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DOE OSTI2024

Science challenges and research opportunities for plasma applications in microelectronics

Low-temperature plasmas (LTPs) are essential to manufacturing devices in the semiconductor industry, from creating extreme ultraviolet photons used in the most advanced lithography to thin film etching, deposition, and surface modifications. It is estimated that 40%–45% of all process steps needed to manufacture semiconductor devices use LTPs in one form or another. LTPs have been an enabling technology in the multidecade progression of the shrinking of device dimensions, often referred to as Moore’s law. New challenges in circuit and device design, novel materials, and increasing demands to achieve environmentally benign processing technologies require advances in plasma technology beyond the current state-of-the-art. The Department of Energy Office of Science Fusion Energy Sciences held a workshop titled Plasma Science for Microelectronics Nanofabrication in August 2022 to discuss the plasma science challenges and technical barriers that need to be overcome to continue to develop the innovative plasma technologies required to support and advance the semiconductor industry. One of the key outcomes of the workshop was identifying a set of priority research opportunities (PROs) to focus attention on the most strategic plasma science challenges to address to benefit the semiconductor industry. For each PRO, scientific challenges and recommended strategies to address those challenges were identified. Furthermore, this article summarizes the PROs identified by the workshop participants.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Multi-Process Tooling

Decisions made early in the automotive design process influence material selection, which in turn dictates process selection and tool design. Because of tool build time and cost of tooling, the original path is not easily altered, even if there is compelling evidence that another material or process would be beneficial. This project focused on tool design that is agile enough to allow its use in multiple processes—injection, injection compression, and extrusion-compression. This tool design allows for the manufacture of components with the most efficient process or materials, without building multiple, single-process tools. The primary purpose of the Multi-Process Tool project was to physically demonstrate that a single, well-designed tool could be used to manufacture parts with a variety of materials that require different processes. A multi-process tool would be beneficial to providing data for any changes to the process since materials and processes can be interchanged without incurring additional tool cost(s). Battery tray parts, (representative of a multi-process tool, were successfully manufactured using various types of materials, such as fiber reinforced (carbon fiber and/or glass fibers, recycled carbon fibers), amorphous (PP, TPU), semi-crystalline (PA6, PA66), and crystalline (thermoset epoxy resin) polymers. Processing of the parts was achieved by injection molding, compression molding, compression overmolding, and injection overmolding. Specimens extracted from various locations on the battery tray parts were evaluated for mechanical properties (flexure and interlaminar shear strength properties). The results show that the tool can be used to produce parts from a wide range of materials and processes with no degradation of the physical or cosmetic properties.

42 ENGINEERING↗

DOE OSTI2023

Automated phase segmentation and quantification of high-resolution TEM image for alloy design

In the alloy design and development process, a wealth of atomically resolved structural high-resolution transmission electron microscopy (HRTEM) images are produced. Identifying the different nano-precipitate phases and tracking their evolution under various compositions and during manufacturing or post-processing requires hundreds of HRTEM images and thousands of precipitates. The nanoscopic phase information labeling and analysis purely relies on humans are prohibitively costly and time-consuming, sometimes not reliable because of the lack of authoritative knowledge. Here, in this work, we develop a novel unsupervised machine learning approach coupled with adaptive computer vision techniques with features in the Fourier space to automatically determine the number of phases and segment/quantify the phases with nanoscale resolution, allowing for quantitative correlation between nanostructure formation, processing and functional properties. To automate the phase extraction/quantification and ascertain its applicability, we have applied the developed framework to the HRTEM images from several alloy systems, processing conditions, image magnifications, and phase types and morphologies (precipitates, nano-twins, stacking faults, crystalline matrix, and amorphous structures) for verification. This study paves the road for compression, visualization, and translation of raw image structural data into physically relevant information in real-time with minimal human supervision. It shows the promise of enabling high-throughput materials characterization for the acceleration of alloy manufacturing and design.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗

DOE OSTI2022

The current state of the industrial energy assessment and its impacts on the manufacturing industry

Energy-intensive manufacturing is the greatest contributor to the U.S. industrial energy consumption today. Globally, manufacturing facilities are being directed to reduce their energy consumption to prepare for a sustainable future. Industrial energy assessment plays a crucial role in helping facilities meet their energy efficiency goals by encouraging the implementation of cost-effective, energy-saving recommendations to the existing equipment and processes. Across the world, programs such as the U.S. Department of Energy (DOE) sponsored Industrial Assessment Centers (IACs) (operational across several states in the U.S. for over four decades), are transforming the future of industrial energy consumption by offering free industrial energy assessments to qualifying facilities. In this review paper, the industrial energy assessment approach and practices are comprehensively reviewed with focus on popular recommendations, procedures, and the current practices of the industrial energy assessment program. Specifically, opportunities for improvement in the most energy-intensive manufacturing processes are examined, concentrating on the energy savings and other non-energy benefits of each of these measures, such as cost savings and emissions reduction. Furthermore, this paper also reviews how these energy-saving opportunities are procedurally evaluated and how factors, such as level and cost of assessments, and assessment metrics, are currently defining industrial energy assessment. In final considerations, existing research on energy management, decarbonization through electrification, and renewable energy in industry is reviewed and discussed, and how these advancements will shape the future of industrial energy assessment is addressed through forward-looking lenses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Multi-physics melt pool modeling and process optimization for laser direct energy deposition of Nb-based refractory C103: Defect formation, geometric precision, and process mapping

Recent developments in additive manufacturing (AM) technology have reignited interest in the fabrication of the Nb-based refractory C103 alloy offering solutions to the challenges posed by traditional manufacturing methods. However, the limited numerical and experimental studies on laser direct energy deposition (DED) of C103 have hindered the understanding of the relationships between process parameters and build quality. This has made it challenging to consistently produce parts with the desired quality and microstructure suitable for critical applications. In this study, we focus on optimizing the laser DED process for C103 by employing a hybrid approach that combines experimental techniques and computational fluid dynamics (CFD). This approach facilitates the development of process maps for defect detection and geometric precision. To achieve this, multi-layer C103 samples were fabricated using laser DED under various process parameters, enabling the creation of a process map for defect detection. Additionally, a multi-physics, multiphase simulation framework was developed within a high-performance computing (HPC) environment to establish process maps for geometric precision. Using these process maps, printability windows were identified for achieving both the desired geometric accuracy and defect-free prints. It was observed that prints with a power-to-velocity (P/V) ratio close to unity resulted in defect-free outcomes. This study provides a foundation for reducing design lead time and rejected parts, ultimately optimizing the laser DED process for C103.

Defect formation and geometric precision↗

DOE OSTI2021

Rapid Open-Air Processing of Low-Cost Perovskite Solar Modules

We report an industrially relevant approach to both scalable and fast open-air perovskite photovoltaic (PV) module production. This work resolves some of the most formidable barriers to module-level scaling that the perovskite community has been facing. Key advances include scalable large-area spray deposition, new monolithic integration scribing techniques, advanced photoluminescence characterization, and reproducible high-throughput manufacturability. Our rapid spray processing techniques enabled the highest perovskite PV efficiency produced in open-air. Innovations in scribing techniques enabled the first single-source laser process to achieve perovskite module monolithic integration and technoeconomic analysis led to a comprehensive cost model for perovskite module manufacturing. We report significant progress in reducing perovskite manufacturing costs necessary to potentially compete with incumbent Si-based PV for utility-scale power generation.

cost modeling↗

DOE OSTI2021

Prediction of Aluminum to Steel RSW Joint Failure (CRADA 405)

General Motors, LLC has developed a resistance spot welding process to join aluminum sheet to steel for body-in-white manufacturing. Efforts to develop the process for any one joint configuration (combination of alloy and thicknesses) is intensive. To aid in process understanding and eventual reduction in process development efforts, an initiative was created to develop an finite element model of the various destructive test configurations (lap shear, cross-tension, and coach peel) to help predict the failure mode and load displacement curves under tensile testing. This report describes the finite element modeling approach, the means by which local material properties were determined, as well as model validation and refinement efforts.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

Laser powder bed fusion (L-PBF) has emerged as one of the mainstream additive manufacturing approaches for fabricating metal parts with complex geometries and intricate internal structures. However, large deformation associated with rapid heating and cooling can lead to build failure and requires post-processing which may increase manufacturing cost and prolong the production period. Here in this work, an island scanning pattern design method is proposed to optimize the scanning direction of each island in order to reduce part deformation after cutting off the build platform. The objective of this optimization is to minimize the upward bending of the part after sectioning, which allows the part deformation to satisfy the tolerance requirement or reduce the post heat treatment time. Inherent strain method is employed in the sequential finite element analysis consisting of layer-by-layer activations and sectioning for fast residual distortion prediction. Full sequential sensitivity analysis for the formulated optimization is provided to update the island scanning directions. To show the feasibility and effectiveness of the proposed method, the scanning patterns of a block structure and a connecting rod were designed and parts were fabricated using an open architecture L-PBF machine. The fabrication experiments demonstrated that the residual deformation of both parts fabricated by optimized scanning pattern can be reduced by over 50% compared to the initial scanning patterns, which demonstrate the effectiveness of the proposed method.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Techno-economic analysis of cathode material production using flame-assisted spray pyrolysis

The cost of cathode materials contributes approximately 32.7% of the total cell construction cost of lithium-ion batteries, significantly affecting the price of battery packs. To reduce the cathode material manufacturing cost, a flame-assisted spray pyrolysis (FSP) method has been developed to utilize a sustainable solvent of glycerol to manufacture the LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC333) cathode materials. The purpose of this study is to evaluate the minimum cathode material selling price (MCSP) of the FSP processes compared with a traditional carbonate co-precipitation pathway. Results show that the MCSP of the FSP is $\$$19.1/kg that is 17% lower than the traditional carbonate co-precipitation pathway as a result of lower fixed operating cost and variable overhead. Sensitivity analysis shows that when the new process is integrated with in-situ sintering and processing, the MCSP can be as low as $\$$15.6/kg. When all the material prices are decreased by 20%, the FSP process can synthesize NMC333 at a price of $\$$2.3/kg lower. According to the simulation result, LiNi 0·8 Mn 0·1 Co 0·1 O 2 (NMC811) has the best potential to meet the U.S. Department of Energy battery price target of $\$$125/kWh, demonstrating that the FSP process is an attractive manufacturing technology for NMC cathode powder material production.

25 ENERGY STORAGE↗

DOE OSTI2021

Interfacial characteristics of P91 steel - Inconel 740H bimetallic structure fabricated using wire-arc additive manufacturing

Although bimetallic structures can offer unique solutions to engineering problems with varying functionality, joining two dissimilar alloys using additive manufacturing involves challenges such as cracking and segregation. In this work, bimetallic structures of Inconel 740H superalloy and P91 steel are processed using wire-arc additive manufacturing (WAAM) for the first time. P91 steel is directly deposited over 740H with a cooling time of 20 minutes in between the two depositions. During microstructure characterization, a large gradient zone with coarse grains spanning for ~2200 μm is observed. Moreover, the microhardness of the gradient zone is the least in comparison with the P91 and 740H deposits. No deleterious phase formation is found; however, intergranular cracks are observed along the gradient zone. In order to deduce the reason for cracking, non-equilibrium solidification simulations are performed for the mixed compositions of P91 and 740H in the gradient zone. Here, the reasons for crack formation in the gradient zone are the sudden change in the volumetric coefficient of thermal expansion due to the formation of MC carbides as well as the development of local strains from the thermal residual stresses. Therefore, altering the deposition sequence and introducing gradient layers with mixed composition between the P91 and 740H deposits will be beneficial in achieving defect-free builds. Through the integration of experiments and simulation, this work gains valuable insights into the processability of dissimilar alloy manufacturing using the WAAM technique.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Assessment of Microstructure Prediction Capabilities for Powder Bed Fusion Stainless Steel 316

The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the characteristic process-structure-property relationships of additive manufacturing (AM) materials pose challenges for the qualification and certification of AM nuclear components. In particular, component-scale variations in microstructure and properties can be driven by localized changes in melt pool dynamics due to how process parameters interact with different part geometries. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents final results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing identified challenges and future opportunities for connecting the developed simulation workflow with mechanics simulations for prediction of part performance.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Recent and future developments in pultrusion technology with consideration for curved geometries: A review

Herein this paper examined the current state and future developments in pultrusion with particular emphasis on its application in curved part manufacturing. The relationship between factors such as resin chemistry, fiber characteristics, and die geometry that influences the properties of pultruded product were highlighted. Moreover, the specific challenges associated with pultruding curved parts such as the complexities in achieving uniformity and structural integrity in such geometries were discussed. The review emphasized mold design, process improvement, adaptive control systems for precise resin impregnation and material selection to address these challenges. Additionally, the paper suggests the integration of real-time monitoring and data analytics as ways to enhance quality control during curved parts pultrusion. These advancements will help to overcome challenges specific to curved pultrusion and make the process more efficient. Other manufacturing techniques such as filament winding, thermoforming, pulforming were mentioned as alternatives to curved parts pultrusion. The review also explores pultruded variable curvature processes, highlighting some notable patents and article related to this subject matter. Production of pultruded variable curvature parts was seen as a key driver that can shape the future of pultrusion. Finally, the paper anticipates future trends, with sustainability, customization, integration of advanced materials, and development of techniques for pultrusion of composites parts.

42 ENGINEERING↗

DOE OSTI2020

Innovative Approaches to the Decommissioning of a Redundant Plutonium Processing Facility - 20147

At Sellafield, in the North West of the United Kingdom (UK), there are a number of redundant plutonium processing facilities. Over the past three decades several decommissioning strategies have been deployed to clean up these redundant facilities. Whilst there have been many successes previously reported, there remain many challenges. As previously presented at WM2017 (Paper Ref 17081) some of these challenges have recently been addressed through a new approach which introduced a number of innovations. The purpose of these innovations is to seek ways to significantly reduce risks to both decommissioning personnel and the environment by minimising the extent of physical 'hands on' decommissioning activities and by simplifying the waste production process. This paper provides an update on the progress of these innovations since 2017. Additionally, the paper also provides details of the new decommissioning technologies which have been introduced over the past 2 years to enable the most challenging aspects of the redundant plutonium processing facility to be decommissioned. These new decommissioning technologies address challenges associated with the preparation of process vessels and pipework to enable their safe in-situ size reduction by remote means: - New decommissioning techniques have been introduced to allow penetrations to be remotely cut into process vessels and pipework to provide a means of accessing and controlling the venting of any potential hydrogen gas present. - Additionally, a new large scale bespoke remote diamond wire cutting machine has been designed and manufactured to enable the process vessels to be size reduced in situ. Both of these new cutting technologies have involved collaborative working with specialist equipment suppliers including extensive development, trialling demonstration and commissioning prior to bringing the equipment into operational service. Several years of work have now culminated in reaching the final stages of decommissioning of the redundant plutonium processing facility with decommissioning of the final process vessels now underway and completion expected by the end of 2019. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

ExaCA: A performance portable exascale cellular automata application for alloy solidification modeling

Modeling the as-solidified grain structures that form during alloy processing is a critical component in understanding process-property relationships, particularly for additive manufacturing (AM) where grain structure is very sensitive to processing conditions. While cellular automata (CA)-based models have proven able to predict aspects of microstructure for several alloys and AM process conditions, long run times and large resource sets required limit the utility and the problem size to which existing CA models can be applied. As part of the ExaAM project, an initiative within the Exascale Computing Project (ECP) to develop, test, and optimize an exascale-capable coupled and self-consistent model of AM parts, we developed ExaCA (https://github.com/LLNL/ExaCA) for the liquid–solid phase transformation in the wake of AM melt pools. The CA-based code is parallelized using MPI and the Kokkos programming model, the latter enabling simulation on both CPUs and GPUs within a single-source implementation. Here, we detail the steps taken to transform a baseline, MPI-based CA code into one that is performant on CPUs and GPUs. Performance testing of ExaCA on Summit (a pre-exascale machine at Oak Ridge National Laboratory) was used to quantify CPU–GPU speedup comparing with equal numbers of nodes. Testing showed comparable CPU performance to the MPI-only CA code and a 5-20x speedup when running AM-based test problems using GPUs. The improved performance of CA through GPU utilization and the performance portable nature of ExaCA will enable accurate part-scale modeling by harnessing the power of current and future generations of high performance computing resources. Future work will include improving the strong scaling of ExaCA on GPUs by reducing load imbalance associated with the locality of the problem, and continuing performance optimization across exascale hardware.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Prospective Life Cycle Assessment of Synthetic Graphite Manufactured via Electrochemical Graphitization

Lithium-ion batteries (LIBs) are expected to play a crucial role in meeting many of the clean energy-related goals. Due to its electrical properties such as good conductance, chemical inertness, and corrosion resistance, graphite is a very popular anode for LIBs. Traditional methods of producing battery-grade graphite (high purity >99%) include processing naturally mined graphite or manufacturing synthetic graphite via the Acheson process, which converts soft amorphous carbons such as petroleum coke into graphite by subjecting it to high temperature (up to 3000 °C) for prolonged periods of times (3–5 days). However, due to a lack of abundant high purity natural graphite sources, synthetic graphite is the preferred choice for many LIBs. A new synthetic electrochemical graphitization method that subjects the amorphous carbon precursor submerged in a molten salt mixture to a constant cathodic polarization (against a graphitic anode) has been discovered that has significantly lower graphitization temperatures (~800 °C) and reduced graphitization time (3–6 h). Furthermore, the method can accept a higher variety of carbon precursors compared to the Acheson process. A prospective life cycle assessment (LCA) is conducted on this new method and compared against the traditional processes. The laboratory-scale demonstration of the method is used to build an inventory, which through various assumptions is scaled up to a commercial scale. An additional scenario is also considered with a biomass-derived carbon precursor for the graphite. The results from the LCA show that while the laboratory scale process is similar to the Acheson process and natural flake graphite in terms of impact, the scaled-up process is drastically better than the Acheson process in all environmental categories. Using a coconut shell-derived biomass precursor has a higher impact due to its manufacturing in Indonesia, as the Indonesian energy grid is highly fossil fuel dependent. Therefore, the biomass carbon may have a higher impact than petroleum coke dependent on the location of production of biomass-derived carbon black. The LCA has identified the molten salt—CaCl 2 —as a potential hotspot and suggests other salts should be considered. Accordingly, the new method shows promise in this early stage LCA in improving the environmental performance of graphite (and by relation LIBs) and therefore needs to be explored more in terms of its commercial viability.

25 ENERGY STORAGE↗

DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Using post-processing heat treatments to elucidate precipitate strengthening of additively manufactured superalloy 718

The poor machinability and extensive work hardening of Ni-based superalloys makes additive manufacturing an attractive option for producing geometrically complex components with distinct microstructures. Although previous studies show recovery of high strength at room temperature, very few studies demonstrate successful properties at elevated temperatures required for industrial applications. Here, the objectives of this study are to present a post-build heat treatment for high strength across a wide temperature range, determine the strength contribution of nanoscale precipitating phases to the overall mechanical properties of superalloy 718, and from these, provide a comprehensive microstructure-property relationship for wrought and AM 718 to guide efforts to simulate the properties of AM components. Laser powder bed fusion–produced superalloy 718 was characterized at multiple length scales using scanning electron microscopy and transmission electron microscopy in the as-built condition and with multiple heat treatments designed to form combinations of γ', γ", and δ precipitates. Uniaxial tensile tests performed from room temperature to 600 °C on subsize specimens determined the yield strength, elastic modulus, ultimate tensile strength, fracture stress, and uniform elongation. Precipitates in this work proved to be weak barriers to dislocation motion through a dispersed barrier model, but they provided strength to the alloy through their consistent high density. The relative contribution to the yield strength from γ" remained consistent between 48% and 57% of the total strength up to 600 °C, the primary influence on the high temperature strength of superalloy 718. The strength factors for γ" and δ precipitates were found to trend inversely with tensile test temperature and may be attributable to the differences in precipitate coherency. A post-build heat treatment is recommended to maintain high strength at elevated temperatures. A quantitative microstructure-property relationship, dependent on precipitate size, density, and morphology, was derived and can estimate the yield strength across a wide temperature range applicable to the operational regimes for superalloy 718.

36 MATERIALS SCIENCE↗