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At least 703 records · Page 39

InAs sidewall tunnel diodes enabled by surface states

Negative differential resistance (NDR), where the device current decreases with increasing bias voltage, is a representative phenomenon where quantum mechanics induces counterintuitive physical behavior and offers promising applications such as high-frequency oscillators, amplifiers, and multilevel logic circuits. While the NDR behavior has been extensively studied in various materials and devices, the role of surface properties in NDR, particularly in InAs-based diodes, remains underexplored. In this work, we report the observation of NDR in vertically structured InAs p + n diodes that exhibit a peak-valley current ratio of ∼6, which is suitably high for applications. Circumference-normalized current–voltage characterization revealed that the NDR originates from band-to-band tunneling between the valence band of p + -InAs and the conduction band of an n + -InAs surface, where the n + surface is due to surface states on otherwise n − -InAs. In addition, by comparing devices with various surface passivation methods (without intentional passivation, benzocyclobutene polymer, and silicon nitride), we found that the surface termination significantly affects the NDR characteristics. We present an equivalent circuit model to explain the observed device behavior. These findings offer insights into surface-enabled NDR phenomena and present new knobs for engineering NDR devices.

Circuit theorems↗

Noninvasive acoustical property measurement of fluids

Methods for noninvasive determination of acoustical properties of flowing in pipes having a large ratio (>10) of pipe diameter to wall thickness, and in highly attenuating fluids are described. When vibrations are excited on the outer surface of the wall of a pipe, the resulting vibrations propagate directly through the wall in a normal direction and through the pipe wall as guided waves, appearing on the opposite side of the pipe. This dual path propagation through pipes, where guided waves take the circumferential path in the wall of the pipe and may interfere with the time of-flight measurement obtained from the direct path through the fluid, is at least in part resolved by subtracting the signal from the guided wave from the combined signal, thereby permitting improved observation of the direct path propagation through the fluid.

Sinha, Dipen N.↗

Systems, methods, and devices for failure detection of one or more energy storage devices

An energy storage device management system can include a management portion for charging/discharging an energy storage device and an ultrasound interrogation portion for passing ultrasound energy through the energy storage device during charge/discharge cycles. A memory stores a stream of capture data instances derived from ultrasound energy exiting the energy storage device and baseline ultrasound data instances corresponding with the energy storage device during normal charging/discharging thereof. A processor can compare each capture data instance with the baseline ultrasound data and detect abnormal operating states of the energy storage device. A warning system can issue a notification when abnormal operating states are detected.

Kowalski, Jeffrey A.↗

Limiter-aware adaptive excitation control for hydropower generators with legacy voltage regulation systems

Hydropower units often rely on legacy excitation systems with fixed automatic voltage regulator (AVR) settings, but parameter drift, changing operating conditions, and evolving grid-service demands can degrade terminal-voltage regulation over time. This problem should be addressed because poor voltage regulation affects reactive-power support, system stability, and reliable plant operation, and replacing installed AVR and limiter logic is costly and disruptive in practice. To address this issue, this paper proposes a retrofit-friendly enhancement for hydropower generator excitation systems that combines adaptive tuning of the AVR middle lead–lag branch with a small proportional-integral correction for removing steady bias and slow drift. The adaptive laws are normalized, projection-bounded, and equipped with leakage, while adaptation is enabled only in the middle branch. Thus, the intent of the underexcitation and overexcitation limiters, as well as legacy current and rate limits, remains unchanged. Stability is analyzed under incremental performance assumptions, yielding boundedness and asymptotic tracking in the absence of saturation. The method is evaluated using real operational data from a utility-scale hydropower unit at Rocky Reach Dam, Unit C-8. Compared with the fixed AVR baseline, the proposed method reduces terminal-voltage mean squared error by about 70%, removes long periods of steady-state bias, and improves transient tracking while coexisting with limiter actions. These results show that substantial voltage-control improvement can be achieved on existing hydropower units with minimal integration effort and without replacing the installed AVR structure.

ESST5B model↗

The corrosion behavior of borosilicate glass in the presence of cementitious waste forms

Borosilicate glasses are widely used for radioactive waste disposal due to their ability to incorporate a variety of contaminants and radionuclides while exhibiting high durability in various disposal scenarios. This research evaluated the dissolution of borosilicate glass using both single-pass-flow-through (ASTM C1662-18) and product consistency test (ASTM C1285-21) methods with different solutions, including a cementitious-contacted water (called grout-contacted, GC, from this point) and solutions with varying levels of dissolved cementitious species such as Si, Ca, Al. Here, the results indicated that the presence of Ca plays a crucial role in suppressing glass corrosion, as evidenced by the slower normalized dissolution rates, which were one order of magnitude lower for boron and two orders of magnitude lower for rhenium, observed in both Ca-amended and GC solutions compared to the pH 12 buffer solution. This effect is attributed to the formation of a dense, low-porosity, and strongly bonded calcium silicate hydrate (CSH) layer on the glass surface, which implies that a glass corrosion process is influenced by ion exchange involving alkali ions Na + , K + , Ca 2+ , and hydrogen-containing species. A small number of glass particles treated in the GC solution showed minor corrosion pits in the form of shallow craters with an average diameter of approximately 500 μm. This observation is correlated with a significant reduction, 2000 to 3000 times lower, in the cumulative volume of glass pores, indicating that smaller pore voids were “sealed” in the presence of Ca 2+ ions, likely attributed to the formation of CSH precipitation or other corrosion products such as calcium carbonate saturated from the grout solution. These findings suggest that the presence of dissolved Ca in the GC solution can slow down the dissolution of borosilicate glass, contrary to the expected trend of higher dissolution rates resulting from exposure to high alkaline and thus higher pH solutions.

36 MATERIALS SCIENCE↗

Exploring direct photodetachment and photodissociation–photodetachment dynamics of platinum iodide anions (PtI n - , n = 2–5) using cryogenic photoelectron spectroscopy

The direct photodetachment and two-photon photodissociation–photodetachment processes of a series of PtI n - (n = 2–5) anions were systematically studied using cryogenic anion photoelectron spectroscopy and first-principles electronic structure calculations. The adiabatic/vertical detachment energies (ADEs/VDEs) of these anions were determined from their 193 nm photoelectron (PE) spectra, i.e., 3.54/3.63, 4.04/4.09, 4.33/4.36, and 4.37/4.41 eV for n = 2–5, respectively, and well reproduced by B3LYP-D3(BJ)/aug-cc-pVTZ-pp calculations. As the coordination number increases, the electron affinity (EA) of PtI n • (n = 2–5) neutrals (equivalent to the corresponding anion’s ADE) gradually increases, exceeding the EA of Cl at n = 3 and exhibiting superhalogen characteristics for n ≥ 3. Meanwhile, the ground state transition contributed from detaching electrons in the highest occupied molecular orbital gradually evolves from the central metal Pt to the iodine ligands. For the PtI 3 - anion, besides one-photon direct detachment, four distinct two-photon photodissociation–photodetachment channels were identified, and the competition between them was discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.

59 BASIC BIOLOGICAL SCIENCES↗

Tomographic Sparse View Selection Using the View Covariance Loss

Standard computed tomography (CT) reconstruction algorithms such as filtered back projection (FBP) and Feldkamp-Davis-Kress (FDK) require many views for producing high-quality reconstructions, which can slow image acquisition and increase cost in non-destructive evaluation (NDE) applications. Over the past 20 years, a variety of methods have been developed for computing high-quality CT reconstructions from sparse views. However, the problem of how to select the best views for CT reconstruction remains open. In this paper, we present a novel view covariance loss (VCL) function that measures the joint information of a set of views by approximating the normalized mean squared error (NMSE) of the reconstruction. We present fast algorithms for computing the VCL along with an algorithm for selecting a subset of views that approximately minimizes its value. Our experiments on simulated and measured data indicate that for a fixed number of views our proposed view covariance loss selection (VCLS) algorithm results in reconstructions with lower NRMSE, fewer artifacts, and greater accuracy than current alternative approaches.

Lin, Jingsong [Purdue University]↗

CTF Validation and Verification: Version 4.3

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the CTF. One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model—rod bundle geometries with operating conditions that are representative of prototypical pressurized water reactor (PWR)s and boiling water reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CTF Validation and Verification: Version 4.4

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the CTF. One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model—rod bundle geometries with operating conditions that are representative of prototypical pressurized water reactor (PWR)s and boiling water reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis

Introduction Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks. Methods We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph). Results The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing. Discussion Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git .

Chen, Xiaoyi↗

Normalized Solar-Induced Fluorescence Responds Earlier Than Vegetation Indices to the 2019 North China Plain Drought

Recently, solar-induced chlorophyll fluorescence (SIF) from satellites has shown potential for evaluating vegetation status and stress responses. Fluorescence quantum yield ($Φ_F$) is essentially linked to vegetation stress. However, the complex physiological and structural responses of SIF and $Φ_F$ to drought need further study. This study normalized SIF as SIFn to account for angular variations and fluctuations in photosynthetically active radiation (PAR), aiming for more accurate drought monitoring. SIFn anomalies were compared to historical baselines (2019–2021 averages) of vegetation indices (VIs), raw SIF, and $Φ_F$ during a 2019 drought in the North China Plain (NCP). Here, the results show SIFn provides an effective method for drought monitoring, showing the earliest decline compared to raw SIF, VIs, and $Φ_F$. In the first two weeks of drought, SIFn decreased by 8.2%, 7.0%, 12.5%, and 8.2% across the four NCP subdivisions. SIFn outperformed other indicators, proving sensitive to early drought detection. SIFn was also examined for tracking drought alleviation by rainfall. The uncertainty under different viewing geometries was quantified. SIFn anomalies showed a strong correlation with rainfall anomalies (R: 0.45 ~ 0.52) and meteorological factors like PAR (R: 0.80 ~ 0.84) and relative humidity (R:0.52 ~ 0.54). The correlation of near-infrared reflectance (NIRv) and $Φ_F$ anomalies with SIF was weak during drought onset (R: 0.16 ~ 0.32) but strong at the end (R: 0.83 ~ 0.87). These suggest both canopy structure (mainly characterized by NIRv) and vegetation chlorophyll ($Φ_F$) are impacted by drought and influence SIF at different stages.

54 ENVIRONMENTAL SCIENCES↗

Recurrence analysis of friction based dry-couplant ultrasonic Lamb waves in plate-like structures

Here, in this study, the effect of friction on the generation of dry-coupled Lamb waves is experimentally investigated. Recurrence analysis is performed to analyze the complex behavior of friction based dry-coupled Lamb waves. In particular, the effect of the normal force, which is necessary for a stronger dry-coupled Lamb wave generation and the friction, on the transmission of mechanical energy and determinism characteristics of Lamb waves are investigated. The results verify that larger friction coefficient and friction force are crucial for generation and propagation of strong Lamb waves supporting the fact that the main mechanism to transfer mechanical energy using dry-couplant is friction. The sensitivity of Lamb waves to the friction coefficient, highlights the importance of designing specific pads with respect to condition of the surface. Besides, the results show that the normal force and friction coefficient can change the determinism characteristics behavior of multimode Lamb waves. Furthermore, it is shown that the determinism value is sensitive to the friction coefficient and normal force. A similar trend is observed in the determinism values and friction coefficient. In general, a smaller friction coefficient indicates smaller determinism value. Additionally, it is shown that a normal load can change the behavior of a system, as observed from recurrence plots, owing to changes in the Lamb waves trajectories in the phase-space domain. In addition, it is shown that recurrence plots enable the detection of mode transitions in multimode Lamb waves. Recurrence analysis is a complementary tool to frequency domain methods for accurate analysis of multimode Lamb waves behavior.

42 ENGINEERING↗

Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains

Abstract In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high‐resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. All DL models produce higher median Nash‐Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

54 ENVIRONMENTAL SCIENCES↗

Next-generation large-scale binary protein interaction network for Drosophila melanogaster

Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the ‘FlyBi’ dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings (dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

59 BASIC BIOLOGICAL SCIENCES↗

CTF Validation and Verification (V.4.2)

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for Light Water Reactor (LWR) analysis. It uses a two-fluid, three-field (i.e. fluid film, fluid drops, and vapor) modeling approach. Both sub-channel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the PSU RDFMG version of COBRA-TF (CTF). One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model-rod bundle geometries with operating conditions that are representative of prototypical Pressurized Water Reactor (PWR)s and Boiling Water Reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Vexcel Imaging's Suitability for Automatic Verification

Accurate, independently verified geospatial data is essential for automated calibration, validation, and operational decision-making. This study evaluated the positional accuracy of Vexcel Imaging™’s UltraCam® Osprey imagery (7.5 cm GSD) using globally distributed Continuously Operating Reference Stations (CORS) as independent control. Despite manufacturer claims of 15 cm horizontal accuracy, residual errors were consistently one to two orders of magnitude larger, with no subset of imagery meeting precision thresholds. These discrepancies cannot be explained by normal photogrammetric or environmental factors and raise concerns about the reliability of the imagery for high-precision tasks. The results demonstrate that Vexcel imagery, in its current form, is unsuitable for workflows requiring rigorous spatial accuracy or automated verification. At the same time, the reproducible validation framework developed in this study establishes a scalable method for assessing commercial imagery, ensuring that future products can be independently and objectively verified before operational adoption.

47 OTHER INSTRUMENTATION↗

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗