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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Advanced Ultra-Supercritical Component Test (ComTest) Project for 760*C Steam Conditions

ComTest is a $27M Department of Energy-funded project. Phase I, which began in November 2015, served to identify the technology gaps, as well as the scope and cost of required testing. Phase II, which was awarded in December 2018, includes an advanced manufacturing effort to complete U.S. based supply chain development for full commercial scale (800-850 MWe) AUSC components made of nickel-based alloys, components operating at up to 760°C. Completion of Phase II scheduled for September 30, 2021. Strategic Objectives of U.S. AUSC Project include: Power Plant Efficiency Improvements –Develop cost-effective, reliable technologies to improve the efficiency of new and existing high-temperature advanced generation power plants. Close gaps to achieve readiness for commercial scale demonstration of Advanced Ultra-Supercritical (AUSC) technology. Fabricate full-scale versions of key nickel-based alloy components. Validate capabilities of US supply chain for cost certainty. Support cross-cutting high-temperature generation technologies. Obtain ASME Code approval for new materials, components and processes. Increase power plant steam temperatures for higher cycle efficiency (Note: Average efficiency of US coal-fired fleet = 33% HHV; A-USC plant efficiency over 47% HHV at 1,400°F (760°C) steam temperature).

fireside corrosion↗
DOE OSTI2020

Scalable Electrolytic Systems for Renewable Hydrogen Production (Cooperative Research and Development Final Report, CRADA Number CRD-18-747)

The project focuses on offshore wind energy which is an emergent renewable energy source in the United States. Onsite hydrogen production for this sector is not available. The overall goal of GTA's work is development of scalable multi-megawatt water electrolysis systems that exclude platinum group metals, are constructed from readily available commodity materials and are mass produced using advanced manufacturing and robotics. They fabricated and successfully tested a scalable TRL 4 laboratory prototype that demonstrated promising results for achieving the goal. They further performed calculations and prepared scale drawings for an envisioned onsite TRL 8 electrolytic hydrogen production system at an offshore 8 MW wind turbine. The work plan of the CRADA proposal between NREL and GTA focuses on validation of the current TRL 4 prototype with potential development and refinement for advancement to a TRL 5 system. GTA, Inc. proposes joining the H2@Scale consortium to leverage DOE funds, benefit from and contribute to the common knowledge-base and work with NREL as a CRADA partner.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Full Scale Engine Demonstration of Additively Manufactured High Gamma Prime Turbine Blade

Additive manufacturing (AM), also known as 3D printing, is a rapidly developing technology with tremendous potential in both developmental and production applications. Solar Turbines Incorporated is committed to AM technology development for gas turbine applications. The ability to metal 3D print novel designs of turbine blades capable of actual turbine engine operation would effectively reduce design validation cycle time and allow acquisition of key performance data early in a design campaign. In support of Solar’s advanced manufacturing development and ongoing engine efficiency improvement goals, ORNL and Solar conducted a project to 3D print, machine, inspect, and engine test a full set of Mercury TM 50 stage 2 turbine blades. This full-scale, hot-fired engine demonstration has identified both the capabilities and limitations of the current technologies required to produce turbine hot-section AM components.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Numerical Analysis of Novel Plate Type Heat Exchanger with Oval-Twisted Channels

The novel heat exchanger (HX) designs implementing geometrical and surface modification combinations are expected to perform better than traditional HX technologies. Applied enhancement techniques seek to achieve (1) higher overall heat transfer performance, (2) increased compactness, and (3) simplified or comparable manufacturability. One innovative enhancement technique is to generate swirling flow vortices induced by channel or tube twisting. The turbulence generated by the twisted cross-section greatly enhances the heat transfer rate with minimal increases in pressure drop. Plate-type HXs and Printed Circuit Heat Exchangers (PCHXs) are compact designs that achieve high heat transfer rates per unit volume by utilizing several small channels, which maximizes the heat transfer surface area between the hot and cold fluids. Currently, advanced manufacturing technologies enable the design and fabrication of compact-type units with complicated channel geometries to achieve the highest performance and meet the compactness criteria of innovative HX technology. The proposed HX design concept combines the compactness of plate-type HXs and twisted channels, which provide additional turbulence and flow swirl enhancement. The plate-type oval-twisted HX (PTOTHX) is a crossflow configuration, with 16 short channels on one side (for hot fluid) and 8 long channels on the perpendicular side (for cold fluid). The inlet plenums have flow guide vanes to redirect flow and produce uniformity across the various flow paths. The compact size and purportedly improved heat transfer performance of the PTOTHX investigated herein prove its viability in various applications. Some notable potential nuclear applications of the PTOTHX include reactor core, spent fuel cooling, and residual heat dissipation. To establish a reference case, circular channels (PTCHX) are also considered in the present study for comparison with (PTOTHX). This paper aims to outline the numerical analysis procedures for determining the viability of the PTOTHX by comparing its heat transfer performance with the PTCHX units. The computational study used STAR-CCM+, a commercial computational fluid dynamics (CFD) code. Sensitivity analysis and model selection studies are conducted to determine the appropriate mesh density and turbulence model to provide the reported results. Numerical analyses comparing the Nusselt number (Nu) of the PTOTHX design with a comparable HX unit, including a circular cross-section and no twisting (PTCHX), show an overall heat transfer performance increase of 29-55% for balanced flow and 29-59% for imbalanced flow. Oval-cross-sectional twisted channels induce swirling flow vortices, enhancing the working fluid's convective heat transfer capabilities.

25 ENERGY STORAGE↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2021

Sustainability of the U.S. Manufacturing Sector: Use of the United Nations Sustainable Development Goals

The United Nations' 17 Sustainable Development Goals (SDGs) aim to improve health and education, reduce inequality, and encourage economic growth, while also preserving or improving the conditions of our oceans and forests. Pursuing these SDGs would mean $12 trillion in economic opportunities for companies, while also improving the lives of all people and bettering the planet. Some manufacturing companies are already focusing on sustainability, but not all. In 2019, almost 30% of National Association of Manufacturers members did not have a sustainable policy, goals, or program in place. Business drivers for sustainability and the SDGs are similar, with focuses on economic growth and consumer demands. Despite the shortcomings of the SDGs, they represent an opportunity for manufacturing companies to further improve energy, material efficiency, and productivity. This report evaluates the SDGs and the manufacturing sector. The manufacturing sector was analyzed using the technology assessments (TAs) introduced in the 2015 Quadrennial Technology Review (QTR) review, which focused on concepts, challenges, and solutions to meet the United States' energy needs. Annual or sustainability reporting of companies performing work in one of those TAs were analyzed for mentions of the SDGs. The call-out boxes throughout this report provide examples of companies making progress toward the SDGs. The possible overlap between the SDGs and the Advanced Manufacturing Office (AMO) was also evaluated. The TAs in the 2015 QTR Review were furthered with detailed targets in the draft Multi-Year Program Plan (MYPP) for Fiscal Years 2017-2021. Direct and likely relationships between the SDGs and the TAs were established. Positives, challenges, SDG-related literature, and future steps are also discussed in this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 1, Characterization of Residual Strain Distribution in Additively-Manufactured Metal Parts Using Energy-Dispersive Diffraction

A machine component fabricated by additive manufacturing (AM) of metal powders often possesses steep residual stress gradients with significant magnitudes due to large temperature gradients that transpire within a localized area during fabrication. These processing-induced residual stresses can cause distortion of the part, and if they are of significant magnitude, they could induce cracking of the component, degrade printability, and/or diminish subsequent mechanical performance. The ability to predict these residual stresses imparted by AM is an important step in permeating AM technology for advanced manufacturing. Calibration and validation of AM process models used for prediction are, therefore, a critical step in understanding the origin and mitigating the challenges associated with residual stresses inherent to the AM process. In the present work, the residual strain distributions in components with simple geometries fabricated by a laser powder bed fusion (LBPF) process were characterized non-destructively using energy-dispersive X-ray diffraction in support of the US Air Force Research Laboratory Additive Manufacturing Modeling Challenge Series Groeber et al. (JOM 70:441-448, 2018). The measurement setup and approach are described in detail so that the data can be used as a benchmark to calibrate and validate models for the prediction of macro-scale residual stresses due to the LPBF process.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Printed Strain Gauges for Anthropomorphic Test Dummies for Vehicle Crash Testing

In Phase 1 of the technical collaboration between Oak Ridge National Laboratory (ORNL) and Humanetics, additive manufacturing was studied as a method to produce high strain – strain gauges that are embedded in an additively manufactured (AM) anthropomorphic crash test dummy (ATD) to provide high fidelity data to significantly improve vehicle safety. In this study commercially available conductive filament was acquired and the mechanical properties were tested for use in this application. The design space of embedded printed strain gauges was explored with multiple configurations printed and tested for performance. The testing resulted in finding that commercially available filament materials were unable to meet the performance requirements. Finally, an extensive literature survey was performed on advanced manufacturing techniques and novel high strain conductive materials to manufacture strain gauges that can be embedded in to the AM ATD. Humanetics have taken the literature survey and have reached out to material suppliers such as Techmer to provide custom blends of materials for testing. Humanetics will continue to build off of the research that was performed and test custom materials for use in AM ATDs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Accessing Atomic-scale Phosphorus Dopant Distribution in Precise Silicon Devices by Advanced STEM Imaging and Spectroscopy

The structural and chemical characterization at the atomic-scale plays a critical role in understanding the structure-property relationship in precise electrical devices such as those produced by atomic-precision advanced manufacturing (APAM). APAM, utilizing hydrogen lithography in a scanning tunneling microscope, offers a potential pathway to ultra-efficient transistors, and has been developed to produce phosphorus (P)-based donor devices integrated into bare Si substrates. Structural characterization of the buried, Si with P dopant (Si:P) delta-layer in the devices by scanning transmission electron microscopy (STEM), however, is a challenge due to similar atomic number and low concentration of the P dopants. In this paper, we describe several efforts of utilizing advanced STEM imagining and spectroscopic techniques to quantify the Si:P deltalayers. STEM imaging combining low-angle and high-angle annular dark-field (LAADF, HAADF) detectors as well as atomic-scale elemental mapping using energy-dispersive X-ray spectroscopy (EDS) are used to reveal the P and defect distribution across the delta-layer processed under various thermal conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Closed-loop additive manufacturing of upcycled commodity plastic through dynamic cross-linking

A sustainable closed-loop manufacturing would become reality if commodity plastics can be upcycled into higher-performance materials with facile processability. Such circularity will be realized when the upcycled plastics can be (re)processed into custom-designed structures through energy/resource-efficient additive manufacturing methods, especially by approachable and scalable fused filament fabrication (FFF). Here, we introduce a circular model epitomized by upcycling a prominent thermoplastic, acrylonitrile butadiene styrene (ABS) into a recyclable, robust adaptive dynamic covalent network (ABS-vitrimer) (re)printable via FFF. The full FFF processing of ABS-vitrimer overcomes the major challenge of (re)printing cross-linked materials and produces stronger, tougher, solvent-resistant three-dimensional objects directly reprintable and separable from unsorted plastic waste. This study thus offers an imminently adoptable approach for advanced manufacturing toward the circular plastics economy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nature of innovations affecting photovoltaic system costs

Innovations improve technology costs through various kinds of engineering advancements, including changes to materials choices and device or process designs. Understanding how these innovations relate to cost change can reveal aspects of the process of technology evolution, yet developing such understanding is often not possible with a strictly quantitative approach due to data limitations. In this paper we develop a hybrid quantitative-qualitative framework for relating specific innovations to cost change by using the variables in a quantitative technology cost change model as an organizing principle. We demonstrate this framework by applying it to the cost decline in photovoltaic (PV) systems over the last five decades. This framework generates new understanding of a set of innovations that contributed to PV modules’ sustained cost decline and the more modest trends observed in balance-of-system (BOS) costs. The results show the great diversity of innovations that affected PV costs, drawing on wide-ranging fields of expertise within scientific research and practice. We find that there are differences in the characteristics of innovations that reduced the cost of PV modules compared to innovations influencing BOS costs. Numerous module innovations reduced costs by advancing manufacturing tools and processes that improved material quality. Many BOS innovations reduced costs through a combination of component design changes, integration, automation, digitalization, and standardization. Overall, most innovations in our sample affected PV hardware. However, some also target ‘soft technologies’ such as task durations through innovations like fast-track permitting, which require improved collaboration and process streamlining. This framework also provides insight into the nature of knowledge spillovers between technologies. Both module and BOS hardware innovations show the benefits of PV’s position within an ‘ecosystem’ of continuously advancing technologies in many industries, in particular semiconductors and electronics, and also point to the importance of public institutions for accelerating testing, permitting, and training.

14 SOLAR ENERGY↗
DOE OSTI2026

LDRD FY25 Program Overview

As Lawrence Livermore National Laboratory’s (LLNL’s) Laboratory Directed Research and Development (LDRD) program enters its fifth decade of leading-edge research and development, its impact and importance have never been stronger. The program continues to advance strategic investments in pioneering science, technology, and engineering, ensuring LLNL will be ready to deliver on our mission as it evolves over the coming decades. Investing in LDRD research, and the people who perform this critical work, gives LLNL the ability to sustain our role as a leader in the Department of Energy and National Nuclear Security Administration enterprise. The LDRD program enables high-risk, high-payoff research that anticipates emerging threats and future mission needs. By nurturing the ingenuity of the Lab’s greatest asset, its people, LDRD funding advances not only our research but also grows and nurtures our workforce: engaging future innovators with student mentoring, challenging postdoctoral researchers to apply their skills to support national security, and strengthening the leadership skills of early career staff. This annual report documents how LDRD investments advance LLNL’s science, technology, and engineering across our mission space. To assess LDRD’s impact we track both short and long-term metrics such as peer-reviewed publications, number of students, or professional fellows. In addition to reviewing these metrics, I encourage you to delve deeper into the breadth of science and technology that illustrate the strategic value of this research portfolio. For instance, a recent exploratory research project used advanced manufacturing to construct miniaturized three-dimensional ion traps for a quantum computer with reduced quantum error rates to enable applications that address national security missions and support basic science. Another project has delved into studying detonation by examining deflagration to enhance the safety and security of the nuclear weapons stockpile. LDRD researchers are also deploying AI agents on two of the world’s most powerful supercomputers to automate and accelerate inertial confinement fusion experiments. Other teams are delivering more accurate optical constants to enable improved validation for aluminum to advance atomic and molecular physics models. LDRD-driven discoveries of how metals deform under extreme conditions strengthen our ability to model and design materials for demanding national security environments. National security challenges are increasingly complex and continuously evolving. LDRD focuses our most innovative science and technology on these challenges, ensuring the Laboratory is developing creative, forward-leaning solutions for our nation and the world. The following pages feature highlights of published scientific advances, patents, and honors that stem from LDRD investments. As you read this report, I hope you will understand how these investments position the Laboratory, and our partners, to meet the demands of the decades ahead.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prioritizing Nuclear Materials for SAM-3 Neutron Irradiation Campaign: Structural and Cladding Materials Candidates

This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

New Materials and an Efficient Processing Approach for Materials for Harsh Environments – Continuous Electric Field Assisted Sintering

Electric-field assisted sintering (EFAS) is an advanced manufacturing method for the consolidation and processing of ceramic and metal materials. It is a particularly excellent candidate for efficient materials processing as it has greater than 90% energy cost savings and improved CO2 emissions compared to traditional sintering in a furnace. This is due to direct rapid heating of the materials and molds leveraging an electrification phenomenon called Joule heating where electrical current is passed through the sample/mold assemblies causing direct heating. The technique does have limitations though as it is traditionally a batch-process and suffers from scale up difficulties. To overcome this, researchers at Idaho National Laboratory changed the form factor of traditional EFAS instruments to develop and construct a continuous rolling electric-field assisted sintering (CEFAS) device. Its unique design creates highly localized electrical, thermal, and mechanical process parameters for continuous samples of limitless length. Advanced core shell powder materials were also created using fluidized powder bed atomic layer deposition of core/shell solid oxide electrochemical electrode/electrolyte BaCe0.7Zr0.1Y0.1Yb0.1O3 (BCZYYb) and yttrium doped BaZrO3 (BZY) to be a feedstock for the new CEFAS instrument. The innovative core/shell powder is hypothesized to have high protonic conductivity with enhanced environmental resistance. The completed project covers innovations in process control and design enabled by control theory, finite element modeling and mechanical design, three dimensionally printed carbon-carbon composite manufacturing and utilization, and green materials processing techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Innovations Driven by Advanced Characterization to Strategize Critical Mineral Production and Beneficial Reuse from Fossil Energy Waste

Critical minerals (CM), such as rare earth elements (REE), cobalt, nickel, and lithium, have important uses in modern electronics and advanced manufacturing, yet are vulnerable to potential supply chain disruptions. Relatively abundant and readily available fossil energy (FE) wastes, such as coal combustion ash, acid mine drainage (AMD) and treatment solids (AMD solids), and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters) are under consideration as CM feedstocks. The National Energy Technology Laboratory (NETL) has studied CM resources for various FE wastes as part of the U.S. Department of Energy’s mission of bolstering the domestic CM supply, and makes the data available to the public on EDX at sites such as the NEWTS group. Advanced characterization utilizing synchrotron x-ray techniques coupled with laboratory extractions has been performed to identify CM hosting phases in these FE wastes to inform CM recoverability mechanisms. Novel methods to selectively recover CMs while co-producing other valuable byproducts have been developed. Successful examples discussed here include: (1) The identification of REE/Co/Ni/Sc binding and hosting phases in select FE waste (coal combustion ash and AMD solids), resulting in the development of a patented CM step-extraction process, (2) coupled production of functional sorbents from these extraction wastes and for CM recovery. A pilot-scale testing to evaluate the patent’s technical feasibility for extracting REE from coal ash on a barrel scale has been successfully performed. Additionally, (3) evaluation and measurements of brine geochemistry from U.S. O&G produced waters has informed a high Li recovery potential from Marcellus Shale produced water. NETL researchers have been developing tailored pre-treatment processes, an innovative and highly durable lithium sorbent, and geochemical model guided precipitation to accelerate Li production from the Marcellus Shale produced waters. These innovations driven by characterization are integral for maximizing and advancing the potential for CM recovery while offsetting the cost and environmental footprint for FE waste management.

critical mineral processing↗
DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗
DOE OSTI2020

Study of Additive Manufacturing Application to Geothermal Technologies

Geothermal reservoir characterization, field construction, and reservoir operations are very technology intensive activities that contribute significantly to the cost of delivering electricity produced from geothermal resources. Many geothermal technologies, such as downhole tools and drilling equipment, have unusual material, design, and manufacturing considerations dictated by the harsh geothermal environment and extreme aspect ratios required for deployment in a borehole. An additional challenge that faces geothermal applications is the low tool production volume needed to support the industry. Whereas tens of thousands of Oil & Gas wells are drilled and completed in the U.S. annually, there are typically only tens of geothermal wells that are drilled and completed. If a tool typically used in Oil & Gas applications cannot be directly used for geothermal, then the cost associated with making the tool suitable for geothermal is often prohibitive. There is therefore a much smaller inventory of technologies available to geothermal as compared to Oil & Gas and the level of efficiency and sophistication associated with field practice suffers accordingly. A number of advanced manufacturing methods, such as additive manufacturing, have received increased R&D as well as commercial attention in recent years because of their ability to rapidly prototype complex parts. Additive manufacturing in particular provides an opportunity to increase the technology available to the geothermal industry by either reducing fabrication costs associated with complex components or enabling economic production of low volume parts where specialized tooling is often required. Additional potential benefits of additive manufacturing include increased design freedom to make higher performing parts that cannot be made conventionally, the ability to integrate components into assemblies without joining operations, and the ability to economically fabricate variations on design in cases, such as casting molds, where there are large up-front costs associated with tooling. We have recently completed a study that investigated technology needs, representative use cases, manufacturability, and a techno-economic framework for comparing conventional to additive manufacturing methods for geothermal applications. This paper will provide an overview of this recent effort, describe the different elements of the assessment, and summarize the key takeaways related to both the feasibility of using additive manufacturing for geothermal technology applications as well as the potential benefits and impacts.

Polsky, Yarom↗
DOE OSTI2020

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗