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At least 1,513 records · Page 84

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DOE OSTI2021

Hardware Design of Medium Voltage SiC-Based Modular Multilevel Converters for Grid-Tied Applications

This paper presents a design of a 10 kV silicon carbide (SiC) MOSFET based modular multilevel converter (MMC). The MMC functions as the interconnection between a 24 kV dc bus and a 13. SkV distribution grid. This paper focuses on the hardware design of the MMC and its submodules. The gate driver, auxiliary power supply and bus bur in submodules are major components that need to meet high dv/dt immunity and high insulation voltage requirements. The gate driver achieves over 200 kV/us common mode transient immunity (CMTI). Its associated auxiliary power supply is based on an on-board transformer with over 30 kV insulation capability and 1.4 pF barrier capacitance. The busbar achieves less than 11 kV/cm electric field in the air to avoid partial discharges. Validation tests of the MMC submodule were performed by double pulse tests at 5 kV and buck converter tests at3 kV, 52A (peak). Reliable operations were achieved in validation tests.

auxiliary power supply↗

DOE OSTI2025

Experimental Validation of a High-Temperature Test Facility for Future Additive Manufactured Supercritical Carbon Dioxide Turbine Testing

For next-generation power plants to achieve high cycle efficiencies consistent with the Department of Energy's 65% efficiency target, turbomachinery capable of operating within high-temperature power cycles must be demonstrated. Pairing additively manufactured superalloy turbines with the supercritical carbon dioxide (sCO 2 ) power cycle could enable turbine inlet temperatures approaching 1300 °C while providing flexibility in turbine cooling strategies. Development of test facilities to characterize and validate such systems is crucial. In this study, a turbine test facility capable of achieving inlet conditions of 800 °C, 11 MPa, and 0.43 kg/s while accommodating complex auxiliary cooling flow requirements has been designed and constructed to support future testing of a Haynes 282 additively manufactured 30 kW turbine-generator system with advanced cooling channels. This facility enables characterization of aerodynamic performance, leakage, and windage losses. Details of the facility's construction and operation are presented, along with experimental validation tests using an orifice as an expansion device in place of the turbine. These tests confirm that the facility can reach the required conditions, distinguish regions of achievable steady and pseudo-steady conditions, and identify the heater power required for each point in the upcoming turbine campaign. The campaign confirmed that ISO 5167-2 can reliably predict orifice mass flow rates in extreme supercritical carbon dioxide conditions with deviations of 0.5–7.5%.

42 ENGINEERING↗

DOE OSTI2022

Selectively patterned Mg-doped GaN by SiN x -driven hydrogen injection

In this work, we demonstrate a method to achieve selectively patterned Mg-doped GaN layers using hydrogen drive-in through plasma-enhanced chemical vapor deposition (PECVD) silicon nitride (SiN x ) films. Activated Mg-doped GaN layers were selectively deactivated by patterned PECVD SiN x films with low-temperature annealing and showed high-resistive behavior. Spatially resolved photoluminescence measurements were used to optically verify the deactivation of Mg acceptors and showed distinct features corresponding to activated and deactivated Mg in GaN. The method suggested here provides a simple and effective method to achieve patterned Mg-doped GaN regions without thermal and plasma damage, which could cause degradation of device performance. The proposed method could provide a way to achieve future high-performance GaN lateral and vertical devices that rely on laterally patterned doping.

42 ENGINEERING↗

DOE OSTI2025

Highly enantioselective synthesis controlled by spin-exchange interaction

We present a strategy to achieve absolute asymmetric catalysis that is effectively controlled by an external magnetic field via a spin-exchange reaction leveraging the chirality-induced spin selectivity effect. Using an external magnetic field to achieve asymmetric synthesis has long been desired. Here, we demonstrate 90% enantiomeric excess (ee) in [3 + 2] cycloadditions and 89% ee in aldol reactions, where the handedness of the product is determined by the ~±150 mT external magnetic polarization of a ferromagnet (FM). Our approach uses an enantioselective crystallization of racemic catalysts on a FM surface, using a small-scale crystallization vial connected to a bulk racemic solution. Racemic catalysts controllably crystallize into their respective enantiopure forms and are directly used in asymmetric reactions. Thus, we demonstrate that an external magnetic field can serve as a versatile symmetry-breaking tool to achieve highly enantioselective organic synthesis eliminating the need of any enantioenriched reagents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Overcoming limitations in propanedehydrogenation by codesigning catalyst-membrane systems

Propylene production through propane dehydrogenation (PDH) is endothermic, and high temperatures required to achieve acceptable propane conversions lead to low selectivity and severe carbon-induced deactivation of conventional catalysts. We developed a catalyst-membrane system that removes the hydrogen by-product and can thus achieve propane conversions that exceed equilibrium limits. In this codesigned system, a silica/alumina (SiO 2 /Al 2 O 3 ) hollow-fiber hydrogen membrane was packed with a selective platinum-tin (Pt 1 Sn 1 /SiO 2 ) PDH catalyst on the tube side with hydrogen diffusing from the tube to the shell side. We demonstrate that the catalyst-membrane system can achieve propane conversions >140% of the nominal equilibrium conversion with a propylene selectivity >98% without deactivation of the system components. Here, we also show that by introducing oxygen on the shell side of the catalyst-membrane system, we can couple the endothermic PDH reaction on the tube side with exothermic hydrogen oxidation on the shell side. This coupling results in higher rates of hydrogen transport, leading to further enhancements in the propane conversion as well as desired thermoneutral system operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Extending the predictive power of perturbative QCD using the principle of maximum conformality and the Bayesian analysis

In addition to the evaluation of high-order loop contributions, the precision and predictive power of perturbative QCD (pQCD) predictions depends on two important issues: (1) how to achieve a reliable, convergent fixed-order series, and (2) how to reliably estimate the contributions of unknown higher-order terms. The recursive use of renormalization group equation, together with the Principle of Maximum Conformality (PMC), eliminates the renormalization scheme-and-scale ambiguities of the conventional pQCD series. The result is a conformal, scale-invariant series of finite order which also satisfies all of the principles of the renormalization group. In this paper we propose a novel Bayesian-based approach to estimate the size of the unknown higher order contributions based on an optimized analysis of probability distributions. We show that by using the PMC conformal series, in combination with the Bayesian analysis, one can consistently achieve high degree of reliability estimates for the unknown high order terms. Thus the predictive power of pQCD can be greatly improved. We illustrate this procedure for two pQCD observables: R e+e– and R τ , which are each known up to four loops in pQCD. Numerical analyses confirm that by using the scale-independent and more convergent PMC conformal series, one can achieve reliable Bayesian probability estimates for the unknown higher-order contributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Accelerated Assessment of Critical Infrastructure in Aiding Recovery Efforts During Natural and Human-made Disaster

Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as "Acute Phase" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.

Thakur, Gautam Malviya↗

DOE OSTI2022

Direction-optimizing Label Propagation Framework for Structure Detection in Graphs: Design, Implementation, and Experimental Analysis

Label Propagation is not only a well-known machine learning algorithm for classification but also an effective method for discovering communities and connected components in networks. We propose a new Direction-optimizing Label Propagation Algorithm (DOLPA) framework that enhances the performance of the standard Label Propagation Algorithm (LPA), increases its scalability, and extends its versatility and application scope. As a central feature, the DOLPA framework relies on the use of frontiers and alternates between label push and label pull operations to attain high performance. It is formulated in such a way that the same basic algorithm can be used for finding communities or connected components in graphs by only changing the objective function used. Additionally, DOLPA has parameters for tuning the processing order of vertices in a graph to reduce the number of edges visited and improve the quality of solution obtained. We present the design and implementation of the enhanced algorithm as well as our shared-memory parallelization of it using OpenMP. We also present an extensive experimental evaluation of our implementations using the LFR benchmark and real-world networks drawn from various domains. Compared with an implementation of LPA for community detection available in a widely used network analysis software, we achieve at most five times the F-Score while maintaining similar runtime for graphs with overlapping communities. We also compare DOLPA against an implementation of the Louvain method for community detection using the same LFR-graphs and show that DOLPA achieves about three times the F-Score at just 10% of the runtime. For connected component decomposition, our algorithm achieves orders of magnitude speedups over the basic LP-based algorithm on large-diameter graphs, up to 13.2× speedup over the Shiloach-Vishkin algorithm, and up to 1.6× speedup over Afforest on an Intel Xeon processor using 40 threads.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Scaling Uintah on the Aurora Exascale System up to 122,880 Intel Ponte Vecchio Xe Stacks

The challenge of being able to scale application codes based on the Asynchronous Many-Task (AMT) Uintah framework on the Department of Energy (DOE) Aurora exascale system is addressed in this work by considering a challenging Reverse Monte Carlo Ray Tracing radiation benchmark calculation. This benchmark involves potentially global all-to-all communication and uses adaptive mesh refinement and ray tracing to achieve scalability. This benchmark has been used as part of previous scalability studies on a number of pre-exascale systems and on the DOE Frontier exascale system. This paper describes steps taken to enable this benchmark to run successfully on up to 10,240 nodes and 122,880 Intel® Ponte Vecchio Xe stacks on the DOE Aurora exascale system. This scalability was achieved through a limited number of experiments on Aurora, given machine loads and its uniqueness. These experiments constitute valuable lessons learned to achieve scalability at this level. The resulting scalability runs, while few in number, demonstrate relatively good strong-scaling characteristics. A detailed analysis of these results provides important indications about the path to scalability on Aurora for future work. Overall, these results continue the remarkable ability of this AMT approach to produce scalable solutions for challenging problems at extreme scale on heterogeneous architectures.

Garcia, Marta [Argonne National Laboratory (ANL)]↗

DOE OSTI2025

Three Birds with One Stone: Improving Performance, Convergence, and System Throughput with NEST

Variational quantum algorithms (VQAs) have the potential to demonstrate quantum utility on near-term quantum computers. However, these algorithms often get executed on the highest-fidelity qubits and computers to achieve the best performance, causing low system throughput. Recent efforts have shown that VQAs can be run on low-fidelity qubits initially and high-fidelity qubits later on to still achieve good performance. We take this effort forward and show that carefully varying the qubit fidelity map of the VQA over its execution using our technique, Nest, does not just (1) improve performance (i.e., help achieve close to optimal results), but also (2) lead to faster convergence. We also use Nest to co-locate multiple VQAs concurrently on the same computer, thus (3) increasing the system throughput, and therefore, balancing and optimizing three conflicting metrics simultaneously.

qaoa↗

DOE OSTI2020

Water Treatment: Are Membranes the Panacea?

Alongside the rising global water demand, continued stress on current water supplies has sparked interest in using nontraditional source waters for energy, agriculture, industry, and domestic needs. Membrane technologies have emerged as one of the most promising approaches to achieve water security, but implementation of membrane processes for increasingly complex waters remains a challenge. The technical feasibility of membrane processes replacing conventional treatment of alternative water supplies (e.g., wastewater, seawater, and produced water) is considered in the context of typical and emerging water quality goals. This review considers the effectiveness of current technologies (both conventional and membrane based), as well as the potential for recent advancements in membrane research to achieve these water quality goals. We envision the future of water treatment to integrate advanced membranes (e.g., mixed-matrix membranes, block copolymers) into smart treatment trains that achieve several goals, including fit-for-purpose water generation, resource recovery, and energy conservation.

catalysis (heterogeneous)↗

DOE OSTI2021

Getting Hydrogen to the Gigaton Scale

Due to its ability to perform clean, efficient processes, hydrogen has long been promoted as the energy carrier of the future, but recent activity and advances suggest a tipping point has been reached as hydrogen is now being recognized by much of the world for its unique capabilities to strongly support global efforts in achieving climate neutrality. The coming decades will require a massive increase in the amount of hydrogen used in the energy system as well as a transition from largely thermochemical to predominantly electrochemical processes involving hydrogen. For this to happen, hydrogen will need to globally approach the gigaton-scale on an annual basis. Thus, before hydrogen can fully achieve its potential, challenges that need to be addressed include achieving scale and further research and development (R&D) advances.

climate neutrality↗

DOE OSTI2024

Optimizing Direct Air Capture Solvents to Minimize Energy Consumption of CO 2 Release in a Carbonate Electrolyzer

Addressing climate change by carbon management is critical to achieving the goal of net zero carbon emissions by 2050. In this work, we examined the electrochemically-driven recovery of CO 2 during alkaline solvent regeneration for solvent-based direct air capture. A mathematical model was developed by incorporating carbonate chemistry with water electrolysis to predict the energy consumption per unit of CO 2 released. The predicted results were consistent with the experimental data, in which the experimental work was achieved by characterizing alkalinity and carbon loading values of solvent collected from a flow carbonate electrolyzer. Through this study, we learned that minimizing the energy expended on CO 2 release can be achieved by using an anolyte with a lower alkalinity, increasing the electric charge input to the electrolyzer, and reducing the ohmic resistance of the electrolyzer. Furthermore, using a supporting electrolyte, e.g., Na 2 SO 4 in the present work, effectively compensates for the higher ohmic resistance from using an anolyte with a lower alkalinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Preparing MPICH for exascale

The advent of exascale supercomputers heralds a new era of scientific discovery, yet it introduces significant architectural challenges that must be overcome for MPI applications to fully exploit its potential. Among these challenges is the adoption of heterogeneous architectures, particularly the integration of GPUs to accelerate computation. Additionally, the complexity of multithreaded programming models has also become a critical factor in achieving performance at scale. The efficient utilization of hardware acceleration for communication, provided by modern NICs, is also essential for achieving low latency and high throughput communication in such complex systems. In response to these challenges, the MPICH library, a high-performance and widely used Message Passing Interface (MPI) implementation, has undergone significant enhancements. Here, this paper presents four major contributions that prepare MPICH for the exascale transition. First, we describe a lightweight communication stack that leverages the advanced features of modern NICs to maximize hardware acceleration. Second, our work showcases a highly scalable multithreaded communication model that addresses the complexities of concurrent environments. Third, we introduce GPU-aware communication capabilities that optimize data movement in GPU-integrated systems. Finally, we present a new datatype engine aimed at accelerating the use of MPI derived datatypes on GPUs. These improvements in the MPICH library not only address the immediate needs of exascale computing architectures but also set a foundation for exploiting future innovations in high-performance computing. By embracing these new designs and approaches, MPICH-derived libraries from HPE Cray and Intel were able to achieve real exascale performance on OLCF Frontier and ALCF Aurora respectively.

Guo, Yanfei [Argonne National Laboratory (ANL), Ar↗

DOE OSTI2019

The use of partial fuel stratification to enable stable ultra-lean deflagration-based Spark-Ignition engine operation with controlled end-gas autoignition of gasoline and E85

Lean operation of Spark-Ignition engines can provide higher thermal efficiency compared to standard stoichiometric operation. However, for a homogeneous lean mixture, the associated reduction of flame speeds becomes an important issue from the perspective of robust ignition and fast flame spread throughout the charge. This study is focused on the use of a lean partial fuel stratification strategy that can stabilize the deflagration, while sufficiently fast combustion is ensured via the use of end-gas autoignition. The engine has a spray-guided Direct-Injection Spark-Ignition combustion system and was fueled with either a high-octane certification gasoline or E85. Partial fuel stratification was achieved using several fuel injections during the intake stroke in combination with a small pilot-injection concurrent with the Spark-Ignition. The results reveal that partial fuel stratification enables very stable combustion, offering higher thermal efficiency for parts of the load range in comparison to well-mixed lean and stoichiometric combustion. The heat release and flame imaging demonstrate that the combustion often has three distinct stages. The combustion of the pilot-injected fuel, ignited by the normal spark, acts as a “super igniter,” ensuring a very repeatable initiation of combustion, and flame incandescence reveals locally rich conditions. The second stage is mainly composed of blue flame propagation in a well-mixed lean mixture. The third stage is the compression autoignition of a well-mixed and typically very lean end-gas. The end-gas autoignition is critical for achieving high combustion efficiency, high thermal efficiency, and stable combustion. Partial fuel stratification enables very effective combustion-phasing control, which is critical for controlling the occurrence and intensity of end-gas autoignition. Comparing the gasoline and E85 fuels, it is noted that achieving end-gas autoignition for the higher octane E85 requires a more aggressive compression of the end-gas via the use of a more advanced combustion phasing or higher intake-air temperature.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Development of prechamber enabled mixing-controlled combustion strategy for ultra-low methane emissions from lean burn natural gas engines

This numerical study explores the optimization of Prechamber Enabled Mixing-Controlled Combustion (PC-MCC) using natural gas in heavy-duty engines, aiming to enhance combustion efficiency to minimize methane slip and NOx emissions. The approach involves a prechamber ignition system, distinct from conventional spark ignition (SI) systems, to initiate combustion of direct injected natural gas. By leveraging the robust ignition characteristics of the prechamber, the PC-MCC method demonstrates significant potential in achieving efficient combustion akin to diesel engines but with lower greenhouse gas emissions. The research evaluates the effects of various geometric and operational parameters on the combustion process and emissions, including prechamber volume, nozzle diameter, direct injector (DI) geometry, and engine operating strategies. Computational Fluid Dynamics (CFD) simulations are utilized, focusing on a heavy-duty, single-cylinder engine modeled after the Caterpillar C9.3B engine. Key findings indicate that a prechamber volume of 3 cc, coupled with a nozzle diameter of 2.75 mm for two prechamber holes, strikes an optimal balance between combustion efficiency and emissions reduction. This configuration ensures robust combustion across a range of operating conditions while maintaining methane slip within targeted limits. Further investigation into DI geometry shows the significance of the injector umbrella angle and nozzle diameter in shaping the fuel-air mixing and combustion dynamics. An umbrella angle of 130° and a nozzle diameter of 300 microns are identified as optimal, promoting rapid and efficient combustion with minimized methane and NOx emissions. The study also investigates the impact of injection timing and pressure, highlighting their roles in controlling combustion timing and influencing emissions levels. Advanced injection timing is found to be crucial in achieving the desired low methane slip, whereas retarded injection timing assists to reduce NOx emissions while having a slight increase in methane emissions. Operating strategies incorporating various levels of Exhaust Gas Recirculation (EGR) are assessed for their effectiveness in further reducing emissions. The research demonstrates that a judicious combination of internal hot EGR and careful calibration of DI pressure and SOI timing can achieve significant reductions in NOx emissions while keeping methane slip under control. Specifically, an internal EGR level of 15%–25%, combined with DI pressures of 200–300 bar and injection timings at or after top dead center, is recommended. These findings contribute valuable insights into the development of advanced combustion techniques for natural gas engines, offering a viable pathway to reduce methane slip without compromising engine efficiency or performance. The PC-MCC system presents a promising solution for the future of heavy-duty natural gas engine technology to reduce methane emissions.

Nsaif, Osama↗

DOE OSTI2025

Data for "Sustainable Potassium Sorbate Production from Triacetic Acid Lactone in Food-Grade Solvents"

This study advances the production of potassium sorbate (KS) from triacetic acid lactone (TAL) utilizing food-grade solvents, ethanol (EtOH) and isopropyl alcohol (IPA). We have previously demonstrated the route to produce KS from TAL in tetrahydrofuran (THF) as the main solvent, but the use of THF is associated with environmental and health risks especially for food applications. The process employs a catalytic approach in food-grade solvents and includes three main steps: hydrogenation, etherification and hydrolysis, and ring-opening hydrolysis to produce KS from TAL. In the synthesis of KS from TAL, the use of IPA leads to higher yields and reduced reaction times compared to EtOH. As a result, the overall reaction time in IPA was reduced to 35.7 h, compared to 42.1 h in our previous study using THF and EtOH, while achieving a comparable KS yield of 84% from TAL. The synthesized KS exhibits a trans-2, trans-4 geometrical configuration, identical to that of commercially available KS. Through techno-economic analysis (TEA) and life cycle assessment (LCA), we estimated full-scale production of KS from sugarcane with the developed process in IPA could achieve a minimum product selling price (MPSP) of $8.27 per kg with a range of $7.06–10.16 per kg [5th–95th percentiles from 6000 Monte Carlo simulations] and a carbon intensity (CI) of 13.7 [9.6–18.6] kg CO2-eq per kg. This study highlights the synthesis of KS from TAL using food-grade solvents, demonstrating improved economic viability and environmental sustainability compared to our previous research (MPSP of $9.68 per kg [$8.47–11.45 per kg] and CI of 16.2 [12.0–21.2] kg CO2-eq per kg), as the total required reaction decreases while achieving the comparable overall yield of KS from TAL.

bioproducts↗

DOE OSTI2025

Data for Production of a δ-Lactam from Glucose through Integrating Biological and Chemical Catalysis

We present a new strategy for the production of a δ-lactam from glucose that integrates biological production of triacetic acid lactone (TAL, 4-hydroxy-6-methyl-2H-2-one) with catalytic transformation of TAL into 6-methylpiperidin-2-one (MPO) through metabolic engineering, isomerization, amination, and catalytic hydrogenation/hydrogenolysis. We developed a sustainable and antibiotic-free fed-batch fermentation using genetically modified Rhodotorula toruloides IFO0880. This process achieved a yield of 2-hydroxy-6-methyl-4H-pyran-4-one (2H4P) at 0.05 g/g of glucose, corresponding to a 9.9 g/L titer. By adjusting the pH of the fermentation broth to 2, 2H4P was quantitatively converted into TAL. The TAL in the fermentation broth was directly converted by aminolysis into 4-hydroxy-6-methylpyridin-2(1H)-one (HMPO), which achieved an 18.5% yield with 94.3% purity. The HMPO yield was lower in the fermentation broth than in a clean feedstock (32.2%), suggesting that the biological impurities are inhibitors in this reaction. Further investigation revealed that lower pH levels and reduced TAL concentrations in the fermentation broth significantly decreased HMPO yields. Subsequently, the precipitated HMPO was filtered and dried and then subjected to the final catalytic conversion in H2O solvent, achieving a MPO yield of 91.8%. This integrated approach demonstrated the direct use of TAL in the filtered aqueous fermentation broth without the need to isolate TAL.

Catalysis↗