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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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DOE OSTI2023

P2M Simulation Exercise on Past Fuel Melting Irradiation Experiments

This paper presents the results of the Power To Melt and Maneuverability (P2M) Simulation Exercise on past fuel melting irradiation experiments, organized within the Organisation for Economic Co-operation and Development/Nuclear Energy Agency Framework for IrraDiation ExperimentS (FIDES) framework by the Core Group (CEA, EDF, and SCK·CEN) and open to all FIDES members. The exercise consisted in simulating two past power ramps where fuel melting was detected: (1) the xM3 staircase power transient [ramp terminal level (RTL) 70 kW·m -1 , average burnup 27 GWd·tU -1 ], carried out in 2005 in the R2 reactor at Studsvik (Sweden), where the rodlet maintained its integrity, and (2) the HBC4 fast power transient (RTL 66 kW·m -1 , average burnup 48 GWd·tU -1 ), carried out in 1987 in the BR2 reactor at SCK·CEN (Belgium), where the cladding failed during the experiment. The exercise was joined by 13 organizations from 9 countries using 11 different fuel performance codes. In this paper, the main results of the Simulation Exercise are presented and compared to available postirradiation examinations (PIE) or on-line measurements during the power ramps (fuel and clad diameters, rod elongation, pellet-clad gap, and fission gas release). Since the focus of the Simulation Exercise is on fuel melting assessment, determination of the boundary between melted/nonmelted fuel and the consequent definition of a melting radius from PIE are first discussed. During the HBC4 ramp, fuel melting was predicted by most of the codes despite differences in the melting models. Higher discrepancies were observed for the xM3 rod that can be attributed partly to power uncertainty and partly to the limited capability of the models to describe partial melting of the fuel during this ramp. Finally, possible code developments to improve simulation results are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Deep Learning-Based Adaptive Remedial Action Scheme with Security Margin for Renewable-Dominated Power Grids

The Remedial Action Scheme (RAS) is designed to take corrective actions after detecting predetermined conditions to maintain system transient stability in large interconnected power grids. However, since RAS is usually designed based on a few selected typical operating conditions, it is not optimal in operating conditions that are not considered in the offline design, especially under frequently and dramatically varying operating conditions due to the increasing integration of intermittent renewables. The deep learning-based RAS is proposed to enhance the adaptivity of RAS to varying operating conditions. During the training, a customized loss function is developed to penalize the negative loss and suggest corrective actions with a security margin to avoid triggering under-frequency and over-frequency relays. Simulation results of the reduced United States Western Interconnection system model demonstrate that the proposed deep learning–based RAS can provide optimal corrective actions for unseen operating conditions while maintaining a sufficient security margin.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Search for IceCube Events in the Direction of ANITA Neutrino Candidates

During the first three flights of the Antarctic Impulsive Transient Antenna (ANITA) experiment, the collaboration detected several neutrino candidates. Two of these candidate events were consistent with an ultra-high-energy upgoing air shower and compatible with a tau neutrino interpretation. A third neutrino candidate event was detected in a search for Askaryan radiation in the Antarctic ice, although it is also consistent with the background expectation. The inferred emergence angle of the first two events is in tension with IceCube and ANITA limits on isotropic cosmogenic neutrino fluxes. Here we test the hypothesis that these events are astrophysical in origin, possibly caused by a point source in the reconstructed direction. Given that any ultra-high-energy tau neutrino flux traversing the Earth should be accompanied by a secondary flux in the TeV-PeV range, we search for these secondary counterparts in 7 yr of IceCube data using three complementary approaches. In the absence of any significant detection, we set upper limits on the neutrino flux from potential point sources. Finally, we compare these limits to ANITA's sensitivity in the same direction and show that an astrophysical explanation of these anomalous events under standard model assumptions is severely constrained regardless of source spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Find the Gap: Black Hole Population Analysis with an Astrophysically Motivated Mass Function

We introduce a novel black hole mass function that realistically models the physics of pair-instability supernovae with a minimal number of parameters. Applying this to all events in the LIGO-Virgo Gravitational-Wave Transient Catalog 2 (GWTC-2), we detect a peak at M BHMG = 46$^{+17}_{-6}$ M ⊙ . Repeating the analysis without the black holes from the event GW190521, we find this feature at M BHMG =54± 6 M ⊙ . These results establish the edge of the anticipated "black hole mass gap" at a value compatible with the expectation from standard stellar structure theory. The mass gap manifests itself as a discontinuity in the mass function and is populated by a distinct, less-abundant population of higher-mass black holes. We find that the primary black hole population scales with power-law index -1.95 ± 0.51 (-1.97 ± 0.44) with (without) GW190521, consistent with models of star formation. Using Bayesian techniques, we establish that our mass function fits a new catalog of black hole masses approximately as well as pre-existing phenomenological mass functions. We also remark on the implications of these results for constraining or discovering new phenomena in nuclear and particle physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Nafion Passivation of c-Si Surface and Edge for Electron Paramagnetic Resonance

Effective surface passivation of crystalline silicon (c-Si) surface by reducing the carrier recombination rate has led to modern c-Si solar cells with efficiencies > 25% in both laboratory and industrial settings. Typical mainstream surface passivation techniques include high-temperature silicon oxide (SiOx), amorphous silicon (a-Si:H), hydrogen-rich silicon nitride (SiNx), and aluminum oxide (Al2O3) [1]. They have demonstrated excellent surface recombination velocity of < 1 cm/s owing to both chemical passivation (via the hydrogen saturation of Si dangling bonds at the c-Si surface), and field-effect passivation (via the band bending from the fixed charge of the dielectric layers). Recently, several groups have studied solution-based organic materials for c-Si passivation, including bis(trifluoromethane)sulfonimide (TFSI), polystyrenesulfonate, and Nafion [2, 3] via spin or dip coating. All films were processed at ambient room temperature, and a high lifetime of 12 ms, as well as a low saturation current density (J0) of 16 fA/cm2, have been demonstrated using Nafion passivation [2]. However, despite the air instability, Nafion has several advantages when introduced to PV applications: (a) Wafer quality can be measured at high throughput after several process stages. (b) It is compatible with PL mapping, compared to HF liquid passivation which cannot be performed in room ambient. (c) Nafion process is fast and poses fewer constraints on process complexity, and cleanness, compared to Al2O3 and a-Si:H passivation. (d) Nafion is the ideal room temperature passivation, which can be applied onto a small fragment of a degraded module to investigate microscopic mechanisms when studying degradation mechanisms. Edge passivation is needed for advanced characterization tests such as Electron Paramagnetic Resonance (EPR), Electrically Detected Magnetic Resonance (EDMR), Deep Level Transient Spectroscopy (DLTS), local cell current-voltage (J-V), and Suns-Voc. In such cases, the laser-damaged minicell edges will obscure the true degradation mechanisms, and Nafion can effectively passivate them without causing further degradation through elevated-temperature processes. In this contribution, we show the passivation results of Nafion on bare nCz and compare it with a Al2O3 witness. We highlight the importance of edge pre-treatment before Nafion to achieve good passivation. We show that Nafion can reach decent passivation without undergoing high-temperature processes. We also explore the temperature dependency of Nafion through photoluminescence (PL) study and demonstrate the application of Nafion under cryogenic temperature (~6 K) through EPR. Our results reveal that Nafion can reduce surface and edge Si dangling bonds at low temperatures. Thus, it can be used as an effective room temperature passivation technique for advanced characterization methods.

c-Si↗
DOE OSTI2021

Intelliquench: An Adaptive Machine Learning System for Detection of Superconducting Magnet Quenches

In superconducting magnets, the irreversible transition of a portion of the conductor to resistive state is called a “quench.” Having large stored energy, magnets can be damaged by quenches due to localized heating, high voltage, or large force transients. Unfortunately, current quench protection systems can only detect a quench after it happens, and mitigating risks in Low Temperature Superconducting (LTS) accelerator magnets often requires fast response (down to ms). Additionally, protection of High Temperature Superconducting (HTS) magnets is still suffering from prohibitively slow quench detection. In this study, we lay the groundwork for a quench prediction system using an auto-encoder fully-connected deep neural network. After dynamically trained with data features extracted from acoustic sensors around the magnet, the system detects anomalous events seconds before the quench in most of our data. While the exact nature of the events is under investigation, we show that the system can “forecast” a quench before it happens under magnet training conditions through a randomized experiment. This opens up the way of integrated data processing, potentially leading to faster and better diagnostics and detection of magnet quenches

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A method to fuse multiphysics waveforms and improve predictive explosion detection: theory, experiment and performance

Natural and human-made sources of transient energy often emit multiple geophysical signatures that include mechanical and electromagnetic waveforms. We present a constructive method to fuse and evaluate statistics that we derive from such multiphysics waveforms that improves our capability to detect small, near-ground explosions over similar methods that consume single signature waveforms. Our method advances Fisher's Combined Probability Test (Fisher's Method) to operate under both hypotheses of a binary test on noisy data and provide researchers with the density functions required to forecast the ability of Fisher's Method to screen fused explosion signatures from noise. We apply this method against 12 d, multisignature explosion and noise records to show (1) that a fused multiphysics waveform statistic that combines radio, acoustic and seismic waveform data can identify explosions roughly 0.8 magnitude units lower than an acoustic emission, STA/LTA detector for the same detection probability and (2) that we can quantitatively predict how this fused, multiphysics statistic performs with Fisher's Method. Our work thereby offers a baseline method for predictive waveform fusion that supports multiphenomenological explosion monitoring (multiPEM) and is applicable to any binary testing problem in observational geophysics.

58 GEOSCIENCES↗
DOE OSTI2021

Alert Classification for the ALeRCE Broker System: The Light Curve Classifier

We present the first version of the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory. The ALeRCE light curve classifier uses variability features computed from the ZTF alert stream and colors obtained from AllWISE and ZTF photometry. We apply a balanced random forest algorithm with a two-level scheme where the top level classifies each source as periodic, stochastic, or transient, and the bottom level further resolves each of these hierarchical classes among 15 total classes. This classifier corresponds to the first attempt to classify multiple classes of stochastic variables (including core- and host-dominated active galactic nuclei, blazars, young stellar objects, and cataclysmic variables) in addition to different classes of periodic and transient sources, using real data. We created a labeled set using various public catalogs (such as the Catalina Surveys and Gaia DR2 variable stars catalogs, and the Million Quasars catalog), and we classify all objects with ≥6 g-band or ≥6 r-band detections in ZTF (868,371 sources as of 2020 June 9), providing updated classifications for sources with new alerts every day. For the top level we obtain macro-averaged precision and recall scores of 0.96 and 0.99, respectively, and for the bottom level we obtain macro-averaged precision and recall scores of 0.57 and 0.76, respectively. Updated classifications from the light curve classifier can be found at the ALeRCE Explorer website (http://alerce.online).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Prompt Detection of Fast Optical Bursts with the Vera C. Rubin Observatory

Abstract The transient optical sky has remained largely unexplored on very short timescales. While there have been some experiments searching for optical transients from minutes to years, none have had the capability to distinguish millisecond fast optical bursts (FOBs). Such very fast transients could be the optical counterparts of fast radio bursts, the prompt emission from γ -ray bursts, or other previously unknown phenomena. Here, we investigate a novel approach to the serendipitous detection of FOBs, which relies on searching for anomalous spatial images. In particular, due to their short duration, the seeing-distorted images of FOBs should look characteristically different than those of steady sources in a standard optical exposure of finite duration. We apply this idea to simulated observations with the Vera C. Rubin Observatory, produced by tracing individual photons through a turbulent atmosphere, and down through the optics and camera of the Rubin telescope. We compare these simulated images to steady-source star simulations in 15 s integrations, the nominal Rubin exposure time. We report the classification accuracy results of a neural network classifier for distinguishing FOBs from steady sources. From this classifier, we derive constraints in duration–intensity parameter space for unambiguously identifying FOBs in Rubin observations. We conclude with estimates of the total number of detections of FOB counterparts to FRBs expected during the 10 yr Rubin Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Palomar Transient Factory Core-collapse Supernova Host-galaxy Sample. I. Host-galaxy Distribution Functions and Environment Dependence of Core-collapse Supernovae

Several thousand core-collapse supernovae (CCSNe) of different flavors have been discovered so far. However, identifying their progenitors has remained an outstanding open question in astrophysics. Studies of SN host galaxies have proven to be powerful in providing constraints on the progenitor populations. In this paper, we present all CCSNe detected between 2009 and 2017 by the Palomar Transient Factory. This sample includes 888 SNe of 12 distinct classes out to redshift z ≈ 1. We present the photometric properties of their host galaxies from the far-ultraviolet to the mid-infrared and model the host-galaxy spectral energy distributions to derive physical properties. The galaxy mass function of Type Ic, Ib, IIb, II, and IIn SNe ranges from 105 to 1011.5 M o˙, probing the entire mass range of star-forming galaxies down to the least-massive star-forming galaxies known. Moreover, the galaxy mass distributions are consistent with models of star-formation-weighted mass functions. Regular CCSNe are hence direct tracers of star formation. Small but notable differences exist between some of the SN classes. Type Ib/c SNe prefer galaxies with slightly higher masses (i.e., higher metallicities) and star formation rates than Type IIb and II SNe. These differences are less pronounced than previously thought. H-poor superluminous supernovae (SLSNe) and SNe Ic-BL are scarce in galaxies above 1010 M o˙. Their progenitors require environments with metallicities of < 0.4 and < 1 solar, respectively. In addition, the hosts of H-poor SLSNe are dominated by a younger stellar population than all other classes of CCSNe. Our findings corroborate the notion that low metallicity and young age play an important role in the formation of SLSN progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Ultrafast kinetics of the antiferromagnetic-ferromagnetic phase transition in FeRh

Understanding how fast short-range interactions build up long-range order is one of the most intriguing topics in condensed matter physics. FeRh is a test specimen for studying this problem in magnetism, where the microscopic spin-spin exchange interaction is ultimately responsible for either ferro- or antiferromagnetic macroscopic order. Femtosecond laser excitation can induce ferromagnetism in antiferromagnetic FeRh, but the mechanism and dynamics of this transition are topics of intense debates. Employing double-pump THz emission spectroscopy has enabled us to dramatically increase the temporal detection window of THz emission probes of transient states without sacrificing any loss of resolution or sensitivity. It allows us to study the kinetics of emergent ferromagnetism from the femtosecond up to the nanosecond timescales in FeRh/Pt bilayers. Our results strongly suggest a latency period between the initial pump-excitation and the emission of THz radiation by ferromagnetic nuclei.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Transferable GeSn ribbon photodetectors for high-speed short-wave infrared photonic applications

We experimentally demonstrate a low-cost transfer process of GeSn ribbons to insulating substrates for short-wave infrared (SWIR) sensing/imaging applications. By releasing the original compressive GeSn layer to nearly fully relaxed state GeSn ribbons, the room-temperature spectral response of the photodetector is further extended to 3.2 μm, which can cover the entire SWIR range. Compared with the as-grown GeSn reference photodetectors, the fabricated GeSn ribbon photodetectors have a fivefold improvement in the light-to-dark current ratio, which can improve the detectivity for high-performance photodetection. The transient performance of a GeSn ribbon photodetector is investigated with a rise time of about 40 μs, which exceeds the response time of most GeSn (Ge)-related devices. In addition, this transfer process can be applied on various substrates, making it a versatile technology that can be used for various applications ranging from optoelectronics to large-area electronics. These results provide insightful guidance for the development of low-cost and high-speed SWIR photodetectors based on Sn-containing group IV low-dimensional structures.

42 ENGINEERING↗
DOE OSTI2025

Tracing priming effects in palsa peat carbon dynamics using a stable isotope-assisted metabolomics approach

Introduction: Peatlands store up to a third of global soil carbon, and in high latitudes their litter inputs are increasing and changing in composition under climate change. Although litter significantly influences peatland carbon and nutrient dynamics by changing the overall lability of peatland organic matter, the physicochemical mechanisms of this impact—and thus its full scope—remain poorly understood. Methods: We applied multimodal metabolomics (UPLC-HRMS, 1 H NMR) paired with 13 C Stable Isotope-Assisted Metabolomics (SIAM) to track litter carbon and its potential priming effects on both existing soil organic matter and carbon gas emissions. Through this approach, we achieved molecule-specific tracking of carbon transformations at unprecedented detail. Results: Our analysis revealed several key findings about carbon dynamics in palsa peat. Microbes responded rapidly to litter addition, producing a short-term increase in CO 2 emissions, fueled nearly exclusively by transformations of litter carbon. Litter inputs significantly contributed to the organic nitrogen pool through amino acids and peptide derivatives, which served as readily accessible nutrient sources for microbial communities. We traced the fate of plant-derived polyphenols including flavonoids like rutin, finding evidence of their degradation through heterocyclic C-ring fission, while accumulation of some polyphenols suggested their role in limiting overall decomposition. The SIAM approach detected subtle molecular changes indicating minimal and transient priming activity that was undetectable through conventional gas measurements alone. This transient response was characterized by brief microbial stimulation followed by rapid return to baseline metabolism. Pre-existing peat organic matter remained relatively stable; significant priming of its consumption was not observed, nor was its structural alteration. Discussion: This suggests that while litter inputs temporarily increase CO 2 emissions, they don’t sustain long-term acceleration of stored carbon decomposition or substantially decrease peat’s carbon store capacity. Our findings demonstrate how technological advancements in analytical tools can provide a more detailed view of carbon cycling processes in complex soil systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Standoff Detection of Chemical Plumes Using Swept-ECQCL Remote Detection Technology: Results from EMRTC Complex Terrain Dual Tracer Experiment

As part of the Complex Terrain Dual Tracer Experiments performed in support of the LYNM program, a swept-wavelength external cavity quantum cascade laser (swept-ECQCL) remote detection system was deployed to measure chemical plume propagation with high temporal resolution. The swept-ECQCL remote detection technology was initially developed at PNNL, and is now under further development at Opticslah, LLC under SBIR funding from DOE (DOE SBIR Phase I Project DE-SC0019855, Remote Detection Technologies, Program Manager Chris Ramos). The swept-ECQCL technology provides a single-frequency infrared laser source which is rapidly scanned over a large wavelength range to measure the infrared absorption of gases, liquids, or solids. Analysis of the measured infrared absorption spectrum is used to detect, identify, and quantify the chemical species which are present. While most previous laser-based techniques used small wavelength tuning ranges to measure only a few isolated spectral lines of a few species, the swept-ECQCL provides the large tuning range needed to measure multiple species simultaneously, and to detect broad absorption features from large molecules or condensed phase materials. In addition, the swept-ECQCL systems have high enough spectral resolution and sensitivity to measure narrow lines of small molecules and determine isotope ratios. The remote detection system for gas plumes is based on the swept-ECQCL technology, and consists of a swept-ECQCL source, infrared detector, control electronics, and beam transmitting and alignment optics. The remote detection system directs the infrared output of the swept-ECQCL to a target retro reflector typically located at ~10-10,000 m distance. The swept-ECQCL wavelength is varied continuously over a large wavelength range (>1000 nm) at rates up to 1000 Hz. The swept ECQCL light reflected from the remote target is collected and focused onto an infrared photodetector. By measuring the detector signal continuously as the swept-ECQCL wavelength is varied, a time-series of absorption spectra are measured for the gases along the beam line of-sight. Based on analysis and fitting of the measured absorption spectra, the time-dependent chemical concentrations of species are determined. Multiple species and mixtures can be detected simultaneously, for all species with absorption features above the sensor noise floor. The sensor output is thus a continuous, high-speed record of identified chemicals along with their concentrations and isotope ratios of interest. The high-speed operation enables low-noise operation in conditions of atmospheric turbulence and allows tracking of fluctuating concentrations in transient chemical plumes as needed for reliable remote detection applications. All components operate with minimal cooling requirements and no cryogens are needed. In addition, the output infrared light is invisible with an intensity below the maximum permissible exposure (MPE) threshold of 100 mW/cm2 for these infrared wavelengths and thus eye safe. The measurement concept for plume detection using the swept-ECQCL remote detection system is as follows. The ECQCL beam is directed toward a remote retro-reflector, which reflects the beam back to the ECQCL system where it is focused onto an infrared photodetector. The line-of-sight from the ECQCL system to the retro-reflector defines the measurement path. The detected infrared signal is recorded continuously and detects the absorption of molecular species along the measurement path. Before a plume release, the system measures absorption from atmospheric constituents, which in this LWIR band consist primarily of lines from H 2 O and CO 2 , with additional weaker absorption from N 2 O, NH 3 , and O 3 possibly contributing. The system then measures any changes in absorption due to the tracer compounds when they enter the measurement path. The shape of absorption features is used to distinguish and identify the different tracer compounds, and the strength of the absorption is used to determine the path-integrated concentration – also called the column density.

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

The Kangaroo’s First Hop: The Early Fast Cooling Phase of EP250108a/SN 2025kg

Fast X-ray transients are a rare and poorly understood population of events. Previously difficult to detect in real time, the launch of the Einstein Probe with its Wide-field X-ray Telescope has led to a rapid expansionof the sample and allowed the exploration of these transients across the electromagnetic spectrum. EP250108a is a recently detected example linked to an optical counterpart, SN 2025kg, or “the kangaroo.” Together with a companion Letter we present our observing campaign and analysis of this event. In this letter, we focus on the early evolution of the optical counterpart over the first 6 days, including our measurement of the redshift of z = 0.17641. We compare to other supernovae and fast transients showing similar features, finding significant similarities with SN 2006aj and SN 2020bvc, and show that the source is well modelled by a rapidly expanding cooling blackbody. We show the observed X-ray and radio properties are consistent with a collapsar-powered jet that is low energy (≲10 51 erg) and/or fails to break out of the dense material surrounding it. While we examine the possibility that the optical emission emerges from the shock produced as the supernova ejecta expand into a dense shell of circumstellar material, due to our X-ray and radio inferences, we favour a model where it arises from a shocked cocoon resulting from a trapped jet. This makes SN 2025 one of the few examples of this currently observationally rare event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Power Module Precursors and Prognostics

The ongoing work involves 1) the identification and evaluation of various electric signals as indicators to module failure and precursors to aging, and 2) the development of corresponding detection techniques. In the current phase, 1) the increase of on-state resistance is selected as the precursor to the power cycle aging of silicon carbide power MOSFET modules based on review and rest data. 2) A detection method leveraging the gate voltage fluctuations magnitude during commutation transients to inform the on-state resistance increase is investigated which has the benefit of being able to be integrated into the gate driver. A dedicated detection circuit for implementation is designed and simulated and is currently in fabrication.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

An efficient and broadly applicable method for transient transformation of plants using vertically aligned carbon nanofiber arrays

Transient transformation in plants is a useful process for evaluating gene function. However, there is a scarcity of minimally perturbing methods for gene delivery that can be used on multiple organs, plant species, and non-excised tissues. We pioneered and demonstrated the use of vertically aligned carbon nanofiber (VACNF) arrays to efficiently perform transient transformation of different tissues with DNA constructs in multiple plant species. The VACNFs permeabilize plant tissue transiently to allow molecules into cells without causing a detectable stress response. We successfully delivered DNA into leaves, roots and fruit of five plant species (Arabidopsis, poplar, lettuce, Nicotiana benthamiana , and tomato) and confirmed accumulation of the encoded fluorescent proteins by confocal microscopy. Using this system, it is possible to transiently transform plant cells with both small and large plasmids. The method is successful for species recalcitrant to Agrobacterium -mediated transformation. VACNFs provide simple, reliable means of DNA delivery into a variety of plant organs and species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗