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At least 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2023

HydroGEN Seedling: High-Temperature Reactor Catalyst Material Development for Low-Cost and Efficient Solar-Driven Sulfur-Based Processes

The HyS process, driven by solar power, has great potential to reach high-efficiency and low-cost hydrogen production without greenhouse gas emissions. The high-temperature section of the HyS cycle, which operates the catalytic decomposition of sulfuric acid into sulfur dioxide, oxygen, and water, is a fundamental part of the cycle affecting the overall plant efficiency and cost. Therefore, a high-performance catalyst (i.e., low cost, high catalytic activity, and low degradation catalyst) is of critical importance to achieve high efficiency and low hydrogen cost. Research and development has highlighted that a Pt-based monometallic catalyst had unacceptable catalytic activity and performance degradation for a high-efficiency and low-cost hydrogen production process. A high-efficiency solar receiver-reactor system, which incorporates the new catalyst, also needs to be developed to achieve the required plant efficiency and cost. Greenway Energy (GWE) and the University of South Carolina (USC), partnering with HydroGEN node laboratories Idaho National Laboratory (INL), Savannah River National Laboratory (SRNL), and National Renewable Energy Laboratory (NREL), propose the development of a new catalyst formulation, included in a novel solar receiver-reactor concept, to be tested experimentally in the last part of the project.

08 HYDROGEN↗

NASA NTRS2018

Hybrid Reduced Order Model for N2-N2 Interactions for Application to Dissociation and Energy Transfer Processes

Recent work in the aerothermodynamics community has focused on the development of reduced-order models for thermo-chemical non-equilibrium which avoid the restrictive assumptions of multi-temperature models and the prohibitive cost associated with State-to-State (StS) models. In the present work, this is accomplished by lumping energy states together and assuming groups of states are roughly in equilibrium. As a result, the non-equilibrium behavior of a gas can be captured at a reduced computational cost from a full StS simulation. In this work, we present a hybrid grouping model for studying energy transfer and dissociation in a mixture of nitrogen molecules due to N2-N2 reactions. This is accomplished by making use of a grouping strategy informed by data from the N2-N StS kinetic data. However, due to the massive computational cost associated with constructing StS data for the N2-N2 system, the kinetic data for the hybrid grouping model are calculated using the quasi-classical trajectory (QCT) method by sampling states for trajectory within the groups. This general framework is called the Maximum-Entropy Quasi-Classical Trajectory (ME-QCT) method. The primary challenge associated with this method is that rates for reverse grouped reactions cannot be obtained through detailed balance at a group level, due to the variation of group internal temperatures. To construct the full model for N2-N2 grouped kinetics using the ME-QCT method, detailed balance is invoked at the microscopic level, allowing for the calculation of the full kinetic data from QCT. Results will be presented using the full ME-QCT model for the N2-N2 system in an isothermal and isochoric reactor simulation. In addition, simple CFD test cases for a one-dimensional standing shock and for a quasi-one-dimensional nozzle will be used for demonstration of the ME-QCT method. This method allows for the calculation of non-equilibrium behavior for the N2-N2 system without the prohibitive cost of a full StS simulation. Moreover, it enables the construction of a unified model for the dissociating and recombining non-equilibrium flows.

nonequilibrium modeling↗

NASA NTRS2008

Enhanced Self Tuning On-Board Real-Time Model (eSTORM) for Aircraft Engine Performance Health Tracking

A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation.

Volponi, Al↗

DOE OSTI2021

Chalcogenide perovskite BaZrS 3 thin-film electronic and optoelectronic devices by low temperature processing

Owing to its superior visible light absorption and high chemical stability, chalcogenide perovskite barium zirconium sulfide (BaZrS 3 ) has attracted significant attention in the past few years as a potential alternative to hybrid halide perovskites for optoelectronics. However, the high processing temperatures of BaZrS 3 thin films at above 1000 °C severely limits their potential for device applications. Herein, we report the synthesis of BaZrS 3 thin films at temperatures as low as 500 °C, by changing the chemical reaction pathway. The single phase BaZrS 3 thin film was confirmed by X-ray diffraction and Raman spectroscopy. Atomic force microscopy and scanning electron microscopy show that crystalline size and surface roughness were consistently reduced with decreasing annealing temperature. The lower temperatures further eliminate sulfur vacancies and carbon contaminations associated with high temperature processing. The ability to synthesize chalcogenide perovskite thin films at lower temperatures removes a major hurdle for their device fabrication. The photodetectors demonstrate fast response and an on/off ratio of 80. Finally, the fabricated field effect transistors show an ambipolar behavior with electron and hole mobilities of 16.8 cm 2 /Vs and 2.6 cm 2 /Vs, respectively.

36 MATERIALS SCIENCE↗

NASA NTRS2013

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗

DOE OSTI2024

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗

NASA NTRS1986

The development of an unconventional food regeneration process: Quantifying the nutritional components of a model methylotrophic yeast

A hybrid chemical/biological approach to unconventional food regeneration is discussed. Carbon dioxide and water, the major wastes of human metabolism would be converted to methanol by one of several physiochemical processes available (thermal, photocatalytic, etc.). Methanol is then used to supply carbon and energy for the culture of microorganisms which in turn produce biological useful basic food stuffs for human nutrition. Our work has focused on increasing the carbohydrate levels of a candidate methylotrophic yeast to more nearly coincide with human nutritional requirements. Yeasts were chosen due to their high carbohydrate levels compared to bacteria and their present familiarity in the human diet. The initial candidate yeast studied was a thermotolerant strain of Hansenula polymor pha, DL-1. The quantitative results that permit an evaluation of the overall efficiency in hybrid chemical/biological food production schemes are discussed. A preliminary evaluation of the overall efficiency of such schemes is also discussed.

Petersen, G. R.↗

DOE OSTI2020

Quantification of the carbon bonding state in amorphous carbon materials: A comparison between EELS and NEXAFS measurements

In this report the quantitative determination of the carbon hybridization is critical for establishing processing-structure-properties relationships for carbon-based materials, including amorphous carbon coatings. While several techniques have been employed to characterize the amount of sp 2 and sp 3 carbon in these materials, direct comparisons between analytical results are limited. Here, we compare near edge X-ray absorption fine structure (NEXAFS) spectra of a silicon- and oxygen-containing hydrogenated amorphous carbon (a-C:H:Si:O) coating acquired in synchrotron-based scanning transmission X-ray microscopy (STXM) mode with electron energy loss spectra (EELS) obtained from the same a-C:H:Si:O lamella. While the fractions of sp 2 carbon computed from STXM and EELS spectra are in close agreement, the comparison of NEXAFS spectra acquired in STXM mode with NEXAFS spectra collected in partial electron yield mode on a flat a-C:H:Si:O surface indicated that the destructive preparation of thin lamellae for STXM analyses induces variations in the structure of a-C:H:Si:O, namely the breakage of carbon-silicon and carbon-hydrogen bonds, a change in ordering of sp 2 -bonded carbon, and an increase in the sp 2 carbon fraction. These findings can help scientists in the careful interpretation of spectroscopic results obtained from the analysis of samples made of metastable materials after the destructive preparation of specimens for analytical purposes.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Self-regulating behavior of hybrid membrane systems as demonstrated in an element-scale forward osmosis-reverse osmosis hybrid system

Hybrid membrane systems can be difficult to design due to the requisite flow rate matching between up- and downstream unit operations. In this work, we use a forward osmosis-reverse osmosis (FO-RO) hybrid system to demonstrate how some membrane systems can exhibit self-regulating behavior due to osmotic coupling. This can reduce the need for complex control systems for flow balancing. We show this behavior using a module-scale test bed that can mimic the behavior of larger scale operations. The system shows permeate flow rate near-convergence between the FO and RO modules after startup or when perturbed by a change in RO module pressure. The behavior of this hybrid system demonstrates that some membrane operations can exploit osmotic interdependence, rather than expensive control systems, to achieve steady state operation.

Debottlenecking↗

DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Toward alcohol synthesis from CO hydrogenation on Cu(111)-supported MoS 2 – predictions from DFT+KMC

In the quest for cheap and efficient catalysts for alcohol synthesis from syngas, a material of interest is single-layer MoS2 owing to its low cost, abundancy, and flexible structure. Because of the inertness of its basal plane, however, it is essential to find ways that make it catalytically active. Herein, by means of density functional theory based calculations of reaction pathways and activation energy barriers and accompanying kinetic Monte Carlo simulations, we show that while S vacancy row structures activate the MoS 2 basal plane, further enhancement of chemical activity and selectivity can be achieved by interfacing the MoS 2 layer with a metallic support. When defect-laden MoS2 is grown on Cu(111), there is not only an increase in the active region (surface area of active sites) but also charge transfer from Cu to MoS 2 , resulting in a shift of the Fermi level such that the frontier states (d orbitals of the exposed Mo atoms) appear close to it, making the MoS 2 /Cu(111) system ready for catalytic activity. Finally, our calculated thermodynamics of reaction pathways lead to the conclusion that the Cu(111) substrate promotes both methanol and ethanol as the products, while kinetic Monte Carlo simulations suggest a high selectivity toward the formation of ethanol.

2D materials↗

DOE OSTI2020

Enhancing Heavy-Oil-Recovery Efficiency by Combining Low-Salinity-Water and Polymer Flooding

Summary Combining low-salinity-water (LSW) and polymer flooding was proposed to unlock the tremendous heavy-oil resources on the Alaska North Slope (ANS). The synergy of LSW and polymer flooding was demonstrated through coreflooding experiments at various conditions. The results indicate that the high-salinity polymer (HSP) (salinity = 27,500 ppm) requires nearly two-thirds more polymer than the low-salinity polymer (LSP) (salinity = 2,500 ppm) to achieve the target viscosity at the condition of this study. Additional oil was recovered from LSW flooding after extensive high-salinity-water (HSW) flooding [3 to 9% of original oil in place (OOIP)]. LSW flooding performed in secondary mode achieved higher recovery than that in tertiary mode. Also, the occurrence of water breakthrough can be delayed in the LSW flooding compared with the HSW flooding. Strikingly, after extensive LSW flooding and HSP flooding, incremental oil recovery (approximately 8% of OOIP) was still achieved by LSP flooding with the same viscosity as the HSP. The pH increase of the effluent during LSW/LSP flooding was significantly greater than that during HSW/HSP flooding, indicating the presence of the low-salinity effect (LSE). The residual-oil-saturation (Sor) reduction induced by the LSE in the area unswept during the LSW flooding (mainly smaller pores) would contribute to the increased oil recovery. LSP flooding performed directly after waterflooding recovered more incremental oil (approximately 10% of OOIP) compared with HSP flooding performed in the same scheme. Apart from the improved sweep efficiency by polymer, the low-salinity-induced Sor reduction also would contribute to the increased oil recovery by the LSP. A nearly 2-year pilot test in the Milne Point Field on the ANS has shown impressive success of the proposed hybrid enhanced-oil-recovery (EOR) process: water-cut reduction (70 to less than 15%), increasing oil rate, and no polymer breakthrough so far. This work has demonstrated the remarkable economical and technical benefits of combining LSW and polymer flooding in enhancing heavy-oil recovery.

Engineering↗

DOE OSTI2021

Event-scale predictions of water and nitrogen exports in coastal watersheds

Focal Area(s): The purpose of this white paper is to call for the improvement of the predictability and explainability of the magnitude and timing of water and nutrient exports in coastal watersheds. In this regard, hybrid machine learning approaches and process-based numerical models provide new opportunities to maximize predictability, emulate process-based model components, and explicitly address model uncertainty associated with event-scale predictions in coastal watersheds.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

Water recovery and solid waste processing for aerospace and domestic applications. Volume 1: Final report

A comprehensive study of advanced water recovery and solid waste processing techniques employed in both aerospace and domestic or commercial applications is reported. A systems approach was used to synthesize a prototype system design of an advanced water treatment/waste processing system. Household water use characteristics were studied and modified through the use of low water use devices and a limited amount of water reuse. This modified household system was then used as a baseline system for development of several water treatment waste processing systems employing advanced techniques. A hybrid of these systems was next developed and a preliminary design was generated to define system and hardware functions.

Murray, R. W.↗

NASA NTRS1999

The Role of Instabilities in Plasmaspheric Heating, Flux Tube Refilling, and the Development of Spatial Structures

Plasma instabilities appear to play an important role in plasmasphere dynamics. Direct interactions between the plasmasphere and other plasma populations lead to energy transfer and heating, to equatorial trapping, and to changes in ionospheric outflow. Super-thermal electron and ring current populations are the dominant sources of energy for these processes. Flute (Interchange), electromagnetic lower-hybrid drift, and E x B drift instabilities can also play important roles in the distribution of thermal, plasmaspheric plasma. As our attention has returned to the remaining plasmaspheric mysteries, it has become clear that the details of plasmaspause formation and erosion and the development of localized, dense thermal plasma structures are almost completely unexplained. Radially sharp density depletions and generalized density loss are seen inside the plasmapause. Narrow and extended regions of enhanced thermal plasma density is found throughout the magnetosphere, even after extended periods of quite geomagnetic conditions. Sharp gradients are often seen on the westward edge of density enhancements, while eastward boundaries are often highly structured.

Gallagher, D. L.↗

NASA NTRS2004

An Evolving Trio of Hybrid Stars: C 111

Our goal is to understand the behavior of the outer atmosphere in this intermediate stage to create a comprehensive picture of atmospheric evolution. In the hybrid phase, the large-scale magnetic dynamo activity decays and hydrodynamic processes assume importance. Some hot plasma is still confined close to the star by magnetic loops, yet the confining field is breaking open, the atmosphere can escape through these open field lines, and the diffuse corona may be warm. There may well be a more extended and variable transition process. It remains for FUSE to identify the controlling parameters of the hybrid stars. It shows the positions of our 3 targets in the color-magnitude diagram where it is seen that they are at the extreme end of the hybrid region. Originally we had been awarded the hybrid star Iota Aur, but due to newly imposed pointing constraints of FUSE, that target was not accessible. And so we substituted Iota Dra, a giant of mass similar to our other targets but less evolved. In addition, Iota Dra was recently found to harbor a sub-stellar objects, possibly a planet, and so it could reveal the stellar environment of the planet. This substitution was accepted.

Oliversen, Ronald↗

NASA NTRS2016

Next Generation Flight Displays Using HTML5

The Human Integrated Vehicles and Environments (HIVE) lab at Johnson Space Center (JSC) is focused on bringing together inter-disciplinary talent to design and integrate innovative human interface technologies for next generation manned spacecraft. As part of this objective, my summer internship project centered on an ongoing investigation in to building flight displays using the HTML5 standard. Specifically, the goals of my project were to build and demo "flight-like" crew and wearable displays as well as create a webserver for live systems being developed by the Advanced Exploration Systems (AES) program. In parallel to my project, a LabVIEW application, called a display server, was created by the HIVE that uses an XTCE (XML (Extensible Markup Language) Telemetry and Command Exchange) parser and CCSDS (Consultative Committee for Space Data System) space packet decoder to translate telemetry items sent by the CFS (Core Flight Software) over User Datagram Protocol (UDP). It was the webserver's job to receive these UDP messages and send them to the displays. To accomplish this functionality, I utilized Node.js and the accompanying Express framework. On the display side, I was responsible for creating the power system (AMPS) displays. I did this by using HTML5, CSS and JavaScript to create web pages that could update and change dynamically based on the data they received from the webserver. At this point, I have not started on the commanding, being able to send back to the CFS, portion of the displays but hope to have this functionality working by the completion of my internship. I also created a way to test the webserver's functionality without the display server by making a JavaScript application that read in a comma-separate values (CSV) file and converted it to XML which was then sent over UDP. One of the major requirements of my project was to build everything using as little preexisting code as possible, which I accomplished by only using a handful of JavaScript libraries. As a side project, I created a model of the HIVE lab and Building 29 using SketchUp. I obtained the floorplans of the building from the JSC Geographic Information Systems (GIS), which were computer-aided design (CAD) files, and imported them into SketchUp. I then took those floorplans and created a 3D model of the building from them. Working in conjunction with the Hybrid Reality lab in Building 32, the SketchUp model was imported into Unreal Engine for use with the HTC Vive. Using the Vive, I was able to interact with the model I created in virtual reality (VR). The purpose of this side project was to be able to visualize potential lab layouts and mockup designs as they are in development in order to finalize design decisions. Pending approval, the model that I created will be used in the Build-As-You-Test: Can Hybrid Reality Improve the SE/HSI Design Process project in the fall. Getting the opportunity to work at NASA has been one of the most memorable experiences of my life. Over the course of my internship, I improved my programming and web development abilities substantially. I will take all the skills and experiences I have had while at NASA back to school with me in the fall and hope to pursue a career in the aerospace industry after graduating in the spring.

Greenwood, Brian↗

DOE OSTI2021

Advanced Electron Microscopy of Nanophased Synthetic Polymers and Soft Complexes for Energy and Medicine Applications

After decades of developments, electron microscopy has become a powerful and irreplaceable tool in understanding the ionic, electrical, mechanical, chemical, and other functional performances of next-generation polymers and soft complexes. The recent progress in electron microscopy of nanostructured polymers and soft assemblies is important for applications in many different fields, including, but not limited to, mesoporous and nanoporous materials, absorbents, membranes, solid electrolytes, battery electrodes, ion- and electron-transporting materials, organic semiconductors, soft robotics, optoelectronic devices, biomass, soft magnetic materials, and pharmaceutical drug design. For synthetic polymers and soft complexes, there are four main characteristics that differentiate them from their inorganic or biomacromolecular counterparts in electron microscopy studies: (1) lower contrast, (2) abundance of light elements, (3) polydispersity or nanomorphological variations, and (4) large changes induced by electron beams. Since 2011, the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory has been working with numerous facility users on nanostructured polymer composites, block copolymers, polymer brushes, conjugated molecules, organic–inorganic hybrid nanomaterials, organic–inorganic interfaces, organic crystals, and other soft complexes. This review crystalizes some of the essential challenges, successes, failures, and techniques during the process in the past ten years. It also presents some outlooks and future expectations on the basis of these works at the intersection of electron microscopy, soft matter, and artificial intelligence. Machine learning is expected to automate and facilitate image processing and information extraction of polymer and soft hybrid nanostructures in aspects such as dose-controlled imaging and structure analysis.

36 MATERIALS SCIENCE↗