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

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dual-Band Electrochromism in Hydrous Tungsten Oxide

The independent modulation of visible and near-infrared light by a single material, termed dualband electrochromism, is highly desirable for smart windows to enhance the energy efficiency of buildings. Tungsten oxides are commercially important electrochromic materials, exhibiting reversible visible and near-infrared absorption when electrochemically reduced in an electrolyte containing small cations or protons. The presence of structural water in tungsten oxides has been associated with faster electrochromic switching speeds. Here, we find that WO 3 ·H 2 O, a crystalline hydrate, exhibits dual-band electrochromism unlike the anhydrous WO 3 providing a heretofore unexplored route to tune the electrochromic response of tungsten oxides. Absorption of near-infrared light is achieved at low Li + /e - injection, followed by the absorption of visible light at higher Li + /e - injection as a result of an electrochemically-induced phase transition. We propose that this dual-band modulation is possible due to the more open structure of WO 3 ·H 2 O as compared to WO 3 . This facilitates a more extended solid solution Li + insertion regime that benefits the modulation of near-infrared radiation via plasmon absorption. Higher degrees of Li + /e - insertion lead to polaronic absorption associated with localized charge storage. Furthermore, these results inform how structural factors influence the electrochemically induced spectral response of transition metal oxides and the important role of structural water beyond optical switching speed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Trends in best-in-class energy-efficient technologies for room air conditioners

Improving the efficiency of room air conditioners (RACs) could provide significant energy and associated emissions savings, particularly in emerging economies with hot climates where the cooling demand is expected to increase dramatically. To help accelerate efficiency improvements, this study identifies “best-in-class” high-efficiency RAC components and products. The findings show that manufacturers tend to minimize manufacturing costs by using RAC designs that are readily available or standardized to their production, and they share components across various models. High-efficiency RAC models use advanced compressor technologies optimized at a low frequency, large heat exchangers with thermodynamically effective materials and designs, highly efficient direct current fan motors, advanced metering devices, and smart sensors for temperature and humidity control. Recently RAC manufacturers have been improving seasonal efficiency – better reflecting part-load operation – especially via variable-speed (inverter) drives for compressor motors. Recent highest-efficiency RAC models use low global warming potential (GWP) refrigerants, having transitioned from conventional high-GWP refrigerants, in regions where RACs that use these low-GWP refrigerants are commercially available. Recently demonstrated innovative technologies show trends toward smart hybrid designs, evaporative cooling, and solid-state materials beyond the conventional vapor-compression technology. This information could help policymakers improve their RAC market-transformation programs to align with the most-efficient global technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Energy Efficient Material Processing through Automated Process Monitoring and Controls

Smart manufacturing is bound to play a crucial role in reducing global energy consumption while accelerating economic development. This phenomenon is evident in advanced sensing technology developments, data analytics and machine learning/AI, automated controls, cloud computing, etc. The immediate opportunity for smart manufacturing is to improve the energy efficiency of manufacturing operations through innovations in processes and controls. The manufacturing industry still consumes about 30% of total global energy production, which is significant. This program focused on the recommendation of heterogeneous sensors to monitor the Chemical Vapor Infiltration (CVI) process parameters, states, and key performance indices and utilize cloud computing to sort and analyze the real-time data. Learning through data analytics helps guide the control parameters affecting energy usage. The target process in the program is the CVI process at the Honeywell South Bend facility, which is one of the most energy-intensive manufacturing industries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Cyberguardians and STEM Warriors (Final Technical Report (FTR))

In the past decade, solar power, with and without energy storage has become the fastest growing source of energy generation in the world. In the U.S., solar employment more than doubled from 105,145 jobs in 2011 to 255,037 jobs in 2021, four times faster than the U.S. job growth rate overall. These factors, combined with technology advancements, creates a skills gap that puts tremendous stress on society to deliver the workers to fill the open job requisitions. The Cyberguardians and STEM Warriors project (Cyberguardians) was designed to address the trained-worker shortage in the energy industry in three ways: 1) by developing educational curriculum that addresses DER technology changes; 2) by delivering curriculum to prospective workers, including military veterans and their families, via universities, community colleges, and vocational training outlets; and 3) introducing individuals who have completed training to employers that can hire them. Cyberguardians exceeded its curriculum goals by producing 27 academic units of university-accredited material (12 total courses) covering energy fundamentals, smart inverters, Distributed Energy Resource (DER) data communication, cybersecurity, standardization, certification, data analytics, and IEEE 1547 standard topics. The North American Board of Certified Energy Practitioners (NABCEP) also accredited the material for use in their credential program. Seven instructors were recruited and trained, and six academic institutions (University of California San Diego, State University of New York, North Carolina State University, Harper Community College, Green Village Academy, and the SunSpec Alliance) were enlisted, meeting program goals. All course material was published under the Creative Commons license and made available royalty free, thus providing a long-lasting public benefit. The program’s outreach program vastly exceeded program goals and incorporated the efforts of 13 outreach partners (11 of which are veteran focused), an advisory board representing 15 companies, webinars and 10’s of thousands of email messages sent to prospective students and hiring managers. Despite these efforts, the global pandemic depressed anticipated program participation by about a third. Still, a total of 396 students enrolled and 289 completed the courses and were accredited. The job applicant task achieved similar results (111 realized vs a 174 goal) but reported job placement was weaker at (9 realized vs. a 51 goal). The Cyberguardians program fills a critical void for cost-effective, royalty-free curriculum and training pertaining to DER technologies and cybersecurity that prospective energy workers must possess to be effective in the 21 st century. On this basis alone, the investment of taxpayer funds will pay dividends for years to come.

14 SOLAR ENERGY↗
DOE OSTI2020

Combined Experimental and Theoretical Investigations of n-Type BiFeO 3 for Use as a Photoanode in a Photoelectrochemical Cell

Combined experimental and theoretical investigations were performed to evaluate the potential of n-type BiFeO 3 as a photoanode. While previous experimental and theoretical studies on BiFeO 3 mainly focused on its ferroelectric properties, several studies have reported the advantages of BiFeO 3 as a photoelectrode for solar water splitting (e.g. bandgap energy and band edge positions relative to water reduction and oxidation potentials). However, the photoelectrochemical properties of n-type BiFeO 3 have not yet been thoroughly investigated. In our experimental investigation, we developed an electrodeposition-based synthesis to prepare uniform n-type BiFeO 3 thin-film electrodes. Furthermore, using a heat treatment under a N 2 environment, we intentionally introduced additional oxygen vacancies into the pristine n-type BiFeO 3 electrodes to increase the majority carrier density. The bandgaps, flatband potentials, photocurrent onset potentials, photocurrent generation, and photoelectrochemical stabilities of the pristine and N 2 -treated BiFeO 3 photoanodes were investigated comparatively to improve our understanding of BiFeO 3 photoanodes and to examine the effect of oxygen vacancies on the photoelectrochemical properties of BiFeO 3 . In our theoretical investigation, we performed first-principles calculations and demonstrated the formation of a small polaron when an extra electron was introduced into the BiFeO 3 lattice. Changes in electronic states cause by the small polaron formation were carefully investigated. We also examined the effects of oxygen vacancies on electron polaron formation and carrier concentration in BiFeO 3 . Using charge formation energy calculations and referencing charge transition levels to the free electron polaron level instead of to the conduction band minimum, we showed that the oxygen vacancy is capable of serving as a donor to enhance the carrier concentration of BiFeO 3 . Furthermore, our theoretical results agree well with our experimental findings. Together, the new experimental and theoretical results and discussion provided in this study have considerably improved our understanding of n-type BiFeO 3 as a photoanode.

25 ENERGY STORAGE↗
DOE OSTI2023

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

14 SOLAR ENERGY↗
DOE OSTI2025

Improving high temperature resilience of fiber sensor embedded smart components through laser shock peening

This study explores the use of laser shock peening (LSP) to enhance material properties and high-temperature performance of fiber-sensor-fused smart parts fabricated by additive manufacturing (AM) methods. Using embedded fiber sensors as distributed strain gauges, the study demonstrates that LSP can induce compressive strains of up to 130 µε on fiber embedded 1-mm below metal surfaces. The electron backscatter diffraction (EBSD) analysis shows that, with optimized LSP parameters, the metallic matrix undergoes substantial microstructural refinement, resulting in denser structures. Thermal cycling tests showed that the LSP process can increase fiber slippage temperatures by more than 50 °C. This work shows that the LSP process is an effective room-temperature process for enhancing both surface quality and increasing fiber slippage threshold under both thermal and mechanical stress.

Zhong, Shuda [University of Pittsburgh, PA (United↗
DOE OSTI2024

Polymer Nanocomposite Sensors with Improved Piezoelectric Properties through Additive Manufacturing

Additive manufacturing (AM) technology has recently seen increased utilization due to its versatility in using functional materials, offering a new pathway for next-generation conformal electronics in the smart sensor field. However, the limited availability of polymer-based ultraviolet (UV)-curable materials with enhanced piezoelectric properties necessitates the development of a tailorable process suitable for 3D printing. This paper investigates the structural, thermal, rheological, mechanical, and piezoelectric properties of a newly developed sensor resin material. The polymer resin is based on polyvinylidene fluoride (PVDF) as a matrix, mixed with constituents enabling UV curability, and boron nitride nanotubes (BNNTs) are added to form a nanocomposite resin. The results demonstrate the successful micro-scale printability of the developed polymer and nanocomposite resins using a liquid crystal display (LCD)-based 3D printer. Additionally, incorporating BNNTs into the polymer matrix enhanced the piezoelectric properties, with an increase in the voltage response by up to 50.13%. This work provides new insights for the development of 3D printable flexible sensor devices and energy harvesting systems.

42 ENGINEERING↗
DOE OSTI2025

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗
DOE OSTI2020

Kirigami-Inspired Self-Assembly of 3D Structures

Self-assembly of 3D structures introduce an attractive and scalable route to realize reconfigurable and functionally capable mesoscale devices without human intervention. A common approach for achieving this is to utilize stimuli-responsive folding of hinged structures, which requires the integration of different materials and/or geometric arrangements along the hinges. It is also demonstrated that the inclusion of Kirigami cuts in planar, hingeless bilayer thin sheets can be used to produce complex 3D shapes in an on-demand manner. Nonlinear finite element models are developed to elucidate the mechanics of shape morphing in bilayer thin sheets and verify the predictions through swelling experiments of planar, millimeter-scaled PDMS (polydimethylsiloxane) bilayers in organic solvents. Building upon the mechanistic understandings, The transformation of Kirigami-cut simple bilayers into 3D shapes such as letters from the Roman alphabet (to make “ADVANCED FUNCTIONAL MATERIALS”) and open/closed polyhedral architectures is experimentally demonstrated. A possible application of the bilayers as tether-less optical metamaterials with dynamically tunable light transmission and reflection behaviors is also shown. As the proposed mechanistic design principles could be applied to a variety of materials, this research broadly contributes toward the development of smart, tetherless, and reconfigurable multifunctional systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultrafast Metal Electrodeposition Revealed by In Situ Optical Imaging and Theoretical Modeling towards Fast–Charging Zn Battery Chemistry

Metallic Zn is a preferred anode material for rechargeable aqueous batteries towards a smart grid and renewable energy storage. Importantly, understanding how the metal nucleates and grows at the aqueous Zn anode is a critical and challenging step to achieve full reversibility of Zn battery chemistry, especially under fast-charging conditions. Here, by combining in situ optical imaging and theoretical modeling, we uncover the critical parameters governing the electrodeposition stability of the metallic Zn electrode, that is, the competition among crystallographic thermodynamics, kinetics, and Zn 2+ -ion diffusion. Moreover, steady-state Zn metal plating/ stripping with Coulombic efficiency above 99 % is achieved at 10-100 mA cm -2 in a reasonably high concentration (3 M) ZnSO 4 electrolyte. Significantly, a long-term cycling-stable Zn metal electrode is realized with a depth of discharge of 66.7% under 50 mA cm -2 in both Zn || Zn symmetrical cells and MnO 2 || Zn full cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Development and Validation of Smart Building Technology Modules for Academic and Professional Education (Final Technical Report)

Smart building technologies can improve building energy efficiency and resilience, reduce carbon emissions, and provide load flexibility to the grid. However, in both college curricula and building professionals’ continuing education, there is a lack of systematic instruction on smart building technologies. Slipstream, partnering with Texas A&M University (TAMU), the Society of Building Science Educators (SBSE), and the National Institute of Building Sciences (NIBS), developed a semester-long smart building curriculum for college students and 16 training videos for building professionals and the general public. The education and training cover the drivers and benefits of smart building technologies, key building energy systems, the latest sensor technologies and IoT devices, and focus on topics related to smart building controls (i.e., energy management information systems, smart building control platforms, cybersecurity, grid-interactive-efficient buildings [GEBs], smart building control methods, and occupant-centric control). The smart building curriculum for college students was taught at TAMU in the Spring semester of 2024 as part of the validation process. Student feedback was collected and summarized in a validation report by TAMU. The curriculum material was also reviewed by SBSE faculty who are interested in teaching smart building technology-related courses. Suggestions on revisions and better adoption of the materials by other faculty across the architectural, engineering, and construction (AEC) domains were compiled in a distinct validation report by SBSE. The SBSE validation report was used to create structured subsets of the curriculum material for adoption at different levels in different sub-disciplines. These subsets are categorized and offered on the SBSE website (https://www.sbse.org/courses/Smart-Building-Technologies). The 16 training videos for building professionals and the general public were previewed by 17 industry experts, and feedback and suggested changes were incorporated into the final version of these videos. The videos are organized into a smart building technology training course and published on the Whole Building Design Guide website (https://www.wbdg.org/ce/doe/bto/sbtt), which is hosted by the National Institute of Building Sciences (NIBS). Project team members created marketing materials to promote the awareness of these free, publicly available education and training resources. Outreach and marketing activities included creating short promotional videos, building project webpages, making project announcements on social media, conducting an email campaign, and directly reaching out to faculties and building professionals. This report describes the project approach, provides outlines of the training materials, along with links to resources, and identifies lessons learned in creating the content. We also suggest ways to scale the instruction of smart building concepts to empower the workforce to accelerate the adoption of smart building technologies in the real world.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗
DOE OSTI2024

NaSICON-type materials for lithium-ion battery applications: Progress and challenges

Lithium-ion batteries (LIBs) are widely used in electric vehicles, energy storage, smart grids, and portable devices due to their high average output voltage and energy density. NaSICON-type materials have been identified as potential candidates for electrode and solid electrolyte materials for LIBs due to their 3D framework, which contains Li + ions, excellent ionic conductivity, and thermal stability. NaSICON-type materials have a 3D framework and a fast Li + diffusion pathway, making them suitable for use in LIBs. However, their application as solid electrolytes is limited due to poorer ionic conductivity and interfacial stability compared to commercialized liquid electrolytes. Furthermore, their use as electrode materials is restricted by their low electronic conductivity. Here, this review provides an overview of NaSICON-type materials, including their common structure, Li + diffusion mechanism, and preparation strategies. The article also discusses the application and modification strategies of NaSICON-type materials for LIBs, classifying them as anode materials, cathode materials, and solid electrolyte materials. Additionally, the potential use of NaSICON-type materials as modification materials for cathode materials for LIBs is briefly mentioned. Building on previous work on NaSICON-type materials, we propose potential areas for further development and wider applications of these materials in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Low power sensor for NO x detection

Detection and capture of toxic nitrogen oxides (NO x ) is important for emissions control of exhaust gases and general public health. The low power sensor provides direct electrically detection of trace (0.5-5 ppm) NO 2 at relatively low temperatures (50° C.) via changes in the electrical properties of nitrogen-oxide-capture active materials. For example, the high impedance of MOF-74 enables applications requiring a near-zero power sensor or dosimeter, such as for smart industrial systems and the internet of things, with 0.8 mg MOF-74 active material drawing <15 pW for a macroscale sensor 35 mm 2 area.

Small, Leo J.↗
DOE OSTI2021

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Chapter 6 - Polymer and composites additive manufacturing: material extrusion processes

This chapter focuses on material extrusion additive manufacturing (AM) processes for polymers and composite materials. Different extrusion AM platforms, along with their operating mechanism concepts, processing capabilities, and limitations, are discussed here. This chapter also covers state-of-the-art developments in new areas such as hybrid systems, integrated systems, and automation, which facilitate the integration of extrusion-based AM processes into smart manufacturing or Industry 4.0. Following this, a comprehensive discussion on materials development, criteria for successful printing of different materials (thermoplastics, thermosets, and their composites), key factors influencing printing, and material-related challenges in extrusion AM is presented. Finally, a brief overview of current and future potential applications of material extrusion AM technology is provided.

Kishore, Vidya↗