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At least 541 records · Page 30

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NASA NTRS2018

Summary of the 2017 Blockage Test in the 10- by 10-Foot Supersonic Wind Tunnel

A limited blockage study was performed in December 2017 to explore exceeding the current published blockage curve for the NASA Glenn 10- by 10-Foot (10x10) Supersonic Wind Tunnel (SWT) at two discrete operating conditions. For the two points tested, the tunnel was found to start outside of the published starting limitations curve, above a certain threshold of Mach and stagnation pressure. Blockage theory was reviewed to further understand these results. In order to gain a firm understanding of the aerodynamic effects a more-detailed follow up blockage study is recommended.

Tunnel Start↗

DOE OSTI2024

The Phenix‐AlphaFold webservice: Enabling AlphaFold predictions for use in Phenix

Abstract Advances in machine learning have enabled sufficiently accurate predictions of protein structure to be used in macromolecular structure determination with crystallography and cryo‐electron microscopy data. The Phenix software suite has AlphaFold predictions integrated into an automated pipeline that can start with an amino acid sequence and data, and automatically perform model‐building and refinement to return a protein model fitted into the data. Due to the steep technical requirements of running AlphaFold efficiently, we have implemented a Phenix‐AlphaFold webservice that enables all Phenix users to run AlphaFold predictions remotely from the Phenix GUI starting with the official 1.21 release. This webservice will be improved based on how it is used by the research community and the future research directions for Phenix.

Poon, Billy K.↗

DOE OSTI2025

ChatPORT: Fine-Tuned LLM for Easy Code {PORT}ing

Fine-tuning existing LLMs for specialized tasks has become a very attractive alternative due to its low cost and quick development cycle. With many pre-trained LLMs available, it is an increasingly complex task to choose the correct model as the starting point or base model. In this work we discuss ChatPORT - a specialized fine-tuned LLM geared towards providing correctly translated codes from one programming model to another. We evaluate a number of base models and compare and contrast their features and characteristics that make them a viable starting point. In this paper, we focus on the OpenMP offload porting capabilities of ChatPORT. We build our training data using kernels from the Heterogeneous Computing Benchmarks (HeCBench) [12] and the OpenMP Validation and Verification suite [5] to fine-tune the base models. We then test the model using unseen kernels extracted from the HeCBench benchmark suite. Our results show that: (1) not all open LLMs geared towards HPC are aware of programming models like OpenMP, (2) although all base models benefit from fine-tuning they learn differently and produce different correctness rates, (3) depending on the memory size and compute resource available, different base models can be used for fine-tuning without significantly affecting the quality of transpiled code they generate, (4) fine-tuning improved the correctness rate of the LLM by an average of 43.2%, and (5) feedback-based training data further increased the correctness rate by an average of 6% over the LLMs tested.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗

DOE OSTI2024

Multistart algorithm for identifying all optima of nonconvex stochastic functions

Here, we propose a multistart algorithm to identify all local minima of a constrained, nonconvex stochastic optimization problem. The algorithm uniformly samples points in the domain and then starts a local stochastic optimization run from any point that is the "probabilistically best" point in its neighborhood. Under certain conditions, our algorithm is shown to asymptotically identify all local optima with high probability; this holds even though our algorithm is shown to almost surely start only finitely many local stochastic optimization runs. We demonstrate the performance of an implementation of our algorithm on nonconvex stochastic optimization problems, including identifying optimal variational parameters for the quantum approximate optimization algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Effect of bisphosphonate treatment on the oim mouse middle ear ossicles' structure, composition and hearing

Hearing loss is common in people with osteogenesis imperfecta (OI or brittle bone disease). Bisphosphonates are commonly used to treat long bone fragility in children with OI. However, its impact on the bone quality of the middle ear ossicles and hearing remains unknown. This study determines whether bisphosphonates treatment itself may contribute to hearing loss in OI by evaluating its effects in the oim/oim mouse model of severe OI having normal auditory function. Specifically, this study reports the effects of alendronate (ALN), a nitrogen-containing bisphosphonate, on ossicle morphology, porosity, and elemental composition in 14-week-old oim/oim mice treated weekly, starting at 2 weeks of age. The ossicles were examined using synchrotron microtomography and X-ray fluorescence microscopy (XFM). Hearing was assessed longitudinally until 26 weeks of age by determining auditory brainstem response (ABR) thresholds in another group of mice also treated weekly starting at 2 weeks of age. ALN treatment further reduces in size the already small oim/oim ossicles, specifically in female mice. Porosity, bone composition, and hearing function, however, were generally not affected by the ALN treatment. Furthermore, ALN does not prevent joint fusions, excessive bone formations, or enlarged joint spaces in WT or oim/oim experimental groups. One ALN-treated oim/oim mouse with a bone formation in the interior of the footplate, and one ALN-treated WT mouse with a fixed footplate had frequency-specific hearing loss. Since footplate abnormalities are not observed in PBS-treated mice in this study, it remains unclear whether ALN fails to prevent these changes or contributes to their development. Future studies should investigate the mechanisms of ossicular abnormalities and bisphosphonates modulatory role in the ossicles.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

DOE OSTI2024

Reactive Fe anode for electrolytic reduction of solid metal oxide in molten LiCl-Li 2 O

Iron metal was investigated for use as a consumable anode for electrolytic reduction of solid metal oxides in molten LiCl-Li 2 O (2.0 - 2.4 wt%). Tests were performed where the potential of Fe anodes was increased incrementally from 0.1 to 1.0 V (vs Ni/NiO). Oxide formation on the anode started at a potential of 0.4 V and was identified as FeO via X-ray diffraction. In the absence of a pre-formed oxide layer, severe attack of the anode started at a potential of 0.7 V and was accompanied by an increase in Fe concentration in the salt. When an oxide layer was allowed to form on the anode, the Fe concentration did not increase in the salt. O 2 was detected in the headspace gas at an anode potential of 1.0 V only when an oxide layer was present on the anode. Finally, the results of this study support the idea that an inexpensive sacrificial anode could be an ideal replacement for expensive Pt that is currently widely used for this process.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

DOE OSTI2025

A new synthetic method of [Ru(2,2′:6′,2″-terpyridine)(2,2′-bipyridine)Cl] + complexes using cis -[Ru(2,2′:6′,2″-terpyridine)(NCCH 3 ) 2 Cl] + as an intermediate and comparison to a method using [Ru(benzene)(2,2′-bipyridine)Cl] + intermediates

A new method of synthesizing [Ru(terpy)(bpy)Cl] + (terpy = 2,2′:6′,2″-terpyridine, bpy = 2,2′-bipyridine) complexes using the starting material cis-[Ru(terpy)(NCCH 3 ) 2 Cl](PF 6 ) is reported. The yields of four derivatives ([Ru(terpy)(NN)Cl](PF 6 ): NN = bpy, 1; 4,4′-(MeO) 2 bpy, 2; 4,4′-(CF 3 ) 2 bpy, 3; 2,2′-biquinoline, 4) with this method range from 58 to 94 % and are similar to or greater than a known reaction in which the starting material is [Ru(benzene)(NN)Cl](PF 6 ). However, the use of cis-[Ru(terpy)(NCCH 3 ) 2 Cl](PF 6 ) results in lower levels of homoleptic Ru byproducts in the synthesis of 1 as compared to the use of [Ru(benzene)(bpy)Cl](PF 6 ) as determined by 1 H NMR spectroscopy. In addition, a high-purity and gram-scale synthesis of cis-[Ru(terpy)(NCCH 3 ) 2 Cl](PF 6 ) that does not use column chromatography is reported, in contrast to the original synthesis disclosed in the literature.

Bipyridine↗

DOE OSTI2025

Free-spray characteristics and spray-wall interactions of methanol on a gasoline direct injector under flash-boiling and non-flash-boiling conditions

Methanol is considered a promising alternative fuel for internal combustion engines (ICEs) due to its high-octane number, fast laminar flame speed, and elevated latent heat of vaporization, all of which support higher compression ratios and improved thermal efficiency. However, its substantial latent heat of vaporization also poses cold-start challenges, such as misfire and fuel film deposition. This study aims to investigate methanol spray morphology and spray-wall interaction using the Spray M injector from the Engine Combustion Network within a constant-pressure flow vessel. A recently developed unified numerical framework capable of modeling both flash and non-flash boiling sprays is validated against experimental liquid volume fraction data acquired via 3-D computed tomography. Here, the results reveal that flash boiling significantly alters the spray morphology, leading to smaller droplets and spray collapse due to enhanced air-entrainment-induced turbulence. Quantitative agreement between experiments and simulations confirms this behavior. Coupled 0-D equilibrium and 3-D computational fluid dynamics analyses show that flash boiling accelerates evaporation and reduces fuel residence time, while non-flash conditions maintain a persistent liquid core more susceptible to wall wetting. Wall temperature diagnostics reveal that spray collapse alters heat transfer patterns by shifting cooling effects. Mixture fraction analysis indicates that evaporation is primarily governed by shear-layer turbulence, though deviations from adiabatic equilibrium mixing emerge under low-turbulence conditions. Finally, increasing fuel, ambient, and wall temperatures reduces wall wetting and film thickness, mitigating cold-start risks. These findings enhance the understanding of methanol sprays’ behavior and support its adoption as a viable, alternative fuel for ICEs.

Engine Combustion Network↗

DOE OSTI2025

Modeling supercritical CO2 injection induced rupture of a minor fault embedded in a poroelastic layered reservoir-caprock system

CO2 injection for geologic carbon sequestration involves hydromechanical processes that lead to changes in fluid pressure and stresses that can activate existing faults. This paper presents a new method and workflow of modeling fault activation considering more complex three-dimensional geometry of natural faults using the TOUGH-FLAC multiphase fluid flow and geomechanical simulator. In this method and workflow, FLAC3D mechanical interfaces and TOUGH3 finite volume elements are discretized using computer aided design and gridding software along with a tailored mesh translation routine. The method and workflow are demonstrated with a model of a curved minor fault embedded in a poro-elastic layered reservoir-caprock system. The model is used for a comprehensive sensitivity analysis of fault responses to fault length, injection mass rate, injection schedule, well-fault distance, and well locations versus fault location. Four metrics (CO2 plume, shear state of fault, pressure and stress path at fault monitoring points) are selected to assess CO2 migration, pressure change, and the reactivation of faults. The results reveal that CO2 can bypass around the tip of the minor impermeable fault, building up pressure and poro-elastic stress on both sides that tends to impede fault rupture. Our study shows the benefit of carefully designing the injection to achieve the targeted final storage volume, starting at a relatively low rate for considerable time, and then ramping up the injection rate to the full rate of injection. The initial low injection has two distinct benefits: (1) it allows for the formation of an extensive CO2 plume with a much higher mobility through a low viscosity that will result in a lower pressure for a given injection rate, and (2) it allows for gradual build-up of horizontal poro-elastic stress within the reservoir that will tend to impede activation of steeply dipping faults. The injection scenario starting at a low injection rate, denoted here as conservative injection, can significantly reduce the risk of fault activation as high fluid mobility and reservoir strengthening poro-elastic stress has been established long before reaching the peak injection rates. Moreover, simultaneous injection in two injection wells on both sides of fault can provide further reservoir strengthening through poro-elastic stress buildup acting on a fault under normal faulting stress regime. The findings presented in the paper can provide practical and effective guidance on long-term, safe, and reliable geological CO2 storage.

Cao, Meng↗

DOE OSTI2025

Autonomous alloy composition optimization using molecular dynamics guided by a large language model

Here, we present an autonomous materials discovery framework that couples a large language model (LLM) with molecular dynamics (MD) simulations to optimize Fe–Cr–Mn alloy compositions for tensile strength. Starting from six distinct compositions, the LLM operated as an intelligent agent, iteratively proposing changes based on prior simulation results and constraints. Over 50 iterations per case, the LLM adaptively explored the composition space, identifying high-strength regions, not easily accessible by conventional methods. The highest strength, 18.7 GPa, was achieved with Fe 71 Cr 25 Mn 4 composition, identified from a Fe 75 Cr 20 Mn 5 starting point. The LLM autonomously adjusted its strategy in real time, demonstrating closed-loop decision-making using commodity hardware. This approach showcases the potential of LLMs as scientific co-pilots, capable of accelerating materials discovery and generalizable to other domains like biology and drug design.

Autonomy↗

DOE OSTI2024

Thoughts on the past, present and future of UHV surface chemistry and the birth of Single-Atom Alloys

Throughout its relatively short lifetime, ultra-high vacuum (UHV) surface chemistry has progressed quickly. In the 1960's, pioneers like Ertl and Somorjai started the field using single crystals and gained significant insight into catalytic processes by relating surface structure to reactivity. The more recent proliferation of scanning probes has significantly increased the power of the single crystal approach by enabling the atomic-scale structure of active sites to be correlated with their reactivity. In this perspective we briefly discuss how the field developed, identify some challenges, and highlight Single-Atom Alloys (SAAs), a new class of heterogeneous catalyst that was developed from a fundamental surface science approach. However, despite recent successes, funding for fundamental surface science has declined. Academic hires in the discipline are also declining in part due to the start-up costs. We make the case that fundamental UHV surface chemistry is still too young a field to be in recession.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Synthesis and characterization of isotopically barcoded nickel, molybdenum, and tungsten taggants for intentional nuclear forensics

Intentional nuclear forensics is a concept wherein the deliberate addition of benign and persistent material signatures to nuclear material can be used to reduce the time between the discovery of material outside of regulatory control and determination of its original provenance. One concept within intentional nuclear forensics involves the use of perturbed stable isotopes to generate unique isotope ratio “barcodes” to encode information (e.g., production batch, location, etc.) and track material throughout the nuclear fuel cycle. Synthesis of taggant species of nickel (Ni), molybdenum (Mo), and tungsten (W) was undertaken via a double-spike mechanism, wherein two highly enriched isotopes of interest per elemental taggant were mixed to form an enriched “double-spike” which was subsequently isotopically diluted with bulk material having a natural isotopic composition. Two taggant species perturbing isotopic ratios, alpha (α) and beta (β), for each of Ni, Mo, and W were synthesized. Independent measurements of double spikes and alpha and beta taggant species agreed within uncertainty and are clearly resolvable from natural compositions. High-precision analyses were independently performed by MC-ICP-MS at two U.S. National Laboratories, with consensus values and uncertainties calculated for all samples. Observed isotopic perturbations in the final taggant species measured on the order of hundreds to thousands of permille (‰) with respect to natural for isotope ratios of interest (e.g., 60 Ni/ 58 Ni, 100 Mo/ 98 Mo, 186 W/ 183 W). Discrepancies between modeled and measured isotopic compositions were observed and are largely attributed to imprecise vendor assay values for starting materials. Using measured starting material compositions as inputs for the mixing model improved the level of agreement between predicted and measured α and β taggant isotope ratios. Overall, characterization of all taggant species demonstrates that this “barcode” concept could have viability for use in nuclear forensics. Finally, it is expected that for any two-isotope mixing array dozens of isotopic barcodes could be encoded into a material system and subsequently resolved utilizing modern mass spectrometric methods.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2026

Reactions of U(DMSO) 8 (ClO 4 ) 4 with Terpyridine Yield Dimeric Hydrolysis Products and Induce C–C Coupling

Reactions have been carried out using UIV(DMSO) 8 (ClO 4 ) 4 with 2,2′:6′,2″-terpyridine (terpy) under nonaqueous conditions. At room temperature in acetonitrile, the combination of the U(IV) starting material with terpy resulted in a mixture containing [UO 2 (DMSO) 2 terpy][ClO 4 ] 2 ·MeCN, while increasing the water content led to the hydrolysis products [(UO 2 (DMSO)terpy) 2 (μ 2 –O)][ClO 4 ] 2 and [(UO 2 terpy) 2 (μ 2 –OH) 2 ][ClO 4 ] 2 ·MeCN·H 2 O. Performing the reaction at slightly elevated temperature with no added water led to the formation of [UO 2 sexipyridine][ClO 4 ] 2 ·MeCN. This new uranyl complex contains the hexadentate ligand 2,2′:6′,2″:6″,2″:6‴,2⁗:6⁗,2⁗′-sexipyridine, which formed in situ from the tetravalent uranium starting material, where photoexcited uranyl or in situ generated peroxide could have induced C–C coupling. Analysis of bonding in the dimeric uranyl species via quantum chemical methods revealed a small increase in covalency of the bridging oxo unit and a slightly greater stability compared to the bridging hydroxo compound, which causes a significant shift in the uranyl symmetric stretch in the Raman spectrum. Structural, spectroscopic, and computational comparisons are made across the series of compounds, providing insight into the bonding and reactivity of uranium in nonaqueous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Low-Energy Isomers of the Magic Number H + (H 2 O) 21 Cluster

Electronic structure calculations are used to characterize low-energy isomers of H + (H 2 O) 21 . Eleven different classes of isomers, based on the (H 2 O) 20 pentagonal dodecahedron with the excess proton localized on the surface (as a hydrated hydronium ion) and the “extra” water molecule located in the interior of the cluster, are characterized. In 10 of these classes, the internal water molecule is engaged in six 5-membered rings, but in the remaining class, which is predicted to start at only 0.6 kcal/mol above the global minimum, the internal water is engaged in a 4- membered ring, an additional 6-membered ring, and four 5- membered rings. In addition, isomers with two 4-membered rings and two 6-membered rings on the cluster surface are predicted to start at only ∼1.3 kcal/mol above the lowest-energy dodecahedralbased structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Electrochemical Activation of Ni–Fe Oxides for the Oxygen Evolution Reaction in Alkaline Media

The oxygen evolution reaction (OER) is essential to many key electrochemical devices, including H 2 O electrolyzers, CO 2 electrolyzers, and metal−air batteries. NiFe oxides have been historically identified as active for the OER, though they have been less studied in their more commercially relevant bulk oxide forms, such as NiFe 2 O 4 . Past works have demonstrated that the initial starting phase of Ni(Fe) precatalysts can influence their activation to the Ni(Fe)OOH active phase, including the rate and degree of conversion, pointing to the necessity of understanding activation protocols and in situ characteristics of catalyst materials at the device level. In this work, we investigate the characteristics of commercially relevant NiFe bulk oxides (NiFe 2 O 4 and a physical mixture of NiO and γ-Fe 2 O 3 ) during multiple activation procedures. Our results demonstrate that significant performance enhancement is observed for these bulk oxides regardless of the Fe incorporation in the initial form (i.e., atomically or macroscopically integrated), leading to significant performance enhancement (up to 30×) over time on stream. We hypothesize that this activation is due to the formation of NiFeOOH active sites on the surface, supported by in situ cyclic voltammetry and Raman spectroscopy results. We further show that not only the starting material but also the method of activation influences the number of Ni(Fe)OOH active sites formed and suggest that these sites can be quantified from the Ni 2+ to Ni 3+ redox transition using cyclic voltammetry. Broadly, this work demonstrates the necessity of in situ characterization of catalyst materials for cell-level design and testing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Identification and Exploration of a Series of SARS-Cov-2 M Pro Cyano-Based Inhibitors Revealing Ortho-Substitution Effects within the P3 Biphenyl Group

Starting from a simple scaffold hopping exercise based on our previous exploration of cysteine protease inhibitors against legumain, compound 6a was identified as a starting point for the development of a SARS-CoV-2 main protease (M Pro ) inhibitor. Compound 6a displayed submicromolar biochemical potency in the ultrasensitive assay developed by Drag and coworkers. Through an iterative structure−activity relationship campaign, we discovered an unexpected improvement in both biochemical and cellular potency through the incorporation of an ortho substituent within the P3 benzamide. X-ray crystallography revealed that incorporation of the ortho substituent caused a subtle but important binding enhancement of the P1 glutamate group within the M Pro S1 pocket. While incorporation of the ortho substituent improved the potency, the off-target selectivity against a panel of cysteine proteases and cell activity remained suboptimal. Further scanning of the P2 core revealed that incorporation of the 3.1.0 proline could address these issues and afford compound 22e, a highly potent and cellularly active M Pro inhibitor.

COVID-19 infection↗