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The dawn of the Nuclear Age occurred on the morning of July 16,1945, when Los Alamos conducted the Trinity test. Scientists and engineers from the U.S., Britain, and Canada proved the feasibility of weaponizing energy from plutonium nuclear fission using an implosion mechanism.
DOE has extremely challenging and diverse missions, each born out of national need. The national labs serve as the science and technology engine for DOE missions. Each Lab stewards distinctive capabilities which DOE leverages through networks of labs address core missions, dynamic programs and rapid response needs. National lab networks have transformative impact.
The “Southeast Regional CO 2 Utilization and Storage Acceleration Partnership” (SECARBUSA) project supports the U.S. Department of Energy (DOE) Office of Fossil Energy's (FE) mission to help the United States meet its need for secure, affordable, and environmentally sound fossil energy supplies by utilizing the advancements made by the current Regional Carbon Sequestration Partnership (RCSP) Initiative to continue to identify and address knowledge gaps. The primary project objective is to identify and address regional onshore storage and transport challenges facing commercial deployment of carbon dioxide (CO 2 ) capture, utilization, and storage (CCUS) technologies. The Research Partners and a selected industry network of experienced CCUS project developers and operators will coordinate their capabilities to accelerate CCUS deployment by achieving four primary research objectives: 1) address key technical challenges; 2) facilitate data collection, sharing and analysis; 3) assess transportation and distribution infrastructure; and 4) promote regional technology transfer and dissemination of knowledge. The SECARB-USA Region includes the states of Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia and portions of Kentucky, Missouri, Oklahoma, Texas, and West Virginia. Under subtask 5.2: Non-Technical Challenges to CCUS Deployment, the Southern States Energy Board (SSEB) will define and identify An Inventory of Non-Technical Challenges to CCUS Deployment. As an initial step, SSEB organized an Industry and Non-Governmental Organization (NGO) Working Group comprised of knowledgeable market participants to assist in the development of an initial list of non-technical challenges to CCUS development.
Here, phononic crystals (PnCs) engineered to manipulate and control the propagation of mechanical waves have enabled the design of a range of novel devices, such as waveguides, frequency modulators, and acoustic cloaks, for which wide and robust phononic band gaps are highly preferable. While numerous PnCs have been designed in recent decades, to the best of our knowledge, PnCs that possess simultaneous wide and robust band gaps (to randomness and deformations) have not yet been reported. Here, we demonstrate that by combining the band-gap formation mechanisms of Bragg scattering and local resonances (the latter one is dominating), PnCs with wide and robust phononic band gaps can be established. The robustness of the phononic band gaps are then discussed from two aspects: robustness to geometric randomness (manufacture defects) and robustness to deformations (mechanical stimuli). Analytical formulations further predict the optimal design parameters, and an uncertainty analysis quantifies the randomness effect of each designing parameter. Moreover, we show that the deformation robustness originates from a local resonance-dominant mechanism together with the suppression of structural instability. Importantly, the proposed PnCs require only a small number of layers of elements (three unit cells) to obtain broad, robust, and strong attenuation bands, which offer great potential in designing flexible and deformable phononic devices.
The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome-scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind. It is also evident that, given the plethora of databases and software efforts, it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models. We work at the forefront of model creation and systems scale data generation. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.
The reports contained herein are for project activities that occurred from October 2013 through September 2014. Project life cycle is indicated under the title as well as the original proposal number (in the following format: site abbreviation--ID #--originating fiscal year; e.g., STL-03-14). Each of the reports describes in detail the discoveries, achievements, and challenges encountered by our principal investigators. As SDRD, by definition, invests in “high-risk” and hopefully “high-payoff” research, the element of uncertainty is inherent. While many of our efforts are “successful” and result in positive outcomes or technology utilization, some fall short of expectations, but cannot be construed as “failure” in the negative sense. The latter is a natural and valid part of the process of advanced research and often leads to unforeseen new pathways to future discovery. Regardless, either result advances our knowledge base and increases our ability to identify solutions and/or avoid costly and unwarranted paths for future challenges. In summary, the SDRD program continues to provide an unfettered mechanism for innovation that returns multifold to our customers, to national security, and to the general public. The program is a vibrant R&D innovation engine, benefited by its discretionary pedigree, enhanced mission spectrum, committed resources, and sound competitiveness to yield maximum taxpayer benefit. The 25 projects described exemplify the creativity and ability of a diverse scientific and engineering talent base. The efforts also showcase an impressive capability and resource that can be brought to find solutions to a broad array of technology needs and applications relevant to the NNSS mission and national security. Further SDRD performance metrics can be found in the appendix at the end of this report.
Safety/transient testing to evaluate performance under off-normal conditions is an essential pillar for both the development of Accident Tolerant Fuels (ATF) and the optimization of fuel operation economics beyond current discharge burnups. Among other factors, the successful interpretation of the transient testing results relies upon the knowledge of the initial conditions of the test, including the characteristics of the fuel system under scrutiny. When testing pre-irradiated material, the assumptions that the fuel and the cladding still have the same properties as in the pre-irradiation stage is obviously wrong and could affect the results of the test. This is particularly true the more burnup accumulates in the fuel rod and irradiation progresses. The knowledge of the initial microstructure of both fuel and cladding allows a clearer interpretation of the subsequent transient testing results, provides validation of the physical phenomena underlying the model predictions and eliminates the uncertainties related to the limited knowledge of the sample status before the test. One example is the phenomenon of fine fragmentation that occurs in Light Water reactor (LWR) fuel. During a Loss of Coolant Accident (LOCA) or Reactivity Initiated Transient (RIA) the fuel can severely fragment. During LOCA, high burnup fuel tend to finely fragment, which has raised safety concerns due to the increased likelihood of dispersal of such small particles once the cladding has burst and due to the increased fission gas release. Therefore, efforts have been devoted to the assessment of a pulverization threshold that could determine the conditions under which fine fragmentation is predominant. However, the lack of information regarding the initial conditions of the fuel, and the connections between those conditions and the pre-transient irradiation history, have hindered the development of a fully mechanistic fragmentation and pulverization criterion. The empirical relationships rely on conservative estimations, due to the lack of information on critical material properties and characteristics. More generally, experimental evidence of the irradiation-induced modifications at microstructural scale are necessary to determine the behavior of the material at the macroscopic scale, with the latter being the one of technological interest. Significant progress has been made in the last two decades in the developments of analytical materials science techniques that can be applied to highly radioactive materials, such as high burnup fuels. The availability of new techniques and the improvement of existing ones has enabled investigations previously not possible that can deepen the understanding of the fuel characteristics and properties at high burnup. The better knowledge of material behavior and irradiation-induced phenomena could help the prediction of its performance. In this context, the scope of the present work is to apply a wide portfolio of advanced characterization techniques to determine properties that are relevant for safety and performance. The results are interpreted in the context of engineering scale post-irradiation examinations and available information on the irradiation conditions.
Cycle benefits of rotating detonation engines show up to five percentage points of efficiency gain for low-pressure ratio engines. An optimal integration between the combustor and the turbine needs to be guaranteed to realize this potential gain. The rotating detonation combustor (RDC) exhausts transonic flow with shocks rotating at frequencies ranging from a few to tens of kilohertz depending on the number of present waves. Hence, the turbine design requires precise knowledge of the fluctuations and losses downstream of the combustor. This paper focuses on the quantification of fluctuations and losses for accelerating and diffusing passages. The analysis of the combustor is performed via reactive unsteady Reynolds Averaged Navier-Stokes (URANS) simulations. The unsteady RANS equations are solved via CFD++ from Metacomp with a one-step reaction mechanism for an H2-air mixture. The resolving of the boundary layer is achieved with a structured mesh of around 36 million cells. Inlet pressure of 10 bar and two different back pressures are applied to the combustor to model the interconnection with downstream turbines. Finally, we present and assess a methodology to reduce the computational time to model these passages ten times.
To ensure that multi-barrier systems in high-level radioactive waste (HLW) repositories can efficiently perform their functions and isolate the waste from the biosphere, coupled thermo-hydro-mechanical-chemical (THMC) processes used for the performance assessment of HLW disposal facilities should be modeled. To evaluate coupled THMC processes, the DECOVALEX project, a unique international research collaboration project initiated in 1992, developed mathematical models and field experiments involving THMC processes in engineered barrier systems and host rocks for HLW disposal. The DECOVALEX project and the current status of coupled THMC model development can provide further insights into the performance assessment of HLW disposal facilities. This study provides information regarding the DECOVALEX project and reviews the development of coupled THMC models. The study results furnish knowledge of coupled THMC processes and techniques for the performance assessment and safety analysis of the final HLW disposal. (authors)
Significance The search for high-efficiency thermoelectric materials encompasses many classes of semiconductors. Zintl phases are attractive thermoelectric materials for thermoelectric applications. Here, we report the high thermoelectric performance of the rarely studied bismuth (Bi)-based Zintl phases (Eu 0.5 Yb 0.5 ) 1−x Ca x Mg 2 Bi 2 with the record figure-of-merit ZT as high as 1.3 at 873 K. This ZT value is, to our knowledge, the highest ever reported in CaAl 2 Si 2 -based structures, especially compared with the best antimony (Sb)-based YbZn 0.4 Cd 1.6 Sb 2 compound. Because Sb-based Zintl compounds have been studied for many decades, this Bi-based Zintl phase with high thermoelectric properties could be a good thermoelectric material candidate in the future.
Despite the success statistical physics has enjoyed at predicting the properties of materials for given parameters, the inverse problem, identifying which material parameters produce given, desired properties, is only beginning to be addressed. Recently, several methods have emerged across disciplines that draw upon optimization and simulation to create computer programs that tailor material responses to specified behaviors. However, so far the methods developed either involve black-box techniques, in which the optimizer operates without explicit knowledge of the material's configuration space, or require carefully tuned algorithms with applicability limited to a narrow subclass of materials. Here we introduce a formalism that can generate optimizers automatically by extending statistical mechanics into the realm of design. The strength of this approach lies in its capability to transform statistical models that describe materials into optimizers to tailor them. Here, by comparing against standard black-box optimization methods, we demonstrate how optimizers generated by this formalism can be faster and more effective, while remaining straightforward to implement. The scope of our approach includes possibilities for solving a variety of complex optimization and design problems concerning materials both in and out of equilibrium.
—The transition from the traditional power grid to the smart grid improves reliability, performance, and management, while simultaneously increasing its susceptibility to cyberattacks. One of the biggest weaknesses in grid security is the human agent responsible for its maintenance and operations. As such, it is crucial to embed hands-on understanding of grid operations and security, especially for students in the Electrical and Computer Engineering (ECE) fields. This paper presents a case study where ECE students from Temple University used an interactive microgrid simulator, "Grid Game", a program developed by Idaho National Laboratory. This case study offers insights into the ECE students’ understanding of key engineering principles (microgrid stability, generation control system, generator inertia, energy storage, and grid security) gained by using the simulator program. Furthermore, the human behavior (strategies to prepare for and respond to cyberattacks, and cooperation and conflict in decision-making) of defenders/ECE students as they experience cyberattacks are also discussed. The paper then offers some limitations and possible suggestions for future research.
Xylose fermentation is a bottleneck in second-generation ethanol production. As such, a comprehensive understanding of xylose metabolism in naturally xylose-fermenting yeasts is essential for prospection and construction of recombinant yeast strains. The objective of the current study was to establish a reliable metabolomics protocol for quantification of key metabolites of xylose catabolism pathways in yeast, and to apply this protocol to Spathaspora arborariae. Ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) was used to quantify metabolites, and afterwards, sample preparation was optimized to examine yeast intracellular metabolites. S. arborariae was cultivated using xylose as a carbon source under aerobic and oxygen-limited conditions. Ion pair chromatography (IPC) and hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS) were shown to efficiently quantify 14 and 5 metabolites, respectively, in a more rapid chromatographic protocol than previously described. Thirteen and eleven metabolites were quantified in S. arborariae under aerobic and oxygen-limited conditions, respectively. This targeted metabolomics protocol is shown here to quantify a total of 19 metabolites, including sugars, phosphates, coenzymes, monosaccharides, and alcohols, from xylose catabolism pathways (glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle) in yeast. Furthermore, to our knowledge, this is the first time that intracellular metabolites have been quantified in S. arborariae after xylose consumption. The results indicated that fine control of oxygen levels during fermentation is necessary to optimize ethanol production by S. arborariae. The protocol presented here may be applied to other yeast species and could support yeast genetic engineering to improve second generation ethanol production. .
Over the last couple of decades vanadium and V-based alloys have received significant attention as a potential structural material for fusion power applications because of their favourable mechanical properties under irradiation and at elevated temperatures. They are also considered as the advanced options of storage materials for hydrogen and its isotopes. However, the higher affinity of V for O, C and N poses critical challenges in its engineering applications since they lead to degradation of mechanical properties. They can further interact with the matrix to produce metallic oxy-carbo-nitride precipitates. To a certain limit, these precipitates are beneficial and can be exploited to enhance the mechanical behaviour of the alloy through suitable microstructural design. However, this requires a prior knowledge of the interaction between the alloy and the impurity solutes. In the present work vanadium specific experiments have been designed and carried out to bring out the V-interstitial solute interaction by charging oxygen in the near surface region of vanadium. Microstructural and microchemical behaviour of the V-O solid solution has been studied through HRTEM (high resolution transmission electron microscopy) and HAADF (high angle annular dark field) coupled with EELS. Quantitative electron microscopy has been carried out to study structural modification of the alloy in atomic level caused by O charging. - Highlights: •Controlled experiments were carried out in pulsed laser ablation set-up to promote V-O interaction. • As a consequence of O dissolution, V transformed into a bct structure which is otherwise a bcc structure. •In V-O solid solution, dissolved O in the V matrix introduces significant amount of lattice strain. • Present work can be extended for introducing interstitial O in other pure transition metals and their alloys.
Classical 1D X-ray Free Electron Laser (X-ray FEL) theory has stood the test of time by guiding FEL design and development prior to any full-scale analysis. Future X-ray FELs and inverse-Compton sources, where photon recoil approaches an electron energy spread value, push the classical theory to its limits of applicability. After substantial efforts by the community to find what those limits are, there is no universally agreed upon quantum approach to design and development of future X-ray sources. We offer a new approach to formulate the quantum theory for 1D X-ray FELs that has an obvious connection to the classical theory, which allows for immediate transfer of knowledge between the two regimes. In conclusion, we exploit this connection in order to draw quantum mechanical conclusions about the quantum nature of electrons and generated radiation in terms of FEL variables.
This paper explores the potential of distributed ledger technology (DLT) to improve fault-tolerant grid operations by leveraging its core features as an immutable, decentralized ledger, a distributed, consensus-based agreement process, and a distributed state-replication engine. Distribution power systems deliver electricity to millions of customers; however, they are susceptible to various threats that can result in customer interruptions. These include faults caused by adverse weather conditions, natural disasters, vegetation growth, equipment failure, and malicious attacks. To minimize the effects of these faults, fault-handling approaches rely on network knowledge to isolate affected areas and reconnect unaffected areas, reducing the number of affected customers while maintaining safety. Here, we present a trusted data-sharing architecture that enables independent, distributed actors to reconstruct the pre-fault system state by enabling distributed resources to make appropriate decisions with limited network/system information. Although the process requires some data sharing between switch-delimited areas, the approach limits the amount of private information shared, preserving customers' privacy and business-sensitive information. We include three use cases that form a foundation for third parties to develop functional solutions that can eventually be deployed in the field. The gross error detection method used within switch-delimited areas can identify sensor errors and accurately detect circuit breaker states. The evaluation of possible reconnection while preserving data ownership resulted in a voltage magnitude difference smaller than 0.001% from the OpenDSS power flow solution that has full system knowledge, which is below the expected power flow tolerance. The approach offers a promising opportunity for improving fault-tolerant distribution grid operations.
Inference techniques play a central role in many cognitive systems. They transform low level observations of the environment into high-level, actionable knowledge which then gets used by mechanisms that drive action, problem-solving, and learning. This paper presents an initial effort at combining results from AI and psychology into a pragmatic and scalable computational reasoning system. Our approach combines a numeric notion of plausibility with first-order logic to produce an incremental inference engine that is guided by heuristics derived from the psychological literature.
Fish passage facilities are used to mitigate impacts of hydropower dams to migratory fish in rivers, but information on the location, types, and characteristics of this infrastructure is incomplete at a national scale. Researchers at Oak Ridge National Laboratory (ORNL) partnered with fish passage engineers and hydropower experts from the US Fish and Wildlife Service (USFWS), the National Oceanic Atmospheric Administration’s National Marine Fisheries Service (NOAA NMFS), and the Low Impact Hydropower Institute (LIHI) to create the first national scale database of fish passage infrastructure at US hydropower developments. This database consists of the ORNL_Fish_Passage_Dataset.zip file with 13 individual .csv files that contain information on fish passage facility engineering characteristics, targeted fish species, operational schedule, and costs. which is of great value to a diverse range of stakeholders. This information was collected between December 2023 and July 2025 from project partners, other hydropower stakeholders, online datasets available for download, and a stakeholder questionnaire Information. This data resource addresses a large gap in knowledge of the deployment of fish passage technology and is freely available to members of the hydropower community, including federal and state regulators and resource agencies, non-governmental organizations (NGOs), industry, and other user groups to support project planning and regulatory (re)licensing activities. This database supports the US Department of Energy Water Power Technologies Office objective to develop decision support tools and data resources that improve environmental performance and ensure hydropower’s long-term value to the American public.