ligands in their Complexation with Uranyl Nitrate Complexes

The idea of covalency being directly correlated with selectivity in f-element separations has gained attention over the years. However, “covalency” as a concept is still under debate as it is not an experimental nor quantum mechanical observable. Regardless, covalency along with ionicity are still the main concepts used to explain the nature of the chemical bond of coordination complexes. Another concept that has gained the attention in the separations community is the hard-soft acid-base (HSAB) theory, which favors soft-donor ligands having the potential to increase selectivity for actinides (An) over the lanthanides (Ln) due to their ability to engage more effectively f-electrons in covalent interactions. However, it has been shown that while using softer donor ligands in fact increased orbital mixing and covalency with the actinides, it compromises the strength of the interaction owing to a decrease in the metal-ligand electrostatic interactions.1 Herein, we study the electronic structure of different types of chalcogenide ligands (LE, E = O, S, Se), their interaction with the uranyl ion, and their complexation free energies. Surprisingly, contrary to the expected order of covalency, i.e. An–LSe > An–LS > An–LO, our results suggest that the degree of covalency and associated complexation free energies depend on the nature of the coordinating moiety rather than solely on the directly coordinated atom. 1) Sadhu, Biswajit, and Michael Dolg. Enhancing actinide (III) over lanthanide (III) selectivity through hard-by-soft donor substitution: exploitation and implication of near-degeneracy-driven covalency. Inorganic Chemistry, 2019, 58, 9738 – 9748.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Towards Content Authenticity: Multimodal Fake News Detection and AI-Generated Text Identification

In today’s digital world, the spread of fake news and the rise of AI-generated text have become major threats to content authenticity and public trust. This thesis addresses both challenges through two complementary research directions: detecting fake news using multimodal features, and identifying AI-generated text using semantic and structural reasoning. The first part of the work focuses on fake news detection by introducing a novel model that combines text and image features through a unique rotational attention mechanism. Unlike traditional attention methods, this approach rotates the roles of query, key, and value across modalities to capture deeper interactions. Additionally, the model incorporates external domain information by linking news posts to top-ranked websites from Google search results, which helps assess the credibility of content based on its broader web context. This results in a more reliable and accurate fake news detection system that outperforms existing state-of-the-art methods. The second part presents SGG-ATD, a new framework for detecting AI-generated text. It uses masked language modeling to measure sentence coherence, followed by constructing a graph where keywords—both original and predicted—are connected based on semantic and contextual similarity. A Graph Convolutional Network (GCN) is then used to learn structural relationships within the text for final classification. Experimental results demonstrate that SGG-ATD achieves high F1-scores and consistently outperforms strong baselines. This method contributes to robust AI text detection, supporting accountability and resilience against AI-driven misinformation.

Gupta, Nidhi↗