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

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Direct Measurements of Dimethyl Sulfide Oxidation Chemistry: Uncovering the Primary Pathways from Gas Phase to Sulfate Aerosols

We report experimental measurements of dimethyl sulfide oxidation, focusing on a major chemical intermediate, hydroperoxymethyl thioformate (HPMTF). The (photo)chemistry and transport properties of HPMTF, which are critical to accurate modeling of tropospheric sulfur, are not known, partly because current analytical methods are not optimized for elusive chemical intermediates. We investigated dimethyl sulfide oxidation using a custom time-resolved photoionization mass spectrometer, interfaced with pulsed laser photolysis, continuous photolysis, and liquid droplet reactors. We detected and characterized HPMTF (along with other reaction intermediates), quantified its yield, and measured its formation rate coefficient. We also developed a clean, intense, online HPMTF source, suitable for further experimental investigations. Lastly, we measured the mass accommodation coefficient of HPMTF on water droplets – a critical quantity for modeling its atmospheric partitioning between the gas and condensed phases. The experimental platform we developed here enables the exploration of other critical elusive reaction intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations

Combined quantum mechanical and molecular mechanical (QM/MM) methods play an important role in multiscale modeling and simulations. QMMM 2023 is a general-purpose program for single-point calculations, geometry optimizations, transition-state optimizations, and molecular dynamics (MD) at the QM/MM level. It calls a QM package and an MM package to perform the required single-level calculations and combines them into a QM/MM energy by a variety of schemes. QMMM 2023 supports GAMESS-US, Gaussian, and ORCA as QM packages and Tinker as the MM package. Four types of treatments are available for embedding the QM subsystem in the MM environment: mechanical embedding with gas-phase calculations of the QM region, electronic embedding that allows polarization of the QM region by the MM environment, polarizable embedding for mutual polarization of the QM and MM regions, and flexible embedding for both mutual polarization and partial charge transfer between the QM and MM regions. Boundaries between QM and MM regions that pass through covalent bonds can be treated by several methods, including the redistributed charge (RC) scheme, redistributed charge and dipole (RCD) scheme, balanced-RC scheme, balanced-RCD scheme, screened charge scheme that takes account of charge penetration effects, and smeared charge scheme that delocalizes the MM charges near the QM–MM boundary. Geometry optimization can be done using the optimizer implemented in QMMM 2023 or the Berny optimizer in Gaussian through external calls to Gaussian. Molecular dynamics simulations can be performed at the pure-MM level, pure-QM level, fixed-partitioning QM/MM level, and adaptive-partitioning QM/MM level. As a result, the adaptive-partitioning treatments permit on-the-fly relocation of the QM–MM boundary by dynamically reclassifying atoms or groups into the QM or MM subsystems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantum Tensor-Product Decomposition from Choi-State Tomography

The Schmidt decomposition is the go-to tool for measuring bipartite entanglement of pure quantum states. Similarly, it is possible to study the entangling features of a quantum operation using its operator-Schmidt or tensor-product decomposition. While quantum technological implementations of the former are thoroughly studied, entangling properties on the operator level are harder to extract in the quantum computational framework because of the exponential nature of sample complexity. Here, we present an algorithm for unbalanced partitions into a small subsystem and a large one (the environment) to compute the tensor-product decomposition of a unitary the effect of which on the small subsystem is captured in classical memory, while the effect on the environment is accessible as a quantum resource. This quantum algorithm may be used to make predictions about operator nonlocality and effective open quantum dynamics on a subsystem, as well as for finding low-rank approximations and low-depth compilations of quantum circuit unitaries. We demonstrate the method and its applications on a time-evolution unitary of an isotropic Heisenberg model in two dimensions. Published by the American Physical Society 2024

Mansuroglu, Refik (ORCID:000000017352513X)↗
DOE OSTI2020

FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters

In this paper, we propose a framework called FPDeep, which uses a hybrid of model and layer paral- lelism to configure distributed reconfigurable clusters to train DNNs. This approach has numerous benefits. First, the design does not suffer from batch size growth. Second, novel workload and weight partitioning leads to balanced loads of both among nodes. And third, the entire system is fine-grained pipeline. This leads to high parallelism and utilization and also minimizes the time features need to be cached while waiting for back-propagation.

Wang, Tianqi↗
DOE OSTI2021

Nonequilibrium information entropy approach to ternary fission of actinides

Ternary fission of actinides probes the state of the nucleus at scission. Light clusters are produced in space and time very close to the scission point. Within the nonequilibrium statistical operator method, a generalized Gibbs distribution is constructed from the information given by the observed yields of isotopes. Using this relevant statistical operator, yields are calculated taking excited states and continuum correlations into account, in accordance with the virial expansion of the equation of state. Furthermore, clusters with mass number A≤10 are well described using the nonequilibrium generalizations of temperature and chemical potentials. Improving the virial expansion, in-medium effects may become of importance in determining the contribution of weakly bound states and continuum correlations to the intrinsic partition function. Yields of larger clusters, which fail to reach this quasiequilibrium form of the relevant distribution, are described by nucleation kinetics, and a saddle-to-scission relaxation time of about 7000 fm/c is inferred. Light-charged particle emission, described by reaction kinetics and virial expansions, may therefore be regarded as a very important tool to probe the nonequilibrium time evolution of actinide nuclei during fission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Fragme∩t: An Open‐Source Framework for Multiscale Quantum Chemistry Based on Fragmentation

Fragment-based quantum chemistry offers a means to circumvent the nonlinear computational scaling of conventional electronic structure calculations, by partitioning a large calculation into smaller subsystems then considering the many-body interactions between them. Variants of this approach have been used to parameterize classical force fields and machine learning potentials, applications that benefit from interoperability between quantum chemistry codes. However, there is a dearth of software that provides interoperability yet is purpose-built to handle the combinatorial complexity of fragment-based calculations. To fill this void we introduce “Fragme∩t”, an open-source software application that provides a tool for community validation of fragment-based methods, a platform for developing new approximations, and a framework for analyzing many-body interactions. Fragme∩t includes algorithms for automatic fragment generation and structure modification, and for distance- and energy-based screening of the requisite subsystems. Checkpointing, database management, and parallelization are handled internally and results are archived in a portable database. Interfaces to various quantum chemistry engines are easy to write and exist already for Q-Chem, PySCF, xTB, Orca, CP2K, MRCC, Psi4, NWChem, GAMESS, and MOPAC. Applications reported here demonstrate parallel efficiencies around 96% on more than 1000 processors but also showcase that the code can handle large-scale protein fragmentation using only workstation hardware, all with a codebase that is designed to be usable by non-experts. Fragme∩t conforms to modern software engineering best practices and is built upon well established technologies including Python, SQLite, and Ray. The source code is available under the Apache 2.0 license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantification of Metabolic Products from Microbial Hosts in Complex Media Using Optically Diffracting Hydrogels

In this work, we herein describe a highly versatile platform approach for the in situ and real-time screening of microbial biocatalysts for enhanced production of bioproducts using photonic crystal hydrogels. This approach was demonstrated by preparing optically diffracting films based on polymerized N-isopropylacrylamide that contracted in the presence of alcohols and organic acids. The hydrogel films were prepared in a microwell plate format, which allows for high-throughput screening, and characterized optically using a microwell plate reader. While demonstrating the ability to detect a broad range of relevant alcohols and organic acids, we showed that the response of the films correlated strongly with the octanol-water partition coefficient (log P) of the analyte. Differences in the secretion of ethanol and succinic acid from strains of Zymomonas mobilis and Actinobacillus succinogenes, respectively, were further detected via optical characterization of the films. These differences, which in some cases were as low as ~3 g/L, were confirmed by high-performance liquid chromatography, thereby demonstrating the sensitivity of this approach. Our findings highlight the potential utility of this multiplexed approach for the detection of small organic analytes in complex biological media, which overcomes a major challenge in conventional optical sensing methods.

09 BIOMASS FUELS↗
DOE OSTI2021

Dimensionality reduction of the many-body problem using coupled-cluster subsystem flow equations: classical and quantum computing perspective

We discuss reduced-scaling strategies employing recently introduced sub-system embedding sub-algebras coupled-cluster formalism (SES-CC) to describe many-body systems. These strategies utilize properties of the SES-CC formulations where the equations describing certain classes of sub- systems can be integrated into a computational flows composed coupled eigenvalue problems of reduced dimensionality. Additionally, these flows can be defined at the level of the CC Ansatz defined by selected classes of cluster amplitudes, which define the wave function ”memory” of possible partitionings of the many-body system into constituent sub-systems. One of the possible ways of solving these coupled problems is through implementing procedures, where the information is passed between the sub-systems in a self-consistent manner. As a special case, we consider local flow formulations where the so-called local character of correlation effects can be closely related to properties of sub-system embedding sub-algebras employing localized molecular basis. We also generalize flow equations to the time domain and to downfolding methods utilizing double exponential unitary CC Ansatz (DUCC), where reduced dimensionality of constituent sub-problems offer a possibility of efficient utilization of limited quantum resources in modeling realistic systems.

Electron correlation, quantum chemistry, quantum c↗
DOE OSTI2021

Electrochemical Manipulation and Radiolytic Evaluation of Organic Phase Neptunium

Presentation for Seed LDRD proposal presentation: This Seed LDRD research proposes to test an innovative approach to precisely control the oxidation state distribution of neptunium (Np) under used nuclear fuel (UNF) reprocessing conditions using novel electrochemical methods. Current UNF reprocessing technologies are not financially viable in the US, requiring significant scientific and technological innovation to improve cost efficiency. Reducing the number of process cycles is one avenue for increasing cost efficiency, of which resolving the challenge associated with isolating Np is critical. Under envisioned process conditions, Np is present in a mixture of extractable (Np(IV) and Np(VI)) and inextractable (Np(V)) oxidation states, the distribution of which is dependent on several factors, including ionizing radiation dose, that change throughout a reprocessing scheme. Consequently, Np unintentionally partitions into various UNF reprocessing phases and product streams, ultimately increasing the number of process cycles to isolate UNF components. Here, we propose to employ novel, high surface area, optically transparent, Ligand Modified tin-doped indium oxide Electrodes (LMES). These LMEs bind Np, and therefore enable concurrent generation and spectroscopic characterization of Np oxidation states in organic solutions. These proof-of-concept experiments will: (i) facilitate optimization of the proposed electrochemical system conditions for Np oxidation state manipulation; (ii) identify the accessible electrochemical window for Np complexes in the organic phase; (iii) report characteristic optical spectra for each accessible complexed Np oxidation state; and (iv) determine the lifetime and partitioning of a given atypical Np oxidation state in the organic phase in the presence and absence of ionizing radiation fields. The data gathered by this Seed LDRD will provide support for the design of an electrochemical process concept for the precise manipulation of Np oxidation states in UNF reprocessing solvent systems, with the intention of providing advanced control over Np mass transfer, and thus greater process efficiency and economy.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗
DOE OSTI2021

Sorption and electrokinetic properties of ASR product and C-S-H: A comparative modelling study

Alkali-silica reaction (ASR) is one of the most important concrete durability issues worldwide. ASR products formed at high temperature have a structure similar to the natural mineral shlykovite. Reactive Grand Canonical Simulations were used to investigate sorption of K{sup +}, Cl{sup −} and Ca{sup 2+} on C-S-H and ASR products at different pH (10.0 to 13.0) and pore water chemistry. Divalent ions can overcompensate for the negative surface charge, in particular for C-S-H, which leads to a co-adsorption of negative species such as Cl{sup −}. At high K/Ca in solution, monovalent K{sup +} can desorb calcium from C-S-H and shlykovite surface. The calculated Ca/K partition coefficient shows a higher affinity of ASR product for K{sup +}, while C-S-H favours Ca{sup 2+}. The uptake of K{sup +} by ASR products lowers the alkali concentration in the solution and could thus slow down the rate of ASR.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Systemwide Planning with a Branch-and-Price Algorithm for Pavement-Marking Assessment Data Collection via the Mobile Retroreflectivity Unit Routing Model

The visibility of pavement markings is one of the most critical factors for traffic safety, and a periodical assessment plan is crucial for maintaining this function. Traditional assessment methods, such as visual windshield surveys or manual testing using handheld devices, are unsafe, time-consuming, and labor-intensive. In recent years, transportation agencies have begun to adopt the use of mobile retroreflectivity units (MRUs) for condition assessment of pavement markings. MRUs, different from other manual methods, can be utilized to collect large-scale retroreflectivity data in an efficient manner. However, no relevant research has yet proposed a mathematical optimization model for arranging the evaluation schedule and paths of MRUs. This study aims to propose a MRU routing model, and an efficient solution methodology. A branch-and-price algorithm, including column generation and branch-and-bound, was implemented. Computational experiments have been conducted based on actual tasks from the Florida MRU program for validation. In conclusion, results show that the proposed solution methodology with a set partitioning model in this study not only finds the optimal solution for problems with tasks less than 60, but also effectively narrows the solution gap to be within 1.0% for problems with tasks less than 131.

42 ENGINEERING↗
DOE OSTI2024

Kinetic study of shock formation and particle acceleration in laser-driven quasi-parallel magnetized collisionless shocks

Quasi-parallel magnetized collisionless shocks are believed to be one of the most efficient accelerators in the universe. Compared to quasi-perpendicular shocks, quasi-parallel shocks are more difficult to form in the laboratory and to simulate because of their large spatial scales and long formation times. Our two-dimensional particle-in-cell simulations show that the early stages of quasi-parallel shock formation are achievable in experiments planned for the National Ignition Facility and that particles accelerated by diffusive shock acceleration (DSA) are expected to be observable in the experiment. Repetitive ion acceleration by crossings of the shock front, a key feature of DSA, is seen in the simulations. Other characteristic features of quasi-parallel shocks such as upstream wave excitation by energetic ions are also observed, and energy partition between the ions and the electrons in the downstream of the shock is briefly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Quantitative measurements of reactive oxygen species partitioning in electron transfer flavoenzyme magnetic field sensing

Biological magnetic field sensing that gives rise to physiological responses is of considerable importance in quantum biology. The radical pair mechanism (RPM) is a fundamental quantum process that can explain some of the observed biological magnetic effects. In magnetically sensitive radical pair (RP) reactions, coherent spin dynamics between singlet and triplet pairs are modulated by weak magnetic fields. The resulting singlet and triplet reaction products lead to distinct biological signaling channels and cellular outcomes. A prevalent RP in biology is between flavin semiquinone and superoxide (O 2 •–) in the biological activation of molecular oxygen. This RP can result in a partitioning of reactive oxygen species (ROS) products to form either O 2 •– or hydrogen peroxide (H 2 O 2 ). Here, we examine magnetic sensing of recombinant human electron transfer flavoenzyme (ETF) reoxidation by selectively measuring O 2 •– and H 2 O 2 product distributions. ROS partitioning was observed between two static magnetic fields at 20 nT and 50 μT, with a 13% decrease in H 2 O 2 singlet products and a 10% increase in O 2 •– triplet products relative to 50 µT. RPM product yields were calculated for a realistic flavin/superoxide RP across the range of static magnetic fields, in agreement with experimental results. For a triplet born RP, the RPM also predicts about three times more O 2 •– than H 2 O 2 , with experimental results exhibiting about four time more O 2 •– produced by ETF. The method presented here illustrates the potential of a novel magnetic flavoprotein biological sensor that is directly linked to mitochondria bioenergetics and can be used as a target to study cell physiology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Processing Particle Data Flows with SmartNICs

Many distributed applications implement complex data flows and need a flexible mechanism for routing data between producers and consumers. Recent advances in programmable network interface cards, or SmartNICs, represent an opportunity to offload data-flow tasks into the network fabric, thereby freeing the hosts to perform other work. System architects in this space face multiple questions about the best way to leverage SmartNICs as processing elements in data flows. In this paper, we advocate the use of Apache Arrow as a foundation for implementing data-flow tasks on SmartNICs. We report on our experiences adapting a partitioning algorithm for particle data to Apache Arrow and measure the on-card processing performance for the BlueField-2 SmartNIC. Our experiments confirm that the BlueField-2’s (de)compression hardware can have a significant impact on in-transit workflows where data must be unpacked, processed, and repacked.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Advanced mass balance characterization and fractionation of algal biomass composition

Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Participation Factor-Based Approach for Defining the EMT Model Boundary for Power System Simulations with Inverter-Based Resources

The increasing penetration of inverter-based resources (IBRs) introduces new challenges to power system simulations, particularly with the emergence of fast electromagnetic transient (EMT) dynamics and sub-synchronous oscillations (SSO) that require time-consuming EMT simulations. To reduce the time cost for simulating a large-scale power grid with IBRs, this paper proposes a novel participation factor-based approach for defining a critical zone for detailed EMT modeling and simulations, which includes the IBRs, synchronous generators, and the network components participating significantly in simulated contingencies. Both model-based and response-based methods are introduced for the estimation of participation factors (PFs). The case study on the 240-bus Western Electricity Coordinating Council (WECC) system demonstrates that the EMT zone determined by the proposed approach can effectively capture power system dynamics involving IBRs.

EMT simulation↗
DOE OSTI2024

Revisiting a Drag Partition Model For Canopy-Like Roughness Elements

Turbulent flows over a large surface area (S) covered by n obstacles experience an overall drag due to the presence of the ground and the protruding obstacles into the flow. The drag partition between the roughness obstacles and the ground is analyzed using an analytical model proposed by Raupach (Boundary-Layer Meteorol 60:375-395, 1992) and is hereafter referred to as R92. The R92 is based on the premise that the wake behind an isolated roughness element can be described by a shelter area A and a shelter volume V. The individual sizes of A and V without any interference from other obstacles can be determined from scaling analysis for the spread of wakes. To upscale from an individual roughness element to n/S elements where wakes may interact, R92 adopted a background stress re-normalizing instead of reducing A or V with each element addition. This work demonstrates that R92’s approach results in a linear background stress reduction in A and V only when the ratio of n/S is small, due to a low probability of wake interactions. This probabilistic nature suggests that up-scaling from individual to multiple roughness elements can be re-formulated using stochastic averaging methods proposed here. The two approaches are shown to recover R92 under plausible conditions. An alternative scaling for the shelter volume is also proposed here using thermodynamic arguments of work and dissipation though the final outcome remains similar to R92. Comparisons between R92 and available data spanning more than two decades after R92 on blocks and vegetation-like roughness elements confirm the practical utility of R92. The agreement between R92 and this updated databases of experiments and simulations confirm the potential use of R92 in large-scale models provided that the relevant parameters accommodate certain features of the roughness element type (cube versus vegetation-like) and, to a lesser extent, their configuration throughout S. Last, a comparison between R92 and models based on first-order closure principles with constant mixing length suggests that R92 can outperform such models when evaluated across a wide range of roughness densities.

canopy turbulence↗