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At least 847 records · Page 47

Properties of Nb x Ti (1–x) N thin films deposited on 300 mm silicon wafers for upscaling superconducting digital circuits

Scaling superconducting digital circuits requires fundamental changes in the current material set and fabrication process. The transition to 300 mm wafers and the implementation of advanced lithography are instrumental in facilitating mature CMOS processes, ensuring uniformity, and optimizing the yield. Here, this study explores the properties of Nb x Ti (1–x) N films fabricated by magnetron DC sputtering on 300 mm Si wafers. As a promising alternative to traditional Nb in device manufacturing, Nb x Ti (1–x) N offers numerous advantages, including enhanced stability and scalability to smaller dimensions, in both processing and design. As a ternary material, Nb x Ti (1–x) N allows engineering material parameters by changing deposition conditions. The engineered properties can be used to modulate device parameters through the stack and mitigate failure modes. We report characterization of Nb x Ti (1–x) N films at less than 2% thickness variability, 2.4% T c variability and 3% composition variability. Film resistivity (140–375 Ωcm) shows a strong correlation with the film oxygen content, while the critical temperature T c (4.6 K–14.1 K) is strongly affected by film stoichiometry and its microstructure has only a moderate effect on modifying T c . Our results offer insights about the interplay between film stoichiometry, film microstructure and critical temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Real-time plasma equilibrium reconstruction and shape control for the MAST Upgrade tokamak

Real-time magnetic control has been developed to deliver precise control of multiple plasma shape parameters for advanced divertor configurations, including double-null, Super-X, X-point target and X-divertor for the first time on the MAST Upgrade (MAST-U) spherical tokamak. Successful real-time magnetic equilibrium control of different plasma shape variables has been accomplished in the 2022–2023 MAST-U experimental campaign for the advanced MAST-U divertor configurations. Application of the MAST-U boundary reconstruction algorithm, LEMUR, is described and compared with off-line equilibrium reconstruction and diagnostic measurements. The process of design and verification of the axisymmetric magnetic control schemes using a suite of control analysis tools (known collectively as TokSys) is also described.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Preliminary design of a helium cryogenic system for SAND detector at LBNF-DUNE near site

The Long-Baseline Neutrino Facility (LBNF) is providing a helium cryogenic system to support the superconducting solenoid magnet of the System for on-Axis Neutrino Detection (SAND) for the Deep Underground Neutrino Experiment (DUNE) Near Site at Fermilab in Batavia, IL. The design started in 2020 and construction is set to begin in the mid 2020‘s.The helium cryogenic system primarily consists of a helium refrigerator system, distribution valve boxes, vacuum-jacketed helium and nitrogen transfer lines, warm gaseous helium transfer system, instruments and control system, and gaseous helium storage tanks. It is designed to provide supercritical helium at around 3 bara and 5 K with expansion from 3 to 1.2 bara in the SAND cryostat and 70K forced cold gas helium to cool the thermal shields of the SAND cryostat. The SAND superconductive magnet is indirectly cooled through a liquid helium thermosiphon cycle. A pair of 3 kA leads is cooled by the gas helium vaporized from the liquid helium reservoir in the cryostat turret. The helium system will share the liquid nitrogen tank and liquid nitrogen phase separator with the Near Site Liquid Argon system. The helium recycle compressor system, GHe tanks and LN2 tank will be located on the Surface. The cryogenic facilities including refrigerator cold box, valve boxes and LN2 phase separator will be located on the shaft cryo-mezzanine in the underground cavern. The shaft connecting surface and cavern is more than 60 meter deep. The helium vacuum-jacketed transfer line between the cold box and the SAND magnet is more than 50 meter long. This paper presents the preliminary design of the helium cryogenic system including the design scheme, process flow diagram, heat load estimates, layout plan and so on.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Modeling of Sagging for 3D Printed Layers During the Curing Process

Here, a printed layer of silica-enforced poly(dimethylsiloxane)-co-(diphenylsiloxane) is modeled as a two-phase system consisting of air and polymer with an interface set up during the printing process. The structural geometry changes mostly due to the action of surface tension, while all material properties are strongly temperature dependent. Polymer flow is described using equations of the extended Herschel–Bulkley model, with parameters strongly dependent on temperature and degree of curing. Parameters of the model are determined using flow sweep measurements and separate experiments with vertical structure sagging at different temperatures. The curing process is modeled using dependencies between the curing rate, degree of curing, and temperature obtained in studies by differential scanning calorimetry. The developed model is used for simulations of printed structure deformations with different initial and boundary conditions.

36 MATERIALS SCIENCE↗

NGPINT V3: a containerized orchestration Python software for discovery of next-generation protein–protein interactions

Abstract Summary Batch yeast two-hybrid (Y2H) assays, leveraged with next-generation sequencing, have afforded successful innovations for the analysis of protein–protein interactions. NGPINT is a Conda-based software designed to process the millions of raw sequencing reads resulting from Y2H–next-generation interaction screens. Over time, increasing compatibility and dependency issues have prevented clean NGPINT installation and operation. A system-wide update was essential to continue effective use with its companion software, Y2H-SCORES. We present NGPINT V3, a containerized implementation built with both Singularity and Docker, allowing accessibility across virtually any operating system and computing environment. Availability and implementation This update includes streamlined dependencies and container images hosted on Sylabs (https://cloud.sylabs.io/library/schuyler/ngpint/ngpint) and Dockerhub (https://hub.docker.com/r/schuylerds/ngpint), facilitating easier adoption and integration into high-throughput and cloud-computing workflows. Full instructions and software can be also found in the GitHub repository https://github.com/Wiselab2/NGPINT_V3 and Zenodo https://doi.org/10.5281/zenodo.15256036.

Biochemistry & Molecular Biology↗

Residual Stresses Affect Cell Fragment Movement

Predictive modeling tools such as the finite element method can be of tremendous help in assessing the reliability and long-term performance of photovoltaic modules. In order to obtain accurate results, the proper modeling of materials and manufacturing processes are of utmost importance. Module fabrication introduces thermo-mechanical stresses inside the module laminate, which need to be accounted for as residual stresses in finite element simulations. We found that cell fragment movement and crack opening displacements of fractured silicon cells within modules are affected by those residual stresses. Cell cracking remains a challenging topic in assessing the reliability and durability of damaged modules. Hence, accurately quantifying the separation and movement between cell fragments creates the foundation for establishing reliable lifetime and performance assessments of fractured silicon modules. Here, we present a modeling approach that uses upper and lower bounds to accurately account for the residual stresses introduced by the module lamination process. We designed a four-point flexure coupon test of a laminated, fractured silicon strip to validate our numerical results and found good agreement between our modeling methodology and the experimental data. Finally, we discuss the implications of the residual stresses on the normal crack opening and metallization wear-out of fractured silicon cells.

14 SOLAR ENERGY↗

Fast Neutron Irradiation of a Multichannel JFET-Based Optical Encoder

Modern electrical components are susceptible to damage from high levels of radiation and extreme temperatures found near reactors in terrestrial nuclear power plants and in aerospace applications. Radiation-hardened electronics are being developed, largely for the aerospace industry, but they sometimes rely on application-specific, small-batch semiconductor fabrication processes. These processes tend to be prohibitively expensive to develop and maintain outside major industrial facilities or governmental agencies. Recently, commercially available, nonradiation-rated junction-gate field-effect transistors (JFETs) were shown to maintain their functionality at gamma doses exceeding 1 MGy, suggesting that nonrated, commercially available electrical components could be used to develop systems that are tolerant to ionizing radiation. However, gamma ray survival is not indicative of neutron dose survival, and few studies characterize JFETs under neutron irradiation. To address this knowledge gap, a JFET-based analog multiplexer and optical pulsewidth modulation (PWM) encoder was developed and irradiated using a 252 Cf source to 1.6×10 13 n/cm 2 . The multiplexed optical encoder (MOE) system maintained functionality throughout testing and showed little evidence of radiation effects. These results indicate that circuitry tolerant to fast neutron damage can be developed using low-cost, nonradiation-rated, commercially available JFETs, which could provide a lower production cost alternative to specialized semiconductor processes when designing and building electronics better able to survive neutron irradiation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs

Despite foreseeing tremendous speedups over conventional deep neural networks, the performance advantage of binarized neural networks (BNNs) has merely been showcased on general-purpose processors such as CPUs and GPUs. In fact, due to being unable to leverage bit-level-parallelism with a word-based architecture, GPUs have been criticized for extremely low utilization (1%) when executing BNNs. Consequently, the latest tensorcores in NVIDIA Turing GPUs start to experimentally support bit computation. In this work, we look into this brand new bit computation capability and characterize its unique features. We show that the stride of memory access can significantly affect performance delivery and a data-format co-design is highly desired to support the tensorcores for achieving superior performance than existing software solutions without tensorcores. We realize the tensorcore-accelerated BNN design, particularly the major functions for fully-connect and convolution layers — bit matrix multiplication and bit convolution. Evaluations on two NVIDIA Turing GPUs show that, with ResNet-18, our BTC-BNN design can process ImageNet at a rate of 5.6K images per second, 77% faster than state-of-the-art. Our BNN approach is released on https://github.com/pnnl/TCBNN.

Li, Ang↗

Performance Evaluation of District Energy Microgrids Planning Tool for Non-Technical Users

Community Microgrids are increasingly gaining popularity worldwide for their efficiency, cost-effectiveness, and local resilience improvement. Microgrid planning tools play a crucial role in their deployment. In the process, tentative designs of the microgrid are simulated, analyzed, and optimized. Due to the complexity of the problem, planning tools must carefully balance computational efficiency while seeking the most optimal solutions. This paper investigates the impact of algorithm selection on CPU and memory utilization of a Community Microgrid planning tool that is specifically designed for non-technical users. We compare two version of the code with two alternatives for Community Microgrid planning tools: a Greedy Algorithm, and a Linear Programming Approach. This comparison examines scenarios spanning from 2 to 50 buildings. Our findings revealed a significant difference in performance between the two algorithms, underscoring the critical role of algorithm selection in optimizing the efficiency of Community Microgrid Planning Tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Real-Time Distribution System State Estimation with Asynchronous Measurements

We report state estimation is a fundamental task in power systems. Although distribution systems are increasingly equipped with sensing devices and smart meters, measurements are typically reported at different rates and asynchronously; these aspects pose severe strains on workhorse state estimation algorithms, which are designed to process batches of data collected in a synchronous manner from all the measurement units. In this paper, we develop a novel state estimation algorithm to continuously update the estimate of the state based on measurements received in an asynchronous manner from measurement units. The synthesis of the algorithm hinges on a proximal-point type method, implemented in an online fashion, and capable of processing measurements received sequentially from sensors. A performance analysis is presented by providing bounds on the estimation error in terms of the mean and variance that hold at each iteration and asymptotically. The scheme is also compared with a more traditional Weighted Least Squares estimator that compensates for the lack of measurement data by using, as pseudo measurements, the measurement retrieved during a certain time window. Numerical simulations on the IEEE 37-bus feeder corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of a 250 Degree C 15kV Supercascode Switch Using SiC JFET Technology

Tetra Corporation is developing a pulsed power drilling system for the geothermal industry. The system requires a high temperature switching technology to replace the existing technology based on Si thyristors with a temperature limit of 150 degrees C. This work focuses on the development of such switch based on a Supercascode configuration using SiC JFET technology. The development presented contains thermal models, packaging design and processes, circuit simulations and prototypes of both the Supercascode switch and the high temperature packaged SiC JFETs.

cascaded switch↗

Addressing amorphization and transgranular fracture of B 4 C through Si doping and TiB 2 microparticle reinforcing

Over the last two decades, many studies have contributed to improving our understanding of the brittle failure mechanisms of boron carbide and provided a road map for inhibiting the underlying mechanisms and improving the mechanical response of boron carbide. This paper provides a review of the design and processing approaches utilized to address the amorphization and transgranular fracture of boron carbide, which are mainly based on what we have found through 9 years of work in the field of boron carbides as armor ceramics.

36 MATERIALS SCIENCE↗

Metamodeling Time-Temperature Creep Parameters

Abstract There exist many time-temperature parameter (TTP) models for creep rupture prediction of components including the Larson–Miller (LM), Manson–Haferd (MH), Manson–Brown (MB), Orr–Sherby–Dorn (OSD), Manson–Succop (MS), Graham–Walles (GW), Chitty–Duval (CD), Goldhoff–Sherby (GS) models. It remains a challenge to determine which model is “best”, capable of accurate interpolation and physically realistic extrapolation of creep rupture data for a given material. In this study, metamodeling is applied to create a unified TTP metamodel that combines and regresses into twelve TTP models (eight existing and four newly derived). An analysis of the mathematical problems that exist in TTP models is provided. A matlab code is written that can: (1) calibrate the material constants of any of the twelve TTP models (using the metamodel); (2) determine the most suitable stress-parameter function; (3) and report the normalized mean square error (NMSE) of rupture predictions for a given material database. Using the metamodel, and code, a design engineer can make an intelligent selection of the “best” TTP model for creep resistant design. This process is demonstrated using four isotherms of alloy P91 creep rupture data. To assess the influence of material, further validation is performed on alloys Hastelloy X, 304SS, and 316SS. It is determined that the “best” model is dependent on material type and the quality and quantity of available data.

Engineering↗

Thermal Optimization of a Silicon Carbide, Half-Bridge Power Module

This project describes the modeling process to design the packaging and heat exchanger for a half-bridge wide-bandgap (WBG) power semiconductor module. The module uses two silicon carbide, metal-oxide-semiconductor field-effect transistor (MOSFET) devices per switch position that are soldered to an aluminum nitride, direct-bond copper (DBC) substrate. A baseplate cooling configuration (e.g., no thermal grease) is used along with a water-ethylene glycol, jet-impingement-style heat exchanger. The heat exchanger was designed to be fabricated using prototyping equipment from the National Renewable Energy Laboratory, complies with automotive standards (for minimal channel sizes, flow rates, and coolant), and considers reliability aspects (i.e., erosion/corrosion). Device-scale computational fluid dynamics (CFD) is used first to design the slot jet impingement cooling configuration and compute the effective heat transfer coefficient (HTC) of the concept. The computed HTCs are then used as boundary conditions for a finite element study to optimize the package geometry (e.g., device layout and baseplate thickness) to minimize thermal resistance and minimize temperature variation between the module's four devices. Finally, a fluid manifold is designed to generate the slot jets and cool the devices. Module-scale CFD predicts a relatively low junction-to-fluid thermal resistance of 16.7 mm2 K/W, a 1.4 degrees C temperature variation between devices, and a total pressure drop of 5,860 Pa (0.85 psi) for the design. The thermal resistance of the module design is about 67% lower than the 2015 BMW i3 power electronics/modules thermal resistance.

DIRECT ENERGY CONVERSION↗

Using block-copolymer nanolithography as a tool to sensitively evaluate variation in chemical dry etching rates of semiconductor materials with sub-5 nm resolution

Ion implantation is a robust and established method to customize the electronic properties of Si. However, fabricating doped, ultrafine semiconductor nanostructures can be challenging. Ion implantation has well-established effects on the dry etch rates of Si, which becomes increasingly consequential as the target dimension shrinks below a few tens of nanometers. While dry etching arrays of block copolymer-templated nanoscale holes (pitch = 37.5 nm, diameter ~25 nm) into p-type, n-type, and undoped Si, we observed that the lateral etch rate was notably larger for the n-type regions than p-type or undoped regions. By doing image analyses on high resolution electron micrographs of the nanostructured hole arrays, we were able to extract the porosity and average radii of the holes with subnanometer sensitivity and compare the relative etch rates between different doping conditions. We found that degenerately doped n-type silicon consistently etches between approximately 17% and 27% faster in the lateral direction than p-type Si, resulting in significantly larger porosity and, consequently, less mechanical stability. Here, we demonstrate that top-down dimensional analysis of a densely packed porous nanostructure is a robust method for assessing extremely small differences in the lateral, chemical etch rate of doped Si to a degree of sensitivity that was previously unachievable. The minute, dense-packed nature of block copolymer self-assembled nanostructures is shown to be ideal for this application. This proposed method could be useful for designing fabrication processes for heterogeneous nanostructures, as slight dry etch rate variations that may be within process tolerance at the micrometer-scale appear to have nontrivial consequences at the nanometer scale.

42 ENGINEERING↗

Revealing Micro-Scale Doping Variations in Thin-Films via Simultaneous Luminescence and Current Collection Measurements

Doping thin films used for photovoltaic absorbers is both critical to maximize device voltage and challenging due to complex interactions between point defects in these materials. Such interactions can result in compensation of the intended dopant species, meaning that the active charge-carrier concentration is lower than the concentration incorporated dopants. Charge-carrier compensation is directly related to the open-circuit voltage (VOC) deficit, or magnitude of VOC relative to the theoretical limit. Understanding how the carrier concentration varies within thin-films is necessary to design material processing schedules to minimize this VOC deficit and produce more efficient devices. Unfortunately, measurements of the free carrier concentration are generally relevant at the device level and cannot resolve local differences. Resolving local doping differences in thin-films such as Cd(Se,Te), CZTS, and CIGSe requires techniques with micron or sub-micron spatial resolution due to the polycrystalline structure as well as intended and unintended composition variations in these materials. In this contribution, we show how simultaneous measurement of cathodoluminescence (CL) and electron-beam-induced current (EBIC) can be used to expose doping variations in Cd(Se,Te) thin-films. Simultaneous collection of these signals reveals unexpected differences in the electric field strength through the device thickness due to spatial variation in the carrier concentration.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Defects vibrations engineering for enhancing interfacial thermal transport in polymer composites

To push upper boundaries of thermal conductivity in polymer composites, understanding of thermal transport mechanisms is crucial. Despite extensive simulations, systematic experimental investigation on thermal transport in polymer composites is limited. To better understand thermal transport processes, we design polymer composites with perfect fillers (graphite) and defective fillers (graphite oxide), using polyvinyl alcohol (PVA) as a matrix model. Measured thermal conductivities of ~1.38 ± 0.22 W m -1 K -1 in PVA/defective filler composites is higher than those of ~0.86 ± 0.21 W m -1 K -1 in PVA/perfect filler composites, while measured thermal conductivities in defective fillers are lower than those of perfect fillers. We identify how thermal transport occurs across heterogeneous interfaces. Thermal transport measurements, neutron scattering, quantum mechanical modeling, and molecular dynamics simulations reveal that vibrational coupling between PVA and defective fillers at PVA/filler interfaces enhances thermal conductivity, suggesting that defects in polymer composites improve thermal transport by promoting this vibrational coupling.

42 ENGINEERING↗

ampworks: Battery analysis tools in Python [SWR-25-39]

Ampworks is a collection of tools designed to process experimental battery data with a focus on model-relevant analyses. It currently provides functions for incremental capacity analysis and GITT data processing, helping extract key properties for life and physics-based models (e.g., SPM and P2D). Some tools, like the incremental capacity analysis module, also include graphical user interfaces for ease of use. https://github.com/NREL/ampworks/ https://pypi.org/project/ampworks/

Randall, Corey [National Renewable Energy Laborato↗