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At least 271 records · Page 15

The InSAR Scientific Computing Environment

We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

geodetic imaging↗

Firmware Development Improves System Efficiency

Most manufacturing processes require physical pointwise positioning of the components or tools from one location to another. Typical mechanical systems utilize either stop-and-go or fixed feed-rate procession to accomplish the task. The first approach achieves positional accuracy but prolongs overall time and increases wear on the mechanical system. The second approach sustains the throughput but compromises positional accuracy. A computer firmware approach has been developed to optimize this point wise mechanism by utilizing programmable interrupt controls to synchronize engineering processes 'on the fly'. This principle has been implemented in an eddy current imaging system to demonstrate the improvement. Software programs were developed that enable a mechanical controller card to transmit interrupts to a system controller as a trigger signal to initiate an eddy current data acquisition routine. The advantages are: (1) optimized manufacturing processes, (2) increased throughput of the system, (3) improved positional accuracy, and (4) reduced wear and tear on the mechanical system.

Chern, E. James↗

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗

Development of a case tool to support decision based software development

A summary of the accomplishments of the research over the past year are presented. Achievements include: made demonstrations with DHC, a prototype supporting decision based software development (DBSD) methodology, for Paramax personnel at ODU; met with Paramax personnel to discuss DBSD issues, the process of integrating DBSD and Refinery and the porting process model; completed and submitted a paper describing DBSD paradigm to IFIP '92; completed and presented a paper describing the approach for software reuse at the Software Reuse Workshop in April 1993; continued to extend DHC with a project agenda, facility necessary for a better project management; completed a primary draft of the re-engineering process model for porting; created a logging form to trace all the activities involved in the process of solving the reengineering problem, and developed a primary chart with the problems involved by the reengineering process.

Wild, Christian J.↗

The application of CFD to rotary wing flow problems

Rotorcraft aerodynamics is especially rich in unsolved problems, and for this reason the need for independent computational and experimental studies is great. Three-dimensional unsteady, nonlinear potential methods are becoming fast enough to enable their use in parametric design studies. At present, combined CAMRAD/FPR analyses for a complete trimmed rotor soltution can be performed in about an hour on a CRAY Y-MP (or ten minutes, with multiple processors). These computational speeds indicate that in the near future many of the large CFD problems will no longer require a supercomputer. The ability to convect circulation is routine for integral methods, but only recently was it discovered how to do the same with differential methods. It is clear that the differential CFD rotor analyses are poised to enter the engineering workplace. Integral methods already constitute a mainstay. Ultimately, it is the users who will integrate CFD into the entire engineering process and provide a new measure of confidence in design and analysis. It should be recognized that the above classes of analyses do not include several major limiting phenomena which will continue to require empirical treatment because of computational time constraints and limited physical understanding. Such empirical treatment should be included, however, into the developing CFD, engineering level analyses. It is likely that properly constructed flow models containing corrections from physical testing will be able to fill in unavoidable gaps in the experimental data base, both for basic studies and for specific configuration testing. For these kinds of applications, computational cost is not an issue. Finally, it should be recognized that although rotorcraft are probably the most complex of aircraft, the rotorcraft engineering community is very small compared to the fixed-wing community. Likewise, rotorcraft CFD resources can never achieve fixed-wing proportions and must be used wisely. Therefore the fixed-wing work must be gleaned for many of the basic methods.

Caradonna, F. X.↗

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗

Organizational Influences on Interdisciplinary Interactions during Research and Design of Large-Scale Complex Engineered Systems

The design of large-scale complex engineered systems (LaCES) such as an aircraft is inherently interdisciplinary. Multiple engineering disciplines, drawing from a team of hundreds to thousands of engineers and scientists, are woven together throughout the research, development, and systems engineering processes to realize one system. Though research and development (R&D) is typically focused in single disciplines, the interdependencies involved in LaCES require interdisciplinary R&D efforts. This study investigates the interdisciplinary interactions that take place during the R&D and early conceptual design phases in the design of LaCES. Our theoretical framework is informed by both engineering practices and social science research on complex organizations. This paper provides preliminary perspective on some of the organizational influences on interdisciplinary interactions based on organization theory (specifically sensemaking), data from a survey of LaCES experts, and the authors experience in the research and design. The analysis reveals couplings between the engineered system and the organization that creates it. Survey respondents noted the importance of interdisciplinary interactions and their significant benefit to the engineered system, such as innovation and problem mitigation. Substantial obstacles to interdisciplinarity are uncovered beyond engineering that include communication and organizational challenges. Addressing these challenges may ultimately foster greater efficiencies in the design and development of LaCES and improved system performance by assisting with the collective integration of interdependent knowledge bases early in the R&D effort. This research suggests that organizational and human dynamics heavily influence and even constrain the engineering effort for large-scale complex systems.

McGowan, Anna-Maria R.↗

An evaluation of software tools for the design and development of cockpit displays

The use of all-glass cockpits at the NASA Langley Research Center (LaRC) simulation facility has changed the means of design, development, and maintenance of instrument displays. The human-machine interface has evolved from a physical hardware device to a software-generated electronic display system. This has subsequently caused an increased workload at the facility. As computer processing power increases and the glass cockpit becomes predominant in facilities, software tools used in the design and development of cockpit displays are becoming both feasible and necessary for a more productive simulation environment. This paper defines LaRC requirements of a display software development tool and compares two available applications against these requirements. As a part of the software engineering process, these tools reduce development time, provide a common platform for display development, and produce exceptional real-time results.

Ellis, Thomas D., Jr.↗

The Design-To-Cost Manifold

Design-to-cost is a popular technique for controlling costs. Although qualitative techniques exist for implementing design to cost, quantitative methods are sparse. In the launch vehicle and spacecraft engineering process, the question whether to minimize mass is usually an issue. The lack of quantification in this issue leads to arguments on both sides. This paper presents a mathematical technique which both quantifies the design-to-cost process and the mass/complexity issue. Parametric cost analysis generates and applies mathematical formulas called cost estimating relationships. In their most common forms, they are continuous and differentiable. This property permits the application of the mathematics of differentiable manifolds. Although the terminology sounds formidable, the application of the techniques requires only a knowledge of linear algebra and ordinary differential equations, common subjects in undergraduate scientific and engineering curricula. When the cost c is expressed as a differentiable function of n system metrics, setting the cost c to be a constant generates an n-1 dimensional subspace of the space of system metrics such that any set of metric values in that space satisfies the constant design-to-cost criterion. This space is a differentiable manifold upon which all mathematical properties of a differentiable manifold may be applied. One important property is that an easily implemented system of ordinary differential equations exists which permits optimization of any function of the system metrics, mass for example, over the design-to-cost manifold. A dual set of equations defines the directions of maximum and minimum cost change. A simplified approximation of the PRICE H(TM) production-production cost is used to generate this set of differential equations over [mass, complexity] space. The equations are solved in closed form to obtain the one dimensional design-to-cost trade and design-for-cost spaces. Preliminary results indicate that cost is relatively insensitive to changes in mass and that the reduction of complexity, both in the manufacturing process and of the spacecraft, is dominant in reducing cost.

Dean, Edwin B.↗

Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model

Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.

Artifical Intelligence↗

The next generation

The next generation of computer systems are studied by examining the processes and methodologies. The present generation is ok for small projects, but not so good for large projects. They are not good for addressing the iterative nature of requirements, resolution, and implementation. They do not address complexity issues of requirements stabilization. They do not explicitly address reuse opportunities, and they do not help with people shortages. Therefore, there is a need to define and automate improved software engineering processes. Some help may be gained by reuse and prototyping, which are two sides of the same coin. Reuse library parts are used to generate good approximations to desired solutions, i.e., prototypes. And rapid prototype composition implies use of preexistent parts, i.e., reusable parts.

Yudkin, Howard↗

Design for reliability: NASA reliability preferred practices for design and test

This tutorial summarizes reliability experience from both NASA and industry and reflects engineering practices that support current and future civil space programs. These practices were collected from various NASA field centers and were reviewed by a committee of senior technical representatives from the participating centers (members are listed at the end). The material for this tutorial was taken from the publication issued by the NASA Reliability and Maintainability Steering Committee (NASA Reliability Preferred Practices for Design and Test. NASA TM-4322, 1991). Reliability must be an integral part of the systems engineering process. Although both disciplines must be weighed equally with other technical and programmatic demands, the application of sound reliability principles will be the key to the effectiveness and affordability of America's space program. Our space programs have shown that reliability efforts must focus on the design characteristics that affect the frequency of failure. Herein, we emphasize that these identified design characteristics must be controlled by applying conservative engineering principles.

Lalli, Vincent R.↗

Coal desulfurization by low-temperature chlorinolysis

Among the three principal methods for precombustion desulfurization of coal, which include physical depyriting, chemical desulfurization, and coal conversion to low-sulfur liquid and gaseous fuels, the potential of chemical methods looks promising in terms of both total sulfur removal and processing cost. The principal chemical methods for coal desulfurization involve treatment with either oxidizing agents or basic media at elevated temperature and pressure. A description is given of some recent experimental results which show the feasibility of removing sulfur, particularly organic sulfur, from high-sulfur coals by a simple method of low-temperature chlorinolysis followed by hydrolysis and dechlorination. The chemical feasibility of sulfur removal by chlorinolysis rather than the detailed engineering process is emphasized.

Hsu, G. C.↗

Cyber-Informed Engineering: Standards Development Organization Quick Start Guide

Cyber-Informed Engineering (CIE) is an emerging methodology focused on identifying and reducing high-consequence events that may affect physical critical infrastructure systems as a result of their dependence on digital technology. CIE, developed by National Laboratories and promoted by the Department of Energy (DOE), incorporates consequence-focused planning into the design and engineering process from the earliest stages of a project. This guide provides a concise overview of CIE and offers practical insight into how Standards Development Organizations (SDOs) can interpret CIE principles and apply those concepts in updates to various standards. It is important to remember that CIE extends beyond a compliance checklist, emphasizing a broader, interpretive approach. Instead, it encourages an interpretive mindset - a "turning of 'what if' to 'even if'" approach that anticipates and engineers out high-consequence events. The authors encourage SDOs to establish and promote CIE principles as enhancements for more resilient-by-design outcomes across critical infrastructure energy sectors. The 12 core principles of CIE outline specific behaviors and actions that SDOs and engineers may adopt to enhance system resilience. This guide applies these principles in a manner intended to be relevant across various technologies and threat landscapes. We welcome institutions and vendors to identify new or different framework alignments and mappings as we collectively work towards a safer and more reliable digital landscape.

97 MATHEMATICS AND COMPUTING↗

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J↗

Advanced Processing of Coal and Coal Waste to Produce Graphite for Fast-Charging Lithium-Ion Battery Anode

The University of North Dakota (UND) Energy & Environmental Research Center (EERC), in collaboration with the UND Center for Process Engineering Research (CPER), conducted a project to validate two technologies capable of converting North Dakota lignite and lignite coal waste to high-quality graphite for fast-charging lithium-ion battery (LIB) anode. The project was conducted over about 3 years from April 7, 2022, to July 6, 2025. The two technological paths pursued in this project include path A – direct conversion of coal or coal waste to graphite by the upgraded carbon ores to products (UCOP) process being developed at the EERC and path B – lignite-derived coal tar pitch (CTP) conversion to graphite (CTP2G) process being developed at CPER. The results from this project validate the two technological approaches and are expected to be an integral part of a portfolio of emerging technologies for making high-quality graphite not only from North Dakota lignite, but from all ranks of U.S. domestic coal and coal waste resources. The quality of the graphite produced by these technologies is high enough for various applications, including batteries for the fast-growing electric vehicle industry, energy storage applications, electric arc furnace electrodes for steel production, and graphene production, among others. Although the two technologies can produce high-quality graphite, they are fundamentally different in that the UCOP technology provides a direct path to transform coal to graphite, while the CTP2G technology needs to go through a CTP intermediate and a coking process for the intermediate, which requires a special facility to accomplish. For application in the industry, the UCOP process is designed to be more flexible, with feedstock to include potentially any carbonaceous material such as all coal ranks and biochar, while the CTP2G process is designed to utilize CTP as the starting precursor. The key project accomplishments include the following: • Successful preparation of high-quality synthetic graphite from North Dakota lignite coal/coal wastes and lignite-derived CTP. • Patent application has been filed for the UCOP process and an internal invention disclosure has been filed for the CTP2G process. • The produced graphite performs better than a commercial battery-grade sample in LIB coin cells, especially fast-charging capability, stability, and long-duration cycling. • Coin-type Li-ion half-cells with CTP2G graphite showed excellent performance, with >370 mAh/g capacity, >90% initial coulombic efficiency, and 93%/67% retention at 1C/2C rate, which outperforms commercial graphite in charging speed, stability, and cycling. • Results of fabricated 18650 cells were consistent with the observations in coin cells. • Preliminary techno-economic analysis (TEA) estimates for the UCOP technology indicate a manufacturing cost of about $\$$39/kg based on 50-metric ton/year capacity. • Preliminary TEA estimates for the CTP2G technology indicate a market price of about $\$$7107/ton ($\$$7/kg) based on 22,000-ton/year production capacity.

01 COAL, LIGNITE, AND PEAT↗