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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Studies of Particle Acceleration, Transport and Radiation in Impulsive Phase of Solar Flares

Solar activity and its most prominent aspect, the solar flares, have considerable influence on terrestrial and space weather. Solar flares also provide a suitable laboratory for the investigation of many plasma and high energy processes important in the magnetosphere of the Earth and many other space and astrophysical situations. Hence, progress in understanding of flares will have considerable scientific and societal impact. The primary goal of this grant is the understanding of two of the most important problems of solar flare physics, namely the determination of the energy release mechanism and how this energy accelerates particles. This is done through comparison of the observations with theoretical models, starting from observations and gradually proceeding to theoretically more complex situations as the lower foundations of our understanding are secured. It is generally agreed that the source of the flare energy is the annihilation of magnetic fields by the reconnection process. Exactly how this energy is released or how it is dissipated remains controversial. Moreover, the exact mechanism of the acceleration of the particles is still a matter of debate. Data from many spacecrafts and ground based instruments obtained over the past decades have given us some clues. Theoretical analyses of these data have led to the standard thick target model (STT) where most of the released energy goes into an (assumed) power law spectrum of accelerated particles, and where all the observed radiations are the consequence of the interaction of these particles with the flare plasma. However, some theoretical arguments, and more importantly some new observations, have led us to believe that the above picture is not complete. It appears that plasma turbulence plays a more prominent role than suspected previously, and that it is the most likely agent for accelerating particles. The model we have developed is based on production of a high level of plasma waves and turbulence in the reconnection region above a flare loop. This turbulence accelerates particles stochastically which radiate some of their energy in this region but carry most of their energy to the footpoints of the loop, where they lose all their energy and radiate bulk of the observed radiation as in the traditional thick target model. In the past we have worked on various aspects of this model. We have evaluated the interaction rates of the plasma waves with electrons and ions, developed theoretical frameworks for the acceleration, transport and radiative processes, and produced numerical codes for the investigation of these processes. The goal of this grant has been further development and testing of this new paradigm, with emphases on the relative acceleration of electrons and ions and on a comprehensive investigation of the turbulence generation, cascade, and damping processes. We review several pieces of important evidence that we have uncovered indicating the crucial roles of turbulence, in and we describe accomplishments during the past two years of this grant.

Petrosian, Vahe↗
DOE OSTI2024

Paradigm for approaching the forbidden phase transition in the one-dimensional Ising model at fixed finite temperature: Single chain in a magnetic field

In a previous paper, the forbidden spontaneous phase transition in the one-dimensional Ising model was found to be approachable arbitrarily closely in decorated ladders by ultra-narrow phase crossover (UNPC) at a given finite temperature T 0 with the crossover width 2δT reduced exponentially, which resemble a genuine first-order transition with large latent heat. Here, I reveal that the forbidden phase transition can be approached at fixed T 0 as well in decorated single-chain Ising models in the presence of a magnetic field, in which T 0 is determined by the interactions involving only the decorated parts and the magnetic field, while 2δT is independently, exponentially reduced (δT = 0 means a genuine transition) by restoring the ferromagnetic interaction between the ordinary spins on the chain backbone-which was neglected in the previous studies of pseudo-transition-thus manifesting that this asymptoticity to the forbidden transition is essentially the buildup of coherence in preformed crossover of local states. Furthermore, I show that the UNPC can be realized even in the absence of the conventional geometric frustration because the magnetic field itself can induce previously unnoticed hidden spin frustration. In conclusion, these findings make the doors wide open to the engineering and utilization of UNPC as a new paradigm for exploring exotic phenomena and 1D device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2018

System-of-Systems Tools for the Analysis of Technological Choices in Space Propulsion

Difficulties in space mission architecture design arise from many factors. Performance, cost, and risk constraints become less obvious due to complex interactions between the systems involved in the mission; decisions regarding long-term goals can heavily impact technological choices for short-term parts of the mission, while conversely decisions in the near future will impact the whole flexibility of long-term plans. Furthermore, the space community is broadening its borders, and space agencies from different countries are collaborating with industry and commercial partners towards large-scale endeavors. This paradigm shift is prompting the development of non-traditional approaches to the design of space missions. This paper reports the results of the first year of a continuing collaboration of the authors to develop and demonstrate System-of-System engineering methodologies for the deep analysis of dependencies and synthesis of robust architectures in exploration mission contexts. We present the procedure that we followed to develop and apply our methodology, obstacles found, steps taken to improve the methods based on the needs of experts and decision makers, required data for the analysis, and results produced by our holistic analysis. In particular, we focus on the analysis of technological choices for space propulsion for a generic cislunar mission, including both complex interactions between subsystems in different type of propulsion and availability of different providers. We identify critical systems and sets of systems based on cascading effects of performance degradation, assessment of the robustness of different designs in the operational domain, and simultaneous analysis of schedule dependencies between the constituent systems.

Guariniello, Cesare↗
NASA NTRS1982

Paradigm transition in cosmic plasma physics

New discoveries in cosmic plasma physics are described, and their applications to solar, interstellar, galactic, and cosmological problems are discussed. The new discoveries include the existence of double layers in magnetized plasmas and in the low magnetosphere, and energy transfer by electric current in the auroral circuit. It is argued that solar flares and the solar wind-magnetosphere interaction should not be interpreted in terms of magnetic merging theories, and that electric current needs to be explicitly taken account of in understanding these phenomena. The filamentary structure of cosmic plasmas may be caused by electric currents in space, and the pinch effect may have a central role to play in the evolutionary history of interstellar clouds, stars, and solar systems. Space may have a cellular structure, with the cell walls formed by thin electric current layers. Annihilation may be the source of energy for quasars and the Hubble expansion, and the big bang cosmology may well be wrong.

Alfven, H.↗
NASA NTRS1993

Newly available technologies present expanding opportunities for scientific and technical information exchange

The potential for expanded communication among researchers, scholars, and students is supported by growth in the capabilities for electronic communication as well as expanding access to various forms of electronic interchange and computing capabilities. Research supported by the National Aeronautics and Space Administration points to a future where workstations with audio and video monitors and screen-sharing protocols are used to support collaborations with colleagues located throughout the world. Instruments and sensors all over the world will produce data streams that will be brought together and analyzed to produce new findings, which in turn can be distributed electronically. New forms of electronic journals will emerge and provide opportunities for researchers and scientists to electronically and interactively exchange information in a wide range of structures and formats. Ultimately, the wide-scale use of these technologies in the dissemination of research results and the stimulation of collegial dialogue will change the way we represent and express our knowledge of the world. A new paradigm will evolve-perhaps a truly worldwide 'invisible college'.

Tolzman, Jean M.↗
NASA NTRS2003

Tracking and Control of Gas Turbine Engine Component Damage/Life

This paper describes damage mechanisms and the methods of controlling damages to extend the on-wing life of critical gas turbine engine components. Particularly, two types of damage mechanisms are discussed: creep/rupture and thermo-mechanical fatigue. To control these damages and extend the life of engine hot-section components, we have investigated two methodologies to be implemented as additional control logic for the on-board electronic control unit. This new logic, the life-extending control (LEC), interacts with the engine control and monitoring unit and modifies the fuel flow to reduce component damages in a flight mission. The LEC methodologies were demonstrated in a real-time, hardware-in-the-loop simulation. The results show that LEC is not only a new paradigm for engine control design, but also a promising technology for extending the service life of engine components, hence reducing the life cycle cost of the engine.

Jaw, Link C.↗
NASA NTRSDate not supplied

Wildfire Segmentation From Remotely Sensed Data Using Quantum-Compatible Conditional Vector Quantized-Variational Autoencoders

Wildfires represent a critical environmental hazard with multifaceted implications for ecosystems, communities, and public health [1]. The escalating frequency and intensity of wildfires globally have intensified the urgency for robust segmentation methodologies to facilitate effective mitigation, response, and recovery strategies [2]. Accurate wildfire segmentation is pivotal for delineating fire boundaries, assessing progression patterns, and prioritizing resource allocation during emergency scenarios. Furthermore, precise segmentation enables stakeholders, including policymakers, environmental scientists, and emergency responders, to formulate evidence-based strategies, thereby minimizing socio-economic disruptions and ecological degradation. Consequently, advancing wildfire segmentation techniques through innovative technological interventions remains a paramount research imperative. Although foundational in wildfire segmentation, traditional deterministic models exhibit inherent limitations that compromise their efficacy in dynamic and uncertain environments. These models often operate on rigid algorithms prioritizing deterministic classifications, thereby overlooking the inherent complexities and uncertainties associated with wildfire behavior and satellite data variability. Such deterministic frameworks tend to produce oversimplified representations that fail to capture the intricate nuances of evolving fire dynamics, spatial heterogeneity, and environmental interactions [1]. Consequently, the deterministic approach’s propensity for uncertainty collapsing [1, 3] hampers the accuracy, reliability, and applicability of segmentation outcomes in real-world scenarios. Contrastingly, stochastic models offer a more nuanced and adaptable framework for wildfire segmentation. By integrating probabilistic elements into the modeling paradigm, stochastic approaches, particularly probabilistic approaches such as variational auto encoders (VAEs) [4], facilitate comprehensive uncertainty assessment, enabling researchers to quantify and incorporate uncertainties into segmentation outcomes effectively. This probabilistic nature empowers stochastic models to encapsulate variability, account for data inconsistencies, and adapt to evolving environmental conditions, enhancing segmentation accuracy, reliability, and robustness. Embracing stochastic methodologies thus catalyzes advancements in wildfire science by fostering a more holistic, adaptive, and resilient segmentation framework. Despite VAEs demonstrating significant promise in various applications, they come with inherent limitations that have garnered attention within the machine learning community. One of the primary drawbacks lies in their reliance on static priors, which essentially assume a fixed distribution for latent variables, thereby limiting the model’s flexibility to capture complex data structures effectively [5]. This static nature leads to suboptimal representations, especially when dealing with complex and high-dimensional data. Additionally, VAEs often struggle with generating sharp and realistic samples, a phenomenon commonly referred to as mode collapse [5, 7, 6]. Furthermore, the optimization process in VAEs, which involves balancing the reconstruction loss and the regularization term, can sometimes be challenging to fine-tune [7]. In recent efforts to address these shortcomings, alternative approaches like Vector Quantized Variational Auto encoders(VQ-VAEs) [7], address the challenges by incorporating discrete latent variables and leveraging techniques that enhance the quality and diversity of generated samples while maintaining efficient training dynamics. VQ-VAEs propose a dynamic prior distribution generation mechanism that diverges from the static priors commonly associated with traditional VAEs. This dynamic approach allows for more adaptive and context-aware latent variable representations, thereby potentially capturing complex data structures more effectively. Unlike autoregressive prior models such as PixelCNN, which, despite their ability to model dependencies across data dimensions, suffer from significant computational inefficiencies and lack flexibility in handling diverse datasets. In our work, we propose to use a generative quantum-compatible approach to help alleviate the shortcomings of autoregressive prior model in VQ-VAEs. Restricted Boltzmann Machines (RBMs) are a viable alternative prior model that can learn prior distributions in a faster and more flexible manner. In this research endeavor, we meticulously curate a state-of-the-art dataset leveraging satellite MODIS data in conjunction with VIIRS fire masks, derived from Fire Radiative Power (FRP), thereby encapsulating diverse wildfire scenarios and environmental contexts. We developed a conditional VQ-VAE architecture with the RBM prior model that is trained in a supervised manner for segmenting wildfire masks. This innovative approach synergistically harnesses deep learning capabilities, enabling the generation of segmentation maps characterized by heightened precision, granularity, and contextual relevance. Furthermore, replacing the autoregressive prior learning method proposed by the original VQ-VAE with a prior density approximation via quantum-compatible RBM facilitates expedited inference processes, augments flexibility in prior sampling, optimizes computational efficiency and establishes a groundbreaking benchmark in wildfire segmentation methodologies.

quantum machine learning↗
NASA NTRS1993

Diamonds in dense molecular clouds - A challenge to the standard interstellar medium paradigm

Observations of a newly discovered infrared C-H stretching band indicate that interstellar diamond-like material appears to be characteristic of dense clouds. In sharp contrast, the spectral signature of dust in the diffuse interstellar medium is dominated by -CH2- and -CH3 groups. This dichotomy in the aliphatic organic component between the dense and diffuse media challenges standard assumptions about the processes occurring in, and interactions between, these two media. The ubiquity of this interstellar diamond-like material rules out models for meteoritic diamond formation in unusual circumstellar environments and implies that the formation of the diamond-like material is associated with common interstellar processes or stellar types.

Allamandola, L. J.↗
NASA NTRS2010

The NASA Constellation Program Procedure System

NASA has used procedures to describe activities to be performed onboard vehicles by astronaut crew and on the ground by flight controllers since Apollo. Starting with later Space Shuttle missions and the International Space Station, NASA moved forward to electronic presentation of procedures. For the Constellation Program, another large step forward is being taken - to make procedures more interactive with the vehicle and to assist the crew in controlling the vehicle more efficiently and with less error. The overall name for the project is the Constellation Procedure Applications Software System (CxPASS). This paper describes some of the history behind this effort, the key concepts and operational paradigms that the work is based upon, and the actual products being developed to implement procedures for Constellation

Phillips, Robert G.↗
NASA NTRS2021

Understanding the Impacts of Land Surface and PBL Observations on the Terrestrial and Atmospheric Legs of Land-Atmosphere Coupling

Accurately representing land-atmosphere (L-A) interactions and coupling in NWP systems remains a challenge. New observations, incorporated into models via assimilation or calibration, hold the promise of improved forecast skill, but erroneous model coupling can hinder the benefits of such activities. To better understand model representation of coupled interactions and feedbacks, this study demonstrates a novel framework for coupled calibration of the Single Column Model (SCM) capability of the NASA Unified Weather Research and Forecasting (NU-WRF) system coupled to NASA’s Land Information System (LIS). The local land-atmosphere coupling (LoCo) process chain paradigm is used to assess the processes and connections revealed by calibration experiments. Two summer case studies in the U. S. Southern Great Plains are simulated in which LSM parameters are calibrated to diurnal observations of LoCo process chain components including 2-meter temperature, 2-meter humidity, surface fluxes (Bowen ratio), and PBL height. Results show a wide range of soil moisture and hydraulic parameter solutions depending on which L-A variable (i.e. observation) is used for calibration, highlighting that improvement in either SHP or ISM when not in tandem with the other can provide undesirable results. Overall, this work demonstrates that a process chain calibration approach can be used to assess L-A connections, feedbacks, strengths, and deficiencies in coupled models, as well as quantify the potential impact of new sources of observations of land-PBL variables on coupled prediction.

Patricia Lawston-Parker↗
NASA NTRS2015

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues. The methodology is two-fold: first, capture the heuristics developed by human analysts over their many years of experience; and secondly, leverage the power of modern computing to evaluate multiple trajectories simultaneously and therefore enable the exploration of the trajectory's design space early during the pre- conceptual and conceptual phases of design. This methodology is coupled with design of experiments in order to train surrogate models, which enables trajectory design space visualization and parametric optimal ascent trajectory information to be available when early design decisions are being made.

Dees, Patrick D.↗
NASA NTRS2004

The Need for Analogue Missions in Scientific Human and Robotic Planetary Exploration

With the increasing challenges of planetary missions, and especially with the prospect of human exploration of the moon and Mars, the need for earth-based mission simulations has never been greater. The current focus on science as a major driver for planetary exploration introduces new constraints in mission design, planning, operations, and technology development. Analogue missions can be designed to address critical new integration issues arising from the new science-driven exploration paradigm. This next step builds on existing field studies and technology development at analogue sites, providing engineering, programmatic, and scientific lessons-learned in relatively low-cost and low-risk environments. One of the most important outstanding questions in planetary exploration is how to optimize the human and robotic interaction to achieve maximum science return with minimum cost and risk. To answer this question, researchers are faced with the task of defining scientific return and devising ways of measuring the benefit of scientific planetary exploration to humanity. Earth-based and spacebased analogue missions are uniquely suited to answer this question. Moreover, they represent the only means for integrating science operations, mission operations, crew training, technology development, psychology and human factors, and all other mission elements prior to final mission design and launch. Eventually, success in future planetary exploration will depend on our ability to prepare adequately for missions, requiring improved quality and quantity of analogue activities. This effort demands more than simply developing new technologies needed for future missions and increasing our scientific understanding of our destinations. It requires a systematic approach to the identification and evaluation of the categories of analogue activities. This paper presents one possible approach to the classification and design of analogue missions based on their degree of fidelity in ten key areas. Various case studies are discussed to illustrate the approach.

Snook, K. J.↗
NASA NTRS1995

Algorithms for the automatic generation of 2-D structured multi-block grids

Two different approaches to the fully automatic generation of structured multi-block grids in two dimensions are presented. The work aims to simplify the user interactivity necessary for the definition of a multiple block grid topology. The first approach is based on an advancing front method commonly used for the generation of unstructured grids. The original algorithm has been modified toward the generation of large quadrilateral elements. The second method is based on the divide-and-conquer paradigm with the global domain recursively partitioned into sub-domains. For either method each of the resulting blocks is then meshed using transfinite interpolation and elliptic smoothing. The applicability of these methods to practical problems is demonstrated for typical geometries of fluid dynamics.

Schoenfeld, Thilo↗
NASA NTRS1999

Implementation of Parallel Computing Technology to Vortex Flow

Mainframe supercomputers such as the Cray C90 was invaluable in obtaining large scale computations using several millions of grid points to resolve salient features of a tip vortex flow over a lifting wing. However, real flight configurations require tracking not only of the flow over several lifting wings but its growth and decay in the near- and intermediate- wake regions, not to mention the interaction of these vortices with each other. Resolving and tracking the evolution and interaction of these vortices shed from complex bodies is computationally intensive. Parallel computing technology is an attractive option in solving these flows. In planetary science vortical flows are also important in studying how planets and protoplanets form when cosmic dust and gases become gravitationally unstable and eventually form planets or protoplanets. The current paradigm for the formation of planetary systems maintains that the planets accreted from the nebula of gas and dust left over from the formation of the Sun. Traditional theory also indicate that such a preplanetary nebula took the form of flattened disk. The coagulation of dust led to the settling of aggregates toward the midplane of the disk, where they grew further into asteroid-like planetesimals. Some of the issues still remaining in this process are the onset of gravitational instability, the role of turbulence in the damping of particles and radial effects. In this study the focus will be with the role of turbulence and the radial effects.

Dacles-Mariani, Jennifer↗
DOE OSTI2026

Hydrophobic Metal–Organic Frameworks Enable Superior High-Pressure Ammonia Storage through Geometric Design

Hydrophobic metal–organic frameworks (MOFs) are typically overlooked for ammonia storage due to weak host–guest interactions. Here, we demonstrate that four structurally analogous aluminum-based MOFs exhibit a counterintuitive behavior whereby framework geometry, rather than ligand hydrophilicity, determines high-pressure NH 3 adsorption performance. The hydrophobic CAU-23 achieved an exceptional capacity matching hydrophilic analogs despite its poor low-pressure uptake. This pressure-dependent enhancement stems from the unique 4-cis-4-trans geometry of CAU-23 compared to the purely cis arrangement of MIL-160 and KMF-1 and the alternating cis-trans configuration of MOF-303. Critically, CAU-23 retained 95% capacity over three high-pressure cycles, whereas hydrophilic MOFs suffered 39–46% irreversible losses due to strong NH 3 -framework interactions that compromise structural integrity. Grand canonical Monte Carlo simulations reveal that high pressure enables NH 3 clustering through intermolecular hydrogen bonding, bypassing the need for strong host–guest interactions. High-pressure powder X-ray diffraction measurements confirm the exceptional mechanical resilience of CAU-23, showing complete structural recovery upon decompression despite exhibiting the highest pressure sensitivity among the studied MOFs. An extended analog, HE-CAU-23, validates this design principle with further enhanced capacity. Furthermore, these findings reveal a paradigm shift toward hydrophobic MOFs with optimized geometry for high-performance and regenerable gas storage applications.

MOFs↗
NASA NTRSDate not supplied

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗
DOE OSTI2025

Self‐Assembled Membranes for High Ion Selectivity and Proton Blocking in Electrochemical Applications

Anion-exchange membranes (AEMs) with high anion/cation selectivity and exceptional proton-blocking ability are critical for applications such as bipolar membrane electrodialysis and electrochemical acid recovery. However, existing AEMs are constrained by a trade-off between ionic conductivity and selectivity, largely due to the intrinsic coupling between charge density and water content, and they suffer from excessive proton leakage facilitated by the Grotthuss hopping mechanism. In this work, poly(vinylimidazolium) membranes functionalized with long alkyl side chains that self-assemble into well-defined microphase-separated morphologies stabilized by hydrophobic and electrostatic interactions are reported. These unique structures localize the charge density along the polymer backbone to promote fast and selective ion transport. As a result, these membranes exhibit ionic conductivities and counter-ion diffusivities surpassing those of conventional homogeneous membranes, along with unprecedented counter-ion/co-ion selectivity and proton-blocking ability. These results establish a new design paradigm for high-performance, phase separated charged polymer membranes that overcome the limitations of homogeneous membranes, with broad implications for advanced electrochemical technologies.

36 MATERIALS SCIENCE↗