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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine Learned Empirical Numerical Integrator from Simulated Data

Recently, a number of state-of-the-art surrogate machine learning (ML) models have been designed for global weather and climate prediction, which have been trained using reanalysis data products. Reanalysis data products are constructed using numerical model simulations that combine numerical integration of partial differential equations and parameterization schemes. These products are typically only archived and made available using coarsened spatial and temporal resolutions. This study explores the impact of the numerical generation methods used to produce the training datasets and the temporal resolution of those datasets on machine learning surrogate models. Using the nonlinear vector autoregression (NVAR) machine as an explainable ML technique, simple dynamical systems are emulated with ML models trained on data produced by three classical numerical integration schemes. NVAR is validated as a skillful ML method, capable of producing accurate predictions and, more importantly, reconstructing both the underlying dynamics and the numerical integration scheme used to generate the training data. However, the machine fails to generalize predictions on unseen test data generated by different numerical integration schemes, despite the underlying dynamical system being the same. This result provides a word of caution for the growing field of machine learning emulation of weather and climate dynamics. Furthermore, we illustrate using NVAR that training on temporally coarsened data may increase the required complexity of ML models and potentially introduce new numerical challenges. Finally, we discover that empirical integration schemes with arbitrary time-stepping sizes can be constructed directly from the data, which implies a potential for the development of empirical numerical integration schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Quality of Life Outcomes From a Phase 2 Trial of Short-Course Radiation Therapy Followed by FOLFOX Chemotherapy as Preoperative Treatment for Rectal Cancer

Purpose: A prospective phase 2 trial of short-course (SC) radiation therapy (RT) with 25 Gy over 5 fractions, followed by 4 cycles of 5-fluorouracil, oxaliplatin, and leucovorin (mFOLFOX6) before surgery was recently completed at our institution. We present here the patient-reported quality of life (QOL) outcomes from this trial. Methods and Materials: Eighty patients with cT3/T4, any N, any M rectal adenocarcinoma planned for resection were enrolled between 2009 and 2012. The QOL data were obtained prospectively using the Functional Assessment of Cancer Therapy-Colon (FACT-C) questionnaire before RT, before surgery, and 1 year after surgery. The previously validated minimally importance difference (MID) method was used to measure clinically significant QOL changes in FACT-C scores for each patient across time points. We examined the role of ostomy on QOL. We also compared QOL with disease outcomes and physician-reported toxicity. Results: The FACT-C questionnaire was completed by 97% of patients before RT, 85% immediately before surgery, and 62% 1 year after surgery. There was no statistically significant change in mean FACT-C scores from before treatment to after treatment. The majority of patients had either no change or an increase in QOL 1 year after treatment using the MID method. There were significant changes in QOL between patients with ostomy versus no ostomy 1 year after treatment for functional well-being (FWB) (14.81 vs 20.52, P=.018) and the colorectal cancer subscale (CCS) using the MID method (P=.004). Patients without ostomy reported stable changes in bowel control 1 year after surgery. There was no statistically significant correlation between QOL and disease recurrence, pathologic complete response, pathologic T stage downstaging, or acute/late toxicity. Conclusions: SC-RT and sequential mFOLFOX6 as preoperative therapy for rectal cancer results in stable patient-reported QOL outcomes 1 year after treatment. These findings in conjunction with previously reported oncologic outcomes support further evaluation of this regimen in a phase 3 setting.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Uniaxial tensile mechanical properties from a scratch on ultra-fine grained tungsten

We demonstrate that surface-based mechanical testing can be used to quantify a wide range of mechanical properties determined using traditional uniaxial tension experiments. These include mapping of dynamic stress–strain behaviour, which can be used as a screening tool for uniaxial tensile ductility (uniform elongation), fracture toughness (K C ), which is shown to be in good agreement with reported plane-strain K IC , as well work-hardening exponents (n), activation volumes (V) energies (Q) and strain-rate sensitivity (m) exponents as a function of temperature. Advantages of the surface-based approach are the ability to work with significantly smaller volumes and accommodate processing defects like pores, voids and cracks. These methods are applied to ultra-fine grained tungsten (average grain size of 650 nm), as it is an ideal candidate for alloy development efforts in advanced energy systems. Tungsten is a useful baseline as it exhibits a near-ambient temperature (approx. 200°C) ductile-to-brittle transition temperature (DBTT), enabling validation efforts for the proposed methods, and extraordinary material properties, including the highest melting temperature of any metal and complex temperature and strain-rate dependencies linked to transitions in dislocation mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

DGs for Service Restoration to Critical Loads in a Secondary Network

During a major outage in a secondary network distribution system, distributed generators (DGs) connected to the primary feeders as well as the secondary network can be used to serve critical loads. This paper proposed a resilience-oriented method to determine restoration strategies for secondary network distribution systems after a major disaster. Technical issues associated with the restoration process are analyzed, including the operation of network protectors, inrush currents caused by the energization of network transformers, synchronization of DGs to the network, and circulating currents among DGs. A look-ahead load restoration framework is proposed, incorporating technical issues associated with secondary networks, limits on DG capacity and generation resources, dynamic constraints, and operational limits. The entire outage duration is divided into a sequence of periods. Restoration strategies can be adjusted at the beginning of each period using the latest information. Numerical simulation of the modified IEEE 342-node low voltage networked test system is performed to validate the effectiveness of the proposed method.

Xu, Yin (ORCID:0000000209459024)↗
DOE OSTI2014

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10{sup 7} xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual generation of medical images and accurate estimation of radiation dose and other imaging parameters. For this, detailed computational phantoms of the patient anatomy must be utilized and implemented within the radiation transport code. Computational phantoms presently come in one of three format types, and in one of four morphometric categories. Format types include stylized (mathematical equation-based), voxel (segmented CT/MR images), and hybrid (NURBS and polygon mesh surfaces). Morphometric categories include reference (small library of phantoms by age at 50th height/weight percentile), patient-dependent (larger library of phantoms at various combinations of height/weight percentiles), patient-sculpted (phantoms altered to match the patient's unique outer body contour), and finally, patient-specific (an exact representation of the patient with respect to both body contour and internal anatomy). The existence and availability of these phantoms represents a very important advance for the simulation of realistic medical imaging applications using Monte Carlo methods. New Monte Carlo simulation codes need to be thoroughly validated before they can be used to perform novel research. Ideally, the validation process would involve comparison of results with those of an experimental measurement, but accurate replication of experimental conditions can be very challenging. It is very common to validate new Monte Carlo simulations by replicating previously published simulation results of similar experiments. This process, however, is commonly problematic due to the lack of sufficient information in the published reports of previous work so as to be able to replicate the simulation in detail. To aid in this process, the AAPM Task Group 195 prepared a report in which six different imaging research experiments commonly performed using Monte Carlo simulations are described and their results provided. The simulation conditions of all six cases are provided in full detail, with all necessary data on material composition, source, geometry, scoring and other parameters provided. The results of these simulations when performed with the four most common publicly available Monte Carlo packages are also provided in tabular form. The Task Group 195 Report will be useful for researchers needing to validate their Monte Carlo work, and for trainees needing to learn Monte Carlo simulation methods. In this symposium we will review the recent advancements in highperformance computing hardware enabling the reduction in computational resources needed for Monte Carlo simulations in medical imaging. We will review variance reduction techniques commonly applied in Monte Carlo simulations of medical imaging systems and present implementation strategies for efficient combination of these techniques with GPU acceleration. Trade-offs involved in Monte Carlo acceleration by means of denoising and “sparse sampling” will be discussed. A method for rapid scatter correction in cone-beam CT (<5 min/scan) will be presented as an illustration of the simulation speeds achievable with optimized Monte Carlo simulations. We will also discuss the development, availability, and capability of the various combinations of computational phantoms for Monte Carlo simulation of medical imaging systems. Finally, we will review some examples of experimental validation of Monte Carlo simulations and will present the AAPM Task Group 195 Report. Learning Objectives: Describe the advances in hardware available for performing Monte Carlo simulations in high performance computing environments. Explain variance reduction, denoising and sparse sampling techniques available for reduction of computational time needed for Monte Carlo simulations of medical imaging. List and compare the computational anthropomorphic phantoms currently available for more accurate assessment of medical imaging parameters in Monte Carlo simulations. Describe experimental methods used for validation of Monte Carlo simulations in medical imaging. Describe the AAPM Task Group 195 Report and its use for validation and teaching of Monte Carlo simulations in medical imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Mechanical Loads on Spent Nuclear Fuel in the General 30 cm Package Drop Scenario

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) research program is guided by the high-level goal of closing prioritized knowledge gaps related to spent nuclear fuel (SNF) storage and transportation, which are summarized by Saltzstein et al. (2020). One of the high-priority knowledge gaps is the identification and quantification of mechanical loads that are expected to affect SNF during normal conditions of transportation and storage to inform the range of physical SNF test programs. This report uses modeling and analysis methods to estimate the mechanical loads on spent nuclear fuel (SNF) in the general 30 cm package drop scenario. The drop scenario assumes impact limiters are in place in the transportation configuration and the impact surface is perfectly rigid. The goal of this analysis is to consider the universe of potential mechanical loading conditions that can happen to SNF and present the results in a manner that is useful for materials testing, decision making, and regulatory rule making purposes. This study uses validated finite element models and methods to perform a broad parametric study of key variables that can affect the mechanical loads on SNF during a hypothetical package free drop scenario. Physical drop test data from a cask and fuel assembly drop test campaign is the basis for model validation. Additionally, the results of the parametric study are used to inform a damage model, which uses multiple nonlinear regression to estimate the relationships between input variables and output response. The parametric finite element analyses consider thousands of input variable combinations, while the damage model estimates millions of combinations. The breadth of this study provides confidence that the potential range of mechanical loads that SNF might experience during the general 30 cm package drop scenario are characterized well enough to consider this knowledge gap closed. While this report documents the overall peak values calculated in this study, the 95 th percentile values, the histograms, and the observed trends are equally important. This study covered a large range of SNF temperatures, room temperature to 300°C, and burnups, 10 GWd/MTU to 62 GWd/MTU. Each temperature and burnup combination has a different cladding yield strain, so it is more meaningful to summarize the calculated cladding strain response as its factor of safety, which is defined relative to the yield strain. The factor of safety is calculated as the yield strain divided by the peak cladding strain. A factor of safety greater than unity indicates that the cladding remains below yield, whereas a value less than unity is indicative of plastic deformation. In all cases of this study a safety factor over 1.0 was calculated, although in the most limiting case at 300°C the safety factor was only 1.01, which suggests that yielding could occur when additional loads like rod internal pressure are included. When the temperature is restricted to 200°C the limiting safety factor increases to 1.28, which has significant margin to accommodate internal pressure and potential local cladding defects that could cause a local stress concentration. An important trend in the calculated fuel rod mechanical loads is that the 2 nd highest loaded fuel rod in an assembly tends to be significantly lower than the highest loaded rod. The implication is that even if one rod in an assembly experiences a failure the loads would have to be significantly higher to cause two or more rods to fail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Confirmation of a realistic reactor model for BNCT dosimetry at the TRIGA Mainz

Purpose: In order to build up a reliable dose monitoring system for boron neutron capture therapy (BNCT) applications at the TRIGA reactor in Mainz, a computer model for the entire reactor was established, simulating the radiation field by means of the Monte Carlo method. The impact of different source definition techniques was compared and the model was validated by experimental fluence and dose determinations. Methods: The depletion calculation code ORIGEN2 was used to compute the burn-up and relevant material composition of each burned fuel element from the day of first reactor operation to its current core. The material composition of the current core was used in a MCNP5 model of the initial core developed earlier. To perform calculations for the region outside the reactor core, the model was expanded to include the thermal column and compared with the previously established ATTILA model. Subsequently, the computational model is simplified in order to reduce the calculation time. Both simulation models are validated by experiments with different setups using alanine dosimetry and gold activation measurements with two different types of phantoms. Results: The MCNP5 simulated neutron spectrum and source strength are found to be in good agreement with the previous ATTILA model whereas the photon production is much lower. Both MCNP5 simulation models predict all experimental dose values with an accuracy of about 5%. The simulations reveal that a Teflon environment favorably reduces the gamma dose component as compared to a polymethyl methacrylate phantom. Conclusions: A computer model for BNCT dosimetry was established, allowing the prediction of dosimetric quantities without further calibration and within a reasonable computation time for clinical applications. The good agreement between the MCNP5 simulations and experiments demonstrates that the ATTILA model overestimates the gamma dose contribution. The detailed model can be used for the planning of structural modifications in the thermal column irradiation channel or the use of different irradiation sites than the thermal column, e.g., the beam tubes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Validation of a Tapered Impact Damper for Traffic Signal Structure Vibrations Using the Method of Harmonic Balance

Significant vibration amplitudes and cycles can be produced when traffic signal structures with low inherent damping are excited near one of their natural frequencies. For the mitigation of wind-induced vibrations, dynamic vibration absorbers coupled to the structure are often used. Here, this research investigates the performance of a tapered impact damper, consisting of a hanging spring-mass oscillator inside a housing capable of reducing vibration amplitude over a broader frequency range than the conventional tuned mass damper. A nonlinear, two degree-of-freedom model is developed with coordinates representing the traffic structure and the tapered impact damper. This research focuses on the application of the harmonic balance method to approximate the periodic solutions of the nonlinear equations to compute the nonlinear dynamics of the damped traffic signal structure. After designing and manufacturing a tapered impact damper, the traffic signal structure is tested with and without the damper using free vibration snapback tests. The experimental frequency and damping backbone curves are used to validate the analytical model, and the effectiveness of the damper is discussed.

42 ENGINEERING↗
DOE OSTI2021

Validation Metrics for Fixed Effects and Mixed-Effects Calibration

The modern scientific process often involves the development of a predictive computational model. To improve its accuracy, a computational model can be calibrated to a set of experimental data. A variety of validation metrics can be used to quantify this process. Some of these metrics have direct physical interpretations and a history of use, while others, especially those for probabilistic data, are more difficult to interpret. In this work, a variety of validation metrics are used to quantify the accuracy of different calibration methods. Frequentist and Bayesian perspectives are used with both fixed effects and mixed-effects statistical models. Through a quantitative comparison of the resulting distributions, the most accurate calibration method can be selected. Two examples are included which compare the results of various validation metrics for different calibration methods. It is quantitatively shown that, in the presence of significant laboratory biases, a fixed effects calibration is significantly less accurate than a mixed-effects calibration. This is because the mixed-effects statistical model better characterizes the underlying parameter distributions than the fixed effects model. The results suggest that validation metrics can be used to select the most accurate calibration model for a particular empirical model with corresponding experimental data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species

Here ecological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally important Barley yellow dwarf virus PAV ( Luteoviridae ), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

J-R Curve Determination for Disk-shaped Compact Specimens Based on the Normalization Method and Direct Current Potential Drop Technique

Material ductile fracture toughness can be described by J-integral versus crack extension relationship (J-R curve). As a conventional J-R curve measurement method, unloading compliance (UC) becomes impractical in elevated temperature testing due to relaxation of the material and a friction induced back-up shape of the J-R curve. In addition, the UC method may underpredict the crack extension for standard disk-shaped compact (DC(T)) specimens. In order to address these issues, the normalization method and direct current potential drop (DCPD) technique were applied for determining J-R curves at 24 C and 500 C for 0.18T DC(T) specimens made from type 316L stainless steel. For comparison purchase, the UC method was also applied in 24 C tests. The normalization method was able to yield valid J-R curves in all tests. The J-R curves from the DCPD technique need adjustment to account for the potential drop induced by plastic deformation, crack blunting, etc. and after applying a newly-developed DCPD adjustment procedure, the post-adjusted DCPD J-R curves essentially matched J-R curves from the normalization method. In contrast, the UC method underpredicted the crack extension in all tests resulting in substantial deviation in the derived J-R curves manifested by high Jq values than the normalization or DCPD method. Only for tests where the UC method underpredicted the crack extension by a very small value, J-R curves determined by the UC method were similar to those determined by the normalization or DCPD method.

DCPD↗
DOE OSTI2015

Consideration for the application of artificial neural networks to criticality code validation - 14270

The artificial neural network (ANN) is a consistent example for non-parametric parameter estimation and regression, with powerful universal approximation properties, that is distribution independent. ANN application to criticality code validation centers on aligning mathematical relationships between code validation parameters and neural network prediction for those parameter values. Two specific goals are: (1) an appropriate ANN architecture to determine validation parameter values, and (2) bootstrapping individual ANNs as a 'Prediction Interval' (PI) technique to estimate the Calculation Margin and Upper Subcritical Limit. The individual ANN workflow is segregated into Training, Validation (network), and Testing Sets, where the network predictive properties and performance are expressed in the latter set. The Bootstrap ANN replicates a large set of individual ANNs (taken from the original data distribution) where (1-α/2)100% PI estimates can be determined. Results from the ANN method are compared to a variety of validation examples: a 'toy example' from ANSI/ANS-8.24, Appendix D, a variety of methods noted in a Nuclear Criticality Safety Division 2009 paper, and several validation campaigns for highly enriched uranium and plutonium systems. The ANN method is robust and can be applied to single or multivariate inputs. A trained ANN can provide both an average estimate (e.g., single value) and an estimate over a range of independent variable values where the kUSL can be formed in a regression relationship suitable for extrapolation. The input dependence has been tested, ranging from 15 to over 400 sample size distributions. An expanded Shapiro-Wilk test (for sample sizes up to 5000) was implemented to confirm that the ANN method is transparent to distribution function. The Principle Component Analysis method was applied as an input preprocessing step embedded within the ANN in order to reduce dimensionality and correlation for multivariable inputs. This can potentially aid in determining accurate margins over applying arbitrary margins. The automatic optimization of the Bootstrap ANN PI is left for future consideration. (authors)

42 ENGINEERING↗
DOE OSTI2017

Preliminary Analysis of FFTF Loss-of-Flow Tests with SAS4A/SASSYS-1

The Fast Flux Test Facility (FFTF) was the most recent Sodium-cooled Fast Reactor (SFR) built in the United States. The Passive Safety Test (PST) program was carried out on FFTF between 1984 and 1986 to demonstrate the capability of passive reactor shutdown and decay heat removal in response to protected and unprotected transients. In order to recover the information and knowledge that has been gained from FFTF, a research project was initiated focusing on the simulation of Unprotected Loss of Flow Without Scram (LOFWOS) tests similar to the knowledge preservation activities conducted for EBR-II by Argonne National Laboratory in earlier years. These knowledge preservation activities are intended to support the validation of computational tools and methods in the area of SFR passive safety. Comparisons with experimental data and other safety codes provide opportunities to improve SFR design and safety analysis codes and methods.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Maskless Fourier transform holography

Fourier transform holography is a lensless imaging technique that retrieves an object's exit-wave function with high fidelity. It has been used to study nanoscale phenomena and spatio-temporal dynamics in solids, with sensitivity to the phase component of electronic and magnetic textures. However, the method requires an invasive and labor-intensive nanopatterning of a holography mask directly onto the sample, which can alter the sample properties, forces a fixed field-of-view, and leads to a low signal-to-noise ratio at high resolution. In this work, we propose using wavefront-shaping diffractive optics to create a structured probe with full control of its phase at the sample plane, circumventing the need for a mask. We demonstrate in silico that the method can image nanostructures and magnetic textures and validate our approach with a visible light-based experiment. The method enables investigation of a plethora of phenomena at the nanoscale including magnetic and electronic phase coexistence in solids, with further uses in soft and biological matter research.

Keskinbora, Kahraman↗
DOE OSTI2018

Validation of statistical uncertainties in subcritical benchmark measurements: Part II – Measured data

Part I of this work presented an uncertainty approach which incorporates the singles and doubles counting rates determined by the Hage-Cifarelli formalism of the Feynman Variance-to-Mean method. This moments-based approach utilizes time correlations between prompt neutrons detections to assess the system multiplication. Additionally, it presented a validation which utilized simulated data generated using a 0-D point-kinetics Monte Carlo code. In Part II, this same method and validation approach is applied to measured data of a subcritical benchmark experiment. These measurements were performed with a 4.5 kg sphere of alpha-phase weapons grade plutonium reflected by copper and/or polyethylene. Finally, the results of 17 configurations are shown including detailed validation for four of the configurations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Phase transformation of Ca{sub 4}[Al{sub 6}O{sub 12}]SO{sub 4} and its disordered crystal structure at 1073 K

The phase transformation of Ca{sub 4}[Al{sub 6}O{sub 12}]SO{sub 4} and the crystal structure of its high-temperature phase were investigated by differential thermal analysis, temperature-dependent Raman spectroscopy and high-temperature X-ray powder diffraction (CuKα{sub 1}). We determined the starting temperature of the orthorhombic-to-cubic transformation during heating (=711 K) and that of the reverse transformation during cooling (=742 K). The thermal hysteresis was negative (=−31 K), suggesting the thermoelasticity of the transformation. The space group of the high temperature phase is I4{sup ¯}3m with the unit-cell dimensions of a=0.92426(2) nm and V=0.78955(2) nm{sup 3} (Z=2) at 1073 K. The initial structural model was derived by the direct methods and further refined by the Rietveld method. The final structural model showed the orientational disordering of SO{sub 4} tetrahedra. The maximum-entropy method-based pattern fitting method was used to confirm the validity of the split-atom model, in which conventional structure bias caused by assuming intensity partitioning was minimized. At around the transformation temperature during heating, the vibrational spectra, corresponding to the Raman-active SO{sub 4} internal stretching mode, showed the continuous and gradual change in the slope of full width at half maximum versus temperature curve. This strongly suggests that the orthorhombic-to-cubic phase transformation would be principally accompanied by the statistical disordering in orientation of the SO{sub 4} tetrahedra, without distinct dynamical reorientation. - Graphical abstract: (Left) Three-dimensional electron-density distributions of the SO{sub 4} tetrahedron with the split-atom model, and (right) a bird's eye view of electron densities on the plane parallel to (111). - Highlights: • Crystal structure of Ca{sub 4}[Al{sub 6}O{sub 12}]SO{sub 4} at 1073 K is determined by powder XRD. • The atom arrangements are represented by the split-atom model. • The MPF method is used to confirm the validity of the model. • The phase transition is accompanied by orientational disordering of SO{sub 4} tetrahedra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Data for A Fluorescence-Based Transient Expression Assay for the Analysis of Upstream Open Reading Frames in Plants

Scripts for the manuscript "A fluorescence-based transient expression assay for the analysis of upstream open reading frames in plant" by Haas et al. Upstream open reading frames (uORFs) are regulatory elements present in the 5′ leaders of mRNA that can significantly impact downstream gene expression in eukaryotes. In crop engineering, editing of uORFs can provide an avenue to upregulate expression of native genes without the need to add persistent transgenic copies. Even with genome- wide methods to identify translated uORFs such as ribosome profiling, their functional characterization depends on validation through reporter gene assays and mutagenesis studies. Current screening methods for plants use luciferases or protoplasts to measure differential gene expression between wild- type and mutated transcript leaders, which requires tissue processing and/or substrate addition. Here, we present a time- and cost- efficient alternative to investigate transcript leaders by co- expression of two fluorescent proteins in Nicotiana benthamiana leaf tissue and test our assay on genes involved in photoprotection, editing of which could provide a pathway to increase CO2 assimilation during sun–shade transitions.

Gene Editing↗