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DOE OSTI2023

Energy Transition: Challenges and Opportunities for the Oil & Gas Industry

The energy sector has been experiencing a massive but gradual shift in recent years toward renewable and low-carbon energy sources. The future of fossil fuels lies in the ability of the industry to adapt to the market, environment, and social trends within the energy transition framework. In this chapter, we review the challenges that the oil and gas industry will be facing in the coming years. We then explore opportunities and growth areas that this transition provides to the industry. This chapter focuses on three areas of digitization and modernization, developing innovative low-carbon fuels, and harnessing underground and offshore facilities and expertise.

blockchain technology↗

DOE OSTI2023

National Wind Workforce Assessment: Industry to Students [Slides]

As a part of the National Wind Workforce Assessment, four presentations have been created in conjunction with the technical report to provide more insight into key findings. The four presentations are catered towards specific stakeholder groups that include: educators, wind industry firms, students, and current wind industry employees. This presentation is intended for use by wind industry employers looking to gain insight into key levers that can influence hiring difficulty and actionable steps that can be taken to help narrow the workforce gap. The report includes the current perception of the wind industry by the potential workforce, current hiring difficulties faced by wind energy firms, and current hiring difficulties faced by the potential workforce. The hiring difficulties for wind industry employers are divided by entry level employees and non-entry-level employees and by cross sections such as firm size, location, value chain segment, and wind industry sector. Hiring challenges faced by students trying to enter the wind industry are divided by 2-year degree and certification programs, 4-year degree programs, and current wind employees.

17 WIND ENERGY↗

DOE OSTI2023

National Wind Workforce Assessment: Educators to Students [Slides]

As a part of the National Wind Workforce Assessment, four presentations have been created in conjunction with the technical report to provide more insight into key findings. The four presentations are catered towards specific stakeholder groups that include: educators, wind industry firms, students, and current wind industry employees. This presentation is intended for use by educators and students looking to gain insight into key levers that can influence hiring difficulty and actionable steps that can be taken to help narrow the workforce gap. The report includes the current student perception of the wind industry, current hiring difficulties faced by wind energy firms, and current hiring difficulties faced by the potential workforce. The hiring difficulties for wind industry employers are divided by entry level employees and non-entry-level employees and by cross sections such as firm size, location, value chain segment, and wind industry sector. Hiring challenges faced by students trying to enter the wind industry are divided by 2-year degree and certification programs, 4-year degree programs, and current wind employees.

17 WIND ENERGY↗

DOE OSTI2023

Advanced Manufacturing and Materials for Hydropower: Challenges and Opportunities

Hydropower is a well-established industry that has been largely contributing to the global generation of clean and renewable energy for more than a century. In the United States in 2021, it accounted for 30% of all renewable energy generation and 6.1% of the total energy portfolio. Hydropower technology and designs have been optimized throughout the years, but manufacturing of hydropower components still relies heavily on traditional methods and materials. Changes in global energy production systems and international supply chain issues are inspiring the manufacturing sector to reconsider their processes. Similarly, the hydropower industry is facing manufacturing challenges stemming from well-known maintenance issues, environmental impact mitigations, and changes in operations. These challenges, along with continued innovation in new hydropower and pumped storage development and modernization of the fleet, present an opportunity for advanced manufacturing and materials (AMM) to provide immense value to the hydropower industry. In support of the US Department of Energy’s (DOE’s) Water Power Technologies Office (WPTO), this report aims to characterize the current and emerging manufacturing-related challenges in US hydropower and to identify the high-impact opportunities in AMM that could address these challenges. The results highlighted in this report were collected through literature review, individual stakeholder interviews, and an in-person workshop organized at DOE’s Oak Ridge National Laboratory Manufacturing Demonstration Facility that brought together hydropower industry stakeholders, advanced manufacturing R&D, and the government.

13 HYDRO ENERGY↗

DOE OSTI2021

Midwest Nuclear-based Net-Zero Carbon Steelmaking Demonstration

Globally, the iron and steel industry accounts for around a quarter of GHG emissions from the manufacturing sector , which is about 7% of the 33 gigatonnes (Gt) of global CO 2 emissions . Thus, globally, the steel industry is a 2-3 Gt CO 2 per year emissions challenge. The steel industry is important to the U.S. economy with output equal to $0.5 trillion and domestic production capacity is critical to national defense, infrastructure, energy production, and transportation. President Biden’s executive order on climate identifies actions and policies to put the Nation on a path to achieve net-zero carbon emissions, economy-wide, by no later than 2050. To achieve this, deep carbon reductions in the power, transportation, buildings and capital-intensive industrial manufacturing segments such as steel, cement and chemicals need to be addressed. In its recent “Accelerating Decarbonization of the U.S. Energy System” report , the National Academy of Sciences (NAS) stated that, “while technology exists to decarbonize all parts of the energy system, some sectors remain at precommercial or first-of-a-kind demonstration stages and require significant improvement in cost and performance to become commercially viable.” The NAS goes on to state that these hard to decarbonize sectors include “aviation, shipping, and industrial subsectors such as steel, cement, and chemicals manufacturing .” The Administration has proposed a timeline to decarbonize energy, transportation and then industry and manufacturing. From a life-cycle approach, decarbonizing steel and other large industrial inputs are necessary to decarbonize transformations in energy and transportation. DOE’s TRI-Lab Consortium’s Integrated Energy Systems (IES) program is a collaboration amongst DOE’s three applied energy laboratories: the National Energy Technology Laboratory; National Renewable Energy Laboratory and Idaho National Laboratory. The IES approach looks at more tightly integrating low-carbon nuclear energy, renewable electricity, energy storage, load/demand balancing, and biomass (including plastics and other wastes) with one or more industrial processes that utilize heat and/or power from these clean and waste energy sources to produce a low-carbon commodity-scale product.

08 HYDROGEN↗

DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk Presentation for EnCyCriS

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk

42 - ENGINEERING↗

DOE OSTI2023

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Integrated Micro‐Scale Concentrating Photovoltaics: A Scalable Path Toward High‐Efficiency, Low‐Cost Solar Power

The global energy market is seeing increases in the electricity demand of a couple of percentage points annually. The photovoltaic (PV) industry is also growing rapidly every year. One of the PV technologies is concentrator photovoltaics (CPV). CPV uses high‐efficiency multijunction solar cells and optics to concentrate sunlight, thereby significantly reducing the amount of semiconductor material needed. Yet, due to the high upfont manufacturing cost of CPV, it currently does not offer a competitive price against silicon PV. With this a new branch is introduced to the industry, micro‐CPV, which can be broadly explained as the miniaturization of the solar cells and optical components. The motivation for micro‐CPV is lowering the cost by decreasing the material volume and enabling new system architectures and high‐throughput manufacturing methods, while still maintaining high electrical efficiencies, taking advantage of a lower thermal load, shorter optical paths, lower resistive losses, and lower material volumes. Herein, a comprehensive review of the technological advances is presented, key synergies between micro‐CPV and other industries sharing similar challenges are identified, exemplified by micro‐light emitting diodes display manufacturing. New assembly process development in these industries will facilitate commercial adoption of micro‐CPV with continued miniaturization while driving down the cost.

Jost, Norman↗

DOE OSTI2024

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↗

DOE OSTI2024

Inaugural Molten Salt Technologies Workshop Powering the Future

Department of Energy↗

DOE OSTI2022

Biofilm formation and genomic features of Listeria monocytogenes strains isolated from meat and dairy industries located in Piedmont (Italy)

Listeria monocytogenes is considered a major challenge for the food industry as it can persist for long periods in food processing plants by forming biofilms. The aims of this study were: i) to assess the biofilm producing ability of 57 Listeria monocytogenes isolates previously subjected to whole-genome sequencing (WGS); ii) to compare the levels of biofilm formation with the presence or absence of biofilm associated genes. To determine the presence or absence of a known set of biofilm associated genes, a comparative genomic analysis was performed on each strain. Among Listeria monocytogenes isolates, 58 %, 38.5 % and 3.5 % exhibited weak, moderate or strong biofilm production, respectively. No difference in biofilm production was observed between food and environmental isolates. The percentage of Listeria monocytogenes strains isolated from meat products (57 %) classified as moderate or strong biofilm producers was higher than the percentage obtained for strains isolated from dairy products (28 %). Here, the presence of the Stress Survival Islet 1, the arsD stress gene and the truncated inlA protein was significantly associated with increased levels of biofilm. Combining biofilm phenotype with molecular and genotyping data may provide the opportunity to better understand the relationship between genes linked to biofilm formation in Listeria monocytogenes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Recycling Perspectives of Electric Arc Furnace Slag in the United States: A Review

This article presents a comprehensive review of electric arc furnace (EAF) slag recycling in the United States, examining its classification and the associated challenges and opportunities of its industrial use. The study affirms EAF slag's nonhazardous status. Here, the main challenges identified in EAF slag applications include substantial variations in composition and volume instability during/after hydration. Analysis of the U.S. recycling practices reveals that EAF slag is predominantly reused, with minimal landfill disposal. However, its prevalent use as a low value-added aggregate in construction applications underscores the industry's ongoing challenge to get additional value from EAF slag recycling. Despite these challenges, the study highlights a great potential for increased value extraction from EAF slag recycling. Beyond conventional applications as a clinker material for the cement industry, the review explores modern technologies for steelmaking slag recycling, revealing options for recovering valuable metals such as Cr, V, Mo, and Fe through methods such as leaching, reduction, and oxidation.

42 ENGINEERING↗

DOE OSTI2020

Designer Metal–Organic Frameworks for Size–Exclusion–Based Hydrocarbon Separations: Progress and Challenges

The separation of hydrocarbons is of primary importance in the petrochemical industry but remains a challenging process. Hydrocarbon separations have traditionally relied predominantly on costly and energy intensive heat-driven procedures such as low temperature distillations. Adsorptive separation based on porous solids represents an alternative technology that is potentially more energy efficient for the separation of some hydrocarbons. Great efforts have been made recently not only on the development of adsorbents with optimal separation performance but also towards the subsequent implementation of adsorption-based separation technology. Emerging as a relatively new class of multifunctional porous materials, metal-organic frameworks hold substantial promise as adsorbents for highly efficient separation of hydrocarbons. This is because of their exceptional and intrinsic porosity tunability which enables size-exclusion based separations that render the highest possible separation selectivity. In this review, we highlight the recent advances in the development of MOFs for separation of selected groups of hydrocarbons, including methane/C2 hydrocarbons, normal alkanes, alkane isomers, alkane/alkene/alkyne, and C8 alkylaromatics, with a particular focus on separations based on size-exclusion mechanism. Insights into tailor-made structures, material design strategies, and structure-property relations will be elucidated. In addition, the existing challenges and possible future directions of this important research field will be discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Linker Vacancy Engineering of a Robust ftw–type Zr–MOF for Hexane Isomers Separation

Discrimination of physically similar molecules by porous solids represents an important yet challenging task in industrially relevant chemical separations. Precisely controlled pore dimension and/or tailored pore surface functionality are crucial to achieve high-efficiency separation. Metal-organic frameworks (MOFs) are promising candidates for these challenging separations in light of their structural diversity as well as highly adjustable pore dimension/functionality. We report here a microporous, ftw-type Zr-based MOF structure, HIAM-410 (HIAM=Hoffmann Institute of Advanced Materials), built on hexanuclear Zr 6 cluster and pyrene-1,3,6,8-tetracarboxylate (ptc 4– ). Its crystallographic structure has been determined using continuous rotation electron diffraction (cRED) technique combined with Rietveld refinement against powder X-ray diffraction data, aided by low-dose high-resolution transmission electron microscopy (HRTEM) imaging. The compound features exceptional framework stability that is comparable to the prototype MOF UiO-66. Interestingly, the linker vacancies in the pristine MOF structure could be partially restored by post-synthetic linker insertion. Its separation capability of hexane isomers is enhanced substantially upon the linker vacancy engineering. As a result, the restored structure exhibits efficient splitting of monobranched and dibranched hexane isomers at both room temperature and industrially relevant temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗

DOE OSTI2024

Scalable electrified cementitious materials production and recycling

The production of Portland cement, the industry-standard cement, contributes ~8% of global CO 2 emissions through fossil-fuel heating and decomposition of limestone (the primary cement raw material). Decarbonization, e.g., via direct electrification, of this 200-year-old liming routine is extremely challenging at the industry scale. We propose a scalable electrochemical decarbonization approach to circumvent the limestone use by switching to carbon-free calcium silicates from abundant minerals and recycled concrete. Water electrolysis produces protons and hydroxides to drive a pH gradient that accelerates Ca 2+ ion leaching from calcium silicates and captures atmospheric CO 2 to form carbon-negative CaCO 3 , which serves as the feedstock for cement manufacturing or as the carbon-mineralized product for cement substitution with permanent carbon storage. Value-added co-products amorphous silica and green H 2 further enhance cement performance and supplant fossil fuels for net-zero transition, respectively. The products readily meet present-day regulatory standards and demands, and the approach readily synergizes with business-as-usual cement manufacturing and concrete construction, which are important for upscaling and structural safety, promising ready reception by the public and industries. Blended Portland cement produced through our approach with carbon-negative CaCO 3 and silica demonstrates enhanced resilience and achieves carbon neutrality or negativity when incorporating storage or circulation of CO 2 from cement plant flue gas, respectively. This low-cost, electrochemical cement production approach using abundant ubiquitous raw materials enables electrification, transition to clean fuel, and decarbonization at a gigaton scale.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Traffic Shaping to Traffic Engineering in Time-Sensitive OT Network

Modern industrial automation systems increasingly depend on network infrastructures for time-critical communication, driving the need for solutions that guarantee timely and reliable data delivery. IEEE 802.1 Time-Sensitive Networking (TSN) holds significant promise for converging Information Technology (IT) and Operational Technology (OT) networks, enabling interoperability and supporting the coexistence of mixed-critical traffic crucial for Industry 4.0 and IIoT. To achieve deterministic communication, TSN employs various traffic shapers such as the Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), and Credit-Based Shaper (CBS). However, the effective deployment of TSN in industrial automation faces several challenges. These include the non-trivial mapping of diverse industrial traffic types to specific shapers, the complexity of optimizing shaper configurations. We present a model for effective traffic engineering within TSN enabled OT Network. Our experiments also demonstrate how shaping of certain traffic types get affected in absence of precise time synchronization and propose possible solutions based on experiment results. Based on our experimental results we provide recommendations on how traffic type assignments should be done and which traffic shaping mechanisms should be used for a particular traffic type.

Sarker, Taposh Kumer [University of Texas at El Pa↗