Search NASA⌕ Search

SEARCH · Search NASA

Results for “correlation screening”

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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probing the Short-Distance Structure of the Quark-Gluon Plasma with Energy Correlators

Energy-energy correlators (EECs) are promising observables to study the dynamics of jet evolution in the quark-gluon plasma (QGP) through its imprint on angular scales in the energy flux of final-state particles. We carry out the first complete calculation of EECs using realistic simulations of high-energy heavy-ion collisions and dissect the different dynamics underlying the final distribution through analyses of jet propagation in a uniform medium. The EECs of γ -jets in heavy-ion collisions are found to be enhanced by the medium response from elastic scatterings instead of induced gluon radiation at large angles. In the meantime, EECs are suppressed at small angles due to energy loss and transverse momentum broadening of jet shower partons. These modifications are further shown to be sensitive to the angular scale of the in-medium interaction, as characterized by the Debye screening mass. Experimental verification and measurement of such modifications will shed light on this scale and the short-distance structure of the QGP in heavy-ion collisions. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1958

Inclined Bodies of Various Cross Sections at Supersonic Speeds

To aid in assessing effects of cross-sectional shape on body aerodynamics, the forces and moments have been measured for bodies with circular, elliptic, square, and triangular cross sections at Mach numbers 1.98 and 3.88. Results for bodies with noncircular cross sections have been compared with results for bodies of revolution having the same axial distribution of cross-sectional area (and, thus, the same equivalent fineness ratio). Comparisons have been made for bodies of fineness ratios 6 and 10 at angles of attack from 0 deg to about 20 deg and for Reynolds numbers, based on body length, of 4.0 x 10(exp 6) and 6.7 x 10(exp 6). The results of this investigation show that distinct aerodynamic advantages can be obtained by using bodies with noncircular cross sections. At certain angles of bank, bodies with elliptic, square, and triangular cross sections develop considerably greater lift and lift-drag ratios than equivalent bodies of revolution. For bodies with elliptic cross sections, lift and pitching-moment coefficients can be correlated with corresponding coefficients for equivalent circular bodies. It has been found that the ratios of lift and pitching-moment coefficients for an elliptic body to those for an equivalent circular body are practically constant with change in both angle of attack and Mach number. These lift and moment ratios are given very accurately by slender-body theory. As a result of this agreement, the method of NACA Rep. 1048 for computing forces and moments for bodies of revolution has been simply extended to bodies with elliptic cross sections. For the cases considered (elliptic bodies of fineness ratios 6 and 10 having cross-sectional axis ratios of 1.5 and 2), agreement of theory with experiment is very good. As a supplement to the force and moment results, visual studies of the flow over bodies have been made by use of the vapor-screen, sublimation, and white-lead techniques. Photographs from these studies are included in the report.

Jorgensen, Leland H.↗
NASA NTRS2016

MOPITT Mechanisms 16 Years In-Orbit Operation on TERRA

The 16th anniversary of the launch of NASA's Terra Spacecraft was marked on December 18, 2015, with the Measurements of Pollution in the Troposphere (MOPITT) instrument being a successful contributor to the NASA EOS flagship. MOPITT has been enabled by a large suite of mechanisms, allowing the instrument to perform long-duration monitoring of atmospheric carbon monoxide, providing global measurements of this important greenhouse gas for 16 years. Mechanisms have been successfully employed for scanning, cooling of detectors, and to optically modulate the gas path length within the instrument by means of pressure and gas cell length variation. The instrument utilizes these devices to perform correlation spectroscopy, enabling measurements with vertical resolution from the nadir view, and has thereby furthered understanding of source and global transport effects of carbon monoxide. Given the design requirement for a 5.25-year lifetime, the stability and performance of the majority of mechanisms have far surpassed design goals. With 16 continuously operating mechanisms in service on MOPITT, including 12 rotating mechanisms and 4 with linear drive elements, the instrument was an ambitious undertaking. The long life requirements combined with demands for cleanliness and optical stability made for difficult design choices including that of the selection of new lubrication processes. Observations and lessons learned with regards to many aspects of the mechanisms and associated monitoring devices are discussed here. Mechanism behaviors are described, including anomalies, long-term drive current/power, fill pressure, vibration and cold-tip temperature trends. The effectiveness of particular lubrication formulations and the screening method implemented is discussed in relation to continuous rotating mechanisms and stepper motors, which have exceeded 15 billon rotations and 2.5 billion steps respectively. Aspects of gas cell hermeticity, optical cleanliness, heater problems and SEU effects on accelerometers are also discussed.

Gibson, Andrew S.↗
DOE OSTI2019

Fissile material detection using neutron time-correlations from photofission

The detection of special nuclear materials (SNM) in commercial cargoes is a major objective in the field of nuclear security. In this work we investigate the use of two-neutron time-correlations from photo-fission using the Prompt Neutrons from Photofission (PNPF) detectors in Passport Systems Inc.’s (PSI) Shielded Nuclear Alarm Resolution (SNAR) platform for the purpose of detecting ~5 kg quantities of fissionable materials in seconds. The goal of this effort was to extend the secondary scan mode of this system to differentiate fissile materials, such as highly enriched uranium, from fissionable materials, such as low enriched and depleted uranium (LEU and DU). Experiments were performed using a variety of material samples, and data were analyzed using the variance-over-mean technique referred to as Y 2F or Feynman-α. Results were compared to computational models to improve our ability to predict system performance for distinguishing fissile materials. Simulations were then combined with empirical formulas to generate receiver operating characteristics (ROC) curves for a variety of shielding scenarios. We show that a 10 second screening with a 200 μA 9 MeV X-ray beam is sufficient to differentiate kilogram quantities of HEU from DU in various shielding scenarios in a standard cargo container.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Harnessing Heterologous Bacterial Two-Component Systems as Biosensors to Address Challenges in Fermentation Scale-Up

Scaling up bacterial fermentation from bench to industrial scale often results in unpredictable performance losses, possibly in part due to changes in microenvironmental conditions such as pH. To investigate this, we developed a suite of pH-sensitive biosensors from bacterial two-component systems (TCSs) that provide a dynamic, fluorescent readout in response to extracellular pH changes. TCSs consist of a periplasmic sensor histidine kinase (HK) that, in response to an extracellular stimulus, autophosphorylates intracellularly and subsequently transfers the phosphate to a cognate response regulator (RR) that modulates transcription of target genes. We utilized three pH-responsive TCSs (referred to here as CVJ1, CVJ30, and CVJ79) and linked their output to GFP. This was achieved by placing the RR promoter upstream of GFP or by constructing a chimeric RR composed of the native receiver domain and the DNA-binding domain of another well-characterized RR with a defined promoter. All components - HK, RR (native or chimeric), and GFP under its corresponding promoter - were cloned into a broad-host-range plasmid. Sensors were validated in Escherichia coli and Pseudomonas putida, including the muconic acid-producing strain P. putida TL207. All three biosensors successfully reported pH, with fluorescence (normalized to optical density) correlating strongly with media pH. Among the native sensors, CVJ79 showed the most robust performance while CVJ1 also performed best in its native form; CVJ30 exhibited improved functionality as a chimera, suggesting that modular RR design can enhance compatibility in some heterologous hosts. Further, CVJ79 was activated by alkaline conditions, while CVJ30 responded to acidic environments. Notably, CVJ1 was induced by high pH in wild-type E. coli and P. putida, but low pH in TL207. The observed differences in sensor activation between strains - particularly the divergent response of CVJ1 - suggest that host-specific regulatory pathways may influence how cells perceive and adapt to pH stress. Moving forward, these biosensors can be used to guide the rational design of more robust strains, optimize process conditions in real time, and inform strategies to minimize physiological heterogeneity during scale-up. Integrating these tools into high-throughput screening and bioreactors will be a key step toward improving predictability and performance in industrial bioprocesses.

09 BIOMASS FUELS↗
DOE OSTI2014

Liver biomarker and in vitro assessment confirm the hepatic origin of aminotransferase elevations lacking histopathological correlate in beagle dogs treated with GABA{sub A} receptor antagonist NP260

NP260 was designed as a first-in-class selective antagonist of α4-subtype GABA{sub A} receptors that had promising efficacy in animal models of pain, epilepsy, psychosis, and anxiety. However, development of NP260 was complicated following a 28-day safety study in dogs in which pronounced elevations of serum aminotransferase levels were observed, although there was no accompanying histopathological indication of hepatocellular injury. To further investigate the liver effects of NP260, we assayed stored serum samples from the 28-day dog study for liver specific miRNA (miR-122) as well as enzymatic biomarkers glutamate dehydrogenase and sorbitol dehydrogenase, which indicate liver necrosis. Cytotoxicity assessments were conducted in hepatocytes derived from dog, rat, and human liver samples to address the species specificity of the liver response to NP260. All biomarkers, except ALT, returned toward baseline by Day 29 despite continued drug treatment, suggesting adaptation to the initial injury. In vitro analysis of the toxicity potential of NP260 to primary hepatocytes indicated a relative sensitivity of dog > human > rat, which may explain, in part, why the liver effects were not evident in the rodent safety studies. Taken together, the data indicate that a diagnostic biomarker approach, coupled with sensitive in vitro screening strategies, may facilitate interpretation of toxicity potential when an adaptive event masks the underlying toxicity. - Highlights: • NP260 caused ALT elevations in dogs without evidence of hepatocellular injury. • SDH, GLDH, and miRNA-122 elevations occurred, confirming hepatocellular necrosis. • NP260 toxicity is greater in dog and human hepatocytes than in rat hepatocytes. • Species sensitivity may explain why the rodent studies failed to indicate risk. • Diagnostic biomarkers and hepatocyte studies aid interpretation of hepatotoxicity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A microbial sensor for organophosphate hydrolysis exploiting an engineered specificity switch in a transcription factor

A whole-cell biosensor utilizing a transcription factor (TF) is an effective tool for sensitive and selective detection of specialty chemicals or anthropogenic molecules, but requires access to an expanded repertoire of TFs. Using homology modeling and ligand docking for binding pocket identification, assisted by conservative mutations in the pocket, we engineered a novel specificity in an Acinetobacter TF, PobR, to ‘sense’ a chemical p-nitrophenol (pNP) and measured the response via a fluorescent protein reporter expressed from a PobR promoter. Out of 107 variants of PobR, four were active when dosed with pNP, with two mutants showing a specificity switch from the native effector 4-hydroxybenzoate (4HB). One of the mutants, pNPmut1 was then used to create a smart microbial cell responding to pNP production from hydrolysis of an insecticide, paraoxon, in a coupled assay involving phosphotriesterase (PTE) enzyme expressed from a separate promoter. We show the fluorescence of the cells correlated with the catalytic efficiency of the PTE variant expressed in each cell. High selectivity between similar molecules (4HB versus pNP), high sensitivity for pNP detection (~2 μM) and agreement of apo- and holo-structures of PobR scaffold with predetermined computational models are other significant results presented in this work.

Jha, Ramesh K.↗
DOE OSTI2012

Manipulating replisome dynamics to enhance lambda Red-mediated multiplex genome engineering

Disrupting the interaction between primase and helicase in Escherichia coli increases Okazaki fragment (OF) length due to less frequent primer synthesis. We exploited this feature to increase the amount of ssDNA at the lagging strand of the replication fork that is available for λ Red-mediated Multiplex Automatable Genome Engineering (MAGE). Supporting this concept, we demonstrate that MAGE enhancements correlate with OF length. Compared with a standard recombineering strain (EcNR2), the strain with the longest OFs displays on average 62% more alleles converted per clone, 239% more clones with 5 or more allele conversions and 38% fewer clones with 0 allele conversions in 1 cycle of co-selection MAGE (CoS-MAGE) with 10 synthetic oligonucleotides. Additionally, we demonstrate that both synthetic oligonucleotides and accessible ssDNA targets on the lagging strand of the replication fork are limiting factors for MAGE. Given this new insight, we generated a strain with reduced oligonucleotide degradation and increased genomic ssDNA availability, which displayed 111% more alleles converted per clone, 527% more clones with 5 or more allele conversions and 71% fewer clones with 0 allele conversions in 1 cycle of 10-plex CoS-MAGE. These improvements will facilitate ambitious genome engineering projects by minimizing dependence on time-consuming clonal isolation and screening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

In Search of Optimum Fresh-Cut Raw Material: Using Computer Vision Systems as a Sensory Screening Tool for Browning-Resistant Romaine Lettuce Accessions

The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.

Agriculture↗
DOE OSTI2015

Prediction of the visual impact of motorways using GIS

Large scale transportation projects can adversely affect the visual perception of environmental quality and require adequate visual impact assessment. In this study, we investigated the effects of the characteristics of the road project and the character of the existing landscape on the perceived visual impact of motorways, and developed a GIS-based prediction model based on the findings. An online survey using computer-visualised scenes of different motorway and landscape scenarios was carried out to obtain perception-based judgements on the visual impact. Motorway scenarios simulated included the baseline scenario without road, original motorway, motorways with timber noise barriers, transparent noise barriers and tree screen; different landscape scenarios were created by changing land cover of buildings and trees in three distance zones. The landscape content of each scene was measured in GIS. The result shows that presence of a motorway especially with the timber barrier significantly decreases the visual quality of the view. The resulted visual impact tends to be lower where it is less visually pleasant with more buildings in the view, and can be slightly reduced by the visual absorption effect of the scattered trees between the motorway and the viewpoint. Based on the survey result, eleven predictors were identified for the visual impact prediction model which was applied in GIS to generate maps of visual impact of motorways in different scenarios. The proposed prediction model can be used to achieve efficient and reliable assessment of visual impact of motorways. - Highlights: • Motorways induce significant visual impact especially with timber noise barriers. • Visual impact is negatively correlated with amount of buildings in the view. • Visual impact is positively correlated with percentage of trees in the view. • Perception-based motorway visual impact prediction model using mapped predictors • Predicted visual impacts in different scenarios are mapped in GIS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

PanFP: Pangenome-based functional profiles for microbial communities

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.

16S rRNA survey↗
DOE OSTI2012

Bronsted-Evans-Polany relationships for C-C bond forming and C-C bond breaking reactions in thiamine-catalyzed decarboxylation of 2-keto acids using density functional theory.

The concept of generalized enzyme reactions suggests that a wide variety of substrates can undergo enzymatic transformations, including those whose biotransformation has not yet been realized. The use of quantum chemistry to evaluate kinetic feasibility is an attractive approach to identify enzymes for the proposed transformation. However, the sheer number of novel transformations that can be generated makes this impractical as a screening approach. Therefore, it is essential to develop structure/activity relationships based on quantities that are more efficient to calculate. In this work, we propose a structure/activity relationship based on the free energy of binding or reaction of non-native substrates to evaluate the catalysis relative to that of native substrates. While Broensted-Evans-Polanyi (BEP) relationships such as that proposed here have found broad application in heterogeneous catalysis, their extension to enzymatic catalysis is limited. We report here on density functional theory (DFT) studies for C-C bond formation and C-C bond cleavage associated with the decarboxylation of six 2-keto acids by a thiamine-containing enzyme (EC 1.2.7.1) and demonstrate a linear relationship between the free energy of reaction and the activation barrier. We then applied this relationship to predict the activation barriers of 17 chemically similar novel reactions. These calculations reveal that there is a clear correlation between the free energy of formation of the transition state and the free energy of the reaction, suggesting that this method can be further extended to predict the kinetics of novel reactions through our computational framework for discovery of novel biochemical transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Long range electrostatic forces in ionic liquids

Ionic liquids are pure salts that are liquid under ambient conditions. As liquids composed solely of ions, the scientific consensus has been that ionic liquids have exceedingly high ionic strengths and thus very short Debye screening lengths. However, several recent experiments from laboratories around the world have reported data for the approach of two surfaces separated by ionic liquids which revealed remarkable long range forces that appear to be electrostatic in origin. Evidence has accumulated demonstrating long range surface forces for several different combinations of ionic liquids and electrically charged surfaces, as well as for concentrated mixtures of inorganic salts in solvent. The original interpretation of these forces, that ionic liquids could be envisioned as “dilute electrolytes,” was controversial, and the origin of long range forces in ionic liquids remains the subject of discussion. Here we seek to collate and examine the evidence for long range surface forces in ionic liquids, identify key outstanding questions, and explore possible mechanisms underlying the origin of these long range forces. Long range surface forces in ionic liquids and other highly concentrated electrolytes hold diverse implications from designing ionic liquids for energy storage applications to rationalizing electrostatic correlations in biological self-assembly.

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

UV + Damp Heat Induced Power Losses in Fielded Utility N-Type Si PV Modules

A recent trend in commercial PV modules is a transition to n-type silicon cells, including passivated emitter rear totally diffused (n-PERT), tunnel oxide passivated contact (TOPCon), and silicon heterojunction (SHJ). There is evidence via lab studies that some of these cells are more susceptible to UV induced degradation (UVID), yet there is a lack of confirmation that such degradation occurs in the field. Current IEC standards designed to screen for early module failures require only minimal UV exposure (15 kWh/m2 280-400 nm, ~2-3 months equivalent outdoor exposure). Here, we investigate fielded n-PERT silicon (Si) modules from a commercial utility that show power losses of ~2%/year. We present a comprehensive picture of the physics and chemistry of degradation supported by both module and cell electronic characterization (EL, PL, IV, EQE, and DLIT) and materials-level morphological and chemical analysis (SEM, EDS, XPS, FTIR, and HPLC). All sampled site modules show short circuit current (Isc) and open circuit voltage (Voc) losses when compared to unfielded spares, with the most severely degraded also having losses in fill factor (FF). We identify two different degradation modes contributing to overall power loss: (1) external quantum efficiency (EQE) measurements show losses in the blue range of the spectra, indicative of cell surface recombination losses, and (2) variations in high series resistance (Rs) at the cell level that are correlated with compositional differences in cell metallization. Using unfielded spares, we were able to reproduce Voc, Isc, and EQE losses via a minimum UV stress of 67.5 kWh/m2 (280-400 nm), 4.5x the exposure currently required in IEC 61215-2 (MQT 10). Degradation continued with additional UV dosage equivalent to the fielded modules (405 kWh/m2 total), with power loss leveling out at an average of 6.1%. Subsequent 1000 h of 85% RH/85degrees C damp heat testing showed that cells exposed to UV underwent additional severe series resistance degradation, even those without the susceptible paste composition seen in the field, whereas non-UV exposed cells saw little change. We attribute this to higher concentrations of acetic acid generated on the UV exposed area of the module, leading to degradation of the gridline/cell interface and high Rs. This study is unique in that it reproduces field observed utility scale UVID with an accelerated test and supports the need for standards development for longer UV exposure combined with other stress factors to catch materials interplay within a module package.

14 SOLAR ENERGY↗
DOE OSTI2022

Exploring the Origin of Anionic Redox Activity in Super Li-Rich Iron Oxide-Based High-Energy-Density Cathode Materials

Super alkali-rich materials (alkali:transition metal ratio of ≥2:1), such as Li 5 FeO 4 , exhibit the potential to realize anionic redox upon deep delithiation. Li 5 FeO 4 was shown to undergo reversible cycling between Li 4 FeO 3.5 and Li 3 FeO 3.5 with combined cation/anion redox, a remarkable capacity of 189 mAh/g, and no O 2 release. However, the impact of phase transformations on the reaction thermodynamics and the correlation between the structural changes and reaction reversibility remain unclear. In this study, we use first-principles calculations to examine the delithiation and (re)lithiation reactions of Li 5 FeO 4 . We show that the experimentally observed charge and discharge processes go through non-equilibrium pathways. Upon delithiation, the compound undergoes a phase transformation from Li 5 FeO 4 , with tetrahedrally coordinated (T d ) Fe ions, to a delithiated disordered rocksalt structure, with octahedral (O h ) Fe ions. Fe-ion migration has an asymmetric kinetic barrier that makes T d → O h migration facile, whereas the reverse process has a much larger barrier, explaining the difficulties in reaction reversibility. We further elucidate the transition metal and O redox sequences during the charge cycle and identify the complex electrochemistry associated with the dual participation of cationic redox (Fe 3+ /Fe 4+ ) and anionic redox (O 2– /O – /O o ). Armed with this knowledge, we conduct high-throughput screening of known alkali-rich transition metal oxides by evaluating their potential to enable reversible anionic redox, with multiple candidates proposed for further experimental trials. Furthermore, our work provides a useful guide for the further development of super alkali-rich anionic-redox-active electrodes for high-energy-density batteries.

25 ENERGY STORAGE↗
DOE OSTI2012

Relationship between Material Properties and Local Formability of DP980 Steels

A noticeable degree of inconsistent forming behaviors has been observed for the 1st generation advanced high strength steels (AHSS) in production, and they appear to be associated with the inherent microstructural-level inhomogeneities for various AHSS. This indicates that the basic material property requirements and screening methods currently used for the mild steels and high strength low alloys (HSLA) are no longer sufficient for qualifying today’s AHSS. In order to establish more relevant material acceptance criteria for AHSS, the fundamental understandings on key mechanical properties and microstructural features influencing the local formability of AHSS need to be developed. For this purpose, in this study, DP980 was selected as model steels and eight different types of DP980 sheet steels were acquired from various steel suppliers. Various experiments were then performed on the eight different DP980 steels such as chemical composition analysis, static tensile test, hole expansion test, channel forming test. Scanning electron microscope (SEM) pictures of the DP980 steels were also obtained, and image processing tools were then adopted to those SEM pictures in order to quantify their various microstructural features. The results show that all DP980 steels show large discrepancy in their performance and that the tensile properties and hole expansion properties of these steels do not correlate with their local formability. According to the results up to date, it is not possible to correlate the microstructural features alone to the macroscopically measured deformation behaviors. In addition to image analysis, other experiments (i.e., nano-indentation test) are also planned to quantify the individual phase properties of the various DP steels.

DP steel↗
DOE OSTI2023

Symmetric Kondo Lattice States in Doped Strained Twisted Bilayer Graphene

We use the topological heavy fermion (THF) model and its Kondo lattice (KL) formulation to study the possibility of a symmetric Kondo (SK) state in twisted bilayer graphene. Via a large-N approximation, we find a SK state in the KL model at fillings v = 0,±1,±2 where a KL model can be constructed. In the SK state, all symmetries are preserved and the local moments are Kondo screened by the conduction electrons. At the mean-field level of the THF model at v = 0,±1,±2,±3 we also find a similar symmetric state that is adiabatically connected to the symmetric Kondo state. We study the stability of the symmetric state by comparing its energy with the ordered (symmetry-breaking) states found in [H. Hu et al., Phys. Rev. Lett. 131, 026502 (2023)., Z.-D. Song and B. A. Bernevig, Phys. Rev. Lett. 129, 047601 (2022).] and find the ordered states to have lower energy at v = 0,±1,±2. However, moving away from integer fillings by doping the light bands, our mean-field calculations find the energy difference between the ordered state and the symmetric state to be reduced, which suggests the loss of ordering and a tendency toward Kondo screening. In order to include many-body effects beyond the mean-field approximation, we also performed dynamical mean-field theory calculations on the THF model in the nonordered phase. The spin susceptibility follows a Curie behavior at v = 0,±1,±2 down to ~2 K where the onset of screening of the local moment becomes visible. This hints to very low Kondo temperatures at these fillings, in agreement with the outcome of our mean-field calculations. At noninteger filling v = ±0.5,±0.8,±1.2 dynamical mean-field theory shows deviations from a 1/T susceptibility at much higher temperatures, suggesting a more effective screening of local moments with doping. Lastly, we study the effect of a C 3⁢z -rotational-symmetry-breaking strain via mean-field approaches and find that a symmetric phase (that only breaks C 3⁢z symmetry) can be stabilized at sufficiently large strain at v = 0,±1,±2. Our results suggest that a symmetric Kondo phase is strongly suppressed at integer fillings, but could be stabilized either at noninteger fillings or by applying strain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗