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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SPECT Analysis of Cardiac Perfusion Changes After Whole-Breast/Chest Wall Radiation Therapy With or Without Active Breathing Coordinator: Results of a Randomized Phase 3 Trial

Purpose: Cardiac muscle perfusion, as determined by single-photon emission computed tomography (SPECT), decreases after breast and/or chest wall (BCW) irradiation. The active breathing coordinator (ABC) enables radiation delivery when the BCW is farther from the heart, thereby decreasing cardiac exposure. We hypothesized that ABC would prevent radiation-induced cardiac toxicity and conducted a randomized controlled trial evaluating myocardial perfusion changes after radiation for left-sided breast cancer with or without ABC. Methods and Materials: Stages I to III left breast cancer patients requiring adjuvant radiation therapy (XRT) were randomized to ABC or No-ABC. Myocardial perfusion was evaluated by SPECT scans (before and 6 months after BCW radiation) using 2 methods: (1) fully automated quantitative polar mapping; and (2) semiquantitative visual assessment. The left ventricle was divided into 20 segments for the polar map and 17 segments for the visual method. Segments were grouped by anatomical rings (apical, mid, basal) or by coronary artery distribution. For the visual method, 2 nuclear medicine physicians, blinded to treatment groups, scored each segment's perfusion. Scores were analyzed with nonparametric tests and linear regression. Results: Between 2006 and 2010, 57 patients were enrolled and 43 were available for analysis. The cohorts were well matched. The apical and left anterior descending coronary artery segments had significant decreases in perfusion on SPECT scans in both ABC and No-ABC cohorts. In unadjusted and adjusted analyses, controlling for pretreatment perfusion score, age, and chemotherapy, ABC was not significantly associated with prevention of perfusion deficits. Conclusions: In this randomized controlled trial, ABC does not appear to prevent radiation-induced cardiac perfusion deficits.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Evaluating the Impact of a Canadian National Anatomy and Radiology Contouring Boot Camp for Radiation Oncology Residents

Background: Radiation therapy treatment planning has advanced over the past 2 decades, with increased emphasis on 3-dimensional imaging for target and organ-at-risk (OAR) delineation. Recent studies suggest a need for improved resident instruction in this area. We developed and evaluated an intensive national educational course (“boot camp”) designed to provide dedicated instruction in site-specific anatomy, radiology, and contouring using a multidisciplinary (MDT) approach. Methods: The anatomy and radiology contouring (ARC) boot camp was modeled after prior single-institution pilot studies and a needs-assessment survey. The boot camp incorporated joint lectures from radiation oncologists, anatomists, radiologists, and surgeons, with hands-on contouring instruction and small group interactive seminars using cadaveric prosections and correlative axial radiographs. Outcomes were evaluated using pretesting and posttesting, including anatomy/radiology multiple-choice questions (MCQ), timed contouring sessions (evaluated relative to a gold standard using Dice similarity metrics), and qualitative questions on satisfaction and perceived effectiveness. Analyses of pretest versus posttest scores were performed using nonparametric paired testing. Results: Twenty-nine radiation oncology residents from 10 Canadian universities participated. As part of their current training, 29%, 75%, and 21% receive anatomy, radiology, and contouring instruction, respectively. On posttest scores, the MCQ knowledge scores improved significantly (pretest mean 60% vs posttest mean 80%, P<.001). Across all contoured structures, there was a 0.20 median improvement in students' average Dice score (P<.001). For individual structures, significant Dice improvements occurred in 10 structures. Residents self-reported an improved ability to contour OARs and interpret radiographs in all anatomic sites, 92% of students found the MDT format effective for their learning, and 93% found the boot camp more effective than educational sessions at their own institutions. All of the residents (100%) would recommend this course to others. Conclusions: The ARC boot camp is an effective intervention for improving radiation oncology residents' knowledge and understanding of anatomy and radiology in addition to enhancing their confidence and accuracy in contouring.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

MicroRNA-Related DNA Repair/Cell-Cycle Genes Independently Associated With Relapse After Radiation Therapy for Early Breast Cancer

Purpose: Local recurrence and distant failure after adjuvant radiation therapy for breast cancer remain significant clinical problems, incompletely predicted by conventional clinicopathologic markers. We had previously identified microRNA-139-5p and microRNA-1274a as key regulators of breast cancer radiation response in vitro. The purpose of this study was to investigate standard clinicopathologic markers of local recurrence in a contemporary series and to establish whether putative target genes of microRNAs involved in DNA repair and cell cycle control could better predict radiation therapy response in vivo. Methods and Materials: With institutional ethics board approval, local recurrence was measured in a contemporary, prospectively collected series of 458 patients treated with radiation therapy after breast-conserving surgery. Additionally, independent publicly available mRNA/microRNA microarray expression datasets totaling >1000 early-stage breast cancer patients, treated with adjuvant radiation therapy, with >10 years of follow-up, were analyzed. The expression of putative microRNA target biomarkers—TOP2A, POLQ, RAD54L, SKP2, PLK2, and RAG1—were correlated with standard clinicopathologic variables using 2-sided nonparametric tests, and to local/distant relapse and survival using Kaplan-Meier and Cox regression analysis. Results: We found a low rate of isolated local recurrence (1.95%) in our modern series, and that few clinicopathologic variables (such as lymphovascular invasion) were significantly predictive. In multiple independent datasets (n>1000), however, high expression of RAD54L, TOP2A, POLQ, and SKP2 significantly correlated with local recurrence, survival, or both in univariate and multivariate analyses (P<.001). Low RAG1 expression significantly correlated with local recurrence (multivariate, P=.008). Additionally, RAD54L, SKP2, and PLK2 may be predictive, being prognostic in radiation therapy–treated patients but not in untreated matched control individuals (n=107; P<.05). Conclusions: Biomarkers of DNA repair and cell cycle control can identify patients at high risk of treatment failure in those receiving radiation therapy for early breast cancer in independent cohorts. These should be further investigated prospectively, especially TOP2A and SKP2, for which targeted therapies are available.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion

Purpose: Defining prostate cancer (PCa) lesion clinical target volumes (CTVs) for multiparametric magnetic resonance imaging (mpMRI) could support focal boosting or treatment to improve outcomes or lower morbidity, necessitating appropriate CTV margins for mpMRI-defined gross tumor volumes (GTVs). This study aimed to identify CTV margins yielding 95% coverage of PCa tumors for prospective cases with high likelihood. Methods and Materials: Twenty-five men with biopsy-confirmed clinical stage T1 or T2 PCa underwent pre-prostatectomy mpMRI, yielding T2-weighted, dynamic contrast-enhanced, and apparent diffusion coefficient images. Digitized whole-mount histology was contoured and registered to mpMRI scans (error ≤2 mm). Four observers contoured lesion GTVs on each mpMRI scan. CTVs were defined by isotropic and anisotropic expansion from these GTVs and from multiparametric (unioned) GTVs from 2 to 3 scans. Histologic coverage (proportions of tumor area on co-registered histology inside the CTV, measured for Gleason scores [GSs] ≥6 and ≥7) and prostate sparing (proportions of prostate volume outside the CTV) were measured. Nonparametric histologic-coverage prediction intervals defined minimal margins yielding 95% coverage for prospective cases with 78% to 92% likelihood. Results: On analysis of 72 true-positive tumor detections, 95% coverage margins were 9 to 11 mm (GS ≥ 6) and 8 to 10 mm (GS ≥ 7) for single-sequence GTVs and were 8 mm (GS ≥ 6) and 6 mm (GS ≥ 7) for 3-sequence GTVs, yielding CTVs that spared 47% to 81% of prostate tissue for the majority of tumors. Inclusion of T2-weighted contours increased sparing for multiparametric CTVs with 95% coverage margins for GS ≥6, and inclusion of dynamic contrast-enhanced contours increased sparing for GS ≥7. Anisotropic 95% coverage margins increased the sparing proportions to 71% to 86%. Conclusions: Multiparametric magnetic resonance imaging–defined GTVs expanded by appropriate margins may support focal boosting or treatment of PCa; however, these margins, accounting for interobserver and intertumoral variability, may preclude highly conformal CTVs. Multiparametric GTVs and anisotropic margins may reduce the required margins and improve prostate sparing.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A Voxel-Based Approach to Explore Local Dose Differences Associated With Radiation-Induced Lung Damage

Purpose: To apply a voxel-based (VB) approach aimed at exploring local dose differences associated with late radiation-induced lung damage (RILD). Methods and Materials: An interinstitutional database of 98 patients who were Hodgkin lymphoma (HL) survivors treated with postchemotherapy supradiaphragmatic radiation therapy was analyzed in the study. Eighteen patients experienced late RILD, classified according to the Radiation Therapy Oncology Group scoring system. Each patient's computed tomographic (CT) scan was normalized to a single reference case anatomy (common coordinate system, CCS) through a log-diffeomorphic approach. The obtained deformation fields were used to map the dose of each patient into the CCS. The coregistration robustness and the dose mapping accuracy were evaluated by geometric and dose scores. Two different statistical mapping schemes for nonparametric multiple permutation inference on dose maps were applied, and the corresponding P<.05 significance lung subregions were generated. A receiver operating characteristic (ROC)-based test was performed on the mean dose extracted from each subregion. Results: The coregistration process resulted in a geometrically robust and accurate dose warping. A significantly higher dose was consistently delivered to RILD patients in voxel clusters near the peripheral medial-basal portion of the lungs. The area under the ROC curves (AUC) from the mean dose of the voxel clusters was higher than the corresponding AUC derived from the total lung mean dose. Conclusions: We implemented a framework including a robust registration process and a VB approach accounting for the multiple comparison problem in dose-response modeling, and applied it to a cohort of HL survivors to explore a local dose–RILD relationship in the lungs. Patients with RILD received a significantly greater dose in parenchymal regions where low doses (∼6 Gy) were delivered. Interestingly, the relation between differences in the high-dose range and RILD seems to lack a clear spatial signature.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Benchmark Credentialing Results for NRG-BR001: The First National Cancer Institute-Sponsored Trial of Stereotactic Body Radiation Therapy for Multiple Metastases

Purpose: The NRG-BR001 trial is the first National Cancer Institute–sponsored trial to treat multiple (range 2-4) extracranial metastases with stereotactic body radiation therapy. Benchmark credentialing is required to ensure adherence to this complex protocol, in particular, for metastases in close proximity. The present report summarizes the dosimetric results and approval rates. Methods and Materials: The benchmark used anonymized data from a patient with bilateral adrenal metastases, separated by <5 cm of normal tissue. Because the planning target volume (PTV) overlaps with organs at risk (OARs), institutions must use the planning priority guidelines to balance PTV coverage (45 Gy in 3 fractions) against OAR sparing. Submitted plans were processed by the Imaging and Radiation Oncology Core and assessed by the protocol co-chairs by comparing the doses to targets, OARs, and conformity metrics using nonparametric tests. Results: Of 63 benchmarks submitted through October 2015, 94% were approved, with 51% approved at the first attempt. Most used volumetric arc therapy (VMAT) (78%), a single plan for both PTVs (90%), and prioritized the PTV over the stomach (75%). The median dose to 95% of the volume was 44.8 ± 1.0 Gy and 44.9 ± 1.0 Gy for the right and left PTV, respectively. The median dose to 0.03 cm{sup 3} was 14.2 ± 2.2 Gy to the spinal cord and 46.5 ± 3.1 Gy to the stomach. Plans that spared the stomach significantly reduced the dose to the left PTV and stomach. Conformity metrics were significantly better for single plans that simultaneously treated both PTVs with VMAT, intensity modulated radiation therapy, or 3-dimensional conformal radiation therapy compared with separate plans. No significant differences existed in the dose at 2 cm from the PTVs. Conclusions: Although most plans used VMAT, the range of conformity and dose falloff was large. The decision to prioritize either OARs or PTV coverage varied considerably, suggesting that the toxicity outcomes in the trial could be affected. Several benchmarks met the dose-volume histogram metrics but produced unacceptable plans owing to low conformity. Dissemination of a frequently-asked-questions document improved the approval rate at the first attempt. Benchmark credentialing was found to be a valuable tool for educating institutions about the protocol requirements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Gradient-based optimization for regression in the functional tensor-train format

Predictive analysis of complex computational models, such as uncertainty quantification (UQ), must often rely on using an existing database of simulation runs. In this paper we consider the task of performing low-multilinear-rank regression on such a database. Specifically we develop and analyze an efficient gradient computation that enables gradient-based optimization procedures, including stochastic gradient descent and quasi-Newton methods, for learning the parameters of a functional tensor-train (FT). We compare our algorithms with 22 other nonparametric and parametric regression methods on 10 real-world data sets and show that for many physical systems, exploiting low-rank structure facilitates efficient construction of surrogate models. Here, we use a number of synthetic functions to build insight into behavior of our algorithms, including the rank adaptation and group-sparsity regularization procedures that we developed to reduce overfitting. Finally we conclude the paper by building a surrogate of a physical model of a propulsion plant on a naval vessel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Historical trends and extremes in boreal Alaska river basins

Climate change will shift the frequency, intensity, duration and persistence of extreme hydroclimate events and have particularly disastrous consequences in vulnerable systems such as the warm permafrost-dominated Interior region of boreal Alaska. This work focuses on recent research results from nonparametric trends and nonstationary generalized extreme value (GEV) analyses at eight Interior Alaskan river basins for the past 50/60 years (1954/64–2013). Trends analysis of maximum and minimum streamflow indicates a strong (>+50%) and statistically significant increase in 11-day flow events during the late fall/winter and during the snowmelt period (late April/mid-May), followed by a significant decrease in the 11-day flow events during the post-snowmelt period (late May and into the summer). The April–May–June seasonal trends show significant decreases in maximum streamflow for snowmelt dominated systems (<–50%) and glacially influenced basins (–24% to –33%). Annual maximum streamflow trends indicate that most systems are experiencing declines, while minimum flow trends are largely increasing. Nonstationary GEV analysis identifies time-dependent changes in the distribution of spring extremes for snowmelt dominated and glacially dominated systems. Temperature in spring influences the glacial and high elevation snowmelt systems and winter precipitation drives changes in the snowmelt dominated basins. The Pacific Decadal Oscillation was associated with changes occurring in snowmelt dominated systems, and the Arctic Oscillation was linked to one lake dominated basin, with half of the basins exhibiting no change in response to climate variability. The paper indicates that broad scale studies examining trend and direction of change should employ multiple methods across various scales and consider regime dependent shifts to identify and understand changes in extreme streamflow within boreal forested watersheds of Alaska.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A semiparametric latent factor model for large scale temporal data with heteroscedasticity

Large scale temporal data have flourished in a vast array of applications, and their sophisticated structures, especially the heteroscedasticity among subjects with inter- and intra-temporal dependence, have fueled a great demand for new statistical models. In this paper, with covariate information, we consider a flexible model for large scale temporal data with subject-specific heteroscedasticity. Formally, the model employs latent semiparametric factors to simultaneously account for the subject-specific heteroscedasticity and the contemporaneous and/or serial correlations. The subject-specific heteroscedasticity is modeled as the product of the unobserved factor process and subject’s covariate effect, which is further characterized via additive models. For estimation, we propose a two-step procedure. First, the latent factor process and nonparametric loading are recovered through projection-based methods, and following, we estimate the regression components by approaches motivated from the generalized least squares. By scrupulously examining the non-asymptotic rates for recovering the factor process and its loading, we show the consistency and efficiency of estimated regression coefficients in the absence of prior knowledge of latent factor process and subject’s covariate effect. Here, the statistical guarantees remain valid even for finite time points that makes our method particularly appealing when the subjects significantly outnumber the observation time points. Using comprehensive simulations, we demonstrate the finite sample performance of our method, which corroborates the theoretical findings. Finally, we apply our method to a data set of air quality and energy consumption collected at 129 monitoring sites in the United States in 2015.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Influence of tumor location on the intensity-modulated radiation therapy plan of helical tomotherapy

Given the design of the Helical TomoTherapy device, the patient's central axis is routinely aligned with the machine's rotational axis to prevent the patient's body from colliding with the machine walls. However, for treatment of tumors located away from the patient's central axis, this position may not be optimal as the adequate radiation dose may not reach the affected site. Our study aimed to investigate the influence of tumor location on dose quality and delivery efficiency of tomotherapy plans. A phantom and 15 patients were selected for this study. Two plans, A and B, were implemented for each case. In plan A, the patient's central axis was aligned with the machine's rotational axis, whereas in plan B, the center of the planning target volume (PTV) was aligned with the machine's rotational axis. Both plans were optimized with the same planning parameters, and the dose quality of the plans was evaluated using dosimetrics. The delivery efficiency was determined from delivery time and monitor units (MUs). A paired t-test or nonparametric Wilcoxon signed-rank test was performed for statistical comparison. In the phantom study, the median delivery times were 358 and 336 seconds for plans A and B, respectively, and this difference was significant (p = 0.005). In the patient study, the median delivery times were 348 and 317 seconds for plans A and B, respectively, and this difference was also significant (p = 0.001). The dose qualities of both plans for each patient were nearly identical. No significant differences were found in the conformal index, heterogeneity index, and mean dose delivered to normal tissue between the plans. Both phantom and patient studies showed that for normal-sized patients, the delivery time reduced as the distance between the PTV and the patient's central axis increased when the PTV center was aligned with the machine axis. In conclusion, aligning the PTV center with the machine's rotational axis by shifting the patient during tomotherapy reduces the delivery time without compromising the dose quality of intensity-modulated radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Best estimate plus uncertainty analysis of departure from nucleate boiling limiting case with CASL core simulator VERA-CS in response to PWR main steam line break event

VERA-CS (Virtual Environment for Reactor Applications, Core Simulator) is a coupled neutron transport and thermal-hydraulics subchannel code under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). VERA-CS was used to simulate a typical pressurized water reactor (PWR) full core response with 17x17 fuel assemblies for a main steam line break (MSLB) accident scenario with the most reactive rod cluster control assembly stuck out of the core. The accident scenario was initiated at the hot zero power (HZP) at the end of the first fuel cycle with return to power state points that were determined by a system analysis code and the most limiting state point was chosen for core analysis. The best estimate plus uncertainty (BEPU) analysis method was applied using Wilks’ nonparametric statistical approach. In this way, 59 full core simulations were performed to provide the minimum departure from nucleate boiling ratio (MDNBR) at the 95/95 (95% probability with 95% confidence level) tolerance limit. The results show that this typical PWR core remains within MDNBR safety limits for the MSLB accident.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Characterizing forecastability of wind sites in the United States

With the rapid growth of wind power, managing its uncertainty and variability becomes critical in power system operations. Wind forecasting is one of the enablers to partially tackle challenges associated with wind power uncertainty. To improve the 'forecasting ability', defined as forecastability, different forecasting methods have been developed to assist grid integration of wind energy. However, forecasting performance not only relies on the power of forecasting models, but is also related to local weather conditions and (known as wind characteristics) wind farm properties. In this study, geospatial and instance spatial distributions of six wind characteristics and two forecasting error metrics are first analyzed based on 126,000 + wind sites in the United States. Forecasts in different look-ahead times are generated by using a machine learning based multi-model forecasting framework model and the Weather Research and Forecasting model. A forecastability quantification method is developed by characterizing the relationship between forecastability and wind series entropy using three regression methods, i.e., linear approximation, locally weighted scatterplot smoother nonlinear nonparametric regression, and quantile regression. It is found that the forecastability of a wind site can be successfully characterized by wind series characteristics, thereby providing valuable information at different stages of wind energy projects.

17 WIND ENERGY↗
DOE OSTI2017

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basis of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Effect of Groundwater Age and Recharge Source on Nitrate Concentrations in Domestic Wells in the San Joaquin Valley

Nitrate is one of the most abundant contaminants in groundwater globally, in the United States, and in California (CA). We studied well construction information, water chemistry, stable isotopes, and noble gases to understand how groundwater travel time and recharge source and mechanism control nitrate concentrations in domestic wells in the San Joaquin Valley (SJV), CA, a large semiarid, irrigated agricultural region. Using nonparametric statistics, we find a decreasing trend in nitrates with groundwater travel time and well depth. Samples collected from wells that are closer to rivers and that show indications of river water recharge, either low recharge temperature or low δ 18 O signature, have lower concentrations of nitrates than samples with isotopic signatures indicating mixed source or local precipitation recharge. The curbing effect of river water recharge on nitrate concentrations in domestic wells is similar for direct river recharge and water applied as irrigation. This suggests that irrigation with river water also has a diluting effect that reduces the concentration of nitrate found in groundwater. This conclusion supports the idea that flood-managed aquifer recharge may be considered for remediation of groundwater nitrate when designing replenishment of aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUs

In recent years, a new kind of accelerated hardware has gained popularity in the artificial intelligence (AI) community which enables extremely high-performance tensor contractions in reduced precision for deep neural network calculations. In this article, we exploit Nvidia Tensor cores, a prototypical example of such AI-hardware, to develop a mixed precision approach for computing a dense matrix factorization of the inverse overlap matrix in electronic structure theory, S –1 . This factorization of S –1 , written as ZZT = S –1 , is used to transform the general matrix eigenvalue problem into a standard matrix eigenvalue problem. Here we present a mixed precision iterative refinement algorithm where Z is given recursively using matrix–matrix multiplications and can be computed with high performance on Tensor cores. To understand the performance and accuracy of Tensor cores, comparisons are made to GPU-only implementations in single and double precision. Additionally, we propose a nonparametric stopping criteria which is robust in the face of lower precision floating point operations. The algorithm is particularly useful when we have a good initial guess to Z, for example, from previous time steps in quantum-mechanical molecular dynamics simulations or from a previous iteration in a geometry optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Physics-Informed Gaussian Process Inference of Liquid Structure from Scattering Data

We present a nonparametric Bayesian framework to infer radial distribution functions from experimental scattering measurements with uncertainty quantification using nonstationary Gaussian processes. The Gaussian process prior mean and kernel functions are designed to mitigate well-known numerical challenges with the Fourier transform, including discrete measurement binning and detector windowing, while encoding fundamental yet minimal physical knowledge of the liquid structure. We demonstrate uncertainty propagation of the Gaussian process posterior to unmeasured quantities of interest. Experimental radial distribution functions of liquid argon and water with uncertainty quantification are provided as both a proof of principle for the method and a benchmark for molecular models.

Chemical structure↗
DOE OSTI2026

Interplay between Ultrafast Electronic and Librational Dynamics in Liquid Nitrobenzene Probed with Two-Color Four-Wave Mixing

Here, we present an experimental and theoretical study of the interplay between ultrafast electron dynamics and librational dynamics in liquid nitrobenzene. A femtosecond ultraviolet pulse and two femtosecond near-infrared pulses interact with nitrobenzene molecules, generating a four-wave mixing nonlinear signal measured in the Optical Kerr Effect geometry. The signal is measured to be nonzero only at negative time delays, corresponding to the near-infrared pulses arriving before the ultraviolet pulse. We perform time-dependent Quantum Master Equation calculations with classical libration to simulate the experiment. The simulations support the conclusion that the near-infrared pulses launch librational motion while creating electronic coherences resulting in a libration-modulated electronic nonlinear response. The analysis of the phase-matched four-wave mixing signals suggests a nonparametric process leaving the molecules in an excited electronic state, providing new insight into ultrafast nonlinear optical interactions in liquids and advancing toward probing ultrafast electronic coherences in complex molecular liquids.

Shivaram, Niranjan [Lawrence Berkeley National Lab↗
DOE OSTI2024

Combining High-Throughput Experiments and Active Learning to Characterize Deep Eutectic Solvents

The high tunability of deep eutectic solvents (DESs) stems from the ease of changing their precursors and relative compositions. However, measuring the physicochemical properties across large composition and temperature ranges, necessary to properly design target-specific DESs, is tedious and error-prone and represents a bottleneck in the advancement and scalability of DES-based applications. As such, active learning (AL) methodologies based on Gaussian processes (GPs) were developed in this work to minimize the experimental effort necessary to characterize DESs. Owing to its importance for large-scale applications, the reduction of DES viscosity through the addition of a low-molecular-weight solvent was explored as a case study. A high-throughput experimental screening was initially performed on nine different ternary DESs. Then, GPs were successfully trained to predict DES viscosity from its composition and temperature, showcasing the ability of these stochastic, nonparametric models to accurately describe the physicochemical properties of complex mixtures. Finally, the ability of GPs to provide estimates of their own uncertainty was leveraged through an AL framework to minimize the number of data points necessary to obtain accurate viscosity modes. This led to a significant reduction in data requirements, with many systems requiring only five independent viscosity data points to be properly described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗