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Results for “PERSPECTIVE”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sustainability perspectives of integrated pulp and paper biorefineries – A systematic critical review

As the pulp and paper industry is impacted by changing product demand trends, an opportunity arises to utilize existing pulp and paper mills (PPMs) and byproduct biomass to produce a wide range of value-added products, i.e., by converting existing PPMs into integrated pulp and paper biorefineries (IPPBs), a form of industrial symbiosis. In addition to the conventional products that a pulp and paper mill produces, IPPBs produce bio-based products that can help generate a new income stream. This paper provides a systematic critical review of IPPBs with a focus on the types of IPPBs and sustainability perspectives. Specifically, this review's objective is to identify and discuss current and emerging types of IPPBs, provide insights into the types of value-added products produced, and the opportunities and barriers they have according to published literature. We reviewed 97 articles and proposed a robust definition for IPPBs. The results show that there is a dominance of studying bioethanol as the main value-added product and black liquor as one of the main feedstocks. Additionally, we found that there are different types of market challenges for bioproducts depending on the conventional product being replaced and that location and policies play a crucial role. This review identified the limited sustainability focus on this topic and the crucial need to invest in new research to more thoroughly cover the environmental, economic, and social impacts of IPPBs.

Biorefinery pathways↗
DOE OSTI2026

Full-scale validation gaps and opportunities for low-head hydropower: a review and perspective

Hydropower is undergoing technological innovation as future development increasingly targets low-head sites (<10 m), primarily through retrofits, rehabilitation, and upgrades of existing infrastructure. This shift toward smaller systems creates a timely opportunity: unlike conventional large projects, many emerging low-head technologies may be small enough for direct full-scale validation. Full-scale testing is particularly important for environmental mitigation technologies, including fish passage, sediment continuity, and water-quality improvements, whose performance is difficult to assess reliably using reduced-scale models. Yet adoption remains constrained by the limited risk-bearing capacity of small hydropower owners, discouraging manufacturers from bringing unvalidated technologies to market. This review and perspective paper examines hydropower trends driving innovation, selected emerging technologies, conventional testing methods, and current U.S. testing capabilities as a case study. We then evaluate the gap between existing capabilities and the needs of low-head powertrains and environmental mitigation measures. Many technologies exceed existing facility flow capacities; in the U.S., the highest combined head–flow capability is limited to 5.66 m3/s, compared with median and 90th-percentile low-head turbine-unit flows of 14.3 and 60 m3/s. To mitigate this gap, we advocate repurposing large, retired, or underused hydraulic infrastructure as full-scale testing facilities to reduce first-adoption risk and support sustainable low-head hydropower deployment.

Tseng, Chien-Yung [Colorado State University, Fort↗
DOE OSTI2025

Perspective on Many-Body Methods for Molecular Polaritonic Systems

Recent advances in strong light–matter interactions have revealed a wealth of new physical phenomena in molecules embedded in optical cavities, including modified chemical reactivity, altered excitation spectra, and novel quantum correlations. To describe these effects from first-principles, the field of ab initio quantum electrodynamics (QED) has emerged as a compelling extension of quantum chemistry that treats electronic and photonic degrees of freedom on equal footing. In this Perspective, we review the growing landscape of many-body QED methods, including Hartree–Fock, density functional theory (QEDFT), time-dependent DFT (QED-TDDFT), configuration interaction (QED-CI), complete active space (QED-CASSCF), coupled cluster (QED-CC), quantum Monte Carlo (QED-QMC), and density matrix renormalization group (QED-DMRG), highlighting recent developments and implementations. We further explore real-time methods, gradient and Hessian formalisms, and the integration of nonadiabatic nuclear dynamics. Applications range from benchmark simulations of polaritonic chemistry to quantum simulations on emerging quantum hardware. We conclude by outlining future directions for theory development and interdisciplinary efforts at the interface of quantum chemistry, condensed matter, and quantum optics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Challenge of Characterizing High-Concentration Electrolytes at the Molecular Level: A Perspective

High-concentration electrolytes (HCEs) are promising materials composed of highly concentrated salt solutions in organic solvents. HCEs have many desirable properties and are particularly important in the field of batteries. However, the number of ways in which these materials can be tuned is very large, which is crucial for tailored electrolyte design. Moreover, the molecular characterization of HCEs is challenging both experimentally and computationally, but it is necessary for their rational design. Therefore, currently the structure–property–performance relationship of these electrolytes has not been directly derived from their characterization. Here, in this Perspective, we present a brief overview of the HCEs and discuss the state-of-the-art characterization methods used to study them at the molecular level. We also address the challenges associated with these methods, including both experimental techniques and computational tools currently available. Emphasis is placed on methods aimed at understanding the physical phenomena that govern the molecular structure and dynamics occurring on the subnanosecond and nanometer time and length scales. Finally, we discuss new strategies for obtaining a comprehensive characterization of HCEs at the molecular level.

electrolytes↗
DOE OSTI2025

A Perspective into Operando Methods for Probing Catalytic Interfaces

Rational design of electrocatalysts for (photo)electrochemical (PEC) processes like hydrogen and oxygen evolution and CO2 reduction reactions is aided by the recent improvements in capabilities of operando measurements, where morphology, composition, and/or function are probed during active catalysis. Through operando microscopy and spectroscopy, structure, catalytic microenvironment, oxidation state, adsorbates, and products can be measured to gain a better understanding of catalyst behavior and suggest possible improvements. Visualizing evolving catalyst morphologies, surface compositions, and electrochemical behavior also helps address many fundamental research questions for a better understanding of catalytic mechanisms. Correlating morphology with chemical identity or functional behavior using a variety of innovative microscopy methods is particularly promising for guiding development of next generation catalysts, and there are also many recent examples of using AI and robotics tools to innovate and speed development. In this Perspective, advances made over the past few years in operando imaging of catalysts relevant to solar fuels will be explored, followed by an outlook on technological developments in instrumentation, sample design, and computational power that may be applied to this field.

Catalysts↗
DOE OSTI2026

Designing Thermomechanically Stable Nanocrystalline Alloys for Low Friction and Wear: A Perspective

In this Perspective, we discuss recent work and future trends on the usage of thermomechanically stable and selflubricating nanocrystalline (NC) alloys for low friction and wear applications. The theoretical underpinnings and mechanistic framework for attaining and maintaining low friction and wear in metal contacts are presented. Initial work on stress, time, and temperature-dependent changes in friction and wear in NC alloys validates the models, demonstrating lower friction from decreased interfacial strength, contact pressure, sliding speed, and temperature and increased roughness and material hardness. Subsequent work reveals that NC Pt−Au, metal nitrides, complex-concentrated, and high-entropy alloys come with additional stabilization factors such as low-friction carbon tribofilms and oxide/amorphous−crystalline layers but are still susceptible to destabilization factors including irradiation and adverse environmental conditions.

alloys↗
DOE OSTI2025

Evolution of Mass Spectrometers for High m / z Biological Ion Formation, Transmission, Analysis and Detection: A Personal Perspective

Mass spectrometry (MS) has become an essential tool in virtually all academic, pharmaceutical, and biopharmaceutical analytical laboratories. The specialized and bespoke area of MS research and application of high m / z ion (> m / z 6000 and high mass, >150 kDa) formation, transmission, analysis, and detection is a relatively new area of focus for MS that has seen dramatic acceleration in interest over the last two decades. Herein we delve into this exciting aspect of MS, discussing how MS instrumentation has been refined and evolved for native-MS analysis. We cover the early groundbreaking experiments showing high m / z ion formation, transmission, and preservation of protein structure in the gas phase. Additionally, we discuss specific instrument optimizations and modifications that have advanced high m / z ion generation, transmission, analysis, and detection, contributing to the research area known as gas-phase structural biology. Native-MS sample introduction methods, emerging technologies, and future perspectives are also examined. Finally, we share personal opinions, observations, and experiences that are new to the community or previously unpublished.

collisions↗
DOE OSTI2025

Early Career Perspectives to Broaden the Scope of Critical Zone Science

Abstract Critical Zone (CZ) scientists have advanced understanding of Earth's surface through process‐based research that quantifies water, energy, and mass fluxes in predominantly undisturbed systems. However, the CZ is being increasingly altered by humans through climate and land use change. Expanding the scope of CZ science to include both human‐ and non‐human controls on the CZ is important for understanding anthropogenic impacts to Earth's surface processes and ecosystem services. Here, we share perspectives from predominantly U.S.‐based, early career CZ scientists centered around broadening the scope of CZ science to focus on societally relevant science through a transdisciplinary science framework. We call for increased training on transdisciplinary methods and collaboration opportunities across disciplines and with stakeholders to foster a scientific community that values transdisciplinary science alongside physical science. Here, we build on existing transdisciplinary research frameworks by highlighting the need for institutional support to include and educate graduate students throughout the research processes. We also call for graduate‐student‐led initiatives to increase their own exposure to transdisciplinary science through activities such as transdisciplinary‐focused seminars and symposiums, volunteering with local conservation groups, and participating in internships outside academia.

Warix, Sara [University of Utah Department of Geol↗
DOE OSTI2025

Perspectives on Systematic Cloud Microphysics Scheme Development With Machine Learning

Cloud microphysics—the collection of processes that govern the small‐scale formation, evolution, and interactions of liquid droplets and ice crystals in clouds and precipitation—remains a major source of uncertainty in weather and climate models. Although too small in scale to be explicitly resolved in any large‐eddy simulation, weather, or climate model, the representation of cloud microphysical processes has significant impact at the climate scale. Current microphysical schemes are limited by both parametric uncertainty, linked to uncertainty in physical parameter values, and structural uncertainty, arising from incomplete physical understanding of the processes at play or approximations made for computational efficiency. Recent advances in the application of machine learning (ML) to the physical sciences show significant potential for minimizing these limitations by leveraging high‐fidelity simulations and observations. Here we outline the challenges that must be addressed to apply ML toward cloud microphysics scheme development. This perspectives paper synthesizes recent progress in using data‐driven methods, including ML, to improve cloud microphysics parameterizations and highlights opportunities to address key uncertainties. We discuss the roles of aleatoric (irreducible, or statistical) and epistemic (reducible, or systematic) errors in contributing to microphysics parameterization uncertainty. ML can leverage observations to improve microphysical schemes via bottom‐up and top‐down constraints. Methods such as differentiable programming and ML‐enhanced sampling strategies and the creation of large scale benchmark data sets promise to bridge the gap between observations and models and to improve the consistency of cloud microphysical representation across temporal and spatial scales.

Lamb, Kara D. [Columbia Univ., New York, NY (Unite↗
DOE OSTI2025

Global and regional perspectives on optimizing thermo-responsive dynamic windows for energy-efficient buildings

Architectural thermo-responsive dynamic windows offer an autonomous solution for solar heat regulation, thereby reducing building energy consumption. Previous work has emphasized the significance of thermo-responsive windows in hot climates due to their role in solar heat control and subsequent energy conservation; conversely, our study provides a different perspective. Through a global-scale analysis, we explore over 100 material samples and execute more than 2.8 million simulations across over two thousand global locations. World heatmap results, derived from well-trained artificial neural network models, reveal that thermo-responsive windows are especially useful in climates where buildings demand both heating and cooling energy, whereas thermo-responsive windows with optimal transition temperatures show no dynamic features in most of low-latitude tropical regions. Additionally, this study provides a practical guideline and an open-source mapping tool to optimize the intrinsic properties of thermo-responsive materials and evaluate their energy performance for sustainable buildings at various geographical scales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

An economic perspective of the circular bioeconomy in the food and agricultural sector

Transforming the agri-food system from a “take-make-waste”, or linear production system, to a circular bioeconomy that reduces, recycles, recovers, reuses, and regenerates wastes and transitions from fossil to biobased fuels and products is being hailed as critical for meeting a growing population’s food and fuel needs in environmentally sustainable ways. While a transformation towards a circular bioeconomy is an appealing strategy to achieve multiple environmental goals, we argue that this strategy needs to go beyond a techno-centric focus and adopt an economic value-based lens to balance the desire for circularity with its costs, benefits, and distributional effects on society. This perspective analyzes the mechanisms that sustain the existing linear economy and proposes a novel social cost-benefit framework to determine the optimal level and path to circularity. We present five critical pathways to achieve a sustainable circular bioeconomy in a market economy consisting of decentralized decision-makers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Demonstration of and future perspective on scaling ultrafast-laser-ablation microstructuring of Li-ion battery electrodes to roll-to-roll production and large-format cells

This work demonstrates integration of an ultrafast laser onto a roll-to-roll machine, the laser structuring of a double-sided, 700 m long roll of graphite battery anode and its subsequent manufacture into 27 Ah prismatic cells. The electrode was ablated with a novel hybrid-microstructure composed of both hexagonally arranged pores for enhanced rate performance and channels for fast electrolyte wetting. Subsequently, this anode and a non-ablated baseline anode are paired with an NMC111 cathode for cell building and electrochemical characterization. Compared to the baseline, laser ablated cells demonstrated a reduction in soaking time of at least 60%, an improvement in fast charge capability with >30% more capacity accepted during 6C charging, and an extension of cycle life of >40% during 0.5C cycling. Further, a perspective is provided on scaling ultrafast laser ablation of battery electrodes to industrial throughputs. Additionally, lessons learned from this pilot-scale demonstration are provided in regards to optical architecture, debris removal, and system control. A techno-economic analysis is used to demonstrate that laser ablation can be integrated into existing electrode manufacturing facilities with only ≈$\$$1.3 per kWh increase (≈2%) in manufacturing cost. Preemptive electrode design for laser ablation is discussed as a further method for enhancing performance. Finally, an analysis of available laser systems and beam-scanning architectures is used to determine design requirements to scale process throughput to a state-of-the-art speed of 50 m min −1 . This analysis demonstrates that laser ablating Li-ion battery electrodes has multiple benefits to manufacturing and battery performance, that the technology already exists to achieve high laser-ablation throughputs, and that integrating ultrafast laser ablation to electrode manufacturing will not create a cost or processing bottleneck.

25 ENERGY STORAGE↗
DOE OSTI2025

Perspectives of active Si photonics devices for data communication and optical sensing

Si photonics has made rapid progress in research and commercialization in the past two decades. While it started with electronic–photonic integration on Si to overcome the interconnect bottleneck in data communications, Si photonics has now greatly expanded into optical sensing, light detection and ranging (LiDAR), optical computing, and microwave/RF photonics applications. From an applied physics point of view, this perspective discusses novel materials and integration schemes of active Si photonics devices for a broad range of applications in data communications, spectrally extended complementary metal–oxide–semiconductor (CMOS) image sensing, as well as 3D imaging for LiDAR systems. We also present a brief outlook of future synergy between Si photonic integrated circuits and Si CMOS image sensors toward ultrahigh capacity optical I/O, ultrafast imaging systems, and ultrahigh sensitivity lab-on-chip molecular biosensing.

electronic band structure↗
DOE OSTI2025

Advancing microelectronics through nanoscale science: A perspective on needs and opportunities from the nanoscale science research centers

Microelectronics are the cornerstone of the modern world, enhancing our daily lives by providing services such as communications and datacenters. These resources are accessible thanks to the continual pursuit of a deeper understanding of the chemical and physical phenomena underlying the materials synthesis approaches and fabrication processes used to create microelectronic components and subsequently the components' responses to electrical, optical, and other stimuli that are utilized within microelectronic systems. Today, further development of microelectronics requires multidisciplinary expertise across scientific disciplines and fields of study—synthesis, materials characterization, nanoscale fabrication, and performance characterization—with focus placed on comprehending the nanoscale forms and features of microelectronic components. The Nanoscale Science Research Centers (NSRCs) are Department of Energy, Office of Science user facilities that support the international scientific community in advancing nanoscale science and technology. As a key component of the U.S. Government's National Nanotechnology Initiative, the NSRCs enable transformative discoveries by providing world-class facilities, expertise, and collaborative opportunities. Here, in this perspective, we showcase a non-exhaustive cross-section of the capabilities housed at and developed by the NSRCs and their user communities to address fundamental synthesis, metrology, fabrication, and performance considerations toward advancing the development of new microelectronics. Finally, we provide a timely outlook on the next major areas of necessary development in nanoscale sciences to continue the innovation of microelectronics into the next generation.

2D materials↗
DOE OSTI2026

Perspective of Fermi’s golden rule and its generalizations in chemical physics

This perspective provides a succinct history of Fermi’s golden rule (FGR), an overview of its derivation, assumptions, and representative forms. Major applications of FGR, mostly in the field of chemical physics, are reviewed. These illustrate the broad applicability and success of FGR. Ambiguities and open issues encountered in practical applications of FGR are clarified. Recent advances in generalizations of FGR and computational methods for practical applications are addressed.

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

Circuit complexity and functionality: A statistical thermodynamics perspective

Circuit complexity, defined as the minimum circuit size required for implementing a particular Boolean computation, is a foundational concept in computer science. Determining circuit complexity is believed to be a hard computational problem. Recently, in the context of black holes, circuit complexity has been promoted to a physical property, wherein the growth of complexity is reflected in the time evolution of the Einstein-Rosen bridge (“wormhole”) connecting the two sides of an anti-de Sitter “eternal” black hole. Here, we are motivated by an independent set of considerations and explore links between complexity and thermodynamics for functionally equivalent circuits, making the physics-inspired approach relevant to real computational problems, for which functionality is the key element of interest. In particular, our thermodynamic framework provides an alternative perspective on the obfuscation of programs of arbitrary length—an important problem in cryptography—as thermalization through recursive mixing of neighboring sections of a circuit, which can be viewed as the mixing of two containers with “gases of gates.” This recursive process equilibrates the average complexity and leads to the saturation of the circuit entropy, while preserving functionality of the overall circuit. The thermodynamic arguments hinge on ergodicity in the space of circuits which we conjecture is limited to disconnected ergodic sectors due to fragmentation. The notion of fragmentation has important implications for the problem of circuit obfuscation as it implies that there are circuits of same size and functionality that cannot be connected via a polynomial number of local moves. Furthermore, we argue that fragmentation is unavoidable unless the complexity classes NP and coNP coincide, a statement that implies the collapse of the polynomial hierarchy of computational complexity theory to its first level.

Science & Technology - Other Topics↗
DOE OSTI2026

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗