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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. Here, we have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ~77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Linear response of molecular polaritons

In this article, we show that the collective light–matter strong coupling regime where N molecular emitters couple to the photon mode of an optical cavity can be mapped to a quantum impurity model where the photon is the impurity that is coupled to a bath of anharmonic transitions. In the thermodynamic limit where N ≫ 1, we argue that the bath can be replaced with an effective harmonic bath, leading to a dramatic simplification of the problem into one of the coupled harmonic oscillators. We derive simple analytical expressions for linear optical spectra (transmission, reflection, and absorption) where the only molecular input required is the molecular linear susceptibility. This formalism is applied to a series of illustrative examples, showing the role of temperature, disorder, vibronic coupling, and optical saturation of the molecular ensemble, explaining that it is useful even when describing an important class of nonlinear optical experiments. For completeness, we provide Appendixes A–C that include a self-contained derivation of the relevant spectroscopic observables for arbitrary anharmonic systems (for both large and small N) within the rotating-wave approximation. While some of the presented results herein have already been reported in the literature, we provide a unified presentation of the results as well as new interpretations that connect powerful concepts in open quantum systems and linear response theory with molecular polaritonics.

Chemistry↗
DOE OSTI2025

A topological approach to magnetic nulls

Magnetic nulls are locations where the magnetic field vanishes. They determine to a large degree the magnetic connectivity in a system, and are sites of magnetic reconnection. We describe a novel approach to understanding movement, appearance, and disappearance of nulls in magnetic fields. This approach is based on the concept of isotropes, or lines where the field direction is constant. These lines are streamlines of a vector field whose flux is sourced by the topological indices of nulls, and can be conceptualized as corresponding to ‘lines of force’ between nulls. We show how this topological approach can be used to generate analytical expressions for the location of nulls in the presence of external fields for dipoles and for a field defined by the Hopf fibration.

magnetic null↗
DOE OSTI2025

Prediction of defect properties in concentrated solid solutions using a Langmuir-like model

The alleged existence of sluggish diffusion in high-entropy alloys has drawn controversy. In high-entropy alloys and, in general, in all solids, transport properties are controlled by point defect concentration, which must be known before performing atomistic simulations to compute transport coefficients. In this work, we present a general Langmuir-like model for defect concentration in an arbitrarily complex solid solution and apply this model to generate expressions for concentrations of vacancies and small interstitial atoms. We then calculate the vacancy concentration as a function of temperature in the equiatomic CoNiCrFeMn and FeAl alloys with modified embedded-atom-method potentials for various chemical orderings, showing there is no clear correlation between vacancy thermodynamics and chemical ordering in the CoNiCrFeMn alloy, but clear systematic patterns for FeAl. We believe this is due to the high stability of disordered, random, and ordered intermetallic phases, respectively, in the CoNiCrFeMn and FeAl systems. Finally, this work provides future avenues to the prediction of thermal interstitials and vacancies in solid solutions, which is necessary for models of nonequilibrium behavior of solid solutions.

composition↗
DOE OSTI2024

CHMMPP: A c++ library for constrained Hidden Markov Models

SAND2024-13027O The CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.

Hart, William↗
DOE OSTI2021

BdERECTA controls vasculature patterning and phloem-xylem organization in Brachypodium distachyon

Background: The vascular system of plants consists of two main tissue types, xylem and phloem. These tissues are organized into vascular bundles that are arranged into a complex network running through the plant that is essential for the viability of land plants. Despite their obvious importance, the genes involved in the organization of vascular tissues remain poorly understood in grasses. Results: We studied in detail the vascular network in stems from the model grass Brachypodium distachyon (Brachypodium) and identified a large set of genes differentially expressed in vascular bundles versus parenchyma tissues. To decipher the underlying molecular mechanisms of vascularization in grasses, we conducted a forward genetic screen for abnormal vasculature. We identified a mutation that severely affected the organization of vascular tissues. This mutant displayed defects in anastomosis of the vascular network and uncommon amphivasal vascular bundles. The causal mutation is a premature stop codon in ERECTA, a LRR receptor-like serine/threonine-protein kinase. Mutations in this gene are pleiotropic indicating that it serves multiple roles during plant development. This mutant also displayed changes in cell wall composition, gene expression and hormone homeostasis. Conclusion: In summary, ERECTA has a pleiotropic role in Brachypodium. We propose a major role of ERECTA in vasculature anastomosis and vascular tissue organization in Brachypodium.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Muon capture on deuteron using local chiral potentials

The muon capture reaction μ – + d → n + n + ν μ in the doublet hyperfine state is studied using nuclear potentials and consistent currents derived in the chiral effective field theory, which are local and expressed in coordinate space (the so-called Norfolk models). Only the largest contribution due to the 1 S 0 nn scattering state is considered. Particular attention is given to the estimate of theoretical uncertainty, for which four sources have been identified: 1) the model dependence, 2) the chiral-order convergence for the weak nuclear current, 3) the uncertainty in the single-nucleon axial form factor, and 4) the numerical technique adopted to solve the bound and scattering A = 2 systems. This last source of uncertainty has turned out to be essentially negligible. For the 1 S 0 doublet muon capture rate Γ D ( 1 S 0 ), we obtain Γ D ( 1 S 0 ) = 255.8(0.6) (4.4)(2.9) s –1 , where the three errors come from the first three sources of uncertainty. The value for Γ D ( 1 S 0 ) obtained within this local chiral framework is compared with previous calculations and found in very good agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A comprehensive model to capture electrical discharge and spark channel evolution during spark-ignition processes

Emissions reduction through engine efficiency improvements is a priority for automakers who have turned to unconventional engine operation such as highly dilute, boosted, and stratified charge. Given its importance to flame initiation and sustained turbulent flame propagation, reliable and accurate spark ignition models are necessary to design ignition systems that reduce cyclic indicated mean effective pressure (IMEP) variability and increase engine efficiency in these operation modes. In this paper, secondary electric circuit, short-circuit, blowout, and re-strike sub-models are added to the Lagrangian-Eulerian spark ignition (LESI) model to simulate electrical discharge and spark channel elongation in an inert cross-flow combustion vessel. First, the physics of the underlying sub-models are described and the governing equations discussed with the spark channel voltage expression playing a critical role. Then, the experimental and simulations setups are presented. The results section begins with the derivation of spark channel voltage from experimental results. Then, electrical discharge and spark channel elongation simulations in inert flows are carried out using LESI and compared against experimental results. Finally, the results validate the model's ability to accurately predict spark channel elongation, as well as the occurrence of short-circuits, blowouts, re-strikes, and end of discharge.

42 ENGINEERING↗
DOE OSTI2025

Excited-State Densities from Time-Dependent Density Functional Response Theory

While the variational principle for excited-state energies leads to a route to obtaining excited-state densities from time-dependent density functional theory, relatively little attention has been paid to the quality of the resulting densities in real space obtained with different exchange-correlation functional approximations or how nonadiabatic approximations developed for energies of states of double-excitation character perform for their densities. Here we derive an expression directly in real space for the excited-state density, which includes the case of nonadiabatic kernels and consequently is able, for the first time, to yield densities of states of double-excitation character. Under some well-defined simplifications, we compare the performance of the local-density approximation and exact-exchange approximation, which are in a sense at the opposite extremes of the fundamental functional approximations, on local and charge-transfer excitations in one-dimensional model systems and show that the dressed Time-Dependent Density Functional Theory (TDDFT) approach gives good densities of double excitations.

approximation↗
DOE OSTI2023

Redox-enabled electronic interrogation and feedback control of hierarchical and networked biological systems

Abstract Microelectronic devices can directly communicate with biology, as electronic information can be transmitted via redox reactions within biological systems. By engineering biology’s native redox networks, we enable electronic interrogation and control of biological systems at several hierarchical levels: proteins, cells, and cell consortia. First, electro-biofabrication facilitates on-device biological component assembly. Then, electrode-actuated redox data transmission and redox-linked synthetic biology allows programming of enzyme activity and closed-loop electrogenetic control of cellular function. Specifically, horseradish peroxidase is assembled onto interdigitated electrodes where electrode-generated hydrogen peroxide controls its activity. E. coli ’s stress response regulon, oxyRS , is rewired to enable algorithm-based feedback control of gene expression, including an eCRISPR module that switches cell-cell quorum sensing communication from one autoinducer to another—creating an electronically controlled ‘bilingual’ cell. Then, these disparate redox-guided devices are wirelessly connected, enabling real-time communication and user-based control. We suggest these methodologies will help us to better understand and develop sophisticated control for biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Microcanonical rates from ring-polymer molecular dynamics: Direct-shooting, stationary-phase, and maximum-entropy approaches

We address the calculation of microcanonical reaction rates for processes involving significant nuclear quantum effects using ring-polymer molecular dynamics (RPMD), both with and without electronically non-adiabatic transitions. After illustrating the shortcomings of the naive free-particle direct-shooting method, in which the temperature of the internal ring-polymer modes is set to the translational energy scale, we investigate alternative strategies based on the expression for the microcanonical rate in terms of the inverse Laplace transform of the thermal reaction rate. It is shown that simple application of the stationary-phase approximation (SPA) dramatically improves the performance of the microcanonical rates using RPMD, particularly in the low-energy region where tunneling dominates. Using the SPA as a Bayesian prior, numerically exact RPMD microcanonical rates are then obtained using maximum entropy inversion of the thermal reaction rates for both electronically adiabatic and non-adiabatic model systems. Finally, the direct-shooting method is revisited using the SPA-determined temperature for the internal ring-polymer modes, leading to a simple, direct-simulation method with improved accuracy in the tunneling regime. This work suggests a general strategy for the extraction of microcanonical dynamical quantities from RPMD (or other approximate thermal) simulations.

Tao, Xuecheng↗
DOE OSTI2026

Optimal binning of correlated measurements

Experimental measurements are commonly represented on a discrete grid, requiring a balance between granularity and statistical noise. Two strategies have traditionally been used to improve such representations: selecting an appropriate bin width to control discretization error and applying kernel-based smoothing to suppress fluctuations. Despite their shared goal, these approaches have largely developed independently, without a unified statistical description of how discretization and correlation jointly determine measurement precision. Here, we extend the discussion of optimal interval averaging to a correlation-aware setting by Gaussian process regression, which explicitly accounts for correlations among neighboring bins. Starting from first principles, we derive the mean-squared error of discretized measurements and obtain closed-form asymptotic expressions for the optimal bin width and correlation length. When recast in reduced variables, the theory reveals distinct universal scaling laws governing the error in the correlation-free and correlation-controlled regimes. Characterized by intrinsically smooth intensity profiles and counting-based statistics, neutron scattering measurements are well suited for demonstrating the enhanced error contraction enabled by inter-bin correlations. We show that such improvement is achievable over the experimentally accessible Q-range and across multiple instruments and material systems. These results show that explicitly accounting for correlations systematically reshapes the limits of precision in discretized, noise-limited measurements. More broadly, the framework provides a transferable statistical foundation for optimizing data representation, inference, and experimental design across the physical and data sciences.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2021

Cost targets to achieve commercially viable thermal storage in buildings

To mitigate the variation in demand on the electric grid, thermal energy storage (TES) is an alternative to electric batteries or installing new peaking power plants. Stakeholders and policy makers across the United States have expressed interests in promoting TES, as demonstrated by the US Department of Energy’s Grid-Interactive Efficient Buildings program and the efforts of various state legislatures. However, the cost value provided by TES are unclear. If reliable cost benefits were determined, stakeholders would have a clearer picture of the financial returns that can be gained from their investment in TES. In this report, EnergyPlus was used to perform whole-building simulations for two residential buildings in Indianapolis and Atlanta. The HVAC system in both buildings were equipped with phase change material TES. The TES tank was charged in off-peak hours and discharged in peak hours to perform load shifting. First, the economic value implied by existing time-of-use (TOU) rates offered by utility companies was analyzed via whole-building simulation. Second, existing demand reduction (DR) incentives sourced from 3 different electrical grid administrators (i.e., California, Texas, and New England region) were surveyed to determine their implied value. Lastly, the economic value implied by different types of deferred peak power plants were reviewed. The full value of TES to the entire society consists of value to the utility, OEMs, facility installers, and other stakeholders. This report focuses on the value to the utility with emphasis on the deferred capital of peak power plant. The value from the deferred capital of peak power plant is manifested to the customer in the form of demand reduction program and Time-of-Use utility rate program. In this report, an initial proxy of the value of TES is made by assuming the deferred capital cost of power plant is the full value to reduce peak demand. Three levels of financial value of TES systems were assessed. Two are currently available to some residential customers: (1) the benefit from TOU pricing alone and (2) the benefit from TOU pricing in combination with DR incentive programs. The third level was computed as the full cost of deferred capital cost of peaking power plants. This represents the potential value that could be gained by the utilities or conceivably be offered to consumers.

25 ENERGY STORAGE↗
DOE OSTI2020

Data-Driven Many-Body Models for Molecular Fluids: CO 2 /H 2 O Mixtures as a Case Study

In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO2) and water (H2O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born–Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO 2 –CO 2 and CO 2 –H 2 O dimers and the energetics of small clusters, as well as to correctly reproduce various properties in both gas and liquid phases. Furthermore, building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions.

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

The role of lignin in the conversion of wheat straw to cellobionic acid by Neurospora crassa HL10

An engineered Neurospora crassa strain (HL10) naturally produces cellulases, cellobiose dehydrogenase (CDH), and heterologously expresses laccase. It can convert Avicel (cellulose) to cellobionic acid (cellobionate) without any enzyme addition at high yields. However, the addition of a catalytic amount of artificial redox mediators was required to achieve a high yield conversion. When a lignocellulosic substrate like wheat straw was used as the carbon source, it was found that adding exogenous artificial redox mediators did not improve cellobionate yield. We hypothesized that lignin and lignin degradation products were able to serve as redox mediators for the CDH-laccase conversion system. Experiments were designed to prove the hypothesis. When N. crassa HL10 was grown on Avicel, the addition of enzyme hydrolyzed lignin (EHL) can achieve a similar level of cellobionate production as with ABTS addition. The addition of EHL can increase the cellobionate production rate in the CDH-laccase bi-enzyme system using cellobiose as the substrate. The formation of lignin radicals, and the quenching of lignin radicals by reduced CDH, were verified by an electron paramagnetic resonance (EPR) experiment, providing further evidence that lignin radicals can serve as the electron acceptor of reduced CDH. Hence, lignocellulosic biomass is a self-sufficient substrate for the production of cellobionate. The conversion of the lignocellulosic substrate to cellobionate using N. crassa HL10 can be achieved without any exogenous enzyme addition or redox mediator addition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗