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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 1,099 records · Page 61

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Using GANs to predict milling stability from limited data

Milling is a key manufacturing process that requires the selection of operating parameters that provide efficient performance. However, the presence of chatter, a self-excited vibration causing poor surface finish and potential damage to the machine and cutting tool, makes it challenging to select the appropriate parameters. To predict chatter, stability maps are commonly used, but their generation requires expensive data, making it difficult to employ these maps in industry. Therefore, there is a pressing need for an approach that can accurately predict stability maps using limited experimental data. This study introduces the new Encoder GAN (EGAN) approach based on Generative Adversarial Networks (GANs) that predicts stability maps using limited experimental data. The approach consists of the encoder, generator, and discriminator subnetworks and uses the trained encoder and generator to predict the target stability map. This versatile method can be applied to various tool setups and can accurately predict stability maps with limited experimental data (five to 10 cutting tests) even when there is little information available for unknown parameters. In conclusion, the study evaluates the proposed approach using both numerical data and experiments and demonstrates its superior performance compared to state-of-the-art benchmarks.

42 ENGINEERING↗

DOE OSTI2025

Using radioactive material to evaluate decontamination of contaminated electronics

Electronic materials are used everywhere and can get easily contaminated by their use in the field/laboratory. The goal of this project was to use radioactive material to track the effectiveness of a cleaning procedure using an off-the-shelf cleaning gel. Radioactive potassium bromide (KBr) was used as a model contaminant in four contamination scenarios to gauge the effectiveness of a cleaning gel in the decontamination of contaminated raspberry pi’s. Finally, the investigated decontamination technique was found to be 75–97% effective in removing contamination from the tested electronic devices. 95% of the contaminated electronic devices retained their functionality post-decontamination.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗

DOE OSTI2024

Storage and persistence of organic carbon in the upper three meters of soil under arable and native prairie land use

Aims: Land use change from native grasslands to arable lands globally impacts soil ecosystem functions, including the storage of soil organic carbon (SOC). Understanding the factors affecting SOC changes in topsoil and subsoil due to land use is crucial for effective mitigation strategies. We determined SOC storage and persistence as affected by land use change from native prairies to arable lands. Methods: Here we examined SOC stocks, soil δ 13 C and Δ 14 C signatures, microbial communities (bacteria and fungi), and soil mineral characteristics under native prairies and long-term arable lands (i.e., > 40 years) down to 3 m in the U.S. Midwest. Results: Native prairie soils had higher SOC stocks in the A horizon and 0–50 cm depth increment than arable soils. For both land use types, the δ 13 C and Δ 14 C values significantly decreased with depth, with the latter pointing towards highly stabilized SOC, especially in the B- and C-horizons. Analysis of the microbial communities indicated that the diversity of bacteria and fungi decreased with increasing soil depth. The content of oxalate soluble Al appeared to be the single most important predictor of SOC across horizons and land use types. Conclusion: Our data suggest that most SOC gains and losses and transformation and translocation processes seem to be restricted to the uppermost 50 cm. Increasing SOC retention in the A and B horizons within the 0–50 cm depth would enhance organic material serving as substrate and nutrients for microbes and plants (A horizon) and facilitate long-term SOC storage in the subsoil (B horizon).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Impact of a Low-Intensity Resource Referral Intervention on Patients’ Knowledge, Beliefs, and Use of Community Resources: Results from the CommunityRx Trial

Background: Connecting patients to community-based resources is now a cornerstone of modern healthcare that supports self-management of health. The mechanisms that connect resource information to behavior change, however, remain poorly understood. Objective: To evaluate the impact of CommunityRx, an automated, low-intensity resource referral intervention, on patients' knowledge, beliefs, and use of community resources. Design: Real-world controlled clinical trial at an urban academic medical center in 2015-2016; participants were assigned by alternating week to receive the CommunityRx intervention or usual care. Surveys were administered at baseline, 1 week, 1 month, and 3 months. Participants: Publicly insured adults, ages 45-74 years. Intervention: CommunityRx generated an automated, personalized list of resources, known as HealtheRx, near each participant's home using condition-specific, evidence-based algorithms. Algorithms used patient demographic and health characteristics documented in the electronic health record to identify relevant resources from a comprehensive, regularly updated database of health-related resources in the study area. Main Measures: Using intent-to-treat analysis, we examined the impact of HealtheRx referrals on (1) knowledge of the most commonly referred resource types, including healthy eating classes, individual counseling, mortgage assistance, smoking cessation, stress management, and weight loss classes or groups, and (2) beliefs about having resources in the community to manage health. Key Results: In a real-world controlled trial of 374 adults, intervention recipients improved knowledge (AOR = 2.15; 95% CI, 1.29-3.58) and beliefs (AOR = 1.68; 95% CI, 1.07-2.64) about common resources in the community to manage health, specifically gaining knowledge about smoking cessation (AOR = 2.76; 95% CI, 1.07-7.12) and weight loss resources (AOR = 2.26; 95% CI 1.05-4.84). Positive changes in both knowledge and beliefs about community resources were associated with higher resource use (P = 0.02). Conclusions: In a middle-age and older population with high morbidity, a low-intensity health IT intervention to deliver resource referrals promoted behavior change by increasing knowledge and positive beliefs about community resources for self-management of health. NIH Trial Registry: NCT02435511

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Towards an Integrated Process for CO 2 Capture and Utilization: Cultivation of Scenedesmus acutus Using Gaseous CO 2 and NH 3

Integrating CO 2 scrubbing from flue gas with its utilization in algae cultivation represents a potential means of lowering the cost of CO 2 capture. Towards this goal, this study sought to assess the feasibility of using gaseous a CO 2 /NH 3 stream, derived from CO 2 capture using aqueous ammonia, as a C- and N-source for algae cultivation. Scenedesmus acutus was cultured in 800 mL photobioreactors using gaseous CO 2 /NH 3 in mole ratios varying from 7 to 18. Excellent growth of Scenedesmus acutus was observed, the average growth rate for CO 2 /NH 3 = 10 of 0.171 ± 0.015 g/L·day exceeding that obtained using 1% CO 2 /N 2 and urea as the N-source (0.099 ± 0.28 g/L·day). Under optimal growth conditions (CO 2 /NH 3 mole ratio of 10), CO 2 utilization ranged from 57% to 72%, while the NH 3 utilization was >90%. The CO 2 /NH 3 feed rate was also found to exert a significant effect on algae productivity, excessive feed rates leading to accumulation of NH 3 in the culture at concentrations that were toxic to the algae. Consequently, to avoid the toxic effects of high NH 3 concentrations (>2.0 mM), it proved necessary to balance the NH 3 supply with the algae growth rate so that excessive NH 3 accumulation was prevented. This indicates that for practical applications, a CO 2 /NH 3 feed control strategy would be required that takes into account the ammonium ion concentration in solution and the pH so as to avoid significant concentrations of free NH 3 . Furthermore, analysis of the harvested biomass revealed a high protein (≥ 47 wt%) and a low ash content (< 3.6 wt%), suggesting it would be well suited for use as animal feed or as a feedstock for the production of bioplastics.

03 NATURAL GAS↗

DOE OSTI2019

Screening of the Suzuki Cross-Coupling Reaction Using Desorption Electrospray Ionization in High-Throughput and in Leidenfrost Droplet Experiments

Suzuki cross-coupling is a widely performed reaction, typically using metal catalysts under heated conditions. Acceleration of the Suzuki cross-coupling reaction has been previously explored in microdroplets using desorption electrospray ionization mass spectrometry (DESI-MS). Building upon previous work, presented here is the use of a high-throughput DESI-MS screening system to identify optimal reaction conditions. Multiple reagents, bases, and stoichiometries were screened using the automated system at rates that approach 10,000 reaction mixture systems per hour. The DESI-MS system utilizes reaction acceleration in microdroplets to allow rapid screening. The results of screening of an array of reaction mixtures using this technique are presented as product ion images via standard MS imaging software, facilitating quick readout. Instructive comparisons are provided with another method of generating droplets for reaction acceleration—the Leidenfrost technique. Acceleration factors greater than 200 were measured for brominated substrates, paralleling the DESI-MS results. Acceleration factors dropped to near unity with highly substituted pyridines, attributable to a steric effect. The reaction proceeded in the absence of a base in Leidenfrost droplets although no product formation was seen without base in the bulk or in the DESI-MS screening experiments. These differences between Leidenfrost chemistry and the bulk and in droplets formed in high-throughput DESI are tentatively attributed to extremes of pH associated with the surfaces of Leidenfrost droplets. .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Accurate Effective Stress Measures: Predicting Creep Life for 3D Stresses Using 2D and 1D Creep Rupture Simulations and Data

Operating structural components experience complex loading conditions resulting in 3D stress states. Current design practice estimates multiaxial creep rupture life by mapping a general state of stress to a uniaxial creep rupture correlation using effective stress measures. The data supporting the development of effective stress measures are nearly always only uniaxial and biaxial, as 3D creep rupture tests are not widely available. This limitation means current effective stress measures must extrapolate from 2D to 3D stress states, potentially introducing extrapolation error. In this work, we use a physics-based, crystal plasticity finite element model to simulate uniaxial, biaxial, and triaxial creep rupture. Here, we use the virtual dataset to assess the accuracy of current and novel effective stress measures in extrapolating from 2D to 3D stresses and also explore how the predictive accuracy of the effective stress measures might change if experimental 3D rupture data was available. We confirm these conclusions, based on simulation data, against multiaxial creep rupture experimental data for several materials, drawn from the literature. The results of the virtual experiments show that calibrating effective stress measures using triaxial test data would significantly improve accuracy and that some effective stress measures are more accurate than others, particularly for highly triaxial stress states. Results obtained using experimental data confirm the numerical findings and suggest that a unified effective stress measure should include an explicit dependence on the first stress invariant, the maximum tensile principal stress, and the von Mises stress.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models

This paper presents an uncertainty quantification (UQ) framework for the physics-based model prediction of material response with a large number of parameters. The application problem presented in this work is that of predicting creep in Grade 91 steel at 600°C. The material response is defined with a physically based microstructural model with constitutive equations emulating several observed phenomena in Grade 91 and embodied into an explicit geometry mesoscale finite element model for prior austenite grains and grain boundaries. Creep within the grains and in grain boundaries are represented by crystal plasticity for dislocation motion and a physics-based model for cavity growth and nucleation, respectively. The creep behavior of this material is influenced by several parameters, some of which have a wide range of variation based on experimental data. UQ combined with microstructural modeling can discover the core microstructural causes of experimental variability, leading to improved materials with lower variability in critical long-term material properties. In this study, we investigate the model's uncertainty to identify material properties that may be modified during production to increase creep life and analyze different components of the crystal plasticity model for improvements. For this purpose, a quantity of interest is defined as time to minimum creep rate, which correlates well to the creep failure of the material. A deep neural network model was trained and validated to be used as a surrogate for the finite element model. Then, a variance-based sensitivity analysis is performed on the surrogate model to find the Sobol indices of the input parameters in respect to the output quantity of interest. The Sobol indices are used to reduce the dimensionality of the model. Generalized polynomial chaos expansion is used on the reduced basis models to propagate the uncertainty from the input parameters to the quantity of interest using the deep neural network surrogate model. These results are benchmarked against uncertainty propagation using Monte Carlo simulations. In conclusion, the UQ performed through the reduced basis model captures almost all the uncertainty in the model with significantly fewer simulations, making it possible to perform the UQ directly via simulations with the finite element model rather than surrogate machine-learned models.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Additively Manufactured Single-Use Molds and Reusable Patterns for Large Automotive and Hydroelectric Components

Additive manufacturing (AM) has the potential to reduce costs in the casting industry, particularly for large parts (i.e., components with any dimension > 12 in.). In this study, pilot-scale production case studies of hydroelectric and automotive parts were used to evaluate two AM-enabled casting methods: the direct printing of sand molds by binder jet and printing of reusable cope and drag patterns for sand casting. An additional benefit was found when additively manufactured patterns were used in combination with heat-treat free aluminum alloys, to produce castings of complex hydrodynamic surfaces. These parts previously required production via subtractive machining due to part distortion induced by the quench step of heat treatments. The machine types used for the three case studies are sand-binder jet, high-resolution polymer fused deposition modeling (FDM), and big area additive manufacturing (BAAM) FDM in combination with CNC machining. Each method demonstrated distinct advantages over traditional casting practices in particular use cases. Single-use molds show great reductions in start-up cost to produce one-off or legacy parts, and additively manufactured impression patterns show promise for innovating the tooling design process for complex geometry and large castings.

36 MATERIALS SCIENCE↗

DOE OSTI2021

The use of teledentistry in facilitating oral health for older adults: A scoping review

Teledentistry is used in many countries to provide oral health care services. However, using teledentistry to provide oral health care services for older adults is not well documented. This knowledge gap needs to be addressed, especially when accessing a dental clinic is not possible and teledentistry might be the only way for many older adults to receive oral health care services. Nine databases were searched and 3,396 studies were screened using established eligibility criteria. Included studies were original research or review articles in which the intervention of interest was delivered to an older adult population (≥ 60 years) via teledentistry. The authors followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review criteria. Nineteen studies were identified that met the criteria for inclusion. Only 1 study was from the United States. Seven studies had results focusing on older adult participants only, with most of those conducted in elder care facilities. The remainder consisted of studies with mixed-age populations reporting distinct results or information for older adults. The included studies used teledentistry, in both synchronous and asynchronous modes, to provide services such as diagnosis, oral hygiene promotion, assessment and referral of oral emergencies, and postintervention follow-up. Teledentistry comprises a variety of promising apps. Lastly, the authors identified and described uses, promising possibilities, and limitations of teledentistry to improve the oral health of older adults.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Rapid determination of supercritical CO 2 and brine relative permeability using an unsteady-state flow method

In this study, relative permeability of supercritical CO 2 (scCO 2 ) and brine was determined in reactive and non-reactive rock cores using a combination of unsteady-state methodology and computed tomography. Experiments were conducted using a medical grade CT scanner to determine saturation using a custom Python script. The saturation and differential pressure across the core were then used to derive four empirical constants to calculate relative permeability. This methodology increases temporal efficiency while reducing experimental complexity. Additionally, we show that the method can be used to determine scCO 2 relative permeability in a wide range of lithologies and flow rates, and with the ability to account for matrix dissolution during scCO 2 flooding.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Numerical simulation of involute-plate research reactor flow behavior using RANS, LES and DNS

This paper investigates the flow behavior of involute-plate research reactors by performing Reynolds-Averaged Navier Stokes simulation (RANS), Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) of the channel flow between fuel plates. By modeling turbulence with different numerical approaches, this study provides data with three levels of fidelity. For the RANS simulation, three widely used turbulence models, i.e., k-ε, k-ω, Reynolds Stress Turbulence model (RST) are applied by using the commercial CFD code STAR-CCM +. For LES and DNS, the open-source CFD code, Nek5000, is used given its outstanding scalability on High Performance Computer (HPC) and high-order technique. The results from RANS simulations are compared with that from LES and DNS for benchmarking. Both macroscale parameters and turbulence statistics, such as velocity magnitude, lateral velocity and turbulence kinetic energy, are presented and analyzed. The results from RANS simulation achieve good agreement with LES and DNS on velocity and turbulence kinetic energy prediction. The RST turbulence model predicts the most similar flow pattern of lateral velocity as compared to LES and DNS. The Lambda-2 (λ2) criterion with a reasonable threshold is used to demonstrate the instantaneous vortices distribution in the involute channel from both LES and DNS calculation. The DNS simulation captures more detailed turbulence especially near the corner, which explains the discrepancy between LES and DNS results near the corner. The normalized RMS error are defined and calculated to assess the performance of those turbulence models. The RST model captures the anisotropic feature of turbulence, which enable it to outperform other turbulence models for predicting the flow behavior in an involute channel. Although some discrepancies are found between LES and DNS results in the corner, the overall deviations between LES and DNS are found to be small. In conclusion, given that the computational cost of DNS calculation is an order of magnitude higher, using LES data for benchmarking RANS model is a cost-effective approach.

DNS↗

DOE OSTI2024

A study on the impact of using a subchannel resolution for modeling of large break loss of coolant accidents

The nuclear industry is investigating the feasibility of transitioning from 18- to 24-month fuel cycles because of the positive impact it would have on the operational costs for the current fleet of light-water reactors. A challenge to making this change is the increased risk of fuel fragmentation, relocation, and dispersal (FFRD) due to the known potential for ceramic fuel to pulverize into fine particles at the higher discharge burnups. Previous work has been performed by the Nuclear Energy Advanced Modeling and Simulation program to assess FFRD risk in high-burnup cores using the BISON fuel performance code and a coarse mesh thermal hydraulics (T/H) solution for a loss-of-coolant accident (LOCA) using the TRACE system T/H code. Because of the importance of the T/H solution for FFRD assessment, this study seeks to investigate the impact of using higher-fidelity subchannel techniques for modeling of the LOCA transient. CTF was used to model a subregion of a high-burnup core that was depleted by the Virtual Environment for Reactor Applications (VERA) multiphysics core simulator. Both coarse-mesh and pin-resolved models were created in CTF, and a consistent coarse-mesh TRACE model was also developed to allow for benchmarking the code results. Further, a large-break loss-of-coolant accident (LBLOCA) reflood transient was simulated using these three models, and results were compared. Results showed some consistent differences between the CTF and TRACE coarse models, including a higher peak cladding temperature (PCT) prediction in CTF and later quenching in CTF; however, the transient clad temperature behavior was similar, and these differences are likely due to post-critical heat flux heat transfer modeling differences and minimum film boiling temperature model differences. The pin-resolved results indicate that the PCT in the lumped model is often under-predicted by as much as 70 °C and that PCT occurs at a different location than the high-power pin in the assembly. The lumped model predicts a difference of 10 °C or less between the average and hot pins in the assembly, whereas the pin-resolved model predicts a range of over 100 °C. These results indicate that higher-fidelity T/H results may have an impact on predicted core behavior during LOCA, which may be important to consider when assessing FFRD risk.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Evaluating the Feasibility of Transactive Approach for Voltage Management Using Inverters of a PV Plant

This article evaluates the feasibility of a double-auction-based Transactive Energy System (TES) for engaging the reactive power (Var) capability of inverters in a utility-scale pho¬tovoltaic (PV) plant for voltage management in distribution feed¬ers. In this approach, a PV plant owner (seller) provides Var supply curves in terms of price-quantity pairs consider¬ing the inverters’ P-Q capability, efficiency, opportunity cost for real power curtail¬ment, losses, etc. At the same time, the utility (buyer) proposes Var demand curves in price-quantity pairs exhibiting the marginal price of Var. Then, market clearing points are obtained from the intersection points of supply and demand curves which are then used to create Var dispatch sig-nals from the PV plant. To conduct a fea¬sibility study of this approach, an Australian distribution network with a utility-scale PV plant (capacity 3.275 MWP) is modeled in RSCAD and simu¬lated in real-time on MATLAB, RSCAD-RTDS co-simulation platform using real historical data. Consid¬ering a use case, namely, conservation voltage reduction (CVR), the operational feasibility along with cost-benefit analysis is demonstrated in software-in-the-loop (SIL) and hardware-in-the-loop (HIL) platform. Another use case, exploring the benefit from tap-change reduction of step-voltage-regulator, is investigated. These studies explore further use cases, e.g., PV hosting capacity, network reconfiguration, etc., to be incorporated in TES for experiencing substantial economic benefits.

Alam, Mollah Rezaul↗

DOE OSTI2025

Selective recovery of native copper from basalt tailings using alkaline glycinate solution

Mafic and ultramafic rocks present an intriguing pathway for CO 2 capture through strategic enhancements to the natural silicate weathering cycle. Simultaneously, these rock types are often hosts to appreciable amounts of metals critical to U.S. energy independence, particularly in the context of alkaline mine tailings from historical metal mining. The research and scientific prerogative, then, is to identify promising mafic and ultramafic feedstocks and conduct exploratory studies to effectively recover these critical minerals while preserving the potential for mineral carbonation. The Keweenaw Peninsula of Michigan hosts the largest native Cu reservoir within basalt in the world and experienced a rich history of Cu production spanning from pre-historic times to the mid-1900s. Today, much of the Cu mining legacy remains as mine waste tailings. In this study, we examined the Cu extractability from Keweenaw Basalt tailings using a sodium glycinate solution, in comparison with acid and sodium hydroxide leaching. Experimental results showed an 85 % Cu extraction rate using sodium glycinate as the extraction solution with negligible release of other cations from the basalt. The kinetic and extraction mechanisms of Cu selective recovery using glycinate solution were discussed using time-resolved experimental data and kinetic geochemical modeling. Theoretical estimation of carbon mineralization potential of all the existing basalt waste tailings (∼500 million tons) can reach 85.5 MMT CO 2 . A total of 0.786 MMT Cu can be recovered with sodium glycinate, with a value of 7.7 billion USD. In conclusion, this novel application of alkaline glycinate for selective Cu recovery from basalt mine tailings demonstrates the viability of selective metal recovery using a non-hazardous chemical while preserving CO 2 capture potential and presents a potential pathway toward reducing energy-related emissions and providing an unconventional domestic source of critical minerals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗

DOE OSTI2019

Mobile sensing of point-source gas emissions using Bayesian inference: An empirical examination of the likelihood function

This paper evaluates likelihood function forms for Bayesian inference of point-source gas emissions using a mobile sensor. Whereas Bayesian inference has been successfully used to estimate emission rates from time-averaged concentration data measured by stationary sensors, data collected by mobile sensors do not represent ensemble or time-averaged conditions. To examine the potential impact of this contrast, controlled release experiments were conducted with a mobile sensor measuring concentrations repeatedly along transverse cross sections of the downwind plumes. Experiments were conducted with measurements made at different downwind distances, different sensor heights, and with different obstacle states. An examination is made between two commonly-used likelihood functions, the Gaussian and the log-normal. For experiments conducted in the absence of obstacles, the Bayesian estimates using the log-normal likelihood function yield a much smaller bias than those based on the Gaussian likelihood function. This finding is consistent with the non-Gaussian nature of concentration fluctuations near a point-source. For experiments conducted in the presence of obstacles, the Bayesian inference based on the Gaussian likelihood function exhibits a better performance. This can be explained by the enhanced turbulent mixing due to the obstacle-introduced wake eddies. Overall, we find that the selection of the likelihood function can be physically related to the underlying conditions, and the proper selection is critical to ensure the performance of the Bayesian inference for source characterization using mobile sensing data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion

NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a “sample and select” method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls ( 1 H, 15 N, and 13 C'). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗