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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 289 records · Page 16

Field Testing of an Affordable Zero-Liquid-Discharge Arsenic-Removal Technology for a Small-Community Drinking Water System in Rural California

Arsenic contamination in groundwater threatens public health, particularly in small, low-income communities lacking affordable treatment solutions. This study investigated the field implementation of novel air cathode assisted iron electrocoagulation (ACAIE) technology for arsenic removal in Allensworth, California, where groundwater arsenic concentrations exceeded 250 µg/L. Over four months, a pilot-scale ACAIE system, operating at 600 L/h, consistently reduced arsenic levels to below the EPA’s maximum contaminant level of 10 µg/L. Laboratory experiments informed the optimization of charge dosage and flow rates, which were validated during field testing of the ACAIE 600 L/h system. The in-situ generation of hydrogen peroxide at the cathode speeded up the reaction kinetics, ensuring high arsenic removal efficiency while allowing high throughput, even with a compact reactor size. An economic analysis demonstrated a treatment cost of USD 0.02/L excluding labor, highlighting the system’s affordability compared to conventional methods. Adding labor costs increased the treatment cost to USD 0.09/L. The regeneration of air cathodes extended their operational life, addressing a key maintenance challenge, thus reducing the costs slightly. Intermittent challenges were encountered with filtration and secondary contaminant removal; these issues highlight opportunities for further operational improvements. Despite these challenges, ACAIE’s low operational complexity, scalability, and cost-effectiveness make it a promising solution for underserved small communities. These findings provide critical insights into deploying sustainable arsenic remediation technologies that are tailored to the needs of rural, low-resource communities.

Bandaru, Siva R S↗

Aircraft Configuration and Flight Crew Compliance with Procedures While Conducting Flight Deck Based Interval Management (FIM) Operations

Flight deck based Interval Management (FIM) applications using ADS-B are being developed to improve both the safety and capacity of the National Airspace System (NAS). FIM is expected to improve the safety and efficiency of the NAS by giving pilots the technology and procedures to precisely achieve an interval behind the preceding aircraft by a specific point. Concurrently but independently, Optimized Profile Descents (OPD) are being developed to help reduce fuel consumption and noise, however, the range of speeds available when flying an OPD results in a decrease in the delivery precision of aircraft to the runway. This requires the addition of a spacing buffer between aircraft, reducing system throughput. FIM addresses this problem by providing pilots with speed guidance to achieve a precise interval behind another aircraft, even while flying optimized descents. The Interval Management with Spacing to Parallel Dependent Runways (IMSPiDR) human-in-the-loop experiment employed 24 commercial pilots to explore the use of FIM equipment to conduct spacing operations behind two aircraft arriving to parallel runways, while flying an OPD during high-density operations. This paper describes the impact of variations in pilot operations; in particular configuring the aircraft, their compliance with FIM operating procedures, and their response to changes of the FIM speed. An example of the displayed FIM speeds used incorrectly by a pilot is also discussed. Finally, this paper examines the relationship between achieving airline operational goals for individual aircraft and the need for ATC to deliver aircraft to the runway with greater precision. The results show that aircraft can fly an OPD and conduct FIM operations to dependent parallel runways, enabling operational goals to be achieved efficiently while maintaining system throughput.

Shay, Rick↗

A Simple and Flexible Infusion Platform for Automated Native Mass Spectrometry Analysis

High throughput native mass spectrometry analysis of proteins and protein complexes has been enabled by recent development of infusion and liquid chromatography (LC) systems, which often include complete LC pumps without fully utilizing their gradient flows. We demonstrated a lower-cost infusion cart for native mass spectrometry applications using a single isocratic solvent pump that can operate at both nano- and high-flow configurations (0.05-150 $μ$L/min) for both infusion and online buffer exchange experiments. In conclusion, the platform is controlled via open-source software and can potentially be expanded for customized experimental designs, offering a lower cost alternative to laboratories with limited budgets and/or needs in student training.

47 OTHER INSTRUMENTATION↗

Wedge-Shaped Hopper Design for Milled Woody Biomass Flow

The bioenergy industry has been challenged by unstable flow and transport of milled biomass in material handling operations. Handling issues such as hopper clogging and auger jamming are attributed to knowledge gaps between existing handling units designed for bulk solids and their suitability for milled biomass with high compressibility. This work investigates various flow behaviors of granular woody biomass in wedge-shaped hoppers. Herein, hopper flow physical experiments and numerical simulations are conducted to study the influence of the critical material attributes and critical processing parameters on the flow pattern, arching, and throughput. The results show that (1) the preferred flow pattern, mass flow, can be achieved by controlling the material’s internal friction angle, hopper inclination, and hopper wall friction; (2) hopper arching, governed by the competing gravity-driven force against flow resistance from material internal friction and material–wall friction, can be controlled by the hopper wall friction angle and the inclination angle; and (3) flow throughput can be accurately estimated from our empirical equation with inputs of hopper outlet geometry and particle-scale to bulk-scale material attributes. This study elucidates woody biomass flow physics and provides guidance for industrial equipment design.

09 BIOMASS FUELS↗

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗

waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data

Error-bounded lossy compression is critical to the success of extreme-scale scientific research because of ever-increasing volumes of data produced by today's high-performance computing (HPC) applications. Not only can error-controlled lossy compressors significantly reduce the I/O and storage burden but they can retain high data fidelity for post analysis. Existing state-of-the-art lossy compressors, however, generally suffer from relatively low compression and decompression throughput (up to hundreds of megabytes per second on a single CPU core), which considerably restrict the adoption of lossy compression by many HPC applications especially those with a fairly high data production rate. In this paper, we propose a highly efficient lossy compression approach based on field programmable gate arrays (FPGAs) under the state-of-the-art lossy compression model SZ. Our contributions are fourfold. (1) We adopt a wavefront memory layout to alleviate the data dependency during the prediction for higher-dimensional predictors, such as the Lorenzo predictor. (2) We propose a co-design framework named WAVESZ based on the wavefront memory layout and the characteristics of SZ algorithm and carefully implement it by using high-level synthesis. (3) We propose a hardware-algorithm co-optimization method to improve the performance. (4) We evaluate our proposed WAVESZ on three real-world HPC simulation datasets from the Scientific Data Reduction Benchmarks and compare it with other state-of-the-art methods on both CPUs and FPGAs. Experiments show that our WAVESZ can improve SZ's compression throughput by 6.9x similar to 8.7x over the production version running on a state-of-the-art CPU and improve the compression ratio and throughput by 2.1x and 5.8x on average, respectively, respectively, compared with the state-of-the-art FPGA design.

Compression Ratio↗

Improved node culture methods for rapid vegetative propagation of switchgrass (Panicum virgatum L.)

Abstract Background Switchgrass ( Panicum virgatum L.) is an important bioenergy and forage crop. The outcrossing nature of switchgrass makes it infeasible to maintain a genotype through sexual propagation. Current asexual propagation protocols in switchgrass have various limitations. An easy and highly-efficient vegetative propagation method is needed to propagate large natural collections of switchgrass genotypes for genome-wide association studies (GWAS). Results Micropropagation by node culture was found to be a rapid method for vegetative propagation of switchgrass. Bacterial and fungal contamination during node culture is a major cause for cultural failure. Adding the biocide, Plant Preservative Mixture (PPM, 0.2%), and the fungicide, Benomyl (5 mg/l), in the incubation solution after surface sterilization and in the culture medium significantly decreased bacterial and fungal contamination. In addition, “shoot trimming” before subculture had a positive effect on shoot multiplication for most genotypes tested. Using the optimized node culture procedure, we successfully propagated 330 genotypes from a switchgrass GWAS panel in three separate experiments. Large variations in shoot induction efficiency and shoot growth were observed among genotypes. Separately, we developed an in planta node culture method by stimulating the growth of aerial axillary buds into shoots directly on the parent plants, through which rooted plants can be generated within 6 weeks. By circumventing the tissue culture step and avoiding application of exterior hormones, the in planta node culture method is labor- and cost-efficient, easy to master, and has a high success rate. Plants generated by the in planta node culture method are similar to seedlings and can be used directly for various experiments. Conclusions In this study, we optimized a switchgrass node culture protocol by minimizing bacterial and fungal contamination and increasing shoot multiplication. With this improved protocol, we successfully propagated three quarters of the genotypes in a diverse switchgrass GWAS panel. Furthermore, we established a novel and high-throughput in planta node culture method. Together, these methods provide better options for researchers to accelerate vegetative propagation of switchgrass.

Wang, Yongqin↗

Evaluation of Flight Deck-Based Interval Management Crew Procedure Feasibility

Air traffic demand is predicted to increase over the next 20 years, creating a need for new technologies and procedures to support this growth in a safe and efficient manner. The National Aeronautics and Space Administration's (NASA) Air Traffic Management Technology Demonstration - 1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The integration of these technologies will increase throughput, reduce delay, conserve fuel, and minimize environmental impacts. The ground-based tools include Traffic Management Advisor with Terminal Metering for precise time-based scheduling and Controller Managed Spacing decision support tools for better managing aircraft delay with speed control. The core airborne technology in ATD-1 is Flight deck-based Interval Management (FIM). FIM tools provide pilots with speed commands calculated using information from Automatic Dependent Surveillance - Broadcast. The precise merging and spacing enabled by FIM avionics and flight crew procedures will reduce excess spacing buffers and result in higher terminal throughput. This paper describes a human-in-the-loop experiment designed to assess the acceptability and feasibility of the ATD-1 procedures used in a voice communications environment. This experiment utilized the ATD-1 integrated system of ground-based and airborne technologies. Pilot participants flew a high-fidelity fixed base simulator equipped with an airborne spacing algorithm and a FIM crew interface. Experiment scenarios involved multiple air traffic flows into the Dallas-Fort Worth Terminal Radar Control airspace. Results indicate that the proposed procedures were feasible for use by flight crews in a voice communications environment. The delivery accuracy at the achieve-by point was within +/- five seconds and the delivery precision was less than five seconds. Furthermore, FIM speed commands occurred at a rate of less than one per minute, and pilots found the frequency of the speed commands to be acceptable at all times throughout the experiment scenarios.

Wilson, Sara R.↗

High-throughput validation of phase formability and simulation accuracy of Cantor alloys

High-throughput methods enable accelerated discovery of novel materials in complex systems such as high-entropy alloys, which exhibit intricate phase stability across vast compositional spaces. Computational approaches, including Density Functional Theory (DFT) and calculation of phase diagrams (CALPHAD), facilitate screening of phase formability as a function of composition and temperature. However, the integration of computational predictions with experimental validation remains challenging in high-throughput studies. In this work, we introduce a quantitative confidence metric to assess the agreement between predictions and experimental observations, providing a quantitative measure of the confidence of machine learning models trained on either DFT or CALPHAD input in accounting for experimental evidence. The experimental dataset was generated via high-throughput in-situ synchrotron X-ray diffraction on compositionally varied FeNiMnCr alloy libraries, heated from room temperature to ~1000 °C. Agreement between the observed and predicted phases was evaluated using either temperature-independent phase classification or a model that incorporates a temperature-dependent probability of phase formation. This integrated approach demonstrates where strong overall agreement between computation and experiment exists, while also identifying key discrepancies, particularly in FCC/BCC predictions at Mn-rich regions to inform future model refinement.

36 - MATERIALS SCIENCE↗

Permanent Magnets Featuring Heavy Main Group Elements for Magnetic Anisotropy

Permanent magnets are the functional component of electric motors and generators found in numerous renewable energy applications. To improve energy conversion in such applications, we require fundamentally new magnets that generate higher magnetic flux per volume while retaining the properties conferred by rare-earth elements incorporated into current technologies. We hypothesize that by engendering a covalent interaction between two elements, we can access a new regime of magnetic materials where the two components of a magnetic moment—spin and orbital angular momentum—come from two separate atoms to form a complete magnetic moment. Our previous research utilized high-pressure conditions to discover two new candidate materials ideal for assessing this hypothesis. The first material, FeBi 2 , enables the study of an unprecedented solid state metal-metal bonding interaction. The second, MnBi 2 represents the second member of the promising Mn–Bi family known for its magnetic properties. Importantly, MnBi 2 is isostructural to FeBi 2 . Together these chemically simple but magnetically rich materials provide an elegant platform for elucidating fundamental design principals of magnetic anisotropy while inspiring the synthesis of new magnetic materials. More generally, solid-state chemistry remains a synthetic black box. To fully harness the potential of such new materials, it is vital to create a window into both the structure and the properties of our high-pressure materials. One missing area of importance to energy science is high-pressure magnetometry. To this end, we assessed the magnetic structure of these materials through two objectives: (1) we performed magnetometry measurements at high-pressures, including performing high-pressure X-ray Magnetic Circular Dichroism (XMCD) experiments on these materials that are only synthesized at high-pressure and cannot be recovered to ambient conditions and (2) we targeted the recovery of these materials using dynamic compression approaches, starting with laser shock techniques. Future directions include expanding our focus to ternary phase space, employing high-throughput computational approaches to direct our search for magnetic materials across the Periodic Table. This award was originated at Northwestern, and reopened as a new grant at MIT. This is the close out for Northwestern.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fuel Specification for Uranium Monocarbide FAST Fuel Specimens

This specification outlines the fabrication requirements for kernel compact uranium monocarbide (UC) fuel to be fabricated at General Atomics (GA) and is already issued in EDMS and is going thru LRS so that it can be shared with the Vendor. The UC fuel will be irradiated in the Advanced Test Reactor (ATR) using the Irradiation System for High-Throughput Acquisition (ISHA-1). The primary objective of the ISHA-1 capsule design is to deliver to Idaho National Lab (INL) a semi-universal drop-in capsule that can facilitate the irradiation of both fissile and structural materials in a variety of ATR positions. This irradiation experiment will support the need for development of Accelerated Fuel Qualification (AFQ) methods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Miniaturized Ignition Screening Rapid Compression Machine for probing low-to-intermediate temperature chemistry

With an objective to achieve net-zero emissions by no later than 2050, biofuels hold enormous potential as sustainable, renewable fuels that can be produced on a large scale. However, fuels of a similar type, derived from limited feedstock batch can dramatically vary in terms of their chemical structures and compositions, causing significant differences in physicochemical properties mainly influencing ignition-relevant properties. Rigorous prescreening and testing efforts are involved to evaluate fuels to comply with engines equipped with advanced combustion modes. The testing of some of these fuels implies low quantity fuel samples, access to relevant temperature and pressure conditions, high reproducibility, and a high throughput rate. In light of these considerations, a Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC). Some design features include a smaller bellows-actuated driver section compared to other RCM designs, an adjustable brake section, and full optical access. The setup is designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions are relevant to low-to-intermediate temperature auto-ignition and can generate data for developing relevant chemical kinetics models or ignition maps. A brief insight into MISR design and its operating mechanism is shown. Also, to demonstrate the performance characteristics of the MISR, Ignition Delay (I.D) experiments for ethanol fuel at different equivalence ratios (Φ) are discussed in the context of plans with additional optical diagnostics, high-speed imaging, and gas sampling experiments.

Tomar, Mukul↗

Ingrained: An Automated Framework for Fusing Atomic-Scale Image Simulations into Experiments

To fully leverage the power of image simulation to corroborate and explain patterns and structures in atomic resolution microscopy, an initial correspondence between the simulation and experimental image must be established at the outset of further high accuracy simulations or calculations. Furthermore, if simulation is to be used in context of highly automated processes or high-throughput optimization, the process of finding this correspondence itself must be automated. In this work, "ingrained," an open-source automation framework which solves for this correspondence and fuses atomic resolution image simulations into the experimental images to which they correspond, is introduced. Here, the overall "ingrained" workflow, focusing on its application to interface structure approximations, and the development of an experimentally rationalized forward model for scanning tunneling microscopy simulation are described.

36 MATERIALS SCIENCE↗

One hundred years into the study of ecotypes, new advances are being made through large-scale field experiments in perennial plant systems

A hundred years after Turesson first clearly described how locally adaptive variation is distributed within species, plant biologists are making major breakthroughs in our understanding of mechanisms underlying adaptation from local populations to the scale of continents. Although the genetics of local adaptation has typically been studied in smaller reciprocal transplant experiments, here it is being evaluated with whole genomes in large-scale networks of common garden experiments with perennial switchgrass and poplar trees. These studies support the hypothesis that a complex combination of loci, both with and without adaptive trade-offs, underlies local adaptation and that hybridization and adaptive introgression play a key role in the evolution of these species. Future studies incorporating high-throughput phenotyping, gene expression, and modeling will be used to predict responses of these species to climate change.

Trade-off↗

Observations on Cost Modeling and Performance Measurement of Long Term Archives

This paper describes a prototype suite of Excel-based tools that could be used for estimating lifecycle costs for newly planned or modified long-term archival facilities. These tools may also prove valuable for monitoring the long-term performance of such facilities once operational. Cost estimation is by analogy, using statistical curve-fitting techniques across a database of comparable data activities. The database currently includes 29 operational data centers ranging from small (2 FTEs) to large (66 FTEs), and is readily expandable to include additional activities specifically involving data preservation and added value. Each comparable data center is described in terms of its staffing, throughput workload, archival and distribution requirements, levels of user service, overall complexity, degree of automation, and other data, comprising 94 distinct descriptors in all. The descriptors were developed by normalizing heterogeneous data from the various centers and mapping them into an Excel framework consistent with the OAIS reference model. A user-friendly tool is provided for generating input to and updating the comparables database. This tool can also be used to benchmark the performance (in terms of cost versus throughput) of an operational data center, and to update the staffing, cost and workload data on a periodic basis. The comparables database could thus provide a history of staffing and throughput over time, as a means of performance monitoring and providing feedback for continuous improvement. Ancillary tools are also provided for performing "what-if' cost exercises for planning purposes, and for graphical display of data and results. We provide a high-level description of the tools; present our experiences and observations on gathering the information and maintaining the database; and discuss how this tool set might be applied to long term archives.

Fontaine, Kathy↗

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A coded aperture with sub-mean-free-path thickness for implosion geometry imaging on ICF and IFE experiments

Inertial confinement fusion and inertial fusion energy experiments diagnose the geometry of the fusion region through imaging of the neutrons released through fusion reactions. Pinhole arrays typically used for such imaging require thick substrates to obtain high contrast along with a small pinhole diameter to obtain high resolution capability, resulting in pinholes that have large aspect ratios. This leads to expensive pinhole arrays that have small solid angles and are difficult to align. Here, we propose a coded aperture with scatter and partial attenuation (CASPA) for fusion neutron imaging that relaxes the thick substrate requirement for good image contrast. These coded apertures are expected to scale to larger solid angles and are easier to align without sacrificing imaging resolution or throughput. We use Monte Carlo simulations (Geant4) to explore a coded aperture design to measure neutron implosion asymmetries on fusion experiments at the National Ignition Facility (NIF) and discuss the viability of this technique, matching the current nominal resolution of 10 µm. The results show that a 10 mm thick tungsten CASPA can image NIF implosions with neutron yields above 10 14 with quality comparable to unprocessed data from a current NIF neutron imaging aperture. Furthermore, this CASPA substrate is 20 times thinner than the current aperture arrays for fusion neutron imaging and less than one mean free-path of 14.1 MeV neutrons through the substrate. Since the resolution, solid angle, and throughput are decoupled in coded aperture imaging, the resolution and solid angle achievable with future designs will be limited primarily by manufacturing capability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗