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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Metal Identity and Coordination Environment Modulate Single-Atom Catalyst Stability During Electrocatalysis

A major hurdle to the implementation of single-atom catalysts (SACs) in real-world systems is a poor understanding of their stability under operating conditions, which is particularly relevant due to the high surface free energy of SACs. Here, we evaluated the aggregation behavior of a suite of SACs varied by metal identity (Fe, Co, Ni, and Cu) during electrocatalytic nitrate reduction using in situ X-ray absorption spectroscopy. The metal center had significant influence on reconstruction, where under identical applied reductive potentials, SACs underwent varying levels of reconstruction, ranging from no discernible change to complete reduction into metallic nanoparticles. Such in situ experiments revealed Cu SACs to be the most susceptible to aggregation, prompting a deeper investigation into how coordination environment (O-, B-, and N-graphene) affected Cu SAC aggregation. We further conducted density functional theory calculations to elucidate the relationship between Cu SAC structure and stability. This work deconvolutes the relationship between SAC architecture and stability, which is essential to evaluate and explain for the realization of SACs for electrocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Neutron Reflectometry Reveals Diffusion in Contrast-Matched Brush Particle Bilayers

A material system for performing layer-spread experiments on brush particle bilayers is presented and used to determine the diffusion constant of brush particles in the melt state. Selective deuteration of the core and shell of organo-silica nanoparticles grafted with poly(methyl methacrylate) was used to match the scattering length density of the core and the polymer canopy layer. This subdued the scattering of particle cores (i.e., formfactor scattering) and enabled the analysis of the interdiffusion kinetics using neutron reflectivity. For low molecular grafts, i.e., grafts with a molecular weight below the entanglement limit, the interdiffusion kinetics revealed both a sub- and Fickian diffusion regime. The former was attributed to the local dynamics that was constrained by the slow-moving cores of neighboring brush particles that acted as long-lived physical cross-links. No transition to Fickian diffusion was observed for entangled systems, even at prolonged annealing times. This suggested a higher level of kinetic restraint in entangled brush particle melts as compared to, for example, star polymers with a comparable chain length for which Fickian diffusion has been reported under similar conditions.

Diffusion, Polymer Grafted Nanoparticles, Neutron ↗
DOE OSTI2025

Atomically Fine-Tuning Organic–Inorganic Carbon Molecular Sieve Membranes for Hydrogen Production

Polymeric membranes with great processability are attractive for the H 2 /CO 2 separation required for hydrogen production from renewable biomass with carbon capture for utilization and sequestration. However, it remains elusive to engineer polymer architectures to obtain desired sub-3.3 Å ultramicropores to efficiently sieve H 2 from CO 2 . Herein, we demonstrate a scalable way of carbonizing polybenzimidazole (PBI) at low temperatures, followed by vapor phase infiltration (VPI) to atomically narrow ultramicropores throughout the films, forming hybrid organic–inorganic carbon molecular sieves (CMSs). One VPI cycle (100 s) for the PBI carbonized at 500 °C remarkably increases H 2 /CO 2 selectivity from 9.6 to 83 at 100 °C, surpassing Robeson’s upper bound. The CMS demonstrates a stable H 2 /CO 2 separation performance when challenged with simulated syngas streams and can be fabricated into thin-film composite membranes, outperforming state-of-the-art membranes. Finally, the scalable approach can be ubiquitous to molecularly fine-tune ultramicropores of leading polymeric membranes to further improve their size-sieving ability and thus separation efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dynamic Metal–Support Interaction Dictates Cu Nanoparticle Sintering on Al 2 O 3 Surfaces

Nanoparticle sintering remains a critical challenge in heterogeneous catalysis. In this work, we present a unified deep potential (DP) model based on the Perdew–Burke–Ernzerhof approximation of density functional theory for Cu nanoparticles on three Al 2 O 3 surfaces (γ-Al 2 O 3 (100), γ-Al 2 O 3 (110), and α-Al 2 O 3 (0001)). Using DP-accelerated simulations, we reveal that the nanoparticle size-mobility relationship strongly depends on the supporting surface. The diffusion of nanoparticles on the two γ-Al 2 O 3 surfaces is almost independent of the size of the nanoparticle, while the diffusion on α-Al 2 O 3 (0001) decreases rapidly with increasing size. Interestingly, nanoparticles with fewer than 55 atoms diffuse several times faster on α-Al 2 O 3 (0001) than on γ-Al 2 O 3 (100) at 800 K while expected to be more sluggish based on their larger binding energy at 0 K. The diffusion on α-Al 2 O 3 (0001) is facilitated by dynamic metal–support interaction (MSI), where Al atoms move out of the surface plane to optimize contact with the nanoparticle and relax back to the plane as the nanoparticle moves away. In contrast, the MSI on γ-Al 2 O 3 (100) and on γ-Al 2 O 3 (110) is dominated by more stable and directional Cu–O bonds, consistent with the limited diffusion observed on these surfaces. Our extended MD simulations provide insight into the sintering processes, showing that the dispersity of the nanoparticles strongly influences the coalescence driven by nanoparticle diffusion. We observed that the coalescence of Cu 13 nanoparticles on α-Al 2 O 3 (0001) can occur in a short time (10 ns) at 800 K even with an initial internanoparticle distance increased to 3 nm, while the coalescence on the two γ-Al 2 O 3 surfaces are inhibited significantly by increasing the initial internanoparticle distance. These findings demonstrate that the dynamics of the supporting surface is crucial to understanding the sintering mechanism and offer guidance for designing sinter-resistant catalysts by engineering the support morphology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Design Principles for the Synthesis of Self-Pillared ZSM-5 Zeolite Nanosheets

The design of next-generation materials for emerging energy and environmental applications heavily relies on empirical approaches to direct nonclassical nucleation and crystal growth pathways, polymorphism, intercrystalline transformations, and seed-assisted growth processes. A long-standing obstacle to nanoporous materials design is the complexity of their crystallization, which hinders the development of predictive models and/or physical descriptors that can guide their synthesis. In this study, we use a combination of state-of-the-art synthesis, characterization, and computational design to prepare hierarchical MFI-type zeolites, which we couple with benchmark catalytic testing to assess structure-property-performance relationships. These hierarchical materials are intergrowths of two commercially relevant zeolite frameworks, MFI and MEL, prepared as self-pillared pentasil (SPP) zeolites through seed-assisted, organic-free syntheses for which little theoretical guidance existed. Here, by comparing a large library of zeolite seeds with different pore sizes, dimensions, and structural composite building units, we determined the relative impact of seed and silica source selection, among other synthesis variables. Combined experimental and computational studies are used to test several hypotheses in literature to rationalize the choice of seed structure and establish a more robust selection criteria for seed-assisted synthesis of zeolites. Specifically, we show that a data-driven approach to develop structural descriptors correlates to new, facile routes to rationally design SPP zeolites, addressing knowledge gaps in the fundamental understanding of (non)classical crystal growth mechanisms that are characteristic of nanoporous aluminosilicates.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Why Seeding Works When Nucleation Barriers Vanish

Crystallization is a process governed by the interplay between nucleation and growth. While crystalline seeds are known to reduce nucleation barriers and accelerate crystallization under nucleation-limited conditions, their influence when nucleation is not the limiting step remains poorly understood. This creates a mechanistic puzzle in systems where nucleation barriers are already negligible, yet seeding still accelerates crystallization. Here, the synthesis of zeolites is a quintessential example of growth-limited crystallization in which seeds accelerate the process despite negligible homogeneous nucleation barriers. Using coarse-grained molecular dynamics simulations─validated across two zeolites and the unrelated case of ice crystallization─we establish that growth-limited crystallization produces many small, misoriented crystallites whose slow coarsening into larger domains controls the emergence of X-ray-detectable crystallinity. Local crystalline order, structural coherence, and X-ray detectability are therefore kinetically decoupled milestones: the first can be reached rapidly while the latter two lag significantly. Seeds resolve this lag by imposing a common orientational registry on nascent crystallites, enabling their coherent coalescence into large seed-bound domains. This early coherence-building step produces a crystallite-size asymmetry that accelerates subsequent coarsening, advancing the onset of X-ray-detectable crystallinity without necessarily increasing the nucleated fraction. We conclude that under growth-limited conditions, the apparent induction period observed in powder X-ray diffraction reflects the time required to build long-range coherence, not the time to form crystalline material. Accordingly, seeds function not primarily by reducing nucleation barriers but by enforcing spatial coherence, thereby shortening the time required to develop long-range order detectable by X-ray diffraction.

Growth-Limited Crystallization↗
DOE OSTI2025

Designing Peptide Fossils That Model the Evolution of the Bacterial Ferredoxin Fold

Electron transfer coupled to redox chemistry is at the heart of metabolism. The proteins responsible for moving electrons (protein electron carriers) must have emerged at the origin of life. The small iron–sulfur-binding bacterial ferredoxins were likely among these first proteins. Embedded within the ferredoxin sequence and structure is a symmetry that points to an ancient gene duplication event. Little is understood about the nature of ferredoxins prior to this duplication event or what environmental factors may have driven the selection for more complex forms. The deep-time molecular history of ferredoxins goes back billions of years and cannot be reconstructed by phylogenetic analyses based on amino acid sequences. Here, we use structure-guided protein design to model a fossil half-ferredoxin stage in the evolution of this fold, the semidoxins, and their symmetric full-length counterparts, the symdoxins. Semidoxin designs homodimerize, exhibiting structural, thermodynamic, and electrochemical behaviors in most cases identical to cognate symdoxins. However, the semi- and symdoxin fossil stages behave differently when incorporated into an in vivo electron transfer complementation assay. Both can support bacterial growth dependent on protein expression. Growth rates of bacteria expressing the semidoxins are much more sensitive to oxygen than those of bacteria expressing symdoxins. Motivated by the in vivo functionality of designed semidoxins, we identified putative naturally occurring semidoxins in extant anaerobic microorganisms. This is consistent with the observed in vivo oxygen sensitivity of the semidoxin designs. One natural semidoxin is shown to be folded and redox active. However, it exists as a mixture of monomers and dimers, suggesting a potential connection between semidoxins and even simpler single iron–sulfur cluster-binding peptides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Increasing Mosquito Abundance Under Global Warming

Mosquitoes are a key virus vector that poses significant health threats globally, affecting 700 million individuals and causing 1 million deaths annually. Accurately predicting mosquito abundance and dispersion remains a challenge. Complex interactions between mosquito dynamics and various environmental factors, notably hydrology, contribute to this challenge. Existing models typically focus on precipitation and temperature and often overlook further impacts of hydrological variables within mosquito modeling. In this study, we developed an artificial intelligence‐based model for mosquito dynamics, explicitly accounting for different hydrological variables, such as precipitation, soil moisture and streamflow. Using Toronto, Canada, as a case study, we identified causal relationships between changes in mosquito populations, hydrological factors, vegetation (e.g., leaf area index), and climate variables (e.g., daylight length, precipitation, and temperature). We embedded these relationships into a Long Short‐Term Memory (LSTM) Neural Network Model capable of accurately detecting mosquito dynamics across annual, seasonal, and monthly time scales. The LSTM is able to explain, on average, approximately 40% of the variance in the observed mosquito abundance data. Using the calibrated model, we predicted that the summer season mosquito abundance would increase by ∼16% and ∼19% under an intermediate greenhouse emission scenario, Shared Socioeconomic Pathway (SSP) 2–4.5, and a high greenhouse emission scenario, SSP5‐8.5, respectively. We expect that this model can serve as a valuable tool and inform science‐based decisions affecting mosquito dynamics and public health. It can also build a foundation for future risk analysis at the regional and larger scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Developing Scenario‐Based Strategies for Health, Climate, and Environmental Preparedness: The One Health, One Earth Approach

Climate change amplifies many threats to human health. Despite advances in understanding climate change dynamics and impacts, there remains a critical gap in translating scientific knowledge into equitable, and community-driven health interventions. The inaugural One Earth, One Health workshop sought to explore this gap through human-centered design exercises involving interdisciplinary researchers from climate and Earth sciences, engineering, epidemiology, microbiology, and environmental health. Although participants did not co-develop solutions with affected communities, they used stakeholder role-playing to guide ideation and lay groundwork for actionable plans. Through these methods, participants identified community needs and proposed prototype solutions to alleviate health threats exacerbated by global environmental change. Prototypes were organized around infectious diseases, extreme weather, and air quality, as illustrative themes rather than an exhaustive set of risks. Key solutions included strategies for anticipatory systems and early warning (e.g., integrating environmental signals with health data), inclusive communication and infrastructure needs for responding to extreme weather events, and integrated platforms visualizing air quality trends to support tailored, context-aware guidance beyond one-size-fits-all alerts. The workshop highlighted opportunities such as leveraging machine learning, Earth observation, and real-time surveillance to protect communities, but also noted barriers including data quality, technological redundancy, privacy, and governance challenges. Additionally, participants emphasized the need for interdisciplinary teams capable of collaborating across sectors, breaking down silos and addressing gaps in training and education. Overall, the workshop illustrates how process-driven, human-centered approaches can help surface user needs and generate testable prototype concepts, while underscoring the importance of direct community partnership for implementation.

Abadi, Azar M. [University of Alabama, Birmingham,↗
DOE OSTI2025

Microphysics Dominates Sub‐Cloud Rain Evaporation in Trade Cumuli Over Barbados

This study investigates the microphysical and thermodynamic influences on North Atlantic trade-cumulus rain evaporation in the sub-cloud layer over Barbados from January to November 2020. Using radar observations and a 1-D model, the results reveal that microphysical properties, namely geometric mean diameter (D g ) and raindrop concentration, primarily control evaporation processes under conditions of limited thermodynamic variability. Thermodynamic factors like cloud base height and relative humidity exert a smaller influence due to their narrow observed ranges. Small D g leads to rapid increases in rain evaporation fraction (REF), as small drops evaporate completely, while larger D g yields slower, more gradual REF changes. Frequent weak-rain cases reduce the mean evaporation flux, whereas infrequent intense-rain events substantially enhance it. These findings highlight the pivotal role of microphysical variability in shaping sub-cloud evaporation in this trade cumulus regime, while thermodynamic effects may be more important in other environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ELM‐MOSART‐DOC: A Large‐Scale Riverine Dissolved Organic Carbon Model and Its Application Over the United States

Riverine dissolved organic carbon (DOC), primarily sourced from soil organic carbon (SOC), plays a crucial role in regional and global carbon cycles. However, the complexities of the underlying mechanisms and limited observations present significant challenges for predictive understanding of DOC at regional or larger scales. Recently, we developed a machine learning‐based (ML) map of DOC transformation rates, bridging the gap between SOC and DOC leaching flux and simplifying terrestrial DOC representation. Building on this advancement, we introduce ELM‐MOSART‐DOC, a DOC module integrated into the riverine component of the Energy Exascale Earth System Model (E3SM)—the Model for Scale Adaptive River Transport (MOSART). ELM‐MOSART‐DOC simulates DOC transport and transformation across both headwater streams and river networks, including those managed. Model validation demonstrates the ability of ELM‐MOSART‐DOC to accurately capture long‐term average DOC concentrations, with Kling‐Gupta Efficiency (KGE) scores of 0.58 and 0.76 at large and local stations, respectively. We further assess the impact of reservoirs through different simulation schemes, revealing that reservoirs significantly alter DOC fluxes by regulating streamflow patterns and promoting DOC mineralization. Model simulations indicate that reservoirs reduce total DOC flux from the Mississippi River into the ocean by 7.5%, with the long‐term average annual export decreasing from 3.34 to 3.14 teragrams (Tg) per year. ELM‐MOSART‐DOC integrates process‐based modeling with ML parameterization to enhance the predictive understanding of riverine biogeochemical processes. This approach reduces uncertainties in modeling regional and global carbon cycle ESMs and provides new insights into carbon cycling and its implications for global environmental change.

Li, Lingbo [Univ. of Houston, TX (United States); ↗
DOE OSTI2025

Spin correlations in the nematic quantum disordered state of FeSe

The quantum-disordered state in FeSe, intertwined with superconductivity and nematicity, has been a research focus in iron-based superconductors. However, the intrinsic spin excitations across the entire Brillouin zone in detwinned FeSe, crucial for understanding its magnetism and superconductivity, have remained unresolved. Using inelastic neutron scattering, we reveal that stripe spin excitations (Q = (1, 0)/(0, 1)) exhibit the C 2 symmetry, while Néel spin excitations (Q = (1, 1)) retain C 4 symmetry within the nematic state. Temperature-dependent differences between Q = (1, 0) and (0, 1) spin excitations above the structural transition unambiguously reveals the nematic quantum disordered state. Comparison with NaFeAs suggests the Néel excitations originate from enhanced 3d xy orbital correlations. Modeling the stripe dispersions using a J 1 -K-J 2 Heisenberg Hamiltonian, we establish a spin-interaction phase diagram, positioning FeSe near a crossover regime between the antiferroquadrupolar, Néel, and stripe orders. Our results provide key insights into the microscopic spin interactions and their role in the intertwined orders in iron-based superconductors.

Electronic properties and materials↗
DOE OSTI2025

Field-resilient supercurrent diode in a multiferroic Josephson junction

The research on supercurrent diodes has surged rapidly due to their potential applications in electronic circuits at cryogenic temperatures. To unlock this functionality, it is essential to find supercurrent diodes that can work consistently at zero magnetic field and under ubiquitous stray fields generated in electronic circuits. However, a supercurrent diode with robust field tolerance is currently lacking. Here, we demonstrate a field-resilient supercurrent diode by incorporating a 2D multiferroic material into a Josephson junction, and observed a pronounced supercurrent diode effect at zero magnetic field. More importantly, the supercurrent rectification persists over a wide and bipolar magnetic field range beyond industrial standards for field tolerance. By theoretically modeling a multiferroic Josephson junction, we unveil that the interplay between spin-orbit coupling and multiferroicity underlies the unusual field resilience of the observed diode effect. This work introduces multiferroic Josephson junctions as a new field-resilient superconducting device for cryogenic electronics.

Yang, Hung-Yu [Univ. of California, Los Angeles, C↗
DOE OSTI2025

Terahertz-field activation of polar skyrons

Unraveling collective modes arising from coupled degrees of freedom is crucial for understanding complex interactions in solids and developing new functionalities. Unique collective behaviors emerge when two degrees of freedom, ordered on distinct length scales, interact. Polar skyrmions, three-dimensional electric polarization textures in ferroelectric superlattices, disrupt the lattice continuity at the nanometer scale with nontrivial topology, leading to previously unexplored collective modes. Here, using terahertz-field excitation and femtosecond x-ray diffraction, we discover subterahertz collective modes, dubbed “skyrons”, which appear as swirling patterns of atomic displacements functioning as atomic-scale gearsets. The key to activating skyrons is the use of the THz field that couples primarily to skyrmion domain walls. Momentum-resolved time-domain measurements of diffuse scattering reveal an avoided crossing in the dispersion relation of skyrons. Atomistic simulations and dynamical phase-field modeling provide microscopic insights into the three-dimensional crystallographic and polarization dynamics. The amplitude and dispersion of skyrons are demonstrated to be controlled by sample temperature and electric-field bias. The discovery of skyrons and their coupling with terahertz fields opens avenues for ultrafast control of topological polar structures.

ferroelectrics↗
DOE OSTI2025

Atmospheric-pressure ammonia synthesis on AuRu catalysts enabled by plasmon-controlled hydrogenation and nitrogen-species desorption

The Haber–Bosch process for ammonia synthesis contributes up to ~3% of global greenhouse gas emissions. Plasmonic catalysts strongly concentrate light and can alter the reaction intermediates via out-of-equilibrium processes, providing the potential for an alternative, less-energy-intensive pathway to synthesize ammonia. Here, in this study, we show that gold-ruthenium (AuRu) bimetallic nanoparticles can synthesize ammonia at room temperature and pressure using visible light. We create AuRu alloys with varying compositions and achieve ammonia production rates of ~60 μmol per gram of catalyst bed per hour. In situ infrared spectroscopy reveals that light accelerates the hydrogenation of nitrogen intermediates compared to conventional thermal catalysis. Through computational modelling, we demonstrate that photo-excited electrons enable associative hydrogenation pathways for nitrogen activation rather than direct nitrogen–nitrogen bond breaking. This light-assisted mechanism requires both hydrogen and light working together to overcome the nitrogen activation barrier, mimicking how biological enzymes produce ammonia naturally and providing fundamental insights for developing sustainable, energy-efficient chemical synthesis.

Yuan, Lin [Stanford Univ., CA (United States)] (OR↗
DOE OSTI2025

Robust supermoiré pattern in large-angle single-twist bilayers

Forming long-wavelength moiré superlattices in van der Waals bilayers that have a small-angle twist between the two layers has been a key approach for creating moiré flat bands. However, for small twist angles, strong lattice reconstruction creates domain walls and other forms of disorder in the moiré pattern, posing considerable challenges for engineering such platforms. At large twist angles, the lattices are more rigid, but it is difficult to produce flat bands in shorter-wavelength moiré superlattices. Here, in this study, we introduce an approach for tailoring robust supermoiré structures in bilayers of transition-metal dichalcogenides using only a single twist near a commensurate angle. Structurally, we show the spontaneous formation of a periodic arrangement of three inequivalent commensurate moiré stackings, where the angle deviation from the commensurate angle determines the periodicity. Electronically, we reveal a large set of van Hove singularities that indicate strong band hybridization, leading to flat bands near the valence band maximum. Our study extends the study of the interplay among band topology, quantum geometry and moiré superconductivity to the large twist angle regime.

electronic properties and materials↗
DOE OSTI2025

Field-tunable valley coupling in a dodecagonal semiconductor quasicrystal

Quasicrystals are characterized by atomic arrangements having long-range order without periodicity. Van der Waals bilayers provide an opportunity to controllably vary the atomic alignment between two layers from a periodic moiré crystal to an aperiodic quasicrystal. Here, in this work, we reveal that in a dodecagonal WSe 2 quasicrystal, two separate valleys in separate layers are brought arbitrarily close in momentum space through higher-order Umklapp scatterings. A modest perpendicular electric field is then sufficient to induce strong interlayer valley hybridization, manifested as another hybrid excitonic doublet. Concurrently, we observe the disappearance of the trion that exists at low field, which we attribute to a modified spatial distribution of the wavefunction due to the quasicrystal potential. This is possibly a precursor to localization. Our findings highlight the ability of incommensurate systems to bring any pair of momenta into close proximity, thereby introducing opportunities for valley engineering.

electronic properties and materials↗
DOE OSTI2026

Integrated fluorescence light microscopy-guided cryo-focused ion beam-milling for in situ montage cryo-ET

Cryogenic-electron tomography (cryo-ET) permits the in situ visualization of biological macromolecules at the molecular level. Owing to the variable thickness of cells, tissues and organisms, frozen specimens may need to be thinned by cryo-focused ion beam (FIB) milling to produce thin (<500 nm) cryo-lamellae suitable for cryo-ET. Locating regions of interest remains a challenge because untargeted milling can lead to inadvertent ablation and removal of regions of interest. Correlative light and electron microscopy, combined with cryo-FIB milling, can guide the identification of labeled targets in the cellular milieu. Multiple transfers between cryo-imaging instruments, cumbersome correlation algorithms, limited accuracy and low throughput have hindered the routine adoption of cryo-FIB milling within a multimodal correlative workflow for in situ structural biology. Here, in this study, we present a workflow for 3D correlative cryo-fluorescence light microscopy-FIB-ET that streamlines fluorescence light microscopy-guided FIB milling, improving throughput while preserving both structural and contextual information. The complete integration of hardware and software described here minimizes sample contamination from cross-platform exchanges and greatly enhances the efficiency of 3D targeting in cryo-milling. We then describe procedures for implementing montage parallel array cryo-ET (MPACT), which can be easily adapted to any modern life-science transmission electron microscope. MPACT supports high-throughput cryo-ET acquisitions (10 tilt series in 1.5 h) for structure determination and comprehensive contextual understanding of macromolecules within their native surroundings. A complete session from sample preparation to MPACT data processing takes 5−7 d for an individual experienced in both cryo-EM and cryo-FIB milling.

Yang, Jie E. [Univ. of Wisconsin, Madison, WI (Uni↗