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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In-situ hydrogen microstructural characterization of Si heterojunction passivation: Addressing V OC degradation and mitigation pathways

Si heterojunction (SHJ) solar cells have demonstrated record efficiency >27%, approaching the theoretical limit of ≈ 29%, primarily due to best surface/interface defect passivation provided by deposited thin layers of hydrogenated amorphous silicon (a-Si:H). Such excellent surface/interface passivation reduces recombination loss and result in >100 mV improvement of cell open circuit voltage (V OC ) to ≈ 750 mV, thus the cell efficiency. However, fielded SHJ modules exhibit loss of V OC and hence efficiency over time in years, presumably due to degradation related to a-Si:H layers. This adversely affects the technology’s market acceptance, and levelized cost of energy (LCOE). It is hypothesized that the origin of a-Si:H degradation is somehow related to the presence of weak Si–Si bonds and hydrogen in a-Si:H films. The objective of this project is to test this hypothesis by directly measuring chemical and structural changes occurring within SHJ component layers and solar cells. This is achieved by developing an innovative in-situ Fourier transform infrared (FTIR) spectrometry apparatus to monitor hydrogen microstructural changes occurring within amorphous silicon and decipher hydrogen evolution kinetics over time when samples are exposed to heat and/or light stress. These in-situ measured hydrogen microstructural changes are correlated to the changes in effective minority carrier lifetime (τ eff ), implied V OC (iV OC ), surface recombination velocity (S), and cell V OC . These mechanistic understandings will provide critical guidance to mitigate the V OC -driven degradation of SHJ solar cell performance. Passivation optimization and degradation analysis of individual SHJ component structures were achieved through systematic deposition of three symmetric structures and the completed SHJ solar cell structure. The three symmetric structures used were intrinsic a-Si:H [(i)a-Si:H] layers in a bilayer structure, intrinsic and p-type doped stacked layers [(i-p)a-Si:H] representing the front heterojunction in the SHJ cell, and intrinsic and n-typed doped stacked layers [(i-n)a-Si:H] representing the back-side back surface field (BSF) in the SHJ cell. State-of-the-art passivation qualities are demonstrated by a champion iV OC of 740 mV for the (i)a-Si:H layers, and the (i-n)a-Si:H symmetric structure. A 725 mV iV OC is observed for the (i-p)a-Si:H symmetric structure. These symmetric passivated SHJ component structures were subsequently subjected to different accelerated lifetime (ALT) stressors to identify which conditions contribute the most to iV OC degradation. Degradation of the thin (10 nm) (i)a-Si:H passivation layers without any additional overlying layers is minimal; complexity of this study arises due to unavoidable surface oxidation of (i)a-Si:H layer during most of the stress application, which is likely irrelevant for a full SHJ cell configuration with overlying protective layers. The iV OC degradation of symmetric structures is found to occur primarily at the (i-p)a-Si:H passivation stack under dark heat stress with associated hydrogen loss from the (p)a-Si:H layer. An activation energy for increase in S (defect creation) of 0.65 eV can be correlated to the activation energy of ≈ 0.4 eV for hydrogen loss from the (i-p)a-Si:H stack. This also suggests the presence of weakly bonded hydrogen in the (p)a-Si:H films, which effuses out of the film stack at such low activation energy. When light and heat stress are applied together, similar hydrogen loss from (i-p)a-Si:H stack is observed, however, does not appreciably degrade iV OC or increase S. This is an important result and departure from direct correlation between hydrogen loss and defect creation. This perhaps indicates additional defect chemistries or annealing that might be occurring in the presence of light requiring further detailed defect measurements. The full SHJ cell structure used for this project is depicted in Fig.1(d). SHJ cells with an initial V OC ≈ 700 mV were fabricated and subjected to similar ALT stress conditions. Cell V OC is found to degrade the most under dark heat stress and is confirmed by observed hydrogen migration out of the (i-p)a-Si:H stack. However, hydrogen cannot escape from the cell stack, it accumulates near the (p)a-Si:H/ITO contact interface, where ITO acts as a barrier preventing hydrogen loss. Furthermore, light-heat combined stress does not degrade V OC appreciably, confirming the occurrence of a defect annealing process.

14 SOLAR ENERGY↗
DOE OSTI2021

Feature Extraction: Improving Remote Sensor Classification of Non-Proliferation

This research focuses on developing algorithms for nuclear non-proliferation detection using remote sensor modeling. To improve the performance of classification models, we implemented a data pipeline with feature extraction. This pipeline takes raw data and transforms it into smaller data points called features that still describe the model. Improving this classification works towards the departments of energy’s missions of ensuring American’s security and prosperity by creating technology that addresses nuclear challenges. To conduct this analysis, we used the Python programming language and some key packages, including tsfresh and TSFEL. Originally tsfresh was selected because it has the most statistical features out of all the packages. Later TSFEL was incorporated due to the additional features it can extract from data, such as temporal and spectral. However, feature extraction becomes challenging in the presence of missing values. In this case, two additional Python packages were added to our workflow, NumPy and pandas, allowing for the feature extraction process to handle unknown values. Our data pipeline was tested on data collected from a simulation that describes the process state of a physical example. The results show the pipeline’s capability to consume and extract a total 17 features from tabular data. Future work includes producing classifications using decision tree-based models such as XGBoost and improving data collection by analyzing feature importance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
NASA NTRS1992

Characterization of radiation-induced damage in high performance polymers by electron paramagnetic resonance imaging spectroscopy

The potential for long-term human activity beyond the Earth's protective magnetosphere is limited in part by the lack of detailed information on the effectiveness and performance of existing structural materials to shield the crew and spacecraft from highly penetrating space radiations. The two radiations of greatest concern are high energy protons emitted during solar flares and galactic cosmic rays which are energetic ions ranging from protons to highly oxidized iron. Although the interactions of such high-energy radiations with matter are not completely understood at this time, the effects of the incident radiation are clearly expected to include the formation of paramagnetic spin centers via ionization and bond-scission reactions in the molecular matrices of structural materials. Since this type of radiation damage is readily characterized by Electron Paramagnetic Resonance (EPR) spectroscopy, the NASA Langley Research Center EPR system was repaired and brought on-line during the 1991 ASEE term. A major goal of the 1992 ASEE term was to adapt the existing core of the LaRC EPR system to meet the requirements for EPR Imaging--a powerful new technique which provides detailed information on the internal structure of materials by mapping the spatial distribution of unpaired spin density in bulk media. Major impetus for this adaptation arises from the fact that information derived from EPRI complements other methods such as scanning electron microscopy which primarily characterize surface phenomena. The modification of the EPR system has been initiated by the construction of specially designed, counterwound Helmholtz coils which will be mounted on the main EPR electromagnet. The specifications of the coils have been set to achieve a static linear magnetic field gradient of 10 gauss/mm/amp along the principal (Z) axis of the Zeeman field. Construction is also in progress of a paramagnetic standard in which the spin distribution is known in all three dimensions. This sample will be used to assess the linearity of the magnetic field gradient and to ensure authentic image reconstruction. A second major task was to secure the computer capability to enable image reconstruction from projection data generated by the magnetic field gradients. To this end, commercially available and public domain software packages which perform inverse Fourier Transform and convoluted (filtered) back projection functions are being integrated into the existing EPR data processing system.

Suleman, Naushadalli K.↗
DOE OSTI2020

Demonstration of Embedded Sensors in Ceramic Structures

The Transformational Challenge Reactor (TCR) program seeks to demonstrate an advanced 3D printed nuclear reactor core. A binder jet additive manufacturing process is used to fabricate the complex SiC ceramic components of the TCR core. After printing, the components are densified via chemical vapor infiltration (CVI). This process allows complex cavities to be created in which sensors can be placed at strategic locations. Inserting the sensors during the CVI process allows the sensors to be embedded within the component as it is infiltrated. The primary challenge for embedding the sensors is identifying the sensors and sensor sheath materials that can survive the temperatures (>1,000°C) and chemical exposure to H 2 and HCl during CVI. The embedded sensors that are being investigated for use during TCR operation include thermocouples, self-powered neutron detectors, and spatially distributed fiber-optic temperature sensors. This report describes the CVI materials compatibility tests and initial trials for embedding functional sensors. Mo is identified as the most suitable sensor sheath material based on its availability in small diameter tubing, relatively low neutron absorption cross section, and compatibility with H 2 , HCl, and the surrounding SiC matrix at the process temperatures. Amorphous SiO2 fiber-optic samples with Au and Cu metal coatings were successfully embedded in SiC along with bare fibers, although the metal coatings showed some evidence of localized melting during CVI. Initial experiments attempting to embed functional sensors showed that the sensors can be embedded in 3D printed SiC parts, but there are still challenges that must be overcome to ensure that the sensors and sensor sheaths do not fail during CVI. In particular, Nb-sheathed Mo-Nb thermocouples failed at temperatures far lower than expected despite thermodynamic calculations and materials compatibility tests that show the Nb sheath to be compatible with the CVI environment. One potential explanation for the large expansion of the Nb sheath could be related to hydride formation in the lower temperature region of the sheath. Future work will focus on Mo-sheathed thermocouples instead of Nb. The fiberoptic sensors tested during the instrumented experiment broke due to the lack of mechanical protection after their polymer-based coatings were vaporized. Future instrumented experiments will use metal-coated optical fibers for strain sensing to provide additional mechanical protection. However, custom coatings with higher melting points than commercially available Au and Cu might be required. Regardless, fiber-optic sensors are still candidates for spatially distributed temperature measurements since they can be inserted into an embedded metal sheath after CVI.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Artificial Intelligence for (AI) Nuclear Security: Expert Perspectives on AI Priorities for the Office of International Nuclear Security

Artificial intelligence (AI) has the potential to transform nuclear security operations, offering opportunities to enhance effectiveness while simultaneously introducing new challenges. As AI technologies rapidly evolve, agencies across the United States Government (USG) are researching, implementing, and evaluating various AI models and systems. Given the broad capabilities and applications of these technologies, it is essential for each agency to identify and articulate those areas where it can make meaningful contributions aligned with its mission and expertise. To address this need for strategic focus, in late Fiscal Year 2025 (FY2025), the Office of International Nuclear Security (INS) established an AI Task Force (AITF) to gather input from subject matter experts (SMEs) regarding the most appropriate role INS could serve in researching, evaluating, or implementing AI for nuclear security. The AITF engaged 15 experts from national laboratories with backgrounds in cyber security, physical security, transport security, insider threat mitigation, nuclear engineering, human-systems engineering, and AI/ML development. This white paper summarizes the insights gathered from these SMEs and presents a potential roadmap for INS engagement with AI technologies. The recommendations outlined here are intended to inform INS leadership as they make strategic decisions about resource allocation and program direction in this rapidly evolving technological domain.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Interim report on Landsat national archive activities

The Department of the Interior (DOI) has the responsibility to preserve and to distribute most Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) data that have been acquired by the five Landsat satellites operational since July 1972. Data that are still covered by exclusive marketing rights, which were granted by the U.S. Government to the commercial Landsat operator, cannot be distributed by the DOI. As the designated national archive for Landsat data, the U.S. Geological Survey's EROS Data Center (EDC) has initiated two new programs to protect and make available any of the 625,000 MSS scenes currently archived and the 200,000 TM scenes to be archived at EDC by 1995. A specially configured system has begun converting Landsat MSS data from obsolete high density tapes (HDT's) to more dense digital cassette tapes. After transcription, continuous satellite swaths are (1) divided into standard scenes defined by a world reference system, (2) geographically located by latitude and longitude, and (3) assessed for overall quality. Digital browse images are created by subsampling the full-resolution swaths. Conversion of the TM HDT's will begin in the fourth quarter of 1992 and will be conducted concurrently with MSS conversion. Although the TM archive is three times larger than the entire MSS archive, conversion of data from both sensor systems and consolidation of the entire Landsat archive at EDC will be completed by the end of 1994. Some MSS HDT's have deteriorated, primarily as a result of hydrolysis of the pigment binder. Based on a small sample of the 11 terabytes of post-1978 MSS data and the 41 terabytes of TM data to be converted, it appears that to date, less than 2 percent of the data have been lost. The data loss occurs within small portions of some scenes; few scenes are lost entirely. Approximately 10,000 pre-1979 MSS HDT's have deteriorated to such an extent, as a result of hydrolysis, that the data cannot be recovered without special treatment of the tapes. An independent consulting division of a major tape manufacturer has analyzed affected tapes and is confident that restorative procedures can be applied to the HDT's to permit one pass to reproduce the data on another recording media. A system to distribute minimally processed Landsat data will be procured in 1992 and will be operational by mid-1994. Any TM or MSS data in the national archive that are not restricted by exclusive marketing rights will be reproduced directly from the archive media onto user specified computer-compatible media. TM data will be produced either at a raw level (radiometrically and geometrically uncorrected) or at an intermediate level (radiometrically corrected and geometrically indexed). MSS data will be produced to an intermediate level or to a fully corrected level (radiometrically corrected and geometrically transformed to an Oblique Mercator projection). The system will be capable of providing ordered scenes within 48 hours of receipt of order.

Boyd, John E.↗
DOE OSTI2024

Wide Bandgap Generation (WBGen): Developing the Future Wide Bandgap Power Electronics Engineering Workforce

This Final Technical Report (FTR) summarizes the work conducted at the Center for Power Electronics Systems (CPES) under the Wide-Bandgap Generation (WBGen) fellowship and traineeship program established by the Advanced Manufacturing and Technologies Office (AMMTO) of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy (EERE) at Virginia Tech, which had as main objective to train the next generation of U.S. citizen power engineers with wide-bandgap (WBG) power semiconductor expertise, with the intent to aid in fulfilling the future workforce needs in this field. The latter was deemed of strategic importance given the fast-paced growth observed—and predicted—in the demand of this technical expertise, whose practitioners have become the enablers and executioners of the electrification transformation process that not just the U.S., but the whole world, is currently undergoing as it seeks for more effective and efficient ways to use energy. As such, the WBGen program set forth to achieve its educational goals, which in addition sought to broaden the range of WBG-based power electronics by conducting research and development on high-efficiency grid apparatus and high-efficiency electrical power systems, and to also enhance the power engineering curriculum by formalizing WBG-oriented design procedures replacing existent yet now obsolete design procedures developed for Silicon (Si) based power electronics. This effort led CPES to spearhead the development of a new major within The Bradley Electrical and Computer Engineering (ECE) Department at Virginia Tech, namely Electronic Power and Energy Systems (EPES), which coalesced power electronics and power systems courses to provide undergraduate students with a strong formation in the power engineering field, while creating a pipeline of graduate students that could pursue the WBG-based curriculum and conduct research at CPES. In all, in what is considered a true success, eight of the twenty WBGen fellows that graduated program were recruited from the ECE department undergraduate cohort. The traineeship emphasized as well, from its beginning, the partnership with industry and national laboratories, which took advantage of the successful industry consortium at CPES that has historically been formed by 80–90 power and energy companies working in close collaboration with the center. This gave WBGen fellows the accessibility and possibility to conduct internships at partner facilities during the summer months, focused solely on the evaluation, testing, and adoption of WBG devices, which were many times tightly related to their respective research work and plans. In addition, WBGen fellows conducted their main research work within the confines of research programs at CPES conducted with these industry partners, providing them with a unique opportunity to develop not just their technical expertise—while advancing their knowledge, but to also learn and practice a slew of skills needed for their professional growth. As such, the fellows tackled a variety of WBG-related research topics, from device reliability and capability aspects as well as packaging and integration, encompassing the use of advanced materials and new structures, current sharing challenges, and insulation systems, to advanced gate-drivers with integrated sensors and protection mechanisms and active current- and voltage-based control, to optimized layouts seeking to maximize the switching and power processing performance of these devices, to power processing solutions adopting Gallium-Nitride (GaN) and Silicon-Carbide (SiC) power semiconductors for a variety of applications; including radiation-hardened converters for space dc distribution systems, direct three-phase ac-to-ac power converters for aerospace systems, dc-ac inverters for automotive traction drives, high-frequency isolated dc-dc battery chargers also for heavy transportation systems, and medium-voltage dc-dc and dc-ac converters for distribution systems and future power grids. The WBGen program ultimately graduated a total of 20 power engineers, all experts on WBG-based power electronics, awarding 18 M.S. and 2 PhD degrees in the process. These fellows, all U.S. citizens, allowed CPES to increase the number of citizens students to 33 % at the peak of the program, as the traineeship made possible the recruitment of talent with more attractive graduate research assistantship (GRA) contracts. Unfortunately, the present U.S. citizen enrollment at CPES has declined back to historic levels—approximately 10 %, as the regular GRA rates are not competitive enough when compared with entry-level industry jobs. In all, WBGen fellows published a total of 7 peer-reviewed journal articles, 44 papers at international technical conferences, made 42 presentations at international technical conferences, and filed 4 invention disclosures and patent applications, which have since then been granted by the U.S. Patent and Trademark Office (USPTO). Their contribution to CPES, Virginia Tech, the United States, and the world, has been significant, and continues to yield results thanks to the exemplary career that the fellows have initiated at many of the partners of the program, which include Wolfspeed, Raytheon Technologies, Infineon, Lockheed Martin, Dominion Energy, Northrop Grumman, Rivian, Aerospace Corporation, Sandia National Laboratory, National Renewable Energy Laboratory, John Hopkins University, and Virginia Tech.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Designing for Advanced Aerial Mobility: Human-Autonomy Teaming and In-Time System-Wide Safety Assurance

The continued growth of aviation shall require new innovative technologies and operational concepts to meet the ever-increasing demands on air transportation. The NASA Advanced Air Mobility (AAM) project focuses on emerging aviation markets, such as Urban Air Mobility (UAM). UAM is defined as “...a safe and efficient system for air passenger and cargo transportation within an urban area. It is inclusive of small package delivery and other urban unmanned aerial system services and supports a mix of onboard/ground-piloted and increasingly autonomous operations” ([1]). The AAM project emphasizes technology development and validating system-level concepts and solutions in coordination with other NASA Aeronautics Research Mission Directorate (ARMD) projects to enable UAM metro- and micro-plex vertiport and airspace concepts of operations. The NASA AAM research portfolio includes the concepts of Remote Supervisor-in-Command (RSC) and Fleet and Airspace Manager (FAM) as possible human roles for consumer fleet providers. NASA research in RSC is focused on development of guidelines and standards for remote pilots/operators passively and actively controlling a large fleet of autonomous aircraft. For FAM, flight and ground system concepts and technologies to enable high density homogeneous operations at increased scale from vertiport(s), and coordination with other humans in the systems (e.g., UAM urban airspace manager, Air Traffic Control) are key research areas. The envisioned UAM operations are posited to require autonomous systems to enable functions ranging from fleet and resource management to vehicle control. Although automation has become increasingly sophisticated and ubiquitous in civil aviation, autonomy represents a significant evolution in automation, which has generally been limited in functional scope and capability. As autonomy takes on increasing responsibilities, humans and machines will be required to work together in new and different ways [2], rather than traditional design approaches focused on how machines (i.e., autonomy) can do the work of people. The emerging field of human-autonomy teaming (HAT) represents a comprehensive and prioritized research-driven approach to enable the success of future emerging aviation market applications through capabilities and principles that facilitate humans and machine working and thinking better together. The NASA Transformational Tools and Technologies (TTT) Autonomous System (AS) Sub-project was created to assist with the transition into higher levels of autonomy to enable new modes of air transportation, such as UAM. TTT-AS has identified HAT as a key research need to enable UAM while maintaining today’s ultra-safe aviation system safety levels. The latter challenge has been taken up by the NASA System-Wide Safety (SWS) Project, which recognizes that aviation safety, as it evolves, shall require new ways of thinking about safety to include integration of a wide-range of existing and new safety systems and practices, enhanced tools and technologies, increased access to data and data fusion, improved data analysis capabilities, enhanced in-time risk monitoring and detection, hazard prioritization and mitigation, safety assurance decision-support, and in-time integrated system analytics [3].The operational concept of UAM represents a variety of work that has been termed, “work-as-imagined” to characterize the idea that how people think that work is done and how work is actually done are often not the same [4]. To ensure design success and system safety, looking at “work-as-done” provides a comparative approach toward UAM concept and technology design through examination of corresponding analogs found today in aviation (e.g., on-demand operations) and other transportation domains (e.g., port operations). The paper shall discuss various alternative applications with specific focus on airline operation center (AOC) operations, and unmanned aerial system (UAS) command-and-control to inform scaled-versions of FAM and RSC, respectively, and with consideration of the national airspace system contextual environment. The tenets and principles of the HAT field and current NASA research efforts under the TTT-AS sub-project shall also be described. Finally, the SWS sub-project efforts to develop In-Time System-Wide Safety Assurance (ISSA) and In-Time Safety Management Systems (IASMS) are discussed in terms of how “in-time” safety assurance may be conceptualized for the on-demand mobility air taxi “work-as-imagined” operational concept [5]. As part of this effort, concepts from the emerging field of resilience engineering, are being studied. Traditional approaches to aviation safety have focused on what can go wrong and how to prevent it. Another approach to thinking about system safety should reflect not only “avoiding things that go wrong” (protective safety) but also “ensuring that things go right” (productive safety), that enables a system to exhibit the resilient performance [6] necessary for the success of the future aviation system emerging concepts of operations. The paper shall describe efforts focused on how productive safety and resilience may enable a more complete approach to system safety thinking and design of ISSA and IASMS for UAM. Future directions and research needs shall also be discussed.

resilience↗
DOE OSTI2024

Phase-field modeling of thermally-grown oxide and damage evolution in environmental barrier coatings

Silicon carbide-based ceramic matrix composites protected by environmental barrier coatings (EBCs) present a promising materials solution for next-generation gas turbines. Developing more robust and efficient EBCs is therefore of significant technological importance. During the service in high-temperature oxidative environments, there is a thermally grown oxide (TGO) layer, spontaneously formed in the EBC system. TGO is recognized as a critical factor for the degradation and failure of EBCs, yet the detailed mechanisms of TGO growth and its effect on EBC failure remain unclear. In this study we develop a comprehensive chemo-mechano-phase-field model to simulate growth of the TGO in EBCs, factoring in creep and deformation, and especially the cracking behaviors. The volume expansion due to TGO growth and the resulting large inelastic deformation are addressed by using our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm, in combination with an adapted Hu-Chen spectral solver for elasticity. Simulations of TGO growth are performed considering different growth modes of TGOs determined mainly by the ratio of oxidant permeability in the topcoat to that in the TGO itself. Large-scale three-dimensional (3D) simulations are performed to model the formation of interconnecting vertical/channel cracks (often called ‘mud cracks’). The simulated crack morphology are in excellent agreement with the experimental observations from the literature. The simulations also provide insights into the cracking of EBCs and its dependence on the structure and constituent properties of the coating system. Furthermore, these results demonstrate the developed damage model can be a useful tool for design of more durable EBCs.

Cracking↗
DOE OSTI2020

Workshop Report for Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications

Artificial intelligence (AI) promises powerful new capabilities in an expansive array of applications. One area is proliferation detection, where AI can provide transformative tools to achieve objectives currently inaccessible using conventional methods. In particular, AI affords the opportunity to use new indicators and process massive amounts of heterogeneous data that can increase sensitivity to proliferant activities and push proliferation detection to the earliest possible stages. However, existing AI tools are not ready to achieve such potential, falling short in regard to some important considerations involved in proliferation detection. One crucial aspect that requires improvement is the explainability of the most powerful AI algorithms (i.e., understanding how the algorithms actually arrive at their conclusions)-the lack of which prevents widespread adoption in national security missions. The Data Science and AI portfolio within the National Nuclear Security Administration's Office of Defense Nuclear Nonproliferation Research and Development is driving the development of next-generation AI for proliferation detection through the expertise and work of the national laboratories and partners in academia. The "Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications" workshop aimed to further this objective. The meeting was held virtually on Sept. 15-16, 2020 and included more than 170 participants, primarily from the national laboratories with additional contributions from university researchers and mission partners. Each day included a keynote presentation, four technical presentations about cutting-edge research in explainability, and a panel to explore considerations in applying explainability and developing AI systems that can accelerate the transition of emerging AI technologies among partners and end users to solve critical mission questions. This report summarizes the Next-Gen AI for Proliferation Detection workshop's content and findings.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Thinking the Other Unthinkable: Disarmament in North Korea and Beyond

The P5 have defined nuclear disarmament as both a process and an end state. Differences of view about the latter are sharp, bitter, and abiding. This has stripped the discussion about the former of much of its potential content and value. Where might we get, practically and conceptually, if we were to set aside for now questions about the ultimate feasibility and desirability of the long-term goal and focus instead on the process? Further, what if we were also to posit that there will be no “fundamental transformation” of the international political system of a kind that would make the nuclear-armed states, and their unarmed neighbors, unconcerned about the effectiveness of mechanisms for peace and security in a disarmed and disarming world? In this context, might it be possible to give states the confidence they would require to take more ambitious incremental steps on the disarmament pathway? How could such steps contribute to the relaxation of international tensions that the NPT itself describes as a critical enabler of disarmament? These questions motivate this timely and innovative new work by Toby Dalton and George Perkovich of the Carnegie Endowment for International Peace. Their core objective is to “infuse needed realism into disarmament discussions.” Using North Korean disarmament as a test case, they explore a series of practical challenges and associated conceptual issues to frame a discussion of the possible disarming nucleararmed states. They begin by rightly noting that neither the advocates of the Ban treaty nor the advocates of North Korean disarmament have set our practical agendas for achieving their aims. They conclude that without an infusion of realism the “two polarized blocks” will continue to “stonewall and repel each other” and thus that “the risks of global nuclear disorder will grow.” This is the latest in the series of Livermore Papers begun in 2017 to stimulate the development of new strategic thought on emerging nuclear challenges. Conceptually, it is a follow-on to the inaugural Livermore Paper by Lewis Dunn on disarmament pathways. The views expressed in these papers are those of the authors and should not be attributed to Lawrence Livermore National Laboratory or any of its sponsors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Data for Development of Vegetative Oil Sorghum: From Lab-to-Field

Biomass crops engineered to accumulate energy-dense triacylglycerols (TAG or ‘vegetable oils’) in their vegetative tissues have emerged as potential feedstocks to meet the growing demand for renewable diesel and sustainable aviation fuel (SAF). Unlike oil palm and oilseed crops, the current commercial sources of TAG, vegetative tissues, such as leaves and stems, only transiently accumulate TAG. In this report, we used grain (Texas430 or TX430) and sugar-accumulating ‘sweet’ (Ramada) genotypes of sorghum, a high-yielding, environmentally resilient biomass crop, to accumulate TAG in leaves and stems. We initially tested several gene combinations for a ‘push-pull-protect’ strategy. The top TAG-yielding constructs contained five oil transgenes for a sorghum WRINKLED1 transcription factor (‘push’), a Cuphea viscosissima diacylglycerol acyltransferase (DGAT; ‘pull’), a modified sesame oleosin (‘protect’) and two combinations of specialized Cuphea lysophosphatidic acid acyltransferases and medium-chain acyl-acyl carrier protein thioesterases. Though intended to generate oils with medium-chain fatty acids, engineered lines accumulated oleic acid-rich oil to amounts of up to 2.5% DW in leaves and 2.0% DW in stems in the greenhouse, 36-fold and 49-fold increases relative to wild-type (WT) plants, respectively. Under field conditions, the top-performing event accumulated TAG to amount to 5.5% DW in leaves and 3.5% DW in stems, 78-fold and 58-fold increases, respectively, relative to WT TX430. Transcriptomic and fluxomic analyses revealed potential bottlenecks for increased TAG accumulation. Overall, our studies highlight the utility of a lab-to-field pipeline coupled with systems biology studies to deliver high vegetative oil sorghum for SAF and renewable diesel production.

Biofuels↗
NASA NTRS2014

Robonaut 2 - IVA Experiments On-Board ISS and Development Towards EVA Capability

Robonaut 2 (R2) has completed its fixed base activities on-board the ISS and is scheduled to receive its climbing legs in early 2014. In its continuing line of firsts, the R2 torso finished up its on-orbit activities on its stanchion with the manipulation of space blanket materials and performed multiple tasks under teleoperation control by IVA astronauts. The successful completion of these two IVA experiments is a key step in Robonaut's progression towards an EVA capability. Integration with the legs and climbing inside the ISS will provide another important part of the experience that R2 will need prior to performing tasks on the outside of ISS. In support of these on-orbit activities, R2 has been traversing across handrails in simulated zero-g environments and working with EVA tools and equipment on the ground to determine manipulation strategies for an EVA Robonaut. R2 made significant advances in robotic manipulation of deformable materials in space while working with its softgoods task panel. This panel features quarter turn latches that secure a space blanket to the task panel structure. The space blanket covers two cloth cubes that are attached with Velcro to the structure. R2 was able to open and close the latches, pull back the blanket, and remove the cube underneath. R2 simulated cleaning up an EVA worksite as well, by replacing the cube and reattaching the blanket. In order to interact with the softgoods panel, R2 has both autonomously and with a human in the loop identified and localized these deformable objects. Using stereo color cameras, R2 identified characteristic elements on the softgoods panel then extracted the location and orientation of the object in its field of view using stereo disparity and kinematic transforms. R2 used both vision processing and supervisory control to successfully accomplish this important task. Teleoperation is a key capability for Robonaut's effectiveness as an EVA system. To build proficiency, crewmembers have attempted increasingly difficult tasks using R2 inside the Station. After donning motion capture equipment and a virtual reality visor, Expedition 34/35 flight engineer Tom Marshburn began operations with simple hand movements. Having gained confidence, Marshburn guided R2's arms in a leader-follower exercise with crewmate Chris Cassidy. He was also able to use the hand to grab a tumbling roll of tape, a task only demonstrable in microgravity. Later efforts saw Cassidy handle softgoods through shared control with ground operators, mimicking an activity previously achieved using only autonomy. Robotic climbing through the ISS on handrails requires both precision motion and compliant grasps in order to both position grippers on handrails/seat track and prevent large internal forces. R2 climbs using actively controlled compliance and torque limiting to meet both the precision and softness requirements. During a step, the attached leg is controlled to be strong and stiff in order to maintain precision trajectory tracking. The swing leg is controlled to be stiff but weak to minimize unintentional impact forces while maintaining precision. During a simulated dual limb grasp (as shown in Figure 1), the R2 controller maintains one limb rigid and one limb soft to prevent large internal forces from building up. R2's grippers also use a form of force control to limit grip force while not fully closed on either a handrail or seat track thus limiting unintentional forces on cables/objects that may be present in R2's translational path. The on-board torso R2 safety system relies on a single end-effector velocity limit to prevent potential impact forces from exceeding Station maximum load requirements. R2's mobile configuration required modifications to the velocity limiting safety function due to its large, dynamic inertia. R2's legs maneuver the robot's mass creating configuration dependent, joint-relative inertias. A single all-encompassing velocity limit to cover worst case inertia is prohibitively low. The upgraded R2 control and safety systems solve this problem using momentum limiting, momentum control, and kinetic energy minimization. Momentum and kinetic energy take the robot mass into account relieving low velocity restrictions on low inertia end-effectors while ensuring that the overall mass of R2 is limited from hazardous velocities. The momentum of R2's five safety nodes (each of the four end-effectors and the body) is monitored and compared to a single momentum limit. If any of the five nodes exceeds the safety limit, the motor power is removed and the robot comes to a stop. Momentum control/limiting also provides a simple, reliable method to integrate hand held tools into the safety system by providing the tool mass to the control system thus automatically reducing the allowable velocity of the end-effector with the tool. Work on the ground continues to build the skill set for an EVA Robonaut. Recent experiments (Figure 2) demonstrate how a teleoperator can use R2 to manipulate a tether hook, an important safety precaution on spacewalks. Another task displayed Robonaut's ability to pull back a protective jacket over a hose and search for damage, as well as inspect a quick-disconnect fitting for debris. Demonstrations such as these are indicative of EVA work done on ISS, specifically seen during a series of spacewalks over 2012 and 2013 where astronauts searched for an ammonia leak in one of the external cooling loops. Through experiments both on ISS and on the ground, R2 is evolving and providing the information needed to plan out the upgrades that will make an EVA Robonaut an effective tool. With the addition of legs, R2 will start climbing inside the space station and supply invaluable information on how the climbing strategies and task stabilization techniques must be refined. Ground R2 systems will continue to work with additional EVA tools and equipment in preparation for onboard IVA testing and future EVA applications.

Diftler, Myron↗
DOE OSTI2021

Specific absorbed fractions for a revised series of the UF/NCI pediatric reference phantoms: internal photon sources

Assessment of radiation absorbed dose to internal organs of the body from the intake of radionuclides, or in the medical setting through the injection of radiopharmaceuticals, is generally performed based upon reference biokinetic models or patient imaging data, respectively. Biokinetic models estimate the time course of activity localized to source organs. The time-integration of these organ activity profiles are then scaled by the radionuclide S-value, which defines the absorbed dose to a target tissue per nuclear transformation in various source tissues. S-values are computed using established nuclear decay information (particle energies and yields), and a parameter termed the specific absorbed fraction (SAF). The SAF is the ratio of the absorbed fraction—fraction of particle energy emitted in the source tissue that is deposited in the target tissue—and the target organ mass. While values of the SAF may be computed using patient-specific or individual-specific anatomic models, they have been more widely available through the use of computational reference phantoms. In this study, we report on an extensive series of photon SAFs computed in a revised series of the University of Florida and the National Cancer Institute pediatric reference phantoms which have been modified to conform to the specifications embodied in the ICRP reference adult phantoms of Publication 110 (e.g. organs modeled, organ ID numbers, blood contribution to elemental compositions). Following phantom anatomical revisions, photon radiation transport simulations were performed using MCNPX v2.7 in each of the ten phantoms of the series—male and female newborn, 1 year old, 5 year old, 10 year old, and 15 year old—for 60 different tissues serving as source and/or target regions. A total of 25 photon energies were considered from 10 keV to 10 MeV along a logarithm energy grid. Detailed analyses were conducted of the relative statistical errors in the Monte Carlo target tissue energy deposition tallies at low photon energies and over all energies for source–target combinations at large intra-organ separation distances. Based on these analyses, various data smoothing algorithms were employed, including multi-point weighted data smoothing, and log–log interpolation at low energies (1 keV and 5 keV) using limiting SAF values based upon target organ mass to bound the interpolation interval. The final dataset is provided in a series of ten electronic supplemental files in MS Excel format. Finally, the results of this study were further used as the basis for assessing the radiative component of internal electron source SAFs as described in our companion paper (Schwarz et al 2021) for this same pediatric phantom series.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Sticky roots--implications of widespread, cryptic, viral infection of plants in natural and managed ecosystems for soil carbon processing in the rhizosphere

Plants strongly influence soil properties through rhizodeposition, in which exudates diffuse from roots, additional secretions are actively released, and root cells are sloughed into the soil. This contribution by plants of carbon compounds belowground is at the core of soil health, water holding capacity, and the soil carbon storage that pulls carbon dioxide out of the atmosphere. Once in soil, organic matter can bind with minerals such as iron hydroxides, where it can be protected from microbial attack for millenia, preserving very large terrestrial soil carbon pools. However, those same compounds contributed by roots to soil may also destabilize the long-term protective associations of SOM with minerals, making that soil organic matter (SOM) more vulnerable to microbial attack and decomposition. Plant roots thus influence both the buildup and breakdown of soil carbon pools. DOE’s E3SM Land Model (ELM) includes a representation of soil carbon storage on minerals, but the potential vulnerability of SOM–mineral associations to effects of rhizodeposition is not yet represented in ELM. To begin testing for this effect of rhizodeposition on soil carbon storage and decomposition, we worked to develop a novel approach during this TES Exploratory project DE-SC0019142 – we harnessed the power of plant viral infection. We examined whether plant virus infection can serve as a tool to intensify rhizodeposition at the root surface, and therefore possibly intensify mobilization of SOM from minerals making it visible to our analytical techniques. Viral infection is widespread in terrestrial ecosystems; 25-70% of plants have virus infection, yet the influence of such infection on root traits and terrestrial soil carbon dynamics remains largely unexplored. We used two plant hosts: the annual Avena sativa (oats) and the genetically tractable, model grass Brachypodium distachyon. These grasses were infected with the broad host range virus Barley Yellow Dwarf Virus (BYDV) via aphids (Rhopalosiphum padi). BYDV infects at least 150 grass species in agricultural and natural ecosystems, and in previous experiments, oats infected with BYDV had roots that were very sticky to the touch, strongly suggesting that infection altered rhizodeposition. We developed this new experimental approach mostly in a one virus (Barley Yellow Dwarf Virus)–one plant (Avena sativa) system. (Several effects of infection in a Brachypodium-BYDV system were similar in nature to effects on Avena sativa, but were more variable.) In the BYDV-Avena system, we developed protocols for consistently infecting target plants (and avoiding infection of control plants) using aphid caging on leaves. We measured that infected plants exhibited reduced photosynthesis, plant (including root) biomass, and root:shoot ratio, as well as simplified root system architecture. We established procedures for sampling the organic compounds carried specifically in phloem (vascular tissue) of leaves and roots, using aphid stylectomy. We used FTICR-MS, Orbitrap GC-MS, and LC-MS/MS to analyze organic compounds in phloem, liquid around roots of plants grown hydroponically, and pore water around roots in soil, and found differences in the compounds in solution bathing roots when infected and uninfected plants were grown hydroponically. Finally, we synthesized isotopically-labeled mineral–organic matter (MAOM) associations in the lab and developed assays using them in solution and in soil. Assays quantified the extent and rate of mineralization of labeled MAOM that was mobilized by functionally distinct rhizodeposits and then attacked by microbes. Two mechanisms for MAOM mobilization emerged, with distinct dynamics. During “direct” mobilization, rhizodeposits such as the strong ligand oxalic acid could drive rapid dissolution of minerals, mobilizing MAOM. During “indirect” mobilization, rhizodeposits such as the simple sugar glucose did not attack minerals directly but instead intensified microbial activity, which led to mobilization via changes in e.g. pH, Eh, and microbial metabolite production (Li et al. 2021). Mechanistic understanding derived from these data and our ongoing experiments using these techniques will inform future development of ELM. Plant roots not only contribute newly fixed organic compounds to soils, but also root activities can drive mineralization of the carbon and nutrients mobilized off minerals via “indirect” or “direct” mechanisms. Using viral infection as a new tool, ongoing combined experimentation and modeling will explore the strength and larger-scale significance of the cascade of processes from rhizodeposition to MAOM mobilization for soil carbon storage and nutrient cycling in terrestrial ecosystems. And if viral infection leads quite generally to “sticky roots”, our perception of the potential importance of prevalent virus infection in terrestrial landscapes will be transformed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗