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At least 379 records · Page 21

Carrier Diffusion Lengths in Continuously Grown and Etched-and-Regrown GaN Pin Diodes

Advanced GaN power devices are promising for many applications in high power electronics but performance limitations due to material quality in etched-and-regrown junctions prevent their widespread use. Carrier diffusion length is a critical parameter that not only determines device performance but is also a diagnostic of material quality. Here we present the use of electron-beam induced current to measure carrier diffusion lengths in continuously grown and etched-and-regrown GaN pin diodes as models for interfaces in more complex devices. Variations in the quality of the etched-and-regrown junctions are observed and shown to be due to the degradation of the n-type material. Finally, we observe an etched-and-regrown junction with properties comparable to a continuously grown junction.

42 ENGINEERING↗

A Robust Statistical Algorithm for Boundary Detection in Liquid Sprays

This work presents a statistical algorithm to detect phase boundaries in liquid sprays. Experimental data were obtained in a nonevaporating acetone spray at atmospheric conditions to minimize the refractive index gradients and associated beam steering. Mie scattering and diffuse background illumination (DBI) diagnostics are implemented to demonstrate the robustness of the approach. The analysis shows that the present algorithm yields similar results for the two different diagnostics, unlike existing threshold-based methodologies providing inconsistent results. The algorithm can be used to identify partial liquid boundaries between single-phase liquid and vapor boundaries. Thus, for each case, liquid boundaries were defined in terms of liquid probability of 100% or less than 100%. Sprays from two different injectors were analyzed to demonstrate the versatility of the methodology. Finally, a parametric study was conducted to demonstrate that motion blur can affect an accurate detection of the phase boundaries, and hence, the exposure time in the experiment must be sufficiently small.

42 ENGINEERING↗

Multiscale Interaction of Turbulence, Temperature, and Soot Formation: Measurements for Critical Assessments of Chemical Kinetics and Mechanisms

This program targeted an improved understanding of how turbulence affects soot formation chemistry (directly and indirectly) with a particular focus on detailing the multiscale coupling between flow turbulence, mixing, thermal transport, and soot formation kinetics in gas-phase reacting systems. In this project, simultaneous, quantitative multi-dimensional velocity, soot volume fraction, and gas-phase temperature measurements in turbulent non-premixed sooting flames were developed. These new diagnostics tools can be used to elucidate the relative effects of fluid kinematics, mixing, thermal processes, and turbulence/scalar time/length scales on soot formation chemistry and topology. Simultaneous multi-parameter measurements were acquired within a series of flames with different Reynolds numbers and spatial locations to investigate the inter-dependence of soot, temperature, and turbulence within the soot inception, growth, and oxidation region. Preliminary assessment of the results has been completed at the project end and detailed analysis is planned following the completed program.

02 PETROLEUM↗

Preliminary Kinetic Analysis of Non-Equilibrium Plasma- Assisted Methanol Pyrolysis and Oxidation Experiments

Efforts to enhance power generation efficiency and reduce emissions have driven interest in novel combustion techniques, including non-equilibrium plasma (NEP) ignitors. NEP ignitors show promise in improving energy conversion efficiency, fuel reforming, emission control, and lean-flammability limits. However, their adoption is hindered by a limited understanding of the interplay between plasma-enhanced combustion and thermal chemistry, particularly for complex fuels under engine-relevant conditions. Developing experimentally validated kinetic mechanisms is therefore critical. Additionally, the increasing interest in renewable biofuels like ethanol and methanol, coupled with the desirable qualities of NEP ignitors, presents a compelling opportunity for study. Therefore, this work acts as an extension of a previous work (Bopaiah et al., 2023) pertaining to the experimental results of NEP-assisted methanol pyrolysis and oxidation. Experiments were performed with a custom-built plasma flow reactor at 0.5 atm and temperatures from 523-1203 K. All reactive mixtures are extremely diluted to minimize exothermicity due to reactivity, allowing isothermal assumptions and the isolation of plasma chemistry from thermal chemistry. A dielectric barrier discharge plasma, at 14 kV and 15 ns full-width half maximum, was applied to the reactive mixture at varying frequencies to maintain the number of pulses with increasing temperature. Steady-state product speciation was performed downstream of the reactor with ex-situ GC/MS diagnostics. The attained experimental results were examined through in-depth analysis performed by means of an in-development plasma-coupled kinetic mechanism. As discussed in the previous work, the plasma significantly accelerates methanol pyrolysis, increasing stable intermediate production, including oxygenated and nitrile species. Plasma-assisted oxidation shows even faster fuel consumption compared to pyrolysis and a 200 K ignition shift compared to thermal oxidation. For plasma-assisted pyrolysis, the model demonstrates that accelerated fuel consumption stems from dissociative quenching of excited N2 states with fuel and H2, generating H radicals that react to rapidly form CH3 and CH2OH radicals. At low temperatures, these radicals recombine to produce oxygenates, while CH3 drives nitrile and hydrocarbon formation at higher temperatures. While the model captures pyrolysis trends well, discrepancies in methane, ethylene, and ethanol predictions are present. Similarly, the model faces challenges in accurately representing plasma-assisted oxidation, predicting a much steeper fuel gradient and ignition 100 K earlier than the experiment. While a similar scheme to pyrolysis is nested in the reaction pathway, the enhancement of the O and H radical fluxes and their initiation of the OH and HO2 radical pools dominate fuel and intermediate oxidation. The overestimation of these processes is shown to be responsible for the divergence of model from experiment. While the modelling predictions of this preliminary mechanism are not perfect, they serve as a valuable starting point. Primarily, they elicited new reaction pathways that are not otherwise possible in thermal chemistry induced reaction kinetics. The results also provide a basis for the future work that should be performed. For example, theoretical and experimental studies on excited nitrogen species and fuel/fuel radical interactions, quantification of the NOx production, and the kinetics behind the slow ignition observed in oxidation should be emphasized.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effects of multiple simultaneous faults on characteristic fault detection features of a heat pump in cooling mode

Faults in air-cooled vapor compression air-conditioning systems are known to reduce performance, including efficiency, capacity, and lifespan. Their effects have been studied, and fault detection and diagnostic (FDD) methods have been developed as tools for field technicians to install or repair systems, or for monitoring to alert operators to the fault’s presence. Most of this work has focused on faults that occur singly. It is likely that in some systems, multiple faults occur simultaneously, but it is uncertain what effects this may have on diagnostics. Here, this paper describes a laboratory study of a split system air source heat pump in which combinations of two, three, and four simultaneous faults occur. The study includes all combinations of: improper evaporator airflow; overcharge or undercharge of refrigerant; liquid line restrictions; and non-condensable gas in the refrigerant, each at multiple fault intensities. Fault features – those characteristics that can be determined from measurements, for use in diagnostics – are analyzed, and the key fault features are presented. A robust existing method for determining refrigerant charge, the virtual refrigerant charge sensor (VRC) is tested using the multiple fault data, in order to understand how its performance is impacted by the combined faults. The VRC performs well, typically able to correctly determine whether a system is undercharged or overcharged, but the magnitude estimates are impacted. The results suggest that simple subcooling-based methods of charging a system are likely to provide unsatisfactory results when other faults are present.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Key Constructs for Reasonable Confidence in System Validation Programs

This paper presents four key constructs developed in preparing IEEE Std P2411TM, Human Factors Engineering Guide for the Validation of System Designs and Integrated Systems Operations at Nuclear Facilities for submission. These constructs reflect judgments that responsible parties make in order to bring validation to closure. Such judgments weigh competing concerns and cost-benefits for stakeholders. Improved processes and methods may support such judgments but cannot alone eliminate uncertainty. Stating and clarifying these constructs aims to reduce uncertainty in the validation process, to better prepare the implementers and reviewers of future validation programs, both in the nuclear industry and beyond. Reasonable Confidence – A proof standard, as used to reach conclusions in a legal case. Legal proof standards are bounded between “preponderance of evidence” and “beyond reasonable doubt”. Reasonable confidence is comparable to an intermediate legal proof standard of “clear and convincing evidence.” Representative Test Set – A collection of scenarios of sufficient variety to represent the anticipated range of operational conditions, events, evolutions, and activities for validating the system(s) under test. Dispositive vs. Diagnostic Criteria – Relevant performance criteria are placed in one of two categories. Dispositive criteria are assessed, without exception, to determine whether a validation test passes or fails overall. Diagnostic criteria are assessed, subject to justified exception, to evaluate the quality or degree of some particular aspect of performance. Repeatability – Consistency in achieving passing results is to be demonstrated for each scenario in the representative test set; thus, the minimum number of formal repetitions for each scenario is two.

99 GENERAL AND MISCELLANEOUS↗

Mechanisms of graphite ablation by sub-millisecond ytterbium fiber laser pulses

Graphite is a key material in a variety of cross-cutting applications in energy conversion, energy storage, and nuclear energy. Recently, temporally modulated continuous wave lasers have been shown to produce well-defined ablation features in graphite at relatively high processing speeds. In this work, we analyze in detail the laser ablation dynamics of single-pulse ablation in the sub-millisecond time regime to elucidate the origins of the resulting well-defined ablation craters using a combination of time-resolved emission imaging, diffuse reflection/scattering imaging, and optical emission spectroscopy. These multimodal in situ diagnostics revealed three main contributors to achieve well-defined ablation features: (1) rapid ejection of particles with ~100 m/s speed, (2) ablation of the graphite in the gaseous form, and (3) absence of bulk liquid motion, which is typically observed in laser processing of metals. Plasma plume formation was sustained throughout the duration of the laser pulse (500 μs). Here, this work provides insights into the complex physical and chemical mechanisms of sub-millisecond laser–matter interactions, which are critical for parameter space optimization and tailoring of laser machining and drilling processes.

42 ENGINEERING↗

Cooperative Education

M-3 Focused Experiments is a group at Los Alamos National Lab (LANL) and is under the Dynamic Experiments Division. Their work surrounds the diagnostics and study of explosives and their interaction with materials. The data collected is used to better understand the erratic nature of explosions and high velocity projectiles. Through better comprehension of this science, the overall national security will be improved while innovations are made along the way. Despite the strong drive for research and development, the lab holds safety above all else and constantly updates procedures to protect LANL employees and their environment. At any time, there are multiple projects going on at once within the team and I am tasked with assisting the Firing Site Leaders and various research diagnosticians in any way possible with the setup, testing, and execution of data collection for each experiment. Such data includes velocity, fragmentation characteristics, and the spread of energy across the material to name a few. During my summer employment with the lab, my main goal is to maintain a questioning attitude and learn as much possible about the research and development side of science and engineering. Throughout the duration of the Co-op, many experiments will take place at specially designed firing sites which is where I will be spending most of my time.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Recovering the phase and amplitude of X-ray FEL pulses using neural networks and differentiable models

Dynamics experiments are an important use-case for X-ray free-electron lasers (XFELs), but time-domain measurements of the X-ray pulses themselves remain a challenge. Shot-by-shot X-ray diagnostics could enable a new class of simpler and potentially higher-resolution pump-probe experiments. Here, we report training neural networks to combine low-resolution measurements in both the time and frequency domains to recover X-ray pulses at high-resolution. Critically, we also recover the phase, opening the door to coherent-control experiments with XFELs. The model-based generative neural-network architecture can be trained directly on unlabeled experimental data and is fast enough for real-time analysis on the new generation of MHz XFELs.

42 ENGINEERING↗

xRage simulations of magnetic velocity gauges used in gas gun shock initiation experiments

Shock initiation gas gun experiments of PBX 9012 have been performed by Burns and Chiquete [2020] using magnetic velocity gauges as the principal diagnostic. In private communications, the experimenters noted that compatibility issues required a different glue to bond the gauges to PBX 9012 then previously used for experiments with PBX 9501 and PBX 9502. The silicon glue used is more viscous and can result in glue layers up to 50 microns, which is about the gauge thickness. This raises the question on what affect the thicker glue layers have on the gauge response. In particular, the width of the lead shock can affect the accuracy of inferring shock locus points used for the shock pressure of Pop plot data points and for Hugoniot data to calibrate the reactants EOS.

36 MATERIALS SCIENCE↗

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗

A Miniaturized Ignition Screening Rapid Compression Machine for probing low-to-intermediate temperature chemistry

With an objective to achieve net-zero emissions by no later than 2050, biofuels hold enormous potential as sustainable, renewable fuels that can be produced on a large scale. However, fuels of a similar type, derived from limited feedstock batch can dramatically vary in terms of their chemical structures and compositions, causing significant differences in physicochemical properties mainly influencing ignition-relevant properties. Rigorous prescreening and testing efforts are involved to evaluate fuels to comply with engines equipped with advanced combustion modes. The testing of some of these fuels implies low quantity fuel samples, access to relevant temperature and pressure conditions, high reproducibility, and a high throughput rate. In light of these considerations, a Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC). Some design features include a smaller bellows-actuated driver section compared to other RCM designs, an adjustable brake section, and full optical access. The setup is designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions are relevant to low-to-intermediate temperature auto-ignition and can generate data for developing relevant chemical kinetics models or ignition maps. A brief insight into MISR design and its operating mechanism is shown. Also, to demonstrate the performance characteristics of the MISR, Ignition Delay (I.D) experiments for ethanol fuel at different equivalence ratios (Φ) are discussed in the context of plans with additional optical diagnostics, high-speed imaging, and gas sampling experiments.

Tomar, Mukul↗

A Bayesian framework to investigate radiation reaction in strong fields

Recent experiments aiming to measure phenomena predicted by strong-field quantum electrodynamics (SFQED) have done so by colliding relativistic electron beams and high-power lasers. In such experiments, measurements of collision parameters are not always feasible. However, precise knowledge of these parameters is required to accurately test SFQED. Here, we present a novel Bayesian inference procedure that infers collision parameters that could not be measured on-shot. This procedure is applicable to all-optical non-linear Compton scattering experiments investigating radiation reaction. The framework allows multiple diagnostics to be combined self-consistently and facilitates the inclusion of known information pertaining to the collision parameters. Using this Bayesian analysis, the relative validity of the classical, quantum-continuous and quantum-stochastic models of radiation reaction was compared for several test cases, which demonstrates the accuracy and model selection capability of the framework and highlight its robustness if the experimental values of fixed parameters differ from their values in the models.

47 OTHER INSTRUMENTATION↗

Active learning of polarizable nanoparticle phase diagrams for the guided design of triggerable self-assembling superlattices

Polarizable nanoparticles are of interest in materials science because of their rich and complex phase behavior that can be used to engineer nanostructured materials with long-range crystalline order. To understand and rationally navigate the design space of polarizable nanoparticles for self-assembling highly ordered superlattices, we developed a coarse-grained computational model to describe the nanoparticle-nanoparticle interactions in implicit solvent and employ the computationally efficient image method to model many-body polarization interactions. We conducted high-throughput virtual screening over a five-dimensional particle design space spanned by temperature, particle size, particle charge, particle dielectric, and solvent dielectric using enhanced sampling molecular dynamics calculations within an active learning framework to efficiently map out the regions of thermodynamic stability of the self-assembled aggregates. We validate our predictions in comparisons against small angle x-ray scattering measurements of gold nanoparticles surface functionalized with metal chalcogenide ligands. Lastly, we use our validated phase maps to computationally design switchable nanostructured materials capable of triggered assembly and disassembly as a function of temperature and solvent dielectric with potential applications as sensors, smart windows, optoelectronic devices, and in medical diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Summer 2021 Co-op Report: X-Ray Scintillation Detector (A Co-op Work Experience Report)

The M-3 team was in need of a detector that could be used properly characterize their X-Ray machines. It can also be used to diagnose the X-ray in the case that problems arise before or during an experiment. They put me in charge of designing, ordering, and constructing said detector. After doing research, I found that scintillation-based detectors would be the best diagnostic tool for this purpose. It will allow the team to collect a full photon count of the X-ray pulse as well as provide spectroscopy functions with which we can view photon counts at different energy levels. This will also allow them to calculate an accurate dose given from the machine. Due to lead times, the crystals are still in manufacturing, thus the detector could not be completed. Although the designs and calculations needed to construct and operate the scintillator have been completed which is what I will be presenting in this document. Compared to the detectors being used before, my design offers a cheaper and far more efficient alternative.

42 ENGINEERING↗

Sandia National Laboratories FY20 Progress Report

The Energetic Neutrons campaign led by Sandia National Laboratories (SNL) had a successful year testing electronic devices and printed circuit boards (PCBs) under 14 MeV neutron irradiation at OMEGA. During FY20 the Energetic Neutrons campaign increased the number and complexity of experiments, continued collaborations with external organizations, and generated knowledge that supports SNL’s National Security mission. In FY20 the Energetic Neutrons campaign was executed by an early career team led by a new PI. The SNL team members were trained to take over new responsibilities during the shot day to increase the number and complexity of experiments in the campaigns. Also, in FY20 for the first time the Energetic Neutrons campaign had a graduate student contributing with pre and post-irradiation characterizations at SNL of the semiconductor devices irradiated at OMEGA. In FY20 SNL collaborated with the Air Force Nuclear Weapons Center (AFNWC) and supported experiments related to radiation effects in semiconductor devices. SNL also gave the opportunity to ride along to Los Alamos National Laboratory and multiple scientists from MIT and LLE. SNL continued using the last two generations of the Neutron Effects Diagnostics (NEDs) to field active and passive experiments but also redesigned the latest generation of the NEDs to accommodate larger components and improve the vacuum sealing as shown in figure 1a. The redesigned NEDs allowed SNL to perform active tests of a high voltage (HV) PCB for the first time at OMEGA; where signals before, during and after the irradiation were recorded. The HV PCB installed in one of the SNL NEDs is shown in figure 1b where a 3D-printed nosecone was used to check for mechanical and electrical interference. Passive irradiations of multiple components were followed up with leakage current, gain measurements and radiation-induced defect characterization.

42 ENGINEERING↗

Electronic Trap-State Modulation in Sm-Doped SnO 2 Nanofibers Enables Ultrasensitive Hydrogen Sensing

The demand for sub-ppm hydrogen (H 2 ) sensing is growing across emerging applications such as environmental monitoring, breath-based disease diagnostics, and early-stage battery failure detection. However, achieving reliable ppb-level detection with chemiresistive metal oxide sensors remains challenging. At trace gas concentrations, resistance modulation is often insufficient, particularly in the absence of noble metal catalysts. Here, we report samarium-doped tin dioxide (Sm-SnO 2 ) nanofibers in which electronic trap-state modulation is exploited to enable ultrasensitive hydrogen sensing. The 2 at% Sm-doped SnO 2 nanofibers exhibited markedly enhanced H 2 sensitivity, achieving clear detection down to 25 ppb H 2 at 200 °C, with a theoretical limit of detection of 4.5 ppb, placing this material among the most sensitive noble-metal-free SnO 2 -based H 2 sensors reported to date. Mechanistic investigations through X-ray photoelectron spectroscopy and electron energy loss spectroscopy revealed that Sm 3+ doping introduces deep trap states associated with charge-compensating defect complexes. These states reduce free carrier density, increase baseline resistance, and enable trap-assisted charge release during H 2 exposure, thereby amplifying the sensing response. Trap-state engineering via rare-earth doping, exemplified by Sm-SnO 2 , provides an effective pathway for achieving ppb-level hydrogen detection in noble-metal-free chemiresistive sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating the relationship between radial pre-stress magnitude and ballistic projectile dwell in heavy confined ceramic targets

A series of bare silicon carbide ceramic armour disks were manufactured with high-strength steel containment to induce varying magnitudes of radial pre-stress. The induced radial stresses, ranging from 0 to 900 MPa, were measured via neutron diffraction and verified by comparison with numerical calculations. Four targets of each configuration, referred to as slip-fit, moderate pre-stress, and high pre-stress, were subject to ballistic testing with hemispherical-nose, tungsten heavy alloy long rod projectiles to determine the interface defeat transition velocity. In-situ diagnostics were unsuccessful in aiding the identification of interface defeat, necessitating a reliance on post-mortem assessment. A transition velocity of approx. 1000 m/s was identified for the unstressed target, increasing to approx. 1200 m/s for the pre-stressed configurations. No performance effect was discernible between the moderate (372 MPa) and high (899 MPa) pre-stress configurations, suggesting that an optimal performance may be achieved for lower pre-stress levels (i.e., <372 MPa). Additionally, the test results were compared with four semi-analytical predictions of interface defeat performance and good agreement was found, albeit with significant range in the model predictions.

42 ENGINEERING↗