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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 181 records · Page 10

Field Validation of Electrocoagulation Treatment for Oily Wastewater at Cleveland-Cliffs Steel Mill in Cleveland, OH

The Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized technologies in the industrial sector to help inform decisions towards accelerating commercialization and deployment. This initiative aims to identify, validate, and showcase new, emerging, and underutilized technologies in the industrial sector to expedite their commercialization and widespread deployment. By conducting thorough validations and demonstrating the efficacy of these technologies, the ITV program facilitates informed decision-making among industry stakeholders, contributing to the transition towards more sustainable and efficient industrial processes. This ITV demonstration involved the testing of an electrocoagulation (EC) treatment system at a steel plant in Ohio. The system was designed to treat oily wastewater generated from cold rolling operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Response of a high-pressure 4 He scintillation detector to nuclear recoils up to 9 MeV

Helium-4-based scintillation detector technology is emerging as a strong alternative to pulse-shape discrimination-capable organic scintillators for fast neutron detection and spectroscopy, particularly in extreme gamma-ray environments. The 4 He detector is intrinsically insensitive to gamma radiation, as it has a relatively low cross-section for gamma-ray interactions, and the stopping power of electrons in the 4 He medium is low compared to that of 4 He recoil nuclei. Consequently, gamma rays can be discriminated by simple energy deposition thresholding instead of the more complex pulse shape analysis. The energy resolution of 4 He scintillation detectors has not yet been well-characterized over a broad range of energy depositions, which limits the ability to deconvolve the source spectra. In this work, an experiment was performed to characterize the response of an Arktis S670 4 He detector to nuclear recoils up to 9 MeV. The 4 He detector was positioned in the center of a semicircular array of organic scintillation detectors operated in coincidence. Deuterium–deuterium and deuterium–tritium neutron generators provided monoenergetic neutrons, yielding geometrically constrained nuclear recoils ranging from 0.0925 to 8.87 MeV. The detector response provides evidence for scintillation linearity beyond the previously reported energy range. Finally, the measured response was used to develop an energy resolution function applicable to this energy range for use in high-fidelity detector simulations needed by future applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Emerging Rare Earth Element Separation Technologies

Rare earth elements are essential for numerous clean energy applications, yet their mining, separation, and processing pose significant environmental challenges. Traditional separation processes often result in ecological damage, highlighting the critical need for innovative techniques that reduce environmental impacts. This article reviews recent advancements in rare earth separation technologies, with a particular focus on the role of neutral organic compounds. It explores how these compounds change selectivity across the rare earth series, offering promising strategies for designing more effective rare earth element separation systems. Furthermore, the article points out research areas requiring additional investigation to improve the sustainability of these critical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Four–Terminal Perovskite–CdSeTe Tandem Solar Cells: From 25% toward 30% Power Conversion Efficiency and Beyond

Thin-film tandem photovoltaic (PV) technology has emerged as a promising avenue to enhance power conversion efficiency beyond the radiative efficiency limit of single-junction devices. Combining a tunable wide-bandgap perovskite cell with a commercially established narrow-bandgap cadmium selenium telluride (CdSeTe) cell in a comparatively easy-to-fabricate four-terminal (4-T) arrangement is a great step in that direction. Herein, the impact of the transparent back contact and the perovskite absorber bandgap on the performance of 4-T perovskite–CdSeTe tandem solar cells is investigated. 4-T perovskite–CdSeTe tandem device architecture with ≈25% efficiency is demonstrated and a feasible pathway is shown to improve the tandem efficiency to more than 30%. Furthermore, the results show that the integration of CdSeTe with perovskite in 4-T tandem PV configurations represents a significant advancement toward achieving higher efficiency and low-cost tandem PVs.

14 SOLAR ENERGY↗

On the emerging potential of quantum annealing hardware for combinatorial optimization

Abstract Over the past decade, the usefulness of quantum annealing hardware for combinatorial optimization has been the subject of much debate. Thus far, experimental benchmarking studies have indicated that quantum annealing hardware does not provide an irrefutable performance gain over state-of-the-art optimization methods. However, as this hardware continues to evolve, each new iteration brings improved performance and warrants further benchmarking. To that end, this work conducts an optimization performance assessment of D-Wave Systems’ Advantage Performance Update computer, which can natively solve sparse unconstrained quadratic optimization problems with over 5,000 binary decision variables and 40,000 quadratic terms. We demonstrate that classes of contrived problems exist where this quantum annealer can provide run time benefits over a collection of established classical solution methods that represent the current state-of-the-art for benchmarking quantum annealing hardware. Although this work does not present strong evidence of an irrefutable performance benefit for this emerging optimization technology, it does exhibit encouraging progress, signaling the potential impacts on practical optimization tasks in the future.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Iridium-cobalt oxide synthesized via surfactant-assisted Adams fusion for efficient oxygen evolution in acidic and alkaline media

A series of iridium-cobalt (Ir-Co) oxide catalysts were synthesized using a modified surfactant-assisted Adams fusion method and evaluated for the oxygen evolution reaction (OER) in both acidic and alkaline media. The effect of varying the Ir/Co ratio was systematically studied and compared with commercial Ir black and pure IrO 2 samples. The actual elemental ratios were quantified using X-ray photoelectron spectroscopy (XPS), energy-dispersive X-ray spectroscopy (EDS), and inductively coupled plasma-mass spectrometry (ICP-MS). Among the synthesized samples, the Ir 6 Co 4 catalyst exhibited the best performance in acidic media, achieving an iR-corrected overpotential of 292 mV. In alkaline conditions, it demonstrated comparable activity to Ir black, with an iR-corrected overpotential of 263 mV. XPS and electron energy loss spectroscopy analyses revealed that increasing Co content led to a higher fraction of metallic Ir (Ir 0 ) in the catalyst. In addition, the role of Ir 3+ in enhancing OER activity was explored. A strong correlation was observed between higher Ir 3+ content and improved OER performance in acidic conditions.

Adams fusion↗

Coal-derived electrically conductive asphalt pavements for snow/ice melting: From laboratory to field

Timely removal of ice and snow from roads is critical to safe, fast, and uninterrupted transportation networks in cold regions. Constructing electrically conductive asphalt pavements to melt the ice and snow on the roads through resistive eating is an emerging alternative technology to traditional snow/ice removal approaches such as utilizing snowplow machines and deicing chemicals. Carbon-based fibers and fillers including carbon fiber and graphite have been widely reported to make electrically conductive hot mix asphalt mixtures for pavement snow/ice-melting applications. This study aimed to develop and demonstrate a novel type of electrically conductive asphalt pavements for snow/ice-melting, which utilizes electrically conductive cold mix asphalt (CMA) mixtures incorporating coal-derived carbon-based coke aggregate as resistive heating elements. Both laboratory experiments and field tests were conducted to investigate the electrical, mechanical, and thermal properties of such electrically conductive asphalt mixtures and pavements. The laboratory experiment results indicated that the electrically conductive CMA mixtures incorporating coke aggregate had sufficiently high electrical conductivity and satisfactory mechanical performance and the pavement prototype slab utilizing a thin layer of such CMA mixtures could successfully raise the pavement surface temperatures to 8.3–11.7 °C rom a low temperature of –5 °C with an input power density of 473 W/m 2 . The field test results showed that the full-scale coal-derived electrically conductive asphalt pavements were able to increase the pavement surface temperatures when electricity was applied, but the magnitude of temperature increase was highly dependent on the power density. Furthermore, it is promising to use coke aggregate to construct coal-derived electrically conductive asphalt pavements for snow/ice melting.

36 MATERIALS SCIENCE↗

Additive manufacturing of metal matrix composites

Although Metal matrix composites (MMCs) are superior to most sought-after metallic alloys, their challenging fabricability has limited their widespread use in bulk-form applications. Among the many advanced fabrication techniques, Additive Manufacturing (AM), owing to its unique capabilities to produce near-net shapes, has drawn significant traction in the past two decades, especially for materials that are difficult to process using traditional methods. However, unlike pure metal/alloy systems, MMCs are highly sensitive to the processing conditions prevailing in AM techniques due to factors such as the high melting point of reinforcement particles and the potential for in-situ reactions. Therefore, it may be a while before metal matrix composites are commercially produced via AM. This review will discuss the current state-of-the-art design, fabricability, and performance of various additively manufactured MMCs. A particular focus will be on microstructural evolution and microstructure-property relationships. The most employed AM techniques, such as directed energy deposition, powder bed fusion, binder jetting, sheet lamination, and solid-state friction stir processing, are fundamentally different in terms of thermo-kinetics, forming the perspective for this review. A detailed comparison of microstructural evolution and process parameter optimization, including feedstock preparation methods and the role of machine learning and modeling among the different AM processes, is also presented. Finally, a critical evaluation of emerging AM technologies for MMCs is also provided, highlighting their potential advantages and challenges.

36 - MATERIALS SCIENCE↗

Aqueous-based recycling of perovskite photovoltaics

Abstract Cumulative silicon photovoltaic (PV) waste highlights the importance of considering waste recycling before the commercialization of emerging PV technologies 1,2 . Perovskite PVs are a promising next-generation technology 3 , in which recycling their end-of-life waste can reduce the toxic waste and retain resources 4,5 . Here we report a low-cost, green-solvent-based holistic recycling strategy to restore all valuable components from perovskite PV waste. We develop an efficient aqueous-based perovskite recycling approach that can also rejuvenate degraded perovskites. We further extend the scope of recycling to charge-transport layers, substrates, cover glasses and metal electrodes. After repeated degradation–recycling processes, the recycled devices show similar efficiency and stability compared with the fresh devices. Our holistic recycling strategy reduces by 96.6% resource depletion and by 68.8% human toxicity (cancer effects) impacts associated with perovskite PVs compared with the landfill treatment. With recycling, the levelized cost of electricity also decreases for both utility-scale and residential systems. This study highlights unique opportunities of perovskite PVs for holistic recycling and paves the way for a sustainable perovskite solar economy.

Science & Technology - Other Topics↗

Chemical and electrochemical pathways to low-carbon iron and steel

Currently, the iron and steel industry is responsible for 7% of global CO 2 emissions. In this review, we summarize the operational principles of current emissions-intensive steelmaking technologies and review emerging low- and zero-carbon technologies that could substantially reduce emissions. Current technologies that are discussed include blast furnaces, electric arc furnaces, and smelting. Promising low-carbon routes include use of alternative reductants for ore processing (hydrogen direct reduction, hydrogen plasma-smelting, hydrogen smelting, and ammonia-based reduction), electrolytic iron production (with aqueous and molten oxide electrolytes) and biocarbon-based electric arc furnace operation. Advantages of each approach are presented, and remaining research hurdles are identified.

36 MATERIALS SCIENCE↗

High-throughput and data-driven search for stable optoelectronic AMSe 3 materials

The rapid advancement in emerging optoelectronic technologies demands highly efficient, affordable, and ecofriendly materials. In this context, ternary chalcogenides, especially ternary selenides, show early promise as a material class due to their stability and remarkable electronic, optical, and transport properties. In this work, we integrate first-principles-based high-throughput computations with machine learning (ML) techniques to predict the thermodynamic stability and optoelectronic properties of 920 valency-satisfied selenide compounds. Through investigating polymorphism, our study reveals the edge-sharing orthorhombic Pnma phase (NH 4 CdCl 3 -type) as the most stable structure for most ternary selenides. High-fidelity supervised ML models are trained and tested to accelerate stability and band gap predictions. These data-driven models pin down the most influential features that dominantly control key material characteristics. The multistep high-throughput computations identify the ternary selenides with optimal direct band gaps, light carrier masses, and strong optical absorption edges. The extensive materials screening considering phase stability, toxicity, and defect tolerance, finally identifies the seven most suitable candidates for photovoltaic applications. Two of these final compounds, SrZrSe 3 and SrHfSe 3 , have already been synthesized in a single-phase form, with the latter showing an optically suitable band gap, aligning well with our findings. The non-adiabatic molecular dynamics reveal sufficiently long photoexcited charge carrier lifetimes (on the order of nanoseconds) in some of these selected selenide materials, indicating their exciting characteristics. Overall, our study suggests a robust in silico framework that can be extended to screen large datasets of various material classes for identifying promising photoactive candidates.

36 MATERIALS SCIENCE↗

Fault localization in a microfabricated surface ion trap using diamond nitrogen-vacancy center magnetometry

Here, as quantum computing hardware becomes more complex with ongoing design innovations and growing capabilities, the quantum computing community needs increasingly powerful techniques for fabrication failure root-cause analysis. This is especially true for trapped-ion quantum computing. As trapped-ion quantum computing aims to scale to thousands of ions, the electrode numbers are growing to several hundred, with likely integrated photonic components also adding to the electrical and fabrication complexity, making faults even harder to locate. In this work, we used a high-resolution quantum magnetic imaging technique, based on nitrogen-vacancy centers in diamond, to investigate short-circuit faults in an ion trap chip. We imaged currents from these short-circuit faults to ground and compared them to intentionally created faults, finding that the root cause of the faults was failures in the on-chip trench capacitors. This work, where we exploited the performance advantages of a quantum magnetic sensing technique to troubleshoot a piece of quantum computing hardware, is a unique example of the evolving synergy between emerging quantum technologies to achieve capabilities that were previously inaccessible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust quantification of the diamond nitrogen-vacancy center charge state via photoluminescence spectroscopy

Nitrogen vacancy (NV) centers in diamond are at the heart of many emerging quantum technologies, all of which require control over the NV charge state. Hence, methods for quantification of the relative photoluminescence intensities of the NV 0 and NV − charge states, i.e., a charge state ratio, are vital. Several approaches to quantify NV charge state ratios have been reported but are either limited to bulk-like NV diamond samples or yield qualitative results. We propose an NV charge state quantification protocol based on the determination of sample- and experimental setup-specific NV 0 and NV − reference spectra. The approach employs blue (400–470 nm) and green (480–570 nm) excitation to infer pure NV 0 and NV − spectra, which are then used to quantify NV charge state ratios in subsequent experiments via least squares fitting. We test our dual excitation protocol (DEP) for a bulk diamond NV sample and 20 and 100 nm nanodiamond particles and compare results with those obtained via other commonly used techniques such as zero-phonon line fitting and non-negative matrix factorization. We find that DEP can be employed across different samples and experimental setups and yields consistent and quantitative results for NV charge state ratios that are in agreement with our understanding of NV photophysics. By providing robust NV charge state quantification across sample types and measurement platforms, DEP will support the development of NV-based quantum technologies.

Color center laser spectroscopy↗

Are there differences in public interest toward automated vehicles’ ownership in burdened and non-burdened communities?

This study examines differences in public interest toward automated vehicle (AV) adoption between burdened communities (BCs) and non-burdened communities (non-BCs). The study uniquely captures travel behavior by integrating the census tract-level community indicators with the 2017–2019 Puget Sound Household Travel Survey. Public interest in AV ownership is modeled as a five-level ordered outcome, ranging from ‘Not interested at all’ to ‘Very interested.’ Segmented ordered logit models and Random Forest are used to identify key drivers and barriers to AV adoption across BCs and non-BCs. Results show that longer commute times, lack of personal vehicles, and concerns about AV performance in adverse weather conditions are significantly associated with higher interest levels toward owning AVs in BCs. In conclusion, the findings offer insights for developing targeted policies to promote AV adoption and address differences between BCs and non-BCs in accessing emerging transportation technologies.

Automated vehicles↗

Review of solar-enabled desalination and implications for zero-liquid-discharge applications

Abstract The production of freshwater from desalinating abundant saline water on the planet is increasingly considered a climate change adaptation measure. Yet, there are challenges associated with the high cost, intensive energy demand, and environmental implications of desalination. Effective integration of solar energy generation and freshwater production can address both issues. This review article highlights recent key advances in such integration achieved in a joint-research university-national laboratory partnership under the auspices of the United States Department of Energy and parallel efforts worldwide. First, an overview of current and emerging desalination technologies and associated pretreatment, brine treatment, and valorization technologies that together can result in zero-liquid-discharge systems is presented, and their technological readiness levels are evaluated. Then, advanced modeling techniques and new software platforms that enable optimization of solar-desalination applications with the dual objective of cost and environmental impact minimization are discussed.

14 SOLAR ENERGY↗

Quantum Spin Probe of Single Charge Dynamics

Electronic defects in semiconductors form the basis for emerging quantum technologies, but many defect centers are difficult to access at the single-particle level. A method for probing optically inactive spin defects would reveal semiconductor physics at the atomic scale and advance the study of new quantum systems. Here, we exploit the intrinsic correlation between the charge and spin states of defect centers to measure the charge populations and dynamics of single substitutional nitrogen spin defects in diamond. By probing their steady-state spin population, read out at the single-defect level with a nearby nitrogen vacancy center, we directly measure the defect ionization-corroborated by first-principles calculations-an effect we do not have access to with traditional coherence-based quantum sensing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Concept Study of Robotic Camera-Based Foreign Object Detection for EV Wireless Charging

Wireless charging of an electric vehicle (EV) is an emerging charging technology promising convenient, autonomous, and highly efficient EV charging without requiring heavy gauge cables. However, due to the strong electromagnetic field created by this process that surrounds the wireless charger, the presence of foreign objects can detrimentally interact with it, thus affecting wireless power transfer (WPT) performance or leading to harmful and unwanted safety risks. This paper presents the results for a concept study on a robotic camera-based foreign object detection (FOD) system, as a supplement to the industry-existing overlapped FOD coil array method, for EV wireless charging. A Raspberry PI 4 control board and compatible Raspberry PI Camera Module 2 are used to implement camera-based object detection. The FOD program was developed using a state-of-the-art deep learning object detection model with the OpenCV and Pytorch library and is compatible with camera module hardware. A dry-run test with Raspberry PI and a camera module was conducted and the preliminary FOD function was verified. The feasibility assessment is also validated by comparing the performance of five existing state-of-the-art deep learning object detection models for vehicles, animals, persons, and metals subsets, respectively. Satisfactory performance on the benchmark datasets is observed by the tests, but further improvements are needed in future work when detecting small-sized metallic objects. A programable robotic car is also under development as ongoing work for carrying the Raspberry PI and camera module while moving for the maintenance process.

24 POWER TRANSMISSION AND DISTRIBUTION↗