Search NASA⌕ Search

SEARCH · Search NASA

Results for “study protocol”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

A study of respiration-correlated cone-beam CT scans to correct target positioning errors in radiotherapy of thoracic cancer

Purpose: There is increasingly widespread usage of cone-beam CT (CBCT) for guiding radiation treatment in advanced-stage lung tumors, but difficulties associated with daily CBCT in conventionally fractionated treatments include imaging dose to the patient, increased workload and longer treatment times. Respiration-correlated cone-beam CT (RC-CBCT) can improve localization accuracy in mobile lung tumors, but further increases the time and workload for conventionally fractionated treatments. This study investigates whether RC-CBCT-guided correction of systematic tumor deviations in standard fractionated lung tumor radiation treatments is more effective than 2D image-based correction of skeletal deviations alone. A second study goal compares respiration-correlated vs respiration-averaged images for determining tumor deviations. Methods: Eleven stage II-IV nonsmall cell lung cancer patients are enrolled in an IRB-approved prospective off-line protocol using RC-CBCT guidance to correct for systematic errors in GTV position. Patients receive a respiration-correlated planning CT (RCCT) at simulation, daily kilovoltage RC-CBCT scans during the first week of treatment and weekly scans thereafter. Four types of correction methods are compared: (1) systematic error in gross tumor volume (GTV) position, (2) systematic error in skeletal anatomy, (3) daily skeletal corrections, and (4) weekly skeletal corrections. The comparison is in terms of weighted average of the residual GTV deviations measured from the RC-CBCT scans and representing the estimated residual deviation over the treatment course. In the second study goal, GTV deviations computed from matching RCCT and RC-CBCT are compared to deviations computed from matching respiration-averaged images consisting of a CBCT reconstructed using all projections and an average-intensity-projection CT computed from the RCCT. Results: Of the eleven patients in the GTV-based systematic correction protocol, two required no correction, seven required a single correction, one required two corrections, and one required three corrections. Mean residual GTV deviation (3D distance) following GTV-based systematic correction (mean {+-} 1 standard deviation 4.8 {+-} 1.5 mm) is significantly lower than for systematic skeletal-based (6.5 {+-} 2.9 mm, p= 0.015), and weekly skeletal-based correction (7.2 {+-} 3.0 mm, p= 0.001), but is not significantly lower than daily skeletal-based correction (5.4 {+-} 2.6 mm, p= 0.34). In two cases, first-day CBCT images reveal tumor changes-one showing tumor growth, the other showing large tumor displacement-that are not readily observed in radiographs. Differences in computed GTV deviations between respiration-correlated and respiration-averaged images are 0.2 {+-} 1.8 mm in the superior-inferior direction and are of similar magnitude in the other directions. Conclusions: An off-line protocol to correct GTV-based systematic error in locally advanced lung tumor cases can be effective at reducing tumor deviations, although the findings need confirmation with larger patient statistics. In some cases, a single cone-beam CT can be useful for assessing tumor changes early in treatment, if more than a few days elapse between simulation and the start of treatment. Tumor deviations measured with respiration-averaged CT and CBCT images are consistent with those measured with respiration-correlated images; the respiration-averaged method is more easily implemented in the clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Radiosensitivity Differences Between Liver Metastases Based on Primary Histology Suggest Implications for Clinical Outcomes After Stereotactic Body Radiation Therapy

Purpose/Objectives: Evidence from the management of oligometastases with stereotactic body radiation therapy (SBRT) reveals differences in outcomes based on primary histology. We have previously identified a multigene expression index for tumor radiosensitivity (RSI) with validation in multiple independent cohorts. In this study, we assessed RSI in liver metastases and assessed our clinical outcomes after SBRT based on primary histology. Methods and Materials: Patients were identified from our prospective, observational protocol. The previously tested RSI 10 gene assay was run on samples and calculated using the published algorithm. An independent cohort of 33 patients with 38 liver metastases treated with SBRT was used for clinical correlation. Results: A total of 372 unique metastatic liver lesions were identified for inclusion from our prospective, institutional metadata pool. The most common primary histologies for liver metastases were colorectal adenocarcinoma (n=314, 84.4%), breast adenocarcinoma (n=12, 3.2%), and pancreas neuroendocrine (n=11, 3%). There were significant differences in RSI of liver metastases based on histology. The median RSIs for liver metastases in descending order of radioresistance were gastrointestinal stromal tumor (0.57), melanoma (0.53), colorectal neuroendocrine (0.46), pancreas neuroendocrine (0.44), colorectal adenocarcinoma (0.43), breast adenocarcinoma (0.35), lung adenocarcinoma (0.31), pancreas adenocarcinoma (0.27), anal squamous cell cancer (0.22), and small intestine neuroendocrine (0.21) (P<.0001). The 12-month and 24-month Kaplan-Meier rates of local control (LC) for colorectal lesions from the independent clinical cohort were 79% and 59%, compared with 100% for noncolorectal lesions (P=.019), respectively. Conclusions: In this analysis, we found significant differences based on primary histology. This study suggests that primary histology may be an important factor to consider in SBRT radiation dose selection.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-P-57: Radiation Doses Assessment to Paediatric Patients for Some Digital Diagnostic Radiology Examination in Emergency Department in Qatar

Purpose: The aim of this study was to evaluate radiation doses to pediatric patients undergoing standard radiographic examinations using Direct Digital Radiography (DDR) in Paediatric emergency center of Hamad General Hospital (HGH) in state of Qatar and compared with regional and international Dose Reference Levels (DRLs). Methods: Entrance Skin Dose (ESD) was measured for 2739 patients for two common X-ray examinations namely: Chest AP/PA, Abdomen. Exposure factors such as kV, mAs and Focal to Skin Distance (FSD) were recorded for each patient. Tube Output was measured for a range of selected kV values. ESD for each individual patient was calculated using the tube output and the technical exposure factors for each examination. The ESD values were compared with the some international Dose Reference Levels (DRL) for all types of examinations. Results: The most performed procedure during the time of this study was chest PA/PA (85%). The mean ESD values obtained from AP chest, PA chest and AP abdomen ranged 91–120, 80–84 and 209 – 659 µGy per radiograph for different age’s groups respectively. Two protocols have been used for chest AP and PA using different radiological parameters, and the different of ESD values for chest PA and were 41% for 1 years old child, 57% for 5 years old for chest AP. Conclusion: The mean ESD were compared with those found in literature and were found to be comparable. The radiation dose can be reduced more for Chest AP and PA examination by optimization of each investigation and hence more studies are required for this task. The results presented will serve as a baseline data needed for deriving local reference doses for pediatric X-ray examinations in this local department and hence it can be applied in the whole Qatar.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Immunohistochemical analysis of cyclin A expression in Wilms tumor

Background: Cyclin A overexpression is found in a variety of human tumors and correlates with unfavorable outcome. We analyzed immunohistochemical expression of cyclin A in Wilms tumor (WT) in relation to clinicopathological characteristics, preoperative chemotherapy (PrOpChTh), and overall survival (OS). Methods: This retrospective study involved 43 patients who underwent nephrectomy from January 1996 to October 2010. Tumor stage and histological subtype were determined by revised Societé International d’Oncologie Pediatrique protocol, based on histological components/alterations caused by PrOpChTh, within the prognostic group of low, intermediate and high risk, and with criteria for anaplasia. The regressive/necrotic changes in total tumor mass of primary tumor and the proportion of epithelial, blastemal, and stromal components in the remaining viable tumor tissue were also determined. Cyclin A expression was evaluated by immunohistochemistry using a polyclonal rabbit, antihuman antibody (H-432). Results: Cyclin A overexpression was found in 34.3% of WTs, with higher frequency in tumors with epithelial (31.3%) and blastemal (37.1%) components than those with stromal component (17.7%). Regarding histological type, cyclin A overexpression was found most often in focal anaplasia (100%), stromal (60%), and diffuse anaplastic (66.7) WTs. The overexpression was also more frequent in stages 3 and 4 (77.8% and 66.7%, respectively) compared to tumors in stages 1 and 2 (13.3% and 12.5%, respectively; p = 0.004) in all components, as well as in blastemal component in stages 3 and 4 (77.8% and 66.7%, respectively) vs. stages 1 and 2 (13.3% and 25%, respectively, p = 0.009). Cyclin A overexpression in all components was 66.7% in WTs with metastasis and 31.3% in WTs without metastasis (p = 0.265, Fisher test). Log-rank testing revealed differences of OS regarding stage (p = 0.000), prognostic groups (p = 0.001), and cyclin A expression in blastemal component (p = 0.025). After univariate analysis, tumor stage (p = 0.001), prognostic group (p = 0.004), and cyclin A expression in blastemal component (p = 0.042) were significant prognostic factors for OS; however, after multivariate analysis, none of these factors were confirmed as independent predictors of survival. Discussion: This study showed that cyclin A overexpression might be associated with the development and progression of WT with anaplasia. Also, cyclin A overexpression was more often observed in advanced stages (3 and 4) of WT, in the group of high-risk WTs, and in focal and diffuse anaplasia WTs. There was no relation of cyclin A overexpression and metastatic ability of WT. Although this study has not confirmed the prognostic value of cyclin A overexpression, its association with unfavorable prognosis should be further evaluated. Copyright 2019 Radojevic-Škodric et al.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗
NASA NTRS1998

Ultrasonic Attenuation Results of Thermoplastic Resin Composites Undergoing Thermal and Fatigue Loading

As part of an effort to obtain the required information about new composites for aviation use, materials and NDE researchers at NASA are jointly performing mechanical and NDE measurements on new composite materials. The materials testing laboratory at NASA is equipped with environmental chambers mounted on load frames that can expose composite materials to thermal and loading cycles representative of flight protocols. Applying both temperature and load simultaneously will help to highlight temperature and load interactions during the aging of these composite materials. This report highlights our initial ultrasonic attenuation results from thermoplastic composite samples that have undergone over 4000 flight cycles to date. Ultrasonic attenuation measurements are a standard method used to assess the effects of material degradation. Recently, researchers have shown that they could obtain adequate contrast in the evaluation of thermal degradation in thermoplastic composites by using frequencies of ultrasound on the order of 24 MHz. In this study, we address the relationship of attenuation measured at lower frequencies in thermoplastic composites undergoing both thermal and mechanical loading. We also compare these thermoplastic results with some data from thermoset composites undergoing similar protocols. The composite s attenuation is reported as the slope of attenuation with respect to frequency, defined as b = Da(f)/Df. The slope of attenuation is an attractive parameter since it is quantitative, yet does not require interface corrections like conventional quantitative attenuation measurements. This latter feature is a consequence of the assumption that interface correction terms are frequency independent. Uncertainty in those correction terms can compromise the value of conventional quantitative attenuation data. Furthermore, the slope of the attenuation more directly utilizes the bandwidth information and in addition, the bandwidth can be adjusted in the post processing stage to compensate for the loss of dynamic range of the signal as the composites age.

Madaras, Eric I.↗
DOE OSTI2022

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here, in this study, we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Optimization of matrix viscosity improves polypropylene fiber dispersion and properties of engineered cementitious composites

Engineered cementitious composites (ECC) is a durable cementitious material with high tensile ductility and strain-hardening characteristics. Although considered as a cost-effective fiber for ECC, polypropylene (PP) fiber is reportedly difficult to disperse in mortar matrix due to its high aspect ratio and hydrophobicity. In this study, the matrix viscosity of a low-carbon ECC based on limestone calcined clay cement was tailored as a variable to improve PP fiber dispersion under a pre-determined mixing protocol. The effect of matrix viscosity on the composite fresh and hardened properties was investigated experimentally. Results suggested an optimal range of matrix viscosity (10.3–11.5 Pa . s) favors the composite tensile strength and strain capacity at 28 days. At the optimal state with a 0.1 % viscosity modifying admixture (VMA)-to-binder mass ratio, PP-ECC achieved 7.0 % tensile strain capacity and 3.5 MPa ultimate tensile strength. When matrix viscosity falls outside the desired range, both ultimate tensile strength and strain capacity were diminished. By tailoring the VMA dosage, the matrix viscosity can be adjusted for desired fiber dispersion, workability, and mechanical properties. Finally, the findings of this study provide a technical reference for the practical design and application of PP-ECC.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Project ARGO: Gas phase formation in simulated microgravity

The ARGO study investigated the reduced incidence of joint pain decompression sickness (DCS) encountered in microgravity as compared with an expected incidence of joint pain DCS experienced by test subjects in Earth-based laboratories (unit gravity) with similar protocols. Individuals who are decompressed from saturated conditions usually acquire joint pain DCS in the lower extremities. Our hypothesis is that the incidence of joint pain DCS can be limited by a significant reduction in the tissue gas micronuclei formed by stress-assisted nucleation. Reductions in dynamic and kinetic stresses in vivo are linked to hypokinetic and adynamic conditions of individuals in zero g. We employed the Doppler ultrasound bubble detection technique in simulated microgravity studies to determine quantitatively the degree of gas phase formation in the upper and lower extremities of test subjects during decompression. We found no evidence of right-to-left shunting through pulmonary vasculature. The volume of gas bubble following decompression was examined and compared with the number following saline contrast injection. From this, we predict a reduced incidence of DCS on orbit, although the incidence of predicted mild DCS still remains larger than that encountered on orbit.

Powell, Michael R.↗
DOE OSTI2016

Poster - 19: Investigation of Electron Reference Dosimetry Based on Optimal Chamber Shift

An addendum/revision to AAPM TG-51 electron reference dosimetry is highly expected to meet the clinical requirement with the increasing usage of new ion chambers not covered in TG-51. A recent study, Med. Phys. 41, 111701, proposed a new fitting equation for the beam quality conversion factor k’{sub Q} to a wide spectrum of chambers. In the study, an optimal Effective Point of Measurement (EPOM) from Monte Carlo calculations was recommended and the fitting parameters to k’{sub Q} was based on it. We investigated the absolute dose obtained based on the optimal EPOM method and the original TG-51 method with k’{sub R50} determined differently. The results showed that using the Markus curve is a better choice than the well-guarded chamber fitting for an IBA PPC-05 parallel plate chamber if we need to strictly follow the AAPM TG-51 protocol. We also examined the usage of the new fitting equation with measurement performed at the physical EPOM, instead of the optimal EPOM. The former is more readily determined and more practical in clinics. Our study indicated that the k’{sub Q} fitting based on the optimal EPOM can be used to measurement at the physical EPOM with no significant clinical impact. The inclusion of Farmer chamber gradient correction P{sub gr} in k’{sub Q}, as in the mentioned study, asks for the precise positioning of chamber center at dref. It is not recommended in clinics to avoid over-correction for low electron energies, especially for an institute having matching Linacs implemented.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Effects of Lead and Arsenic in Soils from Former Orchards on Growth of Three Plant Species

Abstract Historical use of lead arsenate as a pesticide in former orchards of eastern Washington State (USA) has resulted in legacy lead (Pb) and arsenic (As) soil contamination. However, the impacts on plant growth in soils with residual Pb and As contamination have not yet been quantified. To this end, a comparative study of plant growth impacts was performed for native bluegrass ( Poa secunda ), invasive cheatgrass ( Bromus tectorum ), and buttercrunch lettuce ( Lactuca sativa ). Using standard plant growth protocols, germination frequency and biomass growth were measured over a wide range of Pb and arsenate concentrations, with maximum concentrations of 3400 and 790 mg kg −1 for Pb and As, respectively. Results indicated that only the biomass growth for all species decreased in soils with the highest concentrations of Pb and As in the soil, with no impacts on soils with lower residual Pb and arsenate concentrations. No impact on percentage of germination was observed at any soil concentration. These results can be used to determine site‐specific soil screening levels for use in ecological risk assessments for Pb and arsenate in soils. Environ Toxicol Chem 2022;41:1459–1465. © 2022 Battelle Memorial Institute. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A biomimetic approach to fast selection of optimal controlled variables using multiagent algorithms and a decomposition approach

Selection of primary controlled variables (CVs) with due consideration of economic loss and ease of control is an important step for achieving optimal plant operation under design and off-design conditions. However, the computational expense of the combinatorial optimization step that is undertaken for CV selection renders the existing approaches unaffordable for fast selection of optimal CVs. Two approaches are proposed in this paper for improving the computational efficiency of the optimization step. Typically, the CV selection process is typically executed by considering the entire plant together. Opposed to that, the first approach proposed here seeks to decompose the process plant into multiple partitions based on the connectivity strength. Then the CV selection algorithm can be executed on each partition independently. The decomposition algorithm is biomimetic and has been developed, in analogy to neuroscience, mimicking how the information about the connectivity information is extracted using a dynamic casual model. This approach can significantly decrease the number of combinatorial optimization problems that needs to be solved and facilitates parallelization of the solution. In the second approach, a multiagent optimization framework is proposed that utilizes metaheuristic optimization strategies such as the efficient ant colony algorithm, simulated annealing and the genetic algorithm. These two approaches can be used by themselves or in combination. This framework enables cooperative search by a group of algorithmic agents facilitated through an information sharing protocol. These two approaches are applied to a toy problem and an acid gas removal unit as part of an integrated gasification combined cycle. This study shows how the computational time and economic and control performance of the optimal CV sets vary as the number of partitions are changed.

42 ENGINEERING↗
DOE OSTI2018

EStokTP: Electronic Structure to Temperature- and Pressure-Dependent Rate Constants—A Code for Automatically Predicting the Thermal Kinetics of Reactions

A priori rate predictions for gas phase reactions have undergone a gradual but dramatic transformation, with current predictions often rivaling the accuracy of the best available experimental data. The utility of such kinetic predictions would be greatly magnified if they could more readily be implemented for large numbers of systems. Here, we report the development of a new computational environment, namely, EStokTP, that reduces the human effort involved in the rate prediction for single channel reactions essentially to the specification of the methodology to be employed. The code can also be used to obtain all the necessary master equation building blocks for more complex reactions. In general, the prediction of rate constants involves two steps, with the first consisting of a set of electronic structure calculations and the second in the application of some form of kinetic solver, such as a transition state theory (TST)-based master equation solver. EStokTP provides a fully integrated treatment of both steps through calls to external codes to perform first the electronic structure and then the master equation calculations. It focuses on generating, extracting, and organizing the necessary structural properties from a sequence of calls to electronic structure codes, with robust automatic failure recovery options to limit human intervention. The code implements one or multidimensional hindered rotor treatments of internal torsional modes (with automated projection from the Hessian and with optional vibrationally adiabatic corrections), Eckart and multidimensional tunneling models (such as small curvature theory), and variational treatments (based on intrinsic reaction coordinate following). This focus on a robust implementation of high-level TST methods allows the code to be used in high accuracy studies of large sets of reactions, as illustrated here through sample studies of a few hundred reactions. At present, the following reaction types are implemented in EStokTP: abstraction, addition, isomerization, and beta-decomposition. Finally, preliminary protocols for treating barrierless reactions and multiple-well and/or multiple-channel potential energy surfaces are also illustrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantum Chemical Prediction of p K a Values of Cationic Ion-Exchange Groups in Polymer Electrolyte Membranes

The durability of anion-exchange membranes (AEMs) in alkaline fuel cells is largely determined by the stability of anion-exchange groups. Despite continuous research efforts, the commonly employed cations still have limited stability against hydroxide that can act as a strong base and nucleophile. This work is concerned with base-catalyzed degradation of organic cations initiated by proton abstraction to form reactive ylides or carbenes. We report on the performance of 24 methods combining density functional theory and electronic structure methods with implicit solvation calculations for predicting pK a values of organic cations in water and DMSO. The most accurate computational protocols are obtained using a combination of M06-2X/6-311++G** with the SMD solvation model for water (the mean absolute error of 0.4 pK a units) and B3LYP/aug-cc-pVTZ with the IEFPCM solvation model for DMSO (the mean absolute error of 1.4 pK a units). The aqueous pK a calculation protocol is cross-validated against the experimental C–H acidity constants outside the conventional range of 0–14 pK a values. In conclusion, this study rationalizes alkaline degradation of imidazolium cations with C2-alkyl substituents and provides a theoretical scale of C–H acidity for potential anion-exchange groups in AEMs.

25 ENERGY STORAGE↗
DOE OSTI2026

Accelerated Carbon and Water Cycles in the Amazon and Congo Basins Revealed From TRENDY Models and Remote Sensing Products

Tropical forests play a vital role in the global carbon cycle and land–atmosphere interactions. Estimating tropical forest carbon–water dynamics is challenging due to observational and modeling uncertainties. This study leverages the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project models and satellite observations to assess changes (2003–2021) in vegetation carbon, gross primary production (GPP), evapotranspiration (ET), and net biosphere production (NBP) in the Amazon and Congo. Atmospheric CO 2 , climate variability, and land use and land cover changes constrain these variables between 1700 and 2021 with the overall increasing trends of carbon stock and fluxes. The models overestimate vegetation carbon and GPP, while ET and NBP are consistent with observations. Fire-activated models predict lower values for vegetation carbon and GPP, ET, and NBP, aligning more closely with observations. The higher ET from fire-activated models may result from enhanced soil evaporation due to increased canopy openings. Fire-inactivated models could well estimate the magnitudes of NBP. The high vegetation carbon in nitrogen-enabled models points to simulation uncertainties and imbalance in model numbers regarding the nitrogen cycle. Although the nitrogen cycle enhances water use efficiency in both the Amazon and Congo, the models show a higher sensitivity to the nitrogen cycle in the Congo. This study highlights the challenges in accurately representing tropical biogeochemical cycles and the values of satellite products in model evaluations, underscoring the need for standard modeling protocols that address biogeochemical components (e.g., nutrient cycles) to better resolve process-based representations.

Shi, Mingjie [Pacific Northwest National Laborator↗
DOE OSTI2021

Cavity molecular dynamics simulations of vibrational polariton-enhanced molecular nonlinear absorption

We report recent experiments have observed that the chemical and photophysical properties of molecules can be modified inside an optical Fabry– Pérot microcavity under collective vibrational strong coupling (VSC) conditions, and such modification is currently not well understood by theory. In an effort to understand the origin of such cavity-induced phenomena, some recent studies have focused on the effect of the cavity environment on the nonlinear optical response of the molecular subsystem. Here, we use a recently proposed protocol for classical cavity molecular dynamics simulations to numerically investigate the linear and the nonlinear response of liquid carbon dioxide under such VSC conditions following an optical pulse excitation. We find that applying a strong pulse of excitation to the lower hybrid light–matter state, i.e., the lower polariton (LP), can lead to an overall molecular nonlinear absorption that is enhanced by up to two orders of magnitude relative to the excitation outside the cavity. This polariton-enhanced multiphoton absorption also causes an ultrashort LP lifetime (0.2 ps) under strong illumination. Unlike usual polariton relaxation processes—whereby polaritonic energy transfers directly to the manifold of singly excited vibrational dark states—under the present mechanism, the LP transfers energy directly to the manifold of higher vibrationally excited dark states; these highly excited dark states subsequently relax to the manifold of singly excited states with a lifetime of tens of ps. Because the present mechanism is generic in nature, we expect these numerical predictions to be experimentally observed in different molecular systems and in cavities with different volumes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Charge carrier extraction and recombination effects in GaInAs/GaAsP multi-quantum well solar cells

The carrier extraction and transport mechanisms as well as the relative contributions of radiative and non-radiative recombination processes are investigated in high-quality strain-balanced GaInAs/GaAsP multi-quantum well solar cells recently implemented in record efficiency multijunction solar cells. A comprehensive suite of complementary characterization techniques including temperature- and suns-dependent photoluminescence and photovoltaic measurements are employed to analyze thermal escape and tunneling rates, which demonstrate the need to move beyond simple drift-diffusion models of p–n junctions. This study examines the processes that best characterize the operation of these devices across varying temperatures using a simple two-diode model, incorporating multiple transport protocols, and provides insights into the performance-limiting processes and pathways for their optimization.

14 SOLAR ENERGY↗
DOE OSTI2015

Prospective estimation of organ dose in CT under tube current modulation

Purpose: Computed tomography (CT) has been widely used worldwide as a tool for medical diagnosis and imaging. However, despite its significant clinical benefits, CT radiation dose at the population level has become a subject of public attention and concern. In this light, optimizing radiation dose has become a core responsibility for the CT community. As a fundamental step to manage and optimize dose, it may be beneficial to have accurate and prospective knowledge about the radiation dose for an individual patient. In this study, the authors developed a framework to prospectively estimate organ dose for chest and abdominopelvic CT exams under tube current modulation (TCM). Methods: The organ dose is mainly dependent on two key factors: patient anatomy and irradiation field. A prediction process was developed to accurately model both factors. To model the anatomical diversity and complexity in the patient population, the authors used a previously developed library of computational phantoms with broad distributions of sizes, ages, and genders. A selected clinical patient, represented by a computational phantom in the study, was optimally matched with another computational phantom in the library to obtain a representation of the patient’s anatomy. To model the irradiation field, a previously validated Monte Carlo program was used to model CT scanner systems. The tube current profiles were modeled using a ray-tracing program as previously reported that theoretically emulated the variability of modulation profiles from major CT machine manufacturers Li et al., [Phys. Med. Biol. 59, 4525–4548 (2014)]. The prediction of organ dose was achieved using the following process: (1) CTDI{sub vol}-normalized-organ dose coefficients (h{sub organ}) for fixed tube current were first estimated as the prediction basis for the computational phantoms; (2) each computation phantom, regarded as a clinical patient, was optimally matched with one computational phantom in the library; (3) to account for the effect of the TCM scheme, a weighted organ-specific CTDI{sub vol} [denoted as (CTDI{sub vol}){sub organ,weighted}] was computed for each organ based on the TCM profile and the anatomy of the “matched” phantom; (4) the organ dose was predicted by multiplying the weighted organ-specific CTDI{sub vol} with the organ dose coefficients (h{sub organ}). To quantify the prediction accuracy, each predicted organ dose was compared with the corresponding organ dose simulated from the Monte Carlo program with the TCM profile explicitly modeled. Results: The predicted organ dose showed good agreements with the simulated organ dose across all organs and modulation profiles. The average percentage error in organ dose estimation was generally within 20% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. For an average CTDI{sub vol} of a CT exam of 10 mGy, the average error at full modulation strength (α = 1) across all organs was 0.91 mGy for chest exams, and 0.82 mGy for abdominopelvic exams. Conclusions: This study developed a quantitative model to predict organ dose for clinical chest and abdominopelvic scans. Such information may aid in the design of optimized CT protocols in relation to a targeted level of image quality.

60 APPLIED LIFE SCIENCES↗