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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

From ETROC to VTROC

The Endcap Timing ReadOut Chip (ETROC) is designed to process LGAD signals with time resolution down to about 40-50ps per hit, to reach 30-35ps per track with two detector layers. The ETROC2 is the first full size (16x16) prototype design and is fully compatible with the final chip specifications in terms of functionality. The ETROC2 has been extensively tested recently. In this talk, the testing results of the ETROC2 will be presented first, including performance study using charge injection, laser and beam, as well as TID testing and wafer probe testing to study the yield. In addition, future challenges of precision position and timing ASIC design will be discussed, based on what we have learned from the ETROC development, and how the challenges could be addressed in the VTROC, Vertically integrated Timing ReadOut chip (funded as SBIR phase 2) for precision position and timing detector R&D.

Liu, Ted↗
DOE OSTI2020

Task 12 PV Sustainability - Life Cycle Inventories and Life Cycle Assessments of Photovoltaic Systems

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated impacts in the life cycles of products (i.e., goods and services). One of the major goals of IEA PVPS Task 12 is to provide guidance on assuring consistency, balance, transparency and quality of LCA to enhance the credibility and reliability of the results. The current report presents the latest consensus life cycle inventories among the authors, PV LCA experts in North America, Europe, Asia and Australia. At this time consensus is limited to four technologies for which there are well-established and up-to-date life cycle inventory (LCI) data (mono- and multi-crystalline Si, CdTe, CIGS, as well as one emerging technology (perovskite silicon tandem). LCIs are necessary for LCA and the availability of such data is often the greatest barrier for conducting LCA. The Task 12 LCA experts have put great efforts in gathering and compiling the LCI data presented in this report. These include detailed inputs and outputs during manufacturing of cell, wafer, module, and balance-of-system (i.e., structural and electrical components) that were estimated from actual production and operation facilities. In addition, data are presented to enable analyses of various types of PV installations; these include operational data of rooftop and ground-mount PV systems and country-specific PV-mixes. The LCI datasets presented in this report are the latest that are available to the public describing the status in 2018 for crystalline Si (some manufacturing data from 2011 were not updated), 2015 and 2017-2018 for CdTe, 2010 for CIGS, 2010 for HCPV, and 2017 for perovskite silicon tandem technology.

14 SOLAR ENERGY↗
DOE OSTI2023

Scalable Manufacturing of Efficient Perovskite/Silicon Tandem Modules

Crystalline-Si (c-Si) technology produces excellent solar cells with conversion efficiencies of up to 26.7%—nearly their practical limit of 27%—and has been commercialized extensively to produce panels below $\$0.40$/W. Techno-economic analysis shows that module efficiency will continue to be a primary cost driver because of high balance-ofsystems costs, and there is no path to higher efficiencies with single-junction silicon cells. In this project, three research teams from University of North Carolina, Arizona State University and National Renewable National Laboratory worked together to develop perovskite-silicon tandem cells with a high throughput process which can handle 5000 wafers per hour, enabled by very low added CAPEX of ~$20k for a doctor-blade coater. This can potentially increase the module efficiency to 30% (with grid) with small increase of cost, which will drive down the cost of silicon modules to be at least 16% cheaper than present silicon PERC modules. We also explored the alternative narrow bandgap perovskites as silicon replacement for all perovskite tandem cells. This project has substantially advanced the progress of solution-process perovskitessilicon tandem solar cells and perovskite-perovskite tandem solar cells with many inventions and discoveries, evidenced by 18 publications and 6 invention disclosures. Several notable examples include 1) we developed the new idea of small pyramid in combination with solution grown perovskites and demonstrated record-efficiency of 28.5% for 1 cm2 on textured silicon bottom cells and 25.2% for 24 cm2 on chemically etched silicon bottom cells for perovskite-silicon tandem cells. 2) We developed perovskite ink that can coat perovskites onto texture silicon without voids;, and new device structure to enhance the yield of fabrication by reducing shunting 3) We identified the origin of open circuit voltage on mixed halide wide bandgap perovskites, and came with a solution for this problem, reducing the voltage loss to a record small value, which can potentially push the perovskite-silicon tandem cell efficiency to over 31%; 4) We have developed efficient alternative low bandgap semiconductors, i.e. gradient-doped Sn based perovskites by Ba ions, new oxide hole transport layers which increase the efficiency of perovskite/perovskite tandem cells reached record efficiency of 26.3%; 5) We developed bifacial perovskite/perovskite tandem cells by overcoming contacts issues and regaining light absorption, further boosting the equivalent efficiency to 29.3% under 1 sun illumination with 30% albedo light; 6) We developed the first all perovskite tandem module fabricated in air by discovery a combination of oxidization and reduction couples, yield an aperture efficiency of 21.6% for all perovskite mininodules, exceeding that of single junction perovskite minimodules. These discoveries not only accelerate the commercialization of perovskite-silicon tandem solar cells, but also provide guidance in designing other type of perovskite solar cell technologies.

14 SOLAR ENERGY↗
DOE OSTI2023

THOR-aLEU Report

The advanced low enriched uranium (aLEU)-THOR experiment vehicle is designed to irradiate fresh fuel rodlet specimens containing UO 2 (uranium dioxide) in the Temperature Heat-sink Overpower Response (THOR) capsule. The goal of the experiments are to compare the behaviors of standard UO 2 pellets to an aLEU concept in which molybdenum (Mo) foils separate UO 2 wafers increasing the thermal conductivity of the fuel. This experiment is designed to be conducted in the Transient Reactor Test facility (TREAT) using the Minimal Activation Retrievable Capsule Holder (MARCH) irradiation system. The goal of these experiments is to assess the effect of thermally conductive inserts in UO 2 by measuring their net effect on radial thermal conductivity using transient nuclear heating and then to determine their power-to-melt threshold in transient overpower ramps. The objective of the aLEU-THOR fuels experiment is to determine the viability and study the performance of UO 2 fuel pellets employing newly upgraded TREAT capability. A novel transient measurement technique will be used with the THOR capsule, which has a solid heat sink to generate the transient temperature gradient for conductivity measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Contactless Production Testing of Silicon Solar Cells

Critical cost reductions in silicon solar cells are made by minimizing silver usage in their metal contacts. The reason why is both clear and unavoidable—silver is not only expensive, but also a potential limiting resource for scale-up (the PV industry alone used 10.3 % of the global silver supply in 2020 [1]). The result is solar cells with vanishing electrical contact area that are extremely difficult to test prior to module manufacture, when they must be sorted for quality to maximize power output and reliability of the subsequent modules. This project developed a new measurement instrument that enables the transition to solar cells with very low silver content, including cell designs with both minimal busbars and no busbars at all to electrically contact. The resulting instrument at project completion demonstrated the ability to sort cells with comparable—or better—results than existing technology. Compared to existing cell-test instruments, the new tool has minimal contacting requirements, which lowers the maintenance costs and use of consumable parts. We demonstrated innovative, yet pragmatic, solutions for reporting a comprehensive set of measurement results useful for both cell sorting (going forward in the line for module manufacture) and process control (looking backward in the line to identify cell manufacturing issues from wafer to cell-test). In addition to the traditional current-voltage characterization at cell test—short circuit current, open-circuit voltage, power, efficiency and fill factor—the new tool maintains all the advanced parameter characterization of our existing product line such as a substrate doping measurement, carrier recombination (lifetime) analysis, and surface recombination analysis.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling and Design of Micro Flux Monitors for Neutron Fluence Measurements

Measuring neutron flux is critical to understanding the characteristics of nuclear reactors and can provide information on the energy spectrum, total neutron fluence, and operational history of a facility. Such measurements are typically performed by irradiating high-purity materials in an operating reactor for a known length of time. By measuring and identifying activation products in the irradiated materials and referencing the energy-dependent cross section of each isotope, the neutron energy spectrum and total fluence can be determined. Historical techniques use a variety of small, individually pressed foils or wires for dosimeter devices, which can result in excessively high levels of radioactivity and complications in handling after irradiation. The present work describes a new neutron dosimetry concept, named the micro flux monitor, that uses semiconductor device fabrication processes to deposit thin films of flux monitoring materials in precise geometries onto a SiC wafer. This approach allows multiple dosimetry materials to be located on a single device, simplifying irradiation and subsequent analysis. The geometry, and therefore mass, of each material can be custom-tailored for a specific application—considering the expected neutron flux, duration of irradiation, and device retrieval time of a facility. Additionally, hundreds of identical dosimetry monitors can be produced simultaneously, reducing fabrication costs. Finally, the extremely thin metal dimensions of these devices could improve the fidelity of neutron fluence measurements by reducing neutron self-shielding and gamma self-attenuation effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

2D Amorphous Carbon Dielectric Prepared from Solution Precursor for Nanoelectronics

The preparation of amorphous 2D nanodielectrics represents a major challenge due to the metastable nature of amorphous phases. We describe a scalable and solution-based strategy to prepare wafer-scale 2D amorphous carbon with thickness down to 1–2 atomic layers from coal-derived carbon quantum dots as precursors. The prepared atomically thin 2D amorphous carbon can be suspended over cavities as freestanding membranes with high modulus of 400±100 GPa and demonstrate robust dielectric properties with dielectric strength above 20 MV·cm-1 and leakage current density below 10-4 A·cm-2 through a scaled thickness of three-atomic layers. When implemented as ultrathin gate dielectrics in 2D transistors or ion-transport media in memristors, they enable exceptional device performance and spatiotemporal uniformity, resulting from their amorphous form, intrinsic ultrathinness, and 2D atomic structures.

Pham, Viet Hung↗
DOE OSTI2024

Microfabricated Ion Traps on Sapphire for Larger Trap Areas and Higher Qubit Count

Surface ion traps are a promising platform for quantum computing due to their potential to store large numbers of ions that can be addressed by electrical and optical control signals in order to implement quantum algorithms. Increasing the power of the quantum computer requires increasing the number of ions, but this poses a significant challenge in that it leads to a non-linear increase in on-chip power dissipation. The primary contributor to this power scaling in current devices is the capacitance between the radio frequency (RF) electrode and the metal plane that shields the silicon substrate from the RF signals applied to it. Silicon has traditionally been chosen for the substrate material for compatibility with the processing required for multi-metal-level traps. In this work, we address these capacitance and fabrication challenges by replacing the commonly used silicon substrate with an insulating sapphire substrate to fabricate a multi-metal-level ion trap, while still employing common semiconductor manufacturing techniques. This change in substrate allows the design to remove the metal shielding from the device design, reducing the capacitance of the RF electrode. The electrical characteristics of these traps were measured, specifically trap impedance, capacitance, and voltage breakdown, and compared to nearly identical silicon trap devices. Finally, we used laser cutting techniques to shape a sapphire wafer into bowtie shapes matching silicon traps previously fabricated at Sandia National Labs to explore solutions for integrating sapphire substrates into non-rectangular ion trap designs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Solution-Based Synthesis of Ultrathin Quasi-2D Amorphous Carbon for Nanoelectronics

The synthesis of ultrathin 2D amorphous dielectric film represents a major challenge due to the metastable nature of amorphous phases. We describe a scalable and solution-based strategy to prepare wafer-scale 2D amorphous carbon with thickness down to 1–2 atomic layers from coal-derived carbon quantum dots as precursors. The prepared atomically thin 2D amorphous carbon can be suspended over cavities as freestanding membranes with high modulus of 400±100 GPa and demonstrate robust dielectric properties with dielectric strength above 20 MV·cm-1 and leakage current density below 10-4 A·cm-2 through a scaled thickness of three-atomic layers. When implemented as ultrathin gate dielectrics in 2D transistors or ion-transport media in memristors, they enable exceptional device performance and spatiotemporal uniformity, resulting from their amorphous form, intrinsic ultrathinness, and 2D atomic structures.

Pham, Viet Hung [NETL Site Support Contractor, Nat↗
DOE OSTI2024

Machine Learning of Plasma Science for Next Generation Microelectronics (Project Final Report)

Low temperature plasmas (LTPs) are an enabling technology behind reducing device dimensions and the continuation of Moore’s Law. It is estimated that 40-45% of all process steps necessary to manufacture semiconductor devices involve LTPs. However, challenges in plasma process design and continuous incorporation of novel materials for new device architectures are pushing the limits of what is possible with current plasma technology. For example, creating higher aspect ratio structures and etching features at the atomic scale both require finer control of the ion energy/velocity at wafer surfaces. To support these types of future innovations in the plasma processing systems that Sandia and the DOE rely upon, we have developed novel diagnostics, simulations, and machine learning capabilities to discover, characterize, and predict plasma phenomena affecting the ion energy/velocity distribution function (IEDF). These efforts also supported research program development and external collaboration with industry and academia through Sandia’s Plasma Research Facility (PRF). This report will focus on the following topics and accomplishments of this three year LDRD project, briefly summarized.

42 ENGINEERING↗
DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Radiation Hardened Engineered Substrates for Time and Space Resolution

Low Gain Avalanche Diodes (LGADs) have become sensors of choice for fast timing of minimum ionizing particles. The current generation of these devices suffer from only moderate radiation hardness, low fill factor, and limited design options. Cactus Materials Inc. proposes to develop sensors with gain layer implants buried beneath the surface which will, with AC coupling developed by Brookhaven National Laboratory (BNL) and University of California Santa Cruz (UC Santa Cruz) solve these problems. Fermilab has a major role in the CMS timing upgrade using the current generation of LGADs and development of AC-coupled, buried layer LGADs will solve some of the central problems inherent in this technology. Annex B included a two-year work plan, deliverables, schedule and funding for the project’s SBIR Phase II award to develop and test prototype LGADs utilizing wafer bonding technology and epitaxial growth, that will allow for fabrication of radiation hard AC coupled devices with 100% fill factor and adjustable operating point.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

20 kV Gallium Nitride pn Diode Electro-Magnetic Pulse Arrestor for Grid Reliability (Final Scientific/Technical Report)

This project developed vertical Gallium Nitride (GaN) pn diodes under two main thrusts: (1) A focus on relatively higher-voltage devices for use as fast EMP arrestors to protect the electric grid; and (2) A focus on a Foundry effort to establish the manufacturability of relatively lower voltage devices. For the first thrust, the aim was to develop devices that go into avalanche breakdown to clamp the voltage across sensitive grid equipment subject to voltage transients induced by electromagnetic pulses (EMPs). Devices with breakdown voltages exceeding 6.5 kV were achieved, and breakdown times shorter than 1 ns were demonstrated, which is sufficiently fast to protect against the fast component of an EMP-induced signal. Key challenges included the epitaxial growth of thick (50 µm or more), low-doped (low 10 15 cm -3 range) GaN layers comprising the drift regions of the diodes, as well as the design and fabrication of edge termination structures (step-etched junction termination extensions) to prevent premature breakdown. Midway through the project, an additional emphasis was put on large-area, high-current devices, and forward currents of approximately 400 A were achieved in composite devices towards the end of the project. Experimental and theoretical studies of impact ionization and avalanche ruggedness were also conducted. For the second thrust (the Foundry), the focus was primarily on 1.2-kV-class devices, although towards the end of the project outstanding results on 3.3-kV class devices were also achieved. The aim of the Foundry was to develop a high-yield, reliable, and economic vertical GaN pn diode process. The Foundry conducted characterization of incoming epitaxial material and correlated this information with the yield and performance of fully processed devices. Wafer maps of diode characteristics such as forward and reverse current as well as capacitance-voltage curves were measured using auto-probing. Several mask sets comprising different-area devices as well as multiple edge termination designs (implanted junction termination extensions, guard rings, and combinations thereof) were studied, and machine-learning-based approaches were utilized to analyze the data. Packaging and reliability efforts were also undertaken for the Foundry diodes, which are necessary for a viable commercial process.

20KV↗
DOE OSTI2023

20 kV Gallium Nitride pn Diode Electro-Magnetic Pulse Arrestor for Grid Reliability (Final Report)

This project developed vertical Gallium Nitride (GaN) pn diodes under two main thrusts: (1) A focus on relatively higher-voltage devices for use as fast EMP arrestors to protect the electric grid; and (2) A focus on a Foundry effort to establish the manufacturability of relatively lower-voltage devices. For the first thrust, the aim was to develop devices that go into avalanche breakdown to clamp the voltage across sensitive grid equipment subject to voltage transients induced by electromagnetic pulses (EMPs). Devices with breakdown voltages exceeding 6.5 kV were achieved, and breakdown times shorter than 1 ns were demonstrated, which is sufficiently fast to protect against the fast component of an EMP-induced signal. Key challenges included the epitaxial growth of thick (50 um or more), low-doped (low 10 15 cm -3 range) GaN layers comprising the drift regions of the diodes, as well as the design and fabrication of edge termination structures (step-etched junction termination extensions) to prevent premature breakdown. Midway through the project, an additional emphasis was put on large-area, high-current devices, and forward currents of approximately 400 A were achieved in composite devices towards the end of the project. Experimental and theoretical studies of impact ionization and avalanche ruggedness were also conducted. For the second thrust (the Foundry), the focus was primarily on 1.2-kV-class devices, although towards the end of the project outstanding results on 3.3-kV-class devices were also achieved. The aim of the Foundry was to develop a high-yield, reliable, and economic vertical GaN pn diode process. The Foundry conducted characterization of incoming epitaxial material and correlated this information with the yield and performance of fully processed devices. Wafer maps of diode characteristics such as forward and reverse current as well as capacitance-voltage curves were measured using auto-probing. Several mask sets comprising different-area devices as well as multiple edge termination designs (implanted junction termination extensions, guard rings, and combinations thereof) were studied, and machine-learning-based approaches were utilized to analyze the data. Packaging and reliability efforts were also undertaken for the Foundry diodes, which are necessary for a viable commercial process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Keeping LAMMPS cutting edge

Since its inception 30 years ago, LAMMPS has grown to be a world-class molecular dynamics code and a cornerstone of computational materials science research. This project aimed to keep LAMMPS at the forefront of molecular dynamics simulations by adapting LAMMPS to the latest developments in machine learning technology and hardware. Initially, the project set out to provide a unified implementation of active learning for efficient training data generation in LAMMPS, but the research trajectory pivoted to address more immediate and impactful opportunities. On the hardware side, recent record-breaking molecular dynamics simulations were developed on the Cerebras wafer-scale AI chip, and this project has developed an interface between LAMMPS and the hardware-specific molecular dynamics code to accelerate and simplify development and user adoption. On the software side, PyTorch’s Ahead-of-Time (AOT) compilation features promised increased performance for state-of-the-art equivariant neural network potentials, and this project laid the groundwork for their adoption in LAMMPS, resulting in a nearly 20x acceleration in extreme cases. Combined with a comprehensive benchmark study of LAMMPS across all current exascale systems, this project has reinforced LAMMPS’s role as a versatile, high-performance tool for current and future materials science applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Aligned carbon nanotubes for 1,000x improvement in computing (CRADA Final Report)

As part of the Cyclotron Road program, the Aligned Carbon team worked to improve and bring to market their technology to manufacture carbon nanotubes (CNTs) for integrated circuits. There are multiple applications which can benefit from the use of CNT based transistors in integrated circuits, including high performance computing, RF data transmission, and biosensing. Each of these applications faces a problem of poor starting CNT material to come to market. Aligned Carbon offers material with the highest ceiling of performance based around a fully aligned, uniform, on-wafer growth of CNTs and our proprietary purification process to remove metallic CNTs leaving only the semi-conducting ones behind. Further, Aligned Carbon has been guided by scalable manufacturing processes that will fit seamlessly into the integrated circuit foundry model of chip fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Coupled CVD and Float Zone Reactor for Lower Cost, Higher Efficiency Si Boules (Final Technical Report)

This project modeled a new type of photovoltaic (PV) Si production reactor with the promise to reduce the cost, increase the efficiency, and reduce the energy required to manufacture Si wafers. The production of photovoltaic (PV) grade Si is well established, based on the pulling of single crystalline Si boules from polycrystalline Si created from trichlorosilane using the Siemens process. However, these processes are very energy intensive, and manufacturing of PV Si occurs almost entirely in China. To disrupt this paradigm and on-shore production of this critical material and provide benefits to the public, a substantial technological leap is required to move past incumbent technology. This study evaluated a new float zone chemical vapor deposition (Fz-CVD) concept in which trichlorosilane (TCS), the feedstock for polysilicon in the Siemens process, is injected directly into a float zone crystallizer to continuously deposit the feed rod for the boule pulling process through a combination of multiphysics modeling and technoeconomic analysis.

14 SOLAR ENERGY↗