Search NASA⌕ Search

SEARCH · Search NASA

Results for “functional analysis”

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.

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

At least 271 records · Page 15

Molecular orbital symmetry-driven trimer formation in Kagome correlated electron materials

Correlated electron materials with molecular orbital states extending over transition metal clusters can host multiferroicity, spin frustration, and unconventional insulating phases. However, the fundamental criteria that govern cluster formation and stability remain unclear. Here, we identify a symmetry, correlation, and electron-filling-driven criteria that stabilize triangular metal trimers in materials displaying transition metal Kagome patterns. Using density functional theory and chemical bonding analysis, we show that trimer formation emerges when 6–8 electrons occupy molecular orbitals derived from transition metal d-states, achieving near-complete filling of bonding states while avoiding antibonding occupation, and correlations are of intermediate strength. This principle explains the stability of Nb 3 X 8 (X = Cl, Br, I), and more broadly, our findings offer a general design rule to obtain quantum materials with quantum states extended across transition metal clusters.

Kumari, Varsha [Indiana Univ., Bloomington, IN (Un↗

Small-𝑥 gluon GPD constrained from deeply virtual 𝐽/𝜓 production and gluon PDF through universal-moment parametrization

We phenomenologically constrain the small-𝑥 and small-𝜉 gluon generalized parton distributions (GPDs) with the deeply virtual 𝐽/𝜓 production (DV⁢𝐽/𝜓⁢P) in the framework of GPDs through universal moment parameterization (GUMP). We use a hybrid cross-section formula combining collinear factorization to the next-to-leading order (NLO) accuracy of the strong coupling 𝛼 𝑠 , with corrections from nonrelativistic QCD to account for the power corrections due to the heavy 𝐽/𝜓 mass. We reach reasonable fit to the measured differential cross sections of DV⁢𝐽/𝜓⁢P by H1 at the Hadron-Electron Ring Accelerator as well as forward gluon parton distribution functions (PDFs) from JAM22 global analysis. We find that both NLO and nonrelativistic corrections are significant for heavy vector meson productions. Of course, the gluon GPD we obtain still contains considerable freedom in need of inputs from other constraints, particularly in the distribution-amplitude-like region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Revisiting the assignment of atomic charges in metal oxides based on core-level x-ray photoelectron spectra: The case of Ti in SrTiO3(001)

We demonstrate that assigning formal charges to transition metal (TM) cations based on core-level (CL) x-ray photoemission binding energies in oxides leads to physically inconsistent pictures of electronic structure. O 2p–TM 3d hybridization is well known to result in significant covalency in TM–O bonds, thereby reducing TM cation charges from their fully ionic values. However, the ionic bonding model remains the working paradigm for assigning TM CL features, and the resulting cation charges are often taken to be representative of the material under study. Here, we show that a more physically meaningful way to assign charges is to extract information about charge distributions utilizing Dirac–Hartree–Fock theory to calculate CL spectra from first principles and then use the resulting wave functions to determine charges based on orbital occupancies. TM cation charges can also be determined using density functional theory and Bader population analysis. We illustrate these two methods using the Ti 2p spectrum for SrTiO3(001) and show that the agreement between them is excellent. Significantly, the resulting Ti charge is considerably lower than the formal charge. The high degree of similarity between the Ti 2p spectrum for SrTiO3 and those for the rutile and anatase polymorphs of TiO2 suggests that the charge densities surrounding Ti in the latter materials are similar to that in SrTiO3. Taking a broader perspective, oxides containing other first-row transition metals also exhibit covalent character, leading to TM cation charges lower than the analogous fully ionic values in these materials as well.

Chambers, Scott A. (ORCID:000000025415043X)↗

Accessing bands with extended quantum metric in kagome Cs 2 Ni 3 S 4 through soft chemical processing

Flat bands that do not merely arise from weak interactions can produce exotic physical properties, such as superconductivity or correlated many-body effects. The quantum metric can differentiate whether flat bands will result in correlated physics or are merely dangling bonds. A potential avenue for achieving correlated flat bands involves leveraging geometrical constraints within specific lattice structures, such as the kagome lattice; however, materials are often more complex. In these cases, quantum geometry becomes a powerful indicator of the nature of bands with small dispersions. We present a simple, soft-chemical processing route to access a flat band with an extended quantum metric below the Fermi level. By oxidizing Ni-kagome material Cs 2 Ni 3 S 4 to CsNi 3 S 4 , we see a two orders of magnitude drop in the room temperature resistance. However, CsNi 3 S 4 is still insulating, with no evidence of a phase transition. Using experimental data, density functional theory calculations, and symmetry analysis, our results suggest the emergence of a correlated insulating state of unknown origin.

Science & Technology - Other Topics↗

Biochar-compost-based controlled-release nitrogen fertilizer intended for an active microbial community

Nitrogen (N) fertilizers in agriculture suffer losses by volatilization of N to the air, surface runoff and leaching into the soil, resulting in low N use efficiency (NUE) (< 50%) and raising severe environmental pollutions. Controlled- release nitrogen fertilizers (CRNFs) can control the release of N nutrients to NUE in crop production. Different methods were used to develop new CRNFs. However, different CRNF technologies are still underdeveloped due to inadequate controlling on N releasing time and/or unsustainable diffusion. The study on the influences of CRNF processing parameters on microbial conditions are lacking when the CRNFs composed of various bio-ingredients such as biochar, composts, and biowaste. The complexity of processing methods, material biodegradability, and other physical properties make current CRNFs of questionable value in agricultural production. This research aims to develop a novel biochar-compost-based controlled-release urea fertilizer (BCRUF) to preserve microbial properties carried by the compost. The BCRUF was synthesized by pelletizing the 50:50 (dry, wt/wt) mixture of biochar and compost. BCRUF was loaded with urea and then spray-coated with polylactic acid (PLA). The releasing time of two types of BCRUFs, coated and uncoated with PLA, for 80% of N release in water was up to 6 h at three different temperatures (4, 23, and 40 °C), compared to conventional urea fertilizer and commercial environmentally smart N (ESN) fertilizer. The releasing time of coated BCRUF for 80% N release in soil was up to 192 h (8 days). Fourier-transform infrared spectroscopy (FTIR) analysis revealed that no new functional groups were found in the release solution, indicating no new chemical hazards generated. The differential scanning calorimetry (DSC) tests also verified that its thermal stability could be up to 160 °C. The microbe populations in the BCRUF pellets were reduced after the pelleting and drying processes in BCRUF fabrication, but a few bacteria can endure in the air-drying process. BCRUF pellets soaked in water for 4 days retained some bacteria. The BCRUF showed very promising characteristics to improve NUE and sustainability in agricultural production.

58 GEOSCIENCES↗

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

A Portable Wave Tank and Wave Energy Converter for Engineering Dissemination and Outreach

Wave energy converters are a nascent energy generation technology that harnesses the power in ocean waves. To assist in communicating both fundamental and complex concepts of wave energy, a small-scale portable wave tank and wave energy converter have been developed. The system has been designed using commercial off-the-shelf components, and all design hardware and software are openly available for replication. This project builds on prior research conducted at Sandia National Laboratories, particularly in the areas of WEC device design and control systems. By showcasing the principles of causal feedback control and innovative device design, SIWEED not only serves as a practical demonstration tool but also enhances the educational experience for users. This paper presents the detailed system design of this tool. Furthermore, via testing and analysis, we demonstrate the basic functionality of the system.

educational↗

Dimensional Reduction for Sampled Priors and Application to Photometric Redshift Distributions

A typical Bayesian inference on the values of some parameters of interest q from some data D involves running a Markov Chain (MC) to sample from the posterior $p$($q$,$n$|$D$) $\propto$ $\mathcal{L}$($D$|$q$,$n$)$p$(q)$p$($n$), where n are some nuisance parameters with a separable prior. In some cases, the nuisance parameters are high-dimensional, and their prior p(n) is itself defined only by a set of samples that have been drawn from some other MC. The MC for the posterior will typically require evaluation of p(n) at arbitrary values of n, i.e., one needs to provide a density estimator over the full n space from the provided samples. But the high dimensionality of n hinders both the density estimation and the efficiency of the MC for the posterior. We describe a solution to this problem: a linear compression of the n space into a much lower-dimensional space u, which projects away directions in n space that cannot appreciably alter $\mathcal{L}$. The algorithm for doing so is a slight modification to principal components analysis, and is less restrictive on p(n) than other proposed solutions to this issue. We demonstrate this “mode projection” technique using the analysis of 2-point correlation functions of weak lensing fields and galaxy density in the Dark Energy Survey, where n is a binned representation of the redshift distribution n(z) of the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Enzyme Engineering Database (EnzEngDB): a platform for sharing and interpreting sequence–function relationships across protein engineering campaigns

The discovery and engineering of new enzymes is important across the bioeconomy, with diverse applications from foods to pharmaceuticals, sensors to agriculture. However, enzyme engineering, in particular machine learning-guided engineering, is hampered by a lack of data. Currently there exists no database designed to capture and interpret datasets created in this domain, nor are there easy analysis and visualisation tools. We developed the Enzyme Engineering Database to provide a centralized resource and an online analysis tool to consolidate sequence-function data from enzyme engineering campaigns, thereby making three contributions: (i) a database into which researchers can deposit public data, (ii) visualisation and analysis tools for protein engineers to analyse their own data or compare enzyme variants to other engineering campaigns, and (iii) a gold-standard dataset for benchmarking automated extraction along with the first large language model extraction pipeline specific for enzyme engineering campaigns. The Enzyme Engineering Database is accessible at http://enzengdb.org/.

Long, Yueming [California Institute of Technology ↗

Unraveling the Mechanism of Interfacial Charge Transfer and Photoresponsivity of WS 2 Quantum Dots/MoS 2 (0D–2D) Heterostructure-Based Transistors

To assess the efficacy of a mixed-dimensional van der Waals (vdW) heterostructure in modulating the optoelectronic responses of nanodevices, the charge transport properties of the transition-metal dichalcogenide (TMD)-based heterostructure comprising zero-dimensional (0D) WS 2 quantum dots (QDs) and two-dimensional (2D) MoS 2 flakes are critically analyzed. Herein, a facile strategy was materialized in developing an atomically thin phototransistor assembled from mechanically exfoliated MoS 2 and WS 2 QDs synthesized using a one-pot hydrothermal route. The amalgamated photodetectors exhibited a high responsivity of ∼8000 A/W at an incident power of 0.05 nW of white light, surpassing that of the pristine MoS 2 devices. Furthermore, the detectivity of pristine MoS 2 , which was on the order of 10 10 , increased to 10 12 Jones for the WS 2 QDs/MoS 2 heterostructure photodetector, outperforming other WS 2 -based materials. The quasiparticle band gap and density of states (DOS) are further analyzed to elucidate the photophysics of the WS 2 QD/MoS 2 hybrid assembly. The difference in the work function between MoS 2 and WS 2 QDs gives rise to an electric field across the 0D–2D interface, facilitating effective charge separation and migration and contributing to the enhancement of photoresponsivity. The analysis of optical responses using density functional theory (DFT) revealed stronger absorption and less reflection over a broader spectrum of wavelengths for the heterostructure compared to the pristine materials. The estimated optical conductivity aligns well with the experimentally predicted maximum photoresponsivity under visible light, which is attributed to the high absorbance of 2D MoS 2 . In conclusion, combining diverse spectroscopic and imaging techniques with quantum simulation provides insights that clarify the pertinence of 0D–2D TMDs in designing phototransistors.

WS2 QDs/MoS2 heterostructure↗

On the bulk compaction of brittle granular materials, part I: SeS analysis of axial compression to 4000 MPa

The bulk compaction of granular materials has been studied for decades to interpret and manage responses for soils and powder-based component fabrication, and geophysical, celestial, and ballistic impact. Their bulk or macroscopic compaction response is limited by what occurs at the granular or microstructural scale. Motivation existed to more closely examine that association specific to granular brittle materials (e.g., ceramics and glasses). That examination is offered in a series of three companion papers where Part I describes a new supplemental analysis adopted to bulk compaction response involving relatively high compaction stresses (4000 MPa). Bulk compactions of vitreous silicates and crystalline quartzes were interpreted in three ways, including that of a new analysis that considers the product of void ratio (e) and stress (S) as a function of S, hereafter referred to as “SeS analysis”. In conclusion, the SeS analysis was found to be an informative supplement to conventional bulk compaction analyses because it provides more consistent higher sensitivity for the identification of bulk density rate increase with increasing compaction (softening); a rate increase that arises from the cumulative effect of the onsets and progression of compaction-induced yielding, fracture or comminution, densification, phase change, or combinations thereof occurring at the granular or microstructural scale.

compaction↗

Structure analysis of the telomere resolvase from the Lyme disease spirochete Borrelia garinii reveals functional divergence of its C-terminal domain

Borrelia spirochetes are the causative agents of Lyme disease and relapsing fever, two of the most common tick-borne illnesses. A characteristic feature of these spirochetes is their highly segmented genomes which consists of a linear chromosome and a mixture of up to approximately 24 linear and circular extrachromosomal plasmids. The complexity of this genomic arrangement requires multiple strategies for efficient replication and partitioning during cell division, including the generation of hairpin ends found on linear replicons mediated by the essential enzyme ResT, a telomere resolvase. Using an integrative structural biology approach employing advanced modelling, circular dichroism, X-ray crystallography and small-angle X-ray scattering, we have generated high resolution structural data on ResT from B. garinii. Our data provides the first high-resolution structures of ResT from Borrelia spirochetes and revealed active site positioning in the catalytic domain. We also demonstrate that the C-terminal domain of ResT is required for both transesterification steps of telomere resolution, and is a requirement for DNA binding, distinguishing ResT from other telomere resolvases from phage and bacteria. These results advance our understanding of the molecular function of this essential enzyme involved in genome maintenance in Borrelia pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Multiscale structural analysis of polymorphic phase boundaries in doped antiferroelectric sodium niobate

In the current work, we have performed multiscale structural analysis of a Pb-free sodium niobate-based smart system, i.e., 0.9⁢NaNbO 3 –0.1⁢Ba 0.9 ⁢Ca 0.1 ⁢TiO 3 (NN-10BCT) reported earlier for its high ferroelectric response. We have investigated the temperature-dependent evolution of crystal structure at long, medium, and short ranges using synchrotron x-ray diffraction (SXRD), Raman scattering, and pair distribution function(PDF) techniques in conjunction with dielectric studies. Temperature-dependent synchrotron x-ray diffraction data combined with dielectric analysis suggest two unique polymorphic phase boundaries (PPB) with two coexisting ferroelectric phases stable in the wide temperature ranges. These PPBs are stable in different regions viz. (i) cryogenic temperatures with coexisting R3c and Pmc⁢2 1 phases (ii) vicinity of room temperatures with coexisting Pmc⁢2 1 and Amm2 phases. In contrast to the conclusions drawn from SXRD, PDF reveals structures having lower symmetry (with coexisting Cc+ Pmc2 1 phases at 1.7 ≤r≤ 20 Å) at short ranges for these PPBs. In conclusion, the presence of different long- and short-range symmetries (accommodating tilt-oriented ferroelectric phases) in the unique polymorphic phase boundaries makes them thermally stable and advantageous for technological applications.

36 MATERIALS SCIENCE↗

Single-cell proteomics of Arabidopsis leaf mesophyll reveals dynamic protein responses to water-deficit stress

Background The application of single-cell omics tools to biological systems can provide unique insights into diverse cellular populations and their heterogeneous responses to internal and external perturbations. Thus far, most single-cell studies in plant systems have been limited to RNA-sequencing approaches, which only provide indirect readouts of cellular functions. Results Here, we present a single-cell proteomics workflow for plant cells that integrates tape-sandwich protoplasting, piezoelectric cell sorting, nanoPOTS sample preparation, and ion mobility-based MS data acquisition method for label-free single-cell proteomics analysis of Arabidopsis leaf mesophyll cells. From a single leaf protoplast, over 3,000 proteins were quantified with high precision. The workflow is demonstrated to identify stress associated changes in protein abundance by analyzing 117 protoplasts from well-watered and water-deficit stressed plants. Additionally, we describe a new approach for constructing covarying protein networks at the single-cell level and demonstrate how single-cell protein covariation analysis can reveal previously unrecognized protein functions while also capturing stress-induced changes in protein–protein dynamics. Conclusions The label-free scProteomic approach presented here represents a significant advance through the demonstration of a facile protoplast isolation method combined with deep and precise proteomic coverage of Arabidopsis leaf mesophyll cell types. We believe this study will serve as an informative reference to future plant scProteomic investigations.

Arabidopsis↗

Developing a media formulation to sustain ex vivo chloroplast function

Chloroplasts are critical organelles in plants and algae responsible for accumulating biomass through photosynthetic carbon fixation and cellular maintenance through metabolism in the cell. Chloroplasts are increasingly appreciated for their role in biomanufacturing, as they can produce many useful molecules, and a deeper understanding of chloroplast regulation and function would provide more insight for the biotechnological applications of these organelles. However, traditional genetic approaches to manipulate chloroplasts are slow, and generation of transgenic organisms to study their function can take weeks to months, significantly delaying the pace of research. To develop chloroplasts themselves as a quicker and more defined platform, we isolated chloroplasts from the green algae, Chlamydomonas reinhardtii, and examined their photosynthetic function after extraction. Combined with a metabolic modeling approach using flux-balance analysis, we identified key metabolic reactions essential to chloroplast function and leveraged this information into reagents that can be used in a “chloroplast media” capable of maintaining chloroplast photosynthetic function over time ex vivo compared to buffer alone. We envision this could serve as a model platform to enable more rapid design-build-test-learn cycles to study and improve chloroplast function in combination with genetic modifications and potentially as a starting point for the bottom-up design of a synthetic organelle-containing cell.

Chlamydomonas reinhardtii↗

Effective field theory factorization for diffraction

We derive a factorization formula for coherent and incoherent ep diffraction using the soft collinear effective theory, utilizing multiple power expansion parameters to handle different kinematic regions. This goes beyond the known hard-collinear diffractive factorization to address the small-x Regge dynamics and Pomeron exchange from first principles. The effective field theory analysis also uncovers and factorizes an important irreducible incoherent background generated by color-nonsinglet exchange, dubbed “quasi-diffraction”, for which we calculate the associated Sudakov suppression. For unpolarized scattering we show that there are four diffractive structure functions at leading power, and point out the importance of studying ${F}_{3,4}^D$ through asymmetries, in addition to ${F}_{2,L}^D$. For the quasi-diffractive background, we make model independent predictions for ratios of the corresponding structure functions in a perturbative kinematic region. Our analysis also makes predictions for six leading-power spin-dependent structure functions. Finally, we provide connections to diffractive parton distributions, and assess the Ingelman-Schlein model. Our work lays a path for further QCD-based studies of diffraction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗

Constraining calculations of Pu 239 ( n , γ ) cross sections with multistep cascade γ -ray spectra measured at the DANCE facility

Measurements of multistep cascade gamma-ray spectra from several low-lying 1 + resonances in the Pu 239 ( n , γ ) reaction were made using the DANCE detector. The measured spectra are compared to spectra simulated using several models for the photon strength function and the nuclear level density, representing the first analysis of this nature on a fissile nucleus. In general, models of the photon strength function that included a strong M 1 “scissors mode” contribution coupled with a Gilbert-Cameron nuclear level density provided a reasonable description of the spectra. Simulations using photon strength functions and nuclear level densities specifically for Pu 240 , extracted by the Oslo method, resulted in a very good representation of the measured spectra. Neutron-capture cross section calculations that included the scissors mode provided a good estimate of the previously measured values, without additional normalization. However, the scissors-mode energy that produced the best description of the multistep cascade spectra was different from the value that best reproduced the capture cross section. In addition, the 〈 Γ γ 〉 inferred from the multistep cascade calculations was somewhat less than the tabulated value, which was determined from resonance analysis. Published by the American Physical Society 2025

Ullmann, J. L. (ORCID:0000000207784405)↗