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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 19 records
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2025

Test Results of the LQXFA/B02 and LQXFA/B03 Cryo-Assemblies for the High Luminosity LHC Upgrade

Here, the US High-Luminosity LHC Accelerator Upgrade Project (AUP) is responsible for delivering cryo-assemblies for the Q1/Q3 quadrupole optical components of the High Luminosity LHC upgrade at CERN. Total of 10 cryo-assemblies containing two Nb3Sn quadrupole magnets per cold mass will be delivered within this program. After the successful test of the first pre-series cryo-assembly in 2023, two more cryo-assemblies were tested at Fermilab's horizontal test facility. Production overview and the test results of the LQXFA/B02 and LQXFA/B03 cryo-assemblies are summarized in this paper. After the first test, to increase the capability of the horizontal test facility, various improvements have been made. These improvements are also described in this paper.

Chlachidze, Guram [Fermi National Accelerator Labo↗
DOE OSTI2026

Freeze It or Leave It? Evaluating the Role of Cryo-Electron Microscopy in Battery Research

Cryogenic electron microscopy (cryo-EM) continues to gain prominence in materials science, particularly in battery research where it has enabled high-resolution, multimodal characterization of electrode materials and interfaces that otherwise degrade quickly under electron beam irradiation. But as anyone who has attempted cryo-EM techniques knows, freezing comes at a cost; cryo-EM experiments are time-consuming, highly sensitive, and carry an increased risk of artifacts due to issues such as frost contamination. Thus, when planning new characterization of battery materials or other beam-sensitive samples, it is critical to consider whether (and which) cryo-EM techniques are appropriate, based on study goals and an understanding of electron beam-sample interactions. Here we review such considerations for battery materials to elucidate the questions of when, why, and how to freeze to achieve high-quality characterization.

25 ENERGY STORAGE↗
DOE OSTI2025

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗
DOE OSTI2025

Cryo-EM Visualization of Intermolecular π-Electron Interactions within π-Conjugated Peptidic Supramolecular Polymers

The self-assembly of “π-peptides” – molecules with π-electron cores substituted with two or more oligopeptide chains – brings organic electronic function into biologically relevant nanomaterials. π-Peptides assemble into fibrillar nanomaterials as driven by enthalpic peptide-based hydrogen bonding networks and pi-core-based quadrupolar interactions. A large body of spectroscopic, morphological and computational studies informs on the nature of the self-assembly process and the resulting nanostructures, but detailed structural information has remained elusive. Here, inspired by the recent use of cryogenic electron microscopy (cryo-EM) to provide high-resolution structures for synthetic peptide nanomaterials, we present here the use of cryo-EM to offer ca. 3 Å resolution of π-peptide nanomaterial assemblies, visualizing for the first time the nature of the intermolecular π-core electronic interactions responsible for energy transport through these supramolecular materials.

Group theory↗
DOE OSTI2024

Difficult Measurements of Materials Systems at Cryogenic Temperatures: Cryo-EELS and Cryo-4D-STEM

Scanning/transmission electron microscopy (S/TEM) in materials science has traditionally been accomplished at room temperature due to their solid state in this temperature range and relative insensitivity to radiolysis damage. Cooling to cryogenic temperatures tended to introduce instabilities such as vibration and drift and can lead to the buildup of carbon contamination or ice reducing contrast. The need to expand TEM experimental techniques into new fields such as quantum and battery materials led to new efforts to reduce these instabilities while achieving temperatures at or well below liquid nitrogen (77 K). Further, developments in detector and spectrometer technology brought new capabilities for high resolution electron energy loss spectroscopy (EELS) and scanning nanodiffraction (4D-STEM). These experimental modalities can require even tighter controls of drift, vibration, and exposure time. Here this presentation will discuss accomplishing difficult experiments at cryogenic temperatures in honor of the late Dr. Lena Kourkoutis who inspired and led many such experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step in the cryo-EM-based structure determination. However, existing methods trained on a limited amount of cryo-EM data still cannot accurately pick protein particles from noisy cryo-EM images. The general foundational artificial intelligence–based image segmentation model such as Meta’s Segment Anything Model (SAM) cannot segment protein particles well because their training data do not include cryo-EM images. Here, we present a novel approach (CryoSegNet) of integrating an attention-gated U-shape network (U-Net) specially designed and trained for cryo-EM particle picking and the SAM. The U-Net is first trained on a large cryo-EM image dataset and then used to generate input from original cryo-EM images for SAM to make particle pickings. CryoSegNet shows both high precision and recall in segmenting protein particles from cryo-EM micrographs, irrespective of protein type, shape and size. On several independent datasets of various protein types, CryoSegNet outperforms two top machine learning particle pickers crYOLO and Topaz as well as SAM itself. The average resolution of density maps reconstructed from the particles picked by CryoSegNet is 3.33 Å, 7% better than 3.58 Å of Topaz and 14% better than 3.87 Å of crYOLO. It is publicly available at https://github.com/jianlin-cheng/CryoSegNet

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

CryoTEN: efficiently enhancing cryo-EM density maps using transformers

Abstract Motivation Cryogenic electron microscopy (cryo-EM) is a core experimental technique used to determine the structure of macromolecules such as proteins. However, the effectiveness of cryo-EM is often hindered by the noise and missing density values in cryo-EM density maps caused by experimental conditions such as low contrast and conformational heterogeneity. Although various global and local map-sharpening techniques are widely employed to improve cryo-EM density maps, it is still challenging to efficiently improve their quality for building better protein structures from them. Results In this study, we introduce CryoTEN—a 3D UNETR++ style transformer to improve cryo-EM maps effectively. CryoTEN is trained using a diverse set of 1295 cryo-EM maps as inputs and their corresponding simulated maps generated from known protein structures as targets. An independent test set containing 150 maps is used to evaluate CryoTEN, and the results demonstrate that it can robustly enhance the quality of cryo-EM density maps. In addition, automatic de novo protein structure modeling shows that protein structures built from the density maps processed by CryoTEN have substantially better quality than those built from the original maps. Compared to the existing state-of-the-art deep learning methods for enhancing cryo-EM density maps, CryoTEN ranks second in improving the quality of density maps, while running >10 times faster and requiring much less GPU memory than them. Availability and implementation The source code and data are freely available at https://github.com/jianlin-cheng/cryoten.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Progress in the development of an ultrafast pulsed ponderomotive phase plate for cryo-electron tomography

Cryo-electron tomography (cryo-ET) is a powerful modality for resolving cellular structures in their native state. While single-particle cryo-electron microscopy excels in determining protein structures purified from recombinant or endogenous sources due to an abundance of particles, weak contrast issues are accentuated in cryo-ET by low copy numbers in crowded cellular milieux. Continuous laser phase plates offer improved contrast in cryo-ET; however, their implementation demands exceptionally high-peak optical intensities. Instead, a novel experimental approach to enhance contrast in cryo-ET is to manipulate the phase of scattered pulsed electrons using ultrafast pulsed photons. Here, we outline the experimental design of a proof-of-concept electron microscope and demonstrate synchronization between electron packets and laser pulses. Furthermore, we show ultrabright photoemission of electrons from an alloy field emission tip using femtosecond ultraviolet pulses. These experiments pave the way toward exploring the utility of the ponderomotive effect using pulsed radiation to increase phase contrast in cryo-ET of subcellular protein complexes in situ, thus advancing the field of cell biology.

Du, Daniel X. [Columbia Univ., New York, NY (Unite↗
DOE OSTI2024

Artificial intelligence in cryo-EM protein particle picking: recent advances and remaining challenges

Abstract Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of high-resolution 3-Dimensional (3D) structures of large biological macromolecules. Protein particle picking, the process of identifying individual protein particles in cryo-EM micrographs for building protein structures, has progressed from manual and template-based methods to sophisticated artificial intelligence (AI)-driven approaches in recent years. This review critically examines the evolution and current state of cryo-EM particle picking methods, with an emphasis on the impact of AI. We conducted a comparative evaluation of popular AI-based particle picking methods, using both general machine learning metrics and specific cryo-EM structure determination metrics. This analysis involved constructing the 3D density map from the picked protein particles and assessing the obtained resolution and particle orientation diversity, underscoring the significant impact of AI on cryo-EM particle picking. Despite the advancements, we also identified key obstacles, such as handling complex micrographs with small proteins. The analysis provides insights into the future development of more sophisticated and fully automated AI methods in cryo-EM particle recognition.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Investigating intermolecular interactions among CO 2 , water and PEEK-ionene membrane using cryo ToF-SIMS and isotopic labeling

Cryogenic time-of-flight secondary ion mass spectrometry (cryo ToF-SIMS) has emerged as a powerful tool for investigating molecular interactions, speciation, and dynamics in materials for CO 2 capture. In this study, we apply cryo ToF-SIMS to probe interactions between CO 2 , water, and PEEK-ionene membranes—a promising material for direct CO 2 capture due to its selectivity, durability, and efficiency. Despite this potential, the mechanisms governing CO 2 diffusion and the influence of water vapor on CO 2 behavior remain unclear. To address this, we loaded PEEK-ionene membranes with 13 CO 2 and D 2 O and employed cryo ToF-SIMS to visualize the 3D distribution of CO 2 and water within the membrane. While prior studies suggest that 13 CO 2 is absorbed under ambient conditions, our cryo ToF-SIMS analysis revealed no enhancement of the 13 C/ 12 C ratio, suggesting weak CO 2 -membrane interactions. As a result, CO 2 vaporizes even at low temperatures (−140°C) under vacuum conditions. In contrast, D 2 O displayed a relatively homogeneous distribution in the membrane, suggesting stronger water-membrane interactions via hydrogen bonding (18–20 kJ/mol). Interestingly, CO 2 was not detected in D 2 O-loaded membranes, indicating minimal interference from water vapor on CO 2 diffusion. As a comparison, the cryo ToF-SIMS data show that 13 CO 2 can readily react with a basic Na 2 CO 3 aqueous solution to form NaH 13 CO 3 . These findings demonstrate cryo ToF-SIMS as a critical technique for understanding gas-water-membrane interactions, offering insights for membrane functionalization to improve CO 2 capture efficiency.

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

Test results of the LQXFA/B02 and LQXFA/B03 cryo-assemblies for the High Luminosity LHC upgrade

The US High-Luminosity LHC Accelerator Upgrade Project (AUP) is responsible for delivering cryo-assemblies for the Q1/Q3 quadrupole optical components of the High Luminosity LHC upgrade at CERN. Total of 10 cryo-assemblies containing two Nb3Sn quadrupole magnets per cold mass will be delivered within this program. After the successful test of the first pre-series cryo-assembly in 2023, two more cryo-assemblies were tested at Fermilab’s horizontal test facility. Production overview and the test results of the LQXFA/B02 and LQXFA/B03 cryo-assemblies are summarized in this paper. After the first test, to increase the capability of the horizontal test facility, various improvements have been made. These improvements are also described in this paper.

Chlachidze, Guram [Fermilab]↗
DOE OSTI2024

Quantitative Analysis of Rhodobacter sphaeroides Storage Organelles via Cryo-Electron Tomography and Light Microscopy

Bacterial cytoplasmic organelles are diverse and serve many varied purposes. Here, we employed Rhodobacter sphaeroides to investigate the accumulation of carbon and inorganic phosphate in the storage organelles, polyhydroxybutyrate (PHB) and polyphosphate (PP), respectively. Using cryo-electron tomography (cryo-ET), these organelles were observed to increase in size and abundance when growth was arrested by chloramphenicol treatment. The accumulation of PHB and PP was quantified from three-dimensional (3D) segmentations in cryo-tomograms and the analysis of these 3D models. The quantification of PHB using both segmentation analysis and liquid chromatography and mass spectrometry (LCMS) each demonstrated an over 10- to 20-fold accumulation of PHB. The cytoplasmic location of PHB in cells was assessed with fluorescence light microscopy using a PhaP-mNeonGreen fusion-protein construct. The subcellular location and enumeration of these organelles were correlated by comparing the cryo-ET and fluorescence microscopy data. A potential link between PHB and PP localization and possible explanations for co-localization are discussed. Finally, the study of PHB and PP granules, and their accumulation, is discussed in the context of advancing fundamental knowledge about bacterial stress response, the study of renewable sources of bioplastics, and highly energetic compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Bacteria rapidly adapt to environmental cues through morphological and ultrastructural changes that correlate with physiology and behavior. Cryogenic transmission electron microscopy (cryo‐TEM) can capture these phenotypic changes in near‐native, vitrified states, but manual analysis of low‐dose micrographs is labor intensive and limits throughput. Here, we present an end‐to‐end workflow that combines low‐dose cryo‐TEM imaging with a YOLOv11‐based instance‐segmentation model to automatically identify bacteria and quantify key structural features directly from the micrographs. This workflow enables (i) robust bacterial localization and counting from low‐magnification atlas/montage images, (ii) automated measurements of cell‐envelope (outer–inner membrane) thickness and anisotropy from higher‐magnification views, and (iii) detection and quantification of bacteria–flagella interactions, including overlap length and curvature metrics for interacting versus noninteracting flagella. Using Pantoea sp. YR343 grown under distinct media conditions, we show that the automated measurements agree with manual annotations while substantially reducing analysis time. Together, these tools provide a practical framework for scalable bacterial identification and quantitative phenotyping in low‐dose cryo‐TEM datasets and establish a foundation for extending cryo‐TEM image analysis toward higher‐throughput studies of microbial heterogeneity and biointerfaces.

YOLOv11↗
DOE OSTI2024

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PhaseT3M: 3D imaging at 1.6 Å resolution via electron cryo-tomography with nonlinear phase retrieval

Electron cryo-tomography (cryo-ET) enables 3D imaging of complex, radiation-sensitive structures with molecular detail. However, image contrast from the interference of scattered electrons is nonlinear with atomic density and multiple scattering further complicates interpretation. These effects degrade resolution, particularly in conventional reconstruction algorithms, which assume linearity. Particle averaging can reduce such issues but is unsuitable for heterogeneous or dynamic samples ubiquitous in biology, chemistry, and materials sciences. Here, we develop a phase retrieval-based cryo-ET method, PhaseT3M. We experimentally demonstrate its application to an approximately 7 nm Co3O4 nanoparticle on an approximately 30 nm carbon substrate, achieving a maximum resolution of 1.6 Å, surpassing conventional limits using standard cryo-TEM equipment. PhaseT3M uses a multislice model for multiple scattering and Bayesian optimization for alignment and computational aberration correction, with a positivity constraint to recover ‘missing wedge’ information. Applied directly to biological particles, it enhances reconstruction quality and reduces artifacts, establishing a standard for routine 3D imaging with phase contrast.

Biophysics↗
DOE OSTI2024

CryoTRANS: predicting high-resolution maps of rare conformations from self-supervised trajectories in cryo-EM

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Lessons from Testing the First Three US HL-LHC Cryo-Assemblies at FNAL

The US High-Luminosity LHC Accelerator Upgrade Project (AUP) collaborates with CERN to deliver 10 cryo-assemblies for the High-Luminosity LHC upgrade at CERN. Those comprise the Q1/Q3 quadrupole optical elements in the accelerator and are based on Nb3Sn technology, for the first time in a large particle accelerator. So far three cryo-assemblies were tested at the Fermilab’s horizontal magnet test facility, specifically redesigned to serve those needs. This work gives an overview of the facility and its necessary evolution as the campaign progressed; main results and observations from the cryo-assembly tests are presented and discussed in the context of overall performance and expectations toward the completion of efforts. Lessons learned after multiple cryo-assembly tests by the same team are critical to ensure continuous success of the whole enterprise – those are openly shared.

Stoynev, Stoyan [Fermilab]↗