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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Zero Liquid Discharge and Water Reuse in Recirculating Cooling Towers at Power Facilities: Review and Case Study Analysis

Zero liquid discharge (ZLD) systems installed at power facilities with the primary purpose of meeting water discharge regulations have the added benefit of providing high quality effluent that can be reused in the facility. This paper provides a review of water use in power sector recirculating cooling towers and a baseline assessment of on-site water reuse at natural gas combined cycle (NGCC) power facilities. Two NGCC facilities with reverse-osmosis (RO) or brine-concentrator processes followed by evaporation ponds were selected as case studies; data from these facilities were used to quantify the water, energy, and cost implications of implementing conventional and emerging ZLD technologies. At one case study facility, model results show that implementation of ZLD would reduce water withdrawals by 18%, which is less than savings associated with implementation of dry cooling but comparable to current efforts to reduce water withdrawals by increasing cycles of concentration. Implementation of ZLD using high-recovery RO resulted in a doubling of the levelized cost of water (LCOW). LCOW increased more when a brine concentrator was used. For both case studies, the ZLD system using high-recovery RO required less than 0.1% of a facilitiy's annual electricity generation and the ZLD system using a brine concentrator process required less than 0.8%. Additionally, increasing the evaporation pond area to minimize required ZLD system recovery rates and reduce system electricity costs does not reduce the LCOW. Instead, the LCOW increases because less water is recovered and more water is lost to evaporation. Furthermore, if water availability decreases or water competition/cost increases, facilities may be incentivized to maximize water recovery from ZLD systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Chapter 4: Chemical Recycling of PET

The circular economy of poly(ethylene terephthalate) (PET) today is dominated by collection, sorting, cleaning, melting, and re-processing of transparent bottles via mechanical recycling. This has a better environmental impact as assessed by Life Cycle Assessment (LCA) (e.g. uses less non-renewable energy and produces less greenhouse gases) than production of virgin resin and is the preferred method of recycling wherever possible. However, not all PET products can be recycled this way and there is forecast to be a large shortfall between supply of high quality recycled PET (rPET) and the demands of large users who have made commitments to use more recycled resin over the next 5 - 10 years. Consequently, there is renewed interest, and increased activity, in chemical recycling, where waste PET is depolymerized, and the monomer(s) are purified and repolymerized into resin equivalent to that from petroleum-derived raw materials. The LCA is likely to be not as favorable as traditional mechanical recycling, but will likely be better than virgin PET and the process can be applied to a broader range of lower value wastes and thus promises to dramatically increase the overall recycling rate. In this chapter we will review the processes used in chemical recycling of PET, with the VolCat process from IBM as a detailed case study, followed by descriptions of the alternative technologies and emerging players in the field.

chemical recycling↗
DOE OSTI2020

Nanoscale-femtosecond dielectric response of Mott insulators captured by two-color near-field ultrafast electron microscopy

Characterizing and controlling the out-of-equilibrium state of nanostructured Mott insulators hold great promises for emerging quantum technologies while providing an exciting playground for investigating fundamental physics of strongly-correlated systems. Here, we use two-color near-field ultrafast electron microscopy to photo-induce the insulator-to-metal transition in a single VO 2 nanowire and probe the ensuing electronic dynamics with combined nanometer-femtosecond resolution (10 –21 m • s). We take advantage of a femtosecond temporal gating of the electron pulse mediated by an infrared laser pulse, and exploit the sensitivity of inelastic electron-light scattering to changes in the material dielectric function. By spatially mapping the near-field dynamics of an individual nanowire of VO 2 , we observe that ultrafast photo-doping drives the system into a metallic state on a timescale of ~150 fs without yet perturbing the crystalline lattice. Due to the high versatility and sensitivity of the electron probe, our method would allow capturing the electronic dynamics of a wide range of nanoscale materials with ultimate spatiotemporal resolution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

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↗
DOE OSTI2021

Computational design of quantum defects in two-dimensional materials

We report missing atoms or atom substitutions (point defects) in crystal lattices in two-dimensional (2D) materials are potential hosts for emerging quantum technologies, such as single-photon emitters and spin quantum bits (qubits). First-principles-guided design of quantum defects in 2D materials is paving the way for rational spin qubit discovery. Here we discuss the frontier of first-principles theory development and the challenges in predicting the critical physical properties of point defects in 2D materials for quantum information technology, in particular for optoelectronic and spin-optotronic properties. Strong many-body interactions at reduced dimensionality require advanced electronic structure methods beyond mean-field theory. The great challenges for developing theoretical methods that are appropriate for strongly correlated defect states, as well as general approaches for predicting spin relaxation and the decoherence time of spin defects, are yet to be addressed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

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↗
DOE OSTI2020

Bipolar membrane polarization behavior with systematically varied interfacial areas in the junction region

The palette of applications for bipolar membranes (BPMs) has expanded recently beyond electrodialysis as they are now being considered for fuel cell and electrolysis applications. Their deployment in emerging electrochemical technologies arises from the need to have a membrane separator that provides disparate pH environments and to prevent species crossover. Most materials research for BPMs has focused on water dissociation catalysts and less emphasis has been given to the design of the polycation–polyanion interface for improving BPM performance. Here, soft lithography fabricated a series of micropatterned BPMs with precise control over the interfacial area in the bipolar junction. Polarization experiments showed that a 2.28× increase in interfacial area led to a 250 mV reduction in the onset potential. Additionally, the same increase in interfacial area yielded marginal improvements in current density due to the junction region being under kinetics-diffusion control. A simple physics model based on the electric field of the junction region rationalized the reduction in the overpotential for water dissociation as a function of interfacial area. Finally, the soft lithography approach was also conducive for fabricating BPMs with different chemistries ranging from perfluorinated polymer backbones to alkaline stable poly(arylene) hydrocarbon polymers. These polymer chemistries are better suited for fuel cell and electrolysis applications. The BPM featuring the alkaline stable poly(terphenyl) anion exchange membrane had an onset potential of 0.84 V, which was near the thermodynamic limit, and was about 150 mV lower than a commercially available variant.

25 ENERGY STORAGE↗
DOE OSTI2025

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↗
DOE OSTI2023

Photophysics in emerging photovoltaics

Emerging photovoltaic technologies continue to march forward with power conversion efficiencies of lead halide perovskite solar cells (PSCs) nearing 26%, perovskite-Si tandems now exceeding the single junction detailed balance limit of 33%, and organic solar cells (OSCs) showing efficiencies nearing 20%. Yet, some of the photophysics underpinning PSCs and OSCs remain unresolved. A better understanding will enable more efficient and photostable solar cells and optoelectronic devices in the future. Here, this special issue collects the latest cutting-edge research in the photophysics of PSCs and OSCs, contributed by experts on spectroscopy, theory, device physics, and materials science.

14 SOLAR ENERGY↗
DOE OSTI2023

A novel approach to interface high-Q Fabry–Pérot resonators with photonic circuits

The unique benefits of Fabry–Pérot resonators as frequency-stable reference cavities and as an efficient interface between atoms and photons make them an indispensable resource for emerging photonic technologies. To bring these performance benefits to next-generation communications, computation, and time-keeping systems, it will be necessary to develop strategies to integrate compact Fabry–Pérot resonators with photonic integrated circuits. In this paper, we demonstrate a novel reflection cancellation circuit that utilizes a numerically optimized multi-port polarization-splitting grating coupler to efficiently interface high-finesse Fabry–Pérot resonators with a silicon photonic circuit. This circuit interface produces a spatial separation of the incident and reflected waves, as required for on-chip Pound–Drever–Hall frequency locking, while also suppressing unwanted back reflections from the Fabry–Pérot resonator. Using inverse design principles, we design and fabricate a polarization-splitting grating coupler that achieves 55% coupling efficiency. This design realizes an insertion loss of 5.8 dB for the circuit interface and more than 9 dB of back reflection suppression, and we demonstrate the versatility of this system by using it to interface several reflective off-chip devices.

Optics↗
DOE OSTI2024

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↗
DOE OSTI2025

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↗
DOE OSTI2025

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↗
DOE OSTI2022

On-policy learning-based deep reinforcement learning assessment for building control efficiency and stability

Artificial intelligence technologies have emerged as a game changer not only in specific applications such as image recognition and machine translation but also in many scientific domains. In particular, as deep reinforcement learning (DRL) has shown great success in complex control problems, DRL-based control has been considered as a potential solution to efficiently control and manage building systems. However, broad assessment of DRL-based building control is still required to characterize their pros and cons in comparison with conventional building control methods (e.g., rule-based feedback controls). In this paper, we assessed DRL-based controls with on-policy learning-based algorithms and continuous control actions for cooling control of large office buildings in the summer season to minimize whole-building energy use and occupant discomfort. We compared DRL-based control methods with two baseline control methods: (1) a pre-determined schedule with supply temperature and static pressure setpoints, and (2) advanced reset method that adjusts setpoints based on heuristic rules, i.e., ASHRAE Guideline 36. We also tested the DRL algorithms to evaluate their performances in multiple climate locations. We found that DRL-based control methods outperformed the baseline control methods in terms of energy savings while maintaining a thermal comfort. DRL reduced energy use between ~4%–22% on average compared to the baseline methods, depending on climate location. We also evaluated DRL-based control in terms of control stability and showed that DRL-based methods should address the span of hardware lifetimes in practical operations.

control stability↗
DOE OSTI2021

Bilinear dynamic mode decomposition for quantum control

Abstract Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems and desired control objectives are critical for many emerging quantum technologies. We develop a data-driven regression procedure, bilinear dynamic mode decomposition (biDMD), that leverages time-series measurements to establish quantum system identification for QOC. The biDMD optimization framework is a physics-informed regression that makes use of the known underlying Hamiltonian structure. Further, the biDMD can be modified to model both fast and slow sampling of control signals, the latter by way of stroboscopic sampling strategies. The biDMD method provides a flexible, interpretable, and adaptive regression framework for real-time, online implementation in quantum systems. Further, the method has strong theoretical connections to Koopman theory, which approximates nonlinear dynamics with linear operators. In comparison with many machine learning paradigms minimal data is needed to construct a biDMD model, and the model is easily updated as new data is collected. We demonstrate the efficacy and performance of the approach on a number of representative quantum systems, showing that it also matches experimental results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Roadmap on commercialization of metal halide perovskite photovoltaics

Perovskite solar cells (PSCs) represent one of the most promising emerging photovoltaic technologies due to their high power conversion efficiency. However, despite the huge progress made not only in terms of the efficiency achieved, but also fundamental understanding of the relevant physics of the devices and issues which affect their efficiency and stability, there are still unresolved problems and obstacles on the path toward commercialization of this promising technology. In this roadmap, we aim to provide a concise and up to date summary of outstanding issues and challenges, and the progress made toward addressing these issues. While the format of this article is not meant to be a comprehensive review of the topic, it provides a collection of the viewpoints of the experts in the field, which covers a broad range of topics related to PSC commercialization, including those relevant for manufacturing (scaling up, different types of devices), operation and stability (various factors), and environmental issues (in particular the use of lead). We hope that the article will provide a useful resource for researchers in the field and that it will facilitate discussions and move forward toward addressing the outstanding challenges in this fast-developing field.

36 MATERIALS SCIENCE↗
DOE OSTI2024

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↗