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

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DOE OSTI2022

University of Miami Industrial Assessment Center (Final Scientific/Technical Report)

The University of Miami Industrial Assessment Center (MIIAC) is located at the Department of Industrial & Systems Engineering in the College of Engineering at University of Miami. The Center has conducted 402 energy assessments with estimated Total Energy Savings over $\$57.3$ million, Total Non- Energy Cost Savings of $\$23.7$ million, and Total Energy Saving as a 26% of Energy Costs of $\$311$ million. A total of 6.01 TBtu of energy savings were recommended as a result of energy efficiency measures resulting in $\$81$ million in cost savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Establishment of an Industrial Assessment Center (IAC) site at Arizona State University (ASU)

In this document we report the overall accomplishments of the IAC site at ASU. The report is organized in three different areas: conduct industrial assessments; provide training, research, and educational opportunities to IAC students; and other activities. The report includes those assessments made between September 2016 to August 2021.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

NC State University Industrial Assessment Center. Final Report

This report documents work from the Industrial Assessment Center program at NC State University. The program is funded by the US Department of Energy Advanced Manufacturing Office. The IAC provides energy conservation assessments for small and medium sized manufacturers in NC, SC, and VA. Students are involved in all aspects of the assessment including the on-site visit, interacting with plant personnel, collecting data, performing engineering analyses on potential energy efficiency measures, and producing a technical report for the client.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Single‐Step Recovery of Water from Stable Crude Oil‐Water Emulsion Using Surface Engineered Hybrid Inorganic‐Polymer Membranes

ABSTRACT Separating crude oil from water remains one of the most stubborn challenges in environmental remediation, especially for surfactant‐stabilized emulsions that resist conventional demulsification methods. Here, we report a scalable strategy for achieving near‐zero‐discharge separation of crude oil emulsions using a single superhydrophilic membrane. By applying low‐temperature atomic layer deposition (ALD) of various metal oxides onto activated polyvinylidene fluoride (PVDF) membranes, we create atomically precise surface‐engineered (SE) membranes that maintain an exceptionally strong hydration layer at the membrane‐feed interface, even at high oil loadings. Among the various metal oxides, TiO 2 ‐modified SE membranes exhibit superior interfacial water stability, enabling sustained dewatering of complex crude oil‐water emulsions with >98% separation efficiency and >97% water recovery, compared to only 24.6% water recovery for the pristine membrane. This separation performance surpasses conventional hydrophilic membranes and is comparable to complex Janus channel membrane systems, demonstrating near‐complete emulsion separation using a single membrane. This low‐temperature membrane surface engineering process with atomic‐level precision and potential for scalability via roll‐to‐roll fabrication is promising for industrial‐scale, energy‐efficient water treatment and oil spill remediation applications.

Sengupta, Bratin [Applied Materials Division Argon↗
DOE OSTI2022

Modeling and Policy Pathways to Decarbonize South Asia’s Industrial Sector

The industrial sector is responsible for one-third of global greenhouse gas emissions, and industrial decarbonization will be an essential component of limiting emissions and mitigating climate change (Rissman et al., 2020). This holds true for South Asian countries as they work toward their stated commitments to reducing emissions in the coming years. India has pledged to reduce the emissions intensity of its gross domestic product (GDP) by 33–35% by 2030 (Government of India, 2016) and announced at COP26 a target of reaching net-zero CO 2 emissions by 2070, a goal that will require rapid decarbonization of energy-intensive industries (WEF, 2021). Bangladesh’s Nationally Determined Contributions include a commitment to reducing greenhouse gas emissions by 6.73% to 15.12% by 2030 (Ministry of Environment, Forest and Climate Change, 2021). While these Nationally Determined Contributions do not explicitly target emissions reductions in industry, Bangladesh’s Energy Efficiency and Conservation (EE&C) Master Plan highlights industry as an important sector for EE&C (Sustainable and Renewable Energy Development Authority, 2015). Sri Lanka has pledged carbon neutrality by 2050, including a reduction in industrial greenhouse gas emissions (Ministry of Environment, 2021). Nepal’s commitment to net-zero greenhouse gas emissions by 2050 includes plans to establish guidelines and technology transitions facilitating industrial decarbonization (Government of Nepal, 2020).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

2022 Louisiana State University (Final Report)

LSU-IAC started in LSU’s College of Engineering in 2016 with funding from the U.S. Department of Energy’s IAC program. Due to the Covid 19 pandemic, the grant end date was extended from 8/31/2021 to 2/28/2022. In the 5-year performance period, LSU-IAC has conducted a total of 67 industrial assessments and trained a total number of 41 students. We have recommended 408 improvement measures with potential energy savings of 58,951,388 kWh and energy cost savings of $6,817,783 if implemented. Of the 41 students trained, 16 received DOE certificates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

42 ENGINEERING↗
DOE OSTI2022

UF Industrial Assessment Center - Budget Periods 2017-2021. Final Report

This report summarizes the work performed at the University of Florida’s Industrial Assessment Center (UF-IAC) during the five budget periods (BPs) in the years 2017 through 2021 under DOE Award No. DE-EE0007707. The objective of the work is to perform industrial assessments to small- and medium-sized manufacturing facilities in the State of Florida and to train students in industrial energy management and in performing industrial assessments. Specific details about the activities of the UF-IAC (referred to as the Center) during that time can be found in the 20 quarterly reports that were submitted throughout the duration of the contract. The project start and end dates are September 1, 2016 and August 31, 2021, respectively. The project was granted a six-month no-cost extension till February 28, 2022, to accommodate unexpected delays due to the COVID-19 pandemic. This project was performed by the University of Florida (PI: Dr. SA Sherif). The scope of work includes six milestone whose description and outcomes are listed in the Statement of Project Objectives (SOPO).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Pathways Analysis Summary: Decarbonization Potential for Industrial Subsectors - Preliminary Modeling Results

This provides a summary of draft modeling efforts undertaken by the U.S. Department of Energy (DOE) Industrial Efficiency and Decarbonization Office (IEDO) as an extension and expansion of the 2022 Industrial Decarbonization Roadmap. IEDO is providing these draft modeling results to support stakeholder engagement and inform office- and department wide strategy and decision making. Section 1 provides an overview of the context for this analysis and modeling as well as information on the decarbonization pillars characterized and the models themselves. Section 2 presents modeling results of one net-zero emissions pathway each for six industrial subsectors: cement, chemicals, food and beverage, iron and steel, petroleum refining, and pulp and paper. It is important to note that these pathways are just one example and there is no single pathway for any single industrial subsector. Competition across different possible pathways will be essential to industrial decarbonization success. Section 3 provides an overview of the “rest of industry” subsectors and a high-level overview of net-zero barriers, challenges, pathways, and technologies. IEDO will continue to consider net-zero pathways and modeling for these rest of industry subsectors. Additional details will be made available in the future on the IEDO website.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

The Role of Fuels in Transforming Energy End-Use in Buildings and Industrial Processes

This book examines what role fuels have in the transformation of end-use in buildings and industrial processes. Energy efficient technologies are necessary to lower the carbon footprint for a transition towards clean energy in a sustainable manner. Efficient utilization of primary energy resources including renewables to support the current and future energy needs while targeting grid resiliency, energy and environmental security, at an affordable cost is of significant value. Analysis of configurations consisting of heat pumps, fuel driven thermal providers and power systems is presented. Sensitivity of electrical grid's carbon intensity towards carbon footprint in comparison with fuel driven technologies is necessary to recognize the true value proposition of currently available energy solutions for different end consumers. Similarly, the role of low carbon, zero carbon, and carbon negative fuels such as power to gas, power to liquid, hydrogen, biogas, etc. in conjunction with polygeneration technologies are discussed. Transformation of the primary energy resources from conventional fossil fuels to renewable fuels or electricity will have a significant impact on the overall carbon footprint of various end use sectors, including buildings. Hence, this book also examines two different scenarios focused on sensitivity of the pace of decarbonization of electrical grid and fuel supply on operational energy related carbon emissions.

Cheekatamarla, Praveen↗
DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗
DOE OSTI2022

Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single-variable regressors that did not capture all contributions to energy consumption. Further, new modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model is developed to create a general predictor for industrial building energy consumption. The model uses features of air enthalpy, solar radiation, and wind speed to predict weather-dependency; motor, steam, and compressed air system parameters to capture support equipment contributions; and operating schedule, production rate, number of employees, and floor area to determine production-dependency. Results showed that a model that used a linear regressor over a transformed feature space could outperform a support vector machine and utilize features more representative of physical systems. Using informed parameters to build a reliable predictor will more accurately characterize a manufacturing facility's energy savings opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Catalytic Reaction Triggered by Magnetic Induction Heating Mechanistically Distinguishes Itself from the Standard Thermal Reaction

As a recent advancement in chemical engineering, magnetic induction heating (MIH) is utilized to initiate the intended reactions by enabling the self-heating of the ferromagnetic catalyst particles. While MIH can be energy-efficient and industrially scalable, its full potential has been underappreciated in catalysis because of the perception that MIH is merely an alternative heating approach. Unexpectedly, we show that the MIH-triggered reaction could go beyond standard thermal catalysis. Specifically, by probing the representative Pt/Fe 3 O 4 catalysts with CO oxidation in both thermal and MIH modes with consistent temperature profiles and catalyst structures, we found that the MIH mode boosts the reactivity more than 25 times by modifying Pt-FeO x interfacial synergies and promoting facile oxidation of the adsorbed carbonyl species by atomic oxygen. Further, as we preliminarily observed, this beneficial MIH-catalysis can be translational to other thermal reactions, potentially paving the way to launch MIH-catalysis as a distinct reaction category.

CO oxidation↗
DOE OSTI2025

Considerations for Distributed Edge Data Centers and Use of Building Loads to Support Large Interconnections

The rapid expansion of artificial intelligence (AI) and machine learning is driving unprecedented electricity demand from data centers. It is predicted that by 2030, 90% of AI workloads will be inference-based, requiring interconnection of multiple low-latency edge data centers (<20 MW) sited closer to end users - often on already constrained distribution feeders. Although individually small, these loads can aggregate to large loads per feeder, straining infrastructure, creating multi-year interconnection delays, and driving up customer costs. This paper proposes a data center-focused grid-integration framework that combines feeder hosting capacity analysis with building energy efficiency, building load flexibility, and waste heat reuse to expand effective feeder and substation headroom. Such approaches can reduce interconnection delays, lower costs for ratepayers, and accelerate AI-ready infrastructure deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Financing Options for Onsite Generation, Energy Storage, and Energy Efficiency Projects

Across sectors, commercial and industrial facilities are benefiting from the implementation of renewable energy generation, storage, and energy efficiency projects. Despite the potential for these projects to reduce onsite energy consumption, build resiliency, and lower operational costs in the long term, the initial expenses are often high. However, there are a growing number of financing mechanisms that can be leveraged. When deployed strategically, these mechanisms can give organizations the financial tools to install projects that accomplish their energy goals. In 6 steps, this resource introduces organizations to a general process to contextualize the many different financing options, ultimately facilitating an informed selection of financing mechanisms. Step 1 discusses the importance of establishing clear organizational preferences. Step 2 briefly introduces common financing options and Steps 3 and 4 provide guidance for selecting mechanisms based on locational availability and organizational preferences. Finally, Steps 5 and 6 show how mechanisms can be combined with incentives and provide preliminary guidance for selecting and engaging with external partners. While this document provides a general approach to selecting a financing mechanism for renewable energy generation, storage, and/or energy efficiency, it does not contain tax and/or legal advice. A tax advisor should be consulted before taking any action.

25 ENERGY STORAGE↗
DOE OSTI2025

Defining an industrial heat pump: A review & synthesis

Clear and understandable definitions of advanced energy technologies are not common and often confuse those who are not experts. This review paper addresses a critical issue in the field of heat pumps: the ambiguity surrounding the term “industrial heat pump.” The term, as discussed in various literature and media, often leads to misconceptions about the capabilities and applications of heat pumps, particularly in industrial contexts. This review paper seeks to refine and unify the definition of industrial heat pumps by analyzing existing academic and commercial literature, industry reports, and classifications. Unique identifiers explored for the definition of an industrial heat pump include the use of waste heat, operating temperature ranges, size specifications, and specific end-use applications. The study reveals differences in how industrial heat pumps are defined in academic and commercial contexts, highlighting the need for a standardized definition to facilitate better communication among manufacturers, policymakers, and end users. This is especially important considering recent legislative efforts such as the HEAT Act, which seeks to promote industrial heat pump adoption. The proposed definition aims to provide clarity while supporting the effective deployment of industrial heat pumps. With proper adoption, the definition will help promote the role of industrial heat pumps in achieving energy efficiency goals in the industrial sector. The intended impact is for the definition to serve as a foundational reference for future research and policy development.

Heat pump characteristics↗
DOE OSTI2025

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

JUSTIFI: Software for Improving Performance Objectives via Energy Efficiency

With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗