SEARCH · Engineering Papers

Results for “Identifiers”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Identifying recharge sources and their impacts on a North Central New Mexico shallow aquifer using unsupervised machine learning

In this article, shallow aquifers are important but highly variable resources in arid to semi-arid regions. Limited shallow aquifer volume results in high sensitivity to recharge fluctuations, which can impact the local fauna and flora, and transport of contaminants in the aquifer or vadose zone. Aquifer response to external forcing (e.g., precipitation) is usually solved by estimating aquifer parameters and running physics-based models to match known fluctuations of hydraulic head. However, this technique is time and computationally expensive. Furthermore, high aquifer complexity decreases precision in physics-based models. Alternatively supervised machine learning is used to predict aquifer dynamics. However, these techniques rely on input data and struggle to interpret aquifer response for missing sources (i.e., snowpack data). To counter these problems, we propose an unsupervised machine learning technique (NMFk) to estimate the impact of different sources on aquifer recharge. NMFk is used to understand the influence of external forcing on shallow aquifer recharge in the Pajarito Plateau (Los Alamos, NM, USA). The results show how NMFk can be used to reduce the data dimension in a complex field dataset to three recharge signals that cause fluctuations within the field data. Here, the source signals are interpreted as rainfall, snowmelt, and a delayed aquifer response to the previous two signals. These results evidence how heterogeneous aquifers delimited by canyons incised into the Pajarito Plateau respond in similar ways to the source signals identified by NMFk. Furthermore, results show the importance of the local geology where faults act as sinks, and anthropogenic disturbances can facilitate infiltration amplifying the interpreted signal.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Identifying Photoinduced Dipolar Polarization and Orbit–Orbit Interaction between Excitons in Organic–Inorganic Hybrid Perovskites

Abstract Photoinduced polarization and orbit–orbit interaction are important issues in hybrid perovskites toward developing optoelectronic functionalities. This paper identifies that photoinduced polarization occurs in hybrid perovskites with mixed‐cation methylammonium (MA)/formamidinium (FA) (MA x FA (1− x ) PbI 3 ) by measuring bulk polarization at 1 MHz in a magnetic field. Interestingly, when the internal dipole moment is increased upon increasing the MA:FA ratio, the photoinduced dipolar polarization can be substantially enhanced, clarifying the controversial issue of whether photoexcitation can induce a dielectric polarization within dipolar polarization regime in hybrid perovskites. Furthermore, upon increasing photoinduced dipolar polarization, it is found that the intrinsic orbit–orbit interaction between excitons can be increased, revealed by monitoring photocurrent change (Δ J sc ) upon switching the photoexcitation between linear and circular polarizations. This presents that organic cations are directly involved in the orbit–orbit interaction within band structures. Clearly, the studies provide an insightful understanding of the dipole moment effects on photoinduced dipolar polarization and orbit–orbit interaction between excitons in hybrid perovskites toward controlling the optoelectronic properties.

Dou, Yixuan↗

DOE OSTI2020

Establishing a Theoretical Landscape for Identifying Basal Plane Active 2D Metal Borides (MBenes) toward Nitrogen Electroreduction

Abstract To achieve efficient ammonia synthesis via electrochemical nitrogen reduction reaction (NRR), a qualified catalyst should have both high specific activity and large active surface area. However, integrating these two merits into one single material remains a big challenge due to the difficulty in balancing multiple reaction intermediates. Here, it is demonstrated that the boron‐analogues of MXenes, namely “MBenes”, could cope with the challenge and achieve the high activity and large reaction region simultaneously toward NRR. Using extensive density functional theory computations and taking 16 MBenes as representatives, it is identified that seven MBenes (CrB, MoB, WB, Mo 2 B, V 3 B 4 , CrMnB 2 , and CrFeB 2 ) not only have intrinsic basal plane activity for NRR with limiting potentials ranging from −0.22 to −0.82 V, but also possess superior capability of suppressing the competitive hydrogen evolution reaction. Particularly, different from the MXenes whose surface oxidation may block the active sites, once oxidized, these MBenes can catalyze NRR via the self‐activating process, reducing O*/OH* into H 2 O* under reaction conditions, and favoring the N 2 electroreduction. As a result, the exceptional activity and selectivity, high active area (≈10 19 m −2 ), and antioxidation nature render these MBenes as pH‐universal catalysts for NH 3 production without introducing any dopants and defects.

Guo, Xiangyu↗

DOE OSTI2022

Identifying the Signatures of Intermolecular Interactions in Blends of PM6 with Y6 and N4 Using Absorption Spectroscopy

Abstract In organic solar cells, the resulting device efficiency depends strongly on the local morphology and intermolecular interactions of the blend film. Optical spectroscopy was used to identify the spectral signatures of interacting chromophores in blend films of the donor polymer PM6 with two state‐of‐the‐art nonfullerene acceptors, Y6 and N4, which differ merely in the branching point of the side chain. From temperature‐dependent absorption and luminescence spectroscopy in solution, it is inferred that both acceptor materials form two types of aggregates that differ in their interaction energy. Y6 forms an aggregate with a predominant J‐type character in solution, while for N4 molecules the interaction is predominantly in a H‐like manner in solution and freshly spin‐cast film, yet the molecules reorient with respect to each other with time or thermal annealing to adopt a more J‐type interaction. The different aggregation behavior of the acceptor materials is also reflected in the blend films and accounts for the different solar cell efficiencies reported with the two blends.

Kroh, Daniel↗

DOE OSTI2024

Brain phosphoproteomic analysis identifies diabetes‐related substrates in Alzheimer's disease pathology in older adults

INTRODUCTION: Type 2 diabetes increases the risk of Alzheimer's disease (AD) dementia. Insulin signaling dysfunction exacerbates tau protein phosphorylation, a hallmark of AD pathology. However, the comprehensive impact of diabetes on patterns of AD-related phosphoprotein in the human brain remains underexplored. METHODS: We performed tandem mass tag–based phosphoproteome profiling in post mortem human brain prefrontal cortex samples from 191 deceased older adults with and without diabetes and pathologic AD. RESULTS: Among 7874 quantified phosphosites, microtubule-associated protein tau (MAPT) phosphorylated at T529 and T534 (isoform 8 T212 and T217) were more abundant in AD and showed differential associations with diabetes. Network analysis of co-abundance patterns uncovered synergistic interactions between AD and diabetes, with one module exhibiting higher MAPT phosphorylation (15 MAPT phosphosites) and another displaying lower MAP1B phosphorylation (22 MAP1B phosphosites). DISCUSSION: This study offers phosphoproteomics insights into AD in diabetes, shedding light on mechanisms that can inform the development of therapeutics for dementia. Highlights: The risk of Alzheimer's disease (AD) dementia is increased among older adults living with diabetes. The patterns of AD-related phosphoprotein in the human brain in older adults are differential among older adults living with diabetes. Microtubule-associated protein tau phosphorylated at T529 and T534 (isoform 8 T212 and T217) showed differential associations with diabetes. Phosphosite co-abundance networks of synergistic interactions between AD and diabetes were identified.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Superoxide Radicals in Uranyl Peroxide Solids: Lasting Signatures Identified by Electron Paramagnetic Resonance Spectroscopy

Abstract U(VI) peroxide phases (studtite and meta‐studtite) are found throughout the nuclear fuel cycle and exist as corrosion products in high radiation fields. Peroxides are part of a family of reactive oxygen species (ROS) that include hydroperoxyl and superoxide species and are produced during alpha radiolysis of water. While U(VI) peroxides have been thoroughly investigated, the incorporation and stability of ROS species within studtite have not been validated. In the current study, electron paramagnetic resonance (EPR) spectroscopy was used to identify the presence of free radicals within a series of U(VI) peroxide samples containing depleted, highly enriched, and natural uranium. Density functional theory calculations indicated that the predicted EPR signals matched well with a superoxide (O 2 − ⋅) species incorporated into the studtite structure, confirming the presence of ROS in the material. Further analysis of samples that were synthesized between 1945 and 2023 indicated that there is a correlation between the radical signal and the product of specific activity multiplied by age of the sample.

Scherrer, Sarah K.↗

DOE OSTI2024

Superoxide Radicals in Uranyl Peroxide Solids: Lasting Signatures Identified by Electron Paramagnetic Resonance Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

First Fluorescent Acetylspermidine Deacetylation Assay for HDAC10 Identifies Selective Inhibitors with Cellular Target Engagement**

Abstract Histone deacetylases (HDACs) are important epigenetic regulators involved in many diseases, especially cancer. Five HDAC inhibitors have been approved for anticancer therapy and many are in clinical trials. Among the 11 zinc‐dependent HDACs, HDAC10 has received relatively little attention by drug discovery campaigns, despite its involvement, e. g., in the pathogenesis of neuroblastoma. This is due in part to a lack of robust enzymatic conversion assays. In contrast to the protein lysine deacetylase and deacylase activity of most other HDAC subtypes, it has recently been shown that HDAC10 has strong preferences for deacetylation of oligoamine substrates like acetyl‐putrescine or ‐spermidine. Hence, it is also termed a polyamine deacetylase (PDAC). Here, we present the first fluorescent enzymatic conversion assay for HDAC10 using an aminocoumarin‐labelled acetyl‐spermidine derivative to measure its PDAC activity, which is suitable for high‐throughput screening. Using this assay, we identified potent inhibitors of HDAC10‐mediated spermidine deacetylation in vitro. Based on the oligoamine preference of HDAC10, we also designed inhibitors with a basic moiety in appropriate distance to the zinc binding hydroxamate that showed potent inhibition of HDAC10 with high selectivity, and we solved a HDAC10‐inhibitor structure using X‐ray crystallography. We could demonstrate selective cellular target engagement for HDAC10 but a lysosomal phenotype in neuroblastoma cells that was previously associated with HDAC10 inhibition was not observed. Thus, we have developed new chemical probes for HDAC10 that allow further clarification of the biological role of this enzyme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Identifying biomass yield potential of tetra, hexa, and octoploid prairie cordgrass populations grown on marginal lands

As the demand for renewable energy sources with reduced carbon emissions to the atmosphere increases, bioenergy crops remain an attractive alternative to fossil fuels. Another appeal of bioenergy crops is the potential utilization of marginal lands not suitable for food crops. Prairie cordgrass is a perennial warm season polyploid grass species being considered as a bioenergy crop that also exhibits a high tolerance for salinity and flooding. The ploidy level of prairie cordgrass has previously been suggested to correlate with agronomic traits. However, little is known about the agricultural performance of prairie cordgrass on marginal lands and if a correlation of ploidy level to stress tolerance exists. In this experiment, the productivity of tetraploids, hexaploids, and octoploids was investigated when grown on three different marginal sites including waterlogged, saline, and low-nutrient gravelly soils. Here we found that prairie cordgrass populations annually produced dry biomass on a wet marginal site comparable to normal cropland. However, the productivity was remarkedly decreased at both a salt-affected site and a limestone mine reclamation site. We were unable to conclude that different ploidy levels affected the biomass yield of prairie cordgrass grown under abiotic stress. However, there was a differential response of populations to various types of marginal sites. Finally, these results indicate potential genetic resources for developing breeding targets and identifying mechanisms of abiotic stress tolerance. Moreover, we highlight the need to generate diverse ploidy levels of prairie cordgrass in the same genetic backgrounds for future testing.

09 BIOMASS FUELS↗

DOE OSTI2022

Identifying Hidden Li–Si–O Phases for Lithium‐Ion Batteries via First‐Principle Thermodynamic Calculations

SiO–based materials are promising alloys and conversion‐type anode materials for lithium‐ion batteries and are recently found to be excellent dendrite‐proof layers for lithium‐metal batteries. However, only a small fraction of the Li–Si–O compositional space has been reported, significantly impeding the understanding of the phase transition mechanisms and the rational design of these materials both as anodes and as protection layers for lithium‐metal anodes. Herein, we identify three new thermodynamically stable phases within the Li–Si–O ternary system (Li 2 SiO 5 , Li 4 SiO 6, and Li 4 SiO 8 ) in addition to the existing records via first‐principle calculations. The electronic structure simulation shows that Li 2 SiO 5 and Li 4 SiO 8 phases are metallic in nature, ensuring high electronic conductivity required as electrodes. Moduli calculations demonstrate that the mechanical strength of Li–Si–O phases is much higher than that of lithium metal. The diffusion barriers of interstitial Li range from 0.1 to 0.6 eV and the interstitial Li hopping serves as the dominating diffusion mechanism in the Li–Si–O ternary systems compared with vacancy diffusion. These findings provide a new strategy for future discovery of improved alloying anodes for lithium‐ion batteries and offer important insight towards the understanding of the phase transformation mechanism of alloy‐type protection layers on lithium‐metal anodes.

Qu, Jiale↗

DOE OSTI2020

Aqueous Diels–Alder reactions for thermochemical storage and heat transfer fluids identified using density functional theory

Thermal storage and transfer fluids have important applications in industrial, transportation, and domestic settings. Current thermal fluids have relatively low specific heats, often significantly below that of water. However, by introducing a thermochemical reaction to a base fluid, it is possible to enhance the fluid's thermal properties. Here, density functional theory (DFT) is used to screen Diels–Alder reactions for use in aqueous thermal fluids. From an initial set of 52 reactions, four are identified with moderate aqueous solubility and predicted turning temperature near the liquid region of water. These reactions are selectively modified through 60 total functional group substitutions to produce novel reactions with improved solubility and thermal properties. Among the reactions generated by functional group substitution, seven have promising predicted thermal properties, significantly improving specific heat (by as much as 30.5%) and energy storage density (by as much as 4.9%) compared to pure water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Novel compound heterozygous CPLANE1 variants identified in a Chinese family with Joubert syndrome

Abstract Joubert syndrome (JS) and JS‐related disorders (JSRD) are a group of neurodevelopmental diseases that share the “molar tooth sign” on axial brain magnetic resonance imaging (MRI), accompanied by cerebellar vermis hypoplasia, ataxia, hypotonia, and developmental delay. To identify variants responsible for the clinical symptoms of a Chinese family with JS and to explore the genotype–phenotype associations, we conducted a series of clinical examinations, including blood tests, brain MRI scans, ultrasound imaging, and ophthalmologic examination. Genomic DNA was extracted from the peripheral blood of the six‐person family, and the pathogenic variants were detected by whole‐exome sequencing (WES) and verified by Sanger sequencing. WES revealed two novel compound heterozygous variants in CPLANE1 : c.1270C>T (p.Arg424*) in exon 10 and c.8901C>A (p.Tyr2967*) in exon 48 of one child, inherited from each parent. Both variants were absent in ethnically matched Chinese control individuals and were either absent or present at very low frequencies in public databases, suggesting that these variants could be the pathogenic triggers of the JS phenotype. Notably, these CPLANE1 sequence variants were related to the pathogenesis of autosomal recessive JS in this study. The newly discovered variants expand the mutation spectrum of CPLANE1 , which assists in understanding the molecular mechanism underlying JS and improving the recognition of genetic counseling, particularly for families with a history of autosomal recessive JS.

Zhang, Cheng↗

DOE OSTI2021

Identifying crystallographic faces of the fluorites urania and thoria with rotational polarized Raman spectroscopy

Crystallite orientation identification is invaluable, but is often limited to small area identification or requires a large area sample. Nondestructive optical methods such as polarized Raman spectroscopy, in contrast, can be used to completely map a variety of sample sizes, but their potential is not yet fully realized. Here, we report a systematic study of polarized Raman scattering of high-quality, hydrothermally grown, single crystals of urania and thoria. The peak intensity variations for as-grown major crystal planes, post-growth polished crystal planes, and a post-growth polished non-crystallographic plane are directly linked to crystallographic orientation and crystal rotation, and agree with computed models. In particular, the parallel polarized peak intensity results are directly correlated with metal–oxygen–metal chains in the fluorite structure and can be used to determine both orientation and rotational alignment of a given crystal face if sufficiently small rotational steps are applied. These results are structure based, being applicable to the larger fluorite phase space, which is useful for optical, semiconductor, nuclear, and solid oxide fuel cell industries. Further, these results suggest that Raman spectroscopy can identify non-crystallographic orientations that are not discernable by traditional means.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Soybean rust‐resistant and tolerant varieties identified through the Pan‐African Trial Network

Abstract BACKGROUND The global demand for soybeans is increasing rapidly, with projections indicating an escalation of 70–80 million metric tons over the next decade. Sub‐Saharan Africa (SSA) contributes significantly to this growth, with soybean production increasing by 6.8% per year, outpacing the global average increase of 4.7%. Despite the expansion, soybean productivity in Africa remains less than half of the global average. This yield gap is largely due to diseases and pests, such as soybean rust, which can be particularly severe. Effective management of soybean rust depends on several factors, including resistant cultivars. However, there has been limited information on the rust‐resistance levels of African cultivars. To address this gap, the Pan‐African Trial network conducted soybean varietal trials across diverse locations. RESULT Analyzing data from 370 individual trials conducted between 2015–2022, the network identified 81 cultivars with sufficient rust‐resistance data. Six cultivars including, Black Hawk, Dundee, Egret, Heron, Ibis, and Peka 06 were found to be resistant, and 12 were classified as tolerant. CONCLUSION This research is a significant step forward in improving soybean productivity in Africa, and further assessments are being undertaken to address other crop production challenges in the region. © 2025 Society of Chemical Industry.

Favoretto, Vitor Rampazzo [Cenex Harvest States (C↗

DOE OSTI2025

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Identifying Fungal Secondary Metabolites and Their Role in Plant Pathogenesis

Pathogenic fungi are the main infectious agents of plants. Secondary metabolites produced by these fungi, also recognized as natural products, are key mediators of plant-fungal interactions. Knowledge on the biosynthesis of these metabolites, the accessibility to fungal genome sequences, and the development of gene disruption techniques open up opportunities to identify many more of these metabolites both in vitro and in planta. This methodology chapter gives a detailed systematic approach aiming to discover new natural products from phytopathogenic fungi and characterize their role in triggering plant cell death and plant disease. This approach takes advantage of the global regulation of fungal secondary metabolite production by regulatory proteins reported in various fungal species.

Tannous, Joanna↗

DOE OSTI2023

Identifying quenched jets in heavy ion collisions with machine learning

Measurements of jet substructure in ultra-relativistic heavy ion collisions suggest that the jet showering process is modified by the interaction with the quark-gluon plasma. Modifications of the hard substructure of jets can be explored with modern data-driven techniques. In this study, a machine learning approach to the identification of quenched jets is designed. Jet showering processes are simulated with a jet quenching model JEWEL and a non-quenching model PYTHIA 8. Sequential substructure variables are extracted from the jet clustering history following an angular-ordered sequence and are used in the training of a neural network built on top of a long short-term memory network. We show that this approach successfully identifies the quenching effect in the presence of the large uncorrelated background of soft particles created in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Anisotropic flow and flow fluctuations of identified hadrons in Pb–Pb collisions at $ \sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

The first measurements of elliptic flow of π ± , K ± , p+$\bar{p}$, K$_{S}^{0}$, Λ+$\bar{Λ}$, $\phi$, Ξ – +$\barΞ$ + , and Ω – +$\barΩ$ + using multiparticle cumulants in Pb–Pb collisions at $\sqrt{s_{NN}}$= 5.02 TeV are resented. Results obtained with two- (v 2 {2}) and four-particle cumulants (v 2 {4}) are shown as a function of transverse momentum, p T , for various collision centrality intervals. Combining the data for both v 2 {2} and v 2 {4} also allows us to report the first measurements of the mean elliptic flow, elliptic flow fluctuations, and relative elliptic flow fluctuations for various hadron species. These observables probe the event-by-event eccentricity fluctuations in the initial state and the contributions from the dynamic evolution of the expanding quark–gluon plasma. The characteristic features observed in previous p T -differential anisotropic flow measurements for identified hadrons with two-particle correlations, namely the mass ordering at low p T and the approximate scaling with the number of constituent quarks at intermediate p T , are similarly present in the four-particle correlations and the combinations of v 2 {2} and v 2 {4}. In addition, a particle species dependence of flow fluctuations is observed that could indicate a significant contribution from final state hadronic interactions. The comparison between experimental measurements and CoLBT model calculations, which combine the various physics processes of hydrodynamics, quark coalescence, and jet fragmentation, illustrates their importance over a wide p T range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗