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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Surface measurements of solar irradiance: A study of the spatial correlation between simultaneous measurements at separated sites

Pyranometers have been used for many years to measure broadband surface incoming solar irradiance, data that is necessary for surface energy budget, cloud forcing, and satellite validation research. Because such measurements are made at a specific location, it is unclear how representative they may be of a larger area. This study attempts to determine a reasonable spacing between measurement sites for such research by computing the correlation, and standard deviation from perfect correlation, between simultaneous measurements of incoming solar irradiance for a network of surface measurement sites covering a 75 km x 75 km area. Using 1-min data collected from this network of 11 sites during the NASA First ISSCP Radiation Experiment/Surface Radiation Budget (FIRE/SRB) Project temporal averages were calculated. The correlation between any two of these sites was determined by comparing simultaneous measurement averages for the 55 possible combinations of site pairs, along with the distances between them. In an attempt to remove the effect of the diurnal cycle, thus leaving clouds as the primary influence on correlation of the radiation field, model results for a clear day were used to normalize measured irradiances and correlations were again calculated.

Long, Charles N.↗
DOE OSTI2024

Nanoscale structural correlations in a model cuprate superconductor

Understanding the extent and role of inhomogeneity is a pivotal challenge in the physics of cuprate superconductors. While it is known that structural and electronic inhomogeneity is prevalent in the cuprates, it has proven difficult to disentangle compound-specific features from universally relevant effects. Here, in this study, we combine advanced neutron and x-ray diffuse scattering with numerical modeling to obtain insight into bulk structural correlations in HgBa 2 ⁢ CuO 4+δ . This cuprate exhibits a high optimal transition temperature of nearly 100 K, pristine charge-transport behavior, and a simple average crystal structure without long-range structural instabilities, and is therefore uniquely suited for investigations of intrinsic inhomogeneity. We uncover diffuse reciprocal-space patterns that correspond to prominent nanoscale correlations of atomic displacements perpendicular to the CuO 2 planes. The real-space nature of the correlations is revealed through three-dimensional pair distribution function analysis and complementary numerical refinement. We find that relative displacements of ionic and CuO 2 layers play a crucial role, and that the structural inhomogeneity is not directly caused by the presence of conventional point defects. The observed correlations are therefore intrinsic to HgBa 2 ⁢ CuO 4+δ , and thus likely important for the physics of cuprates more broadly. It is possible that the structural correlations are closely related to the unusual superconducting fluctuations and Mott-localization in these complex oxides. As advances in scattering techniques yield increasingly comprehensive data, the experimental and analysis tools developed here for large volumes of diffuse scattering data can be expected to aid future investigations of a wide range of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Glomerular filtration drug injury: In vitro evaluation of functional and morphological podocyte perturbations

Highlights: • The use of nephrotoxic drugs is often unavoidable. • Human podocyte cell line allows the study of the simplified glomerular filtration. • Filtration perturbations are correlated with morphological and phenotypic changes. • Functional and morphological tests are interesting tools for drug screening. The kidney is an organ that plays a major role in the excretion of numerous compounds such as drugs and chemicals. However, a great number of pharmacological molecules are nephrotoxic, affecting the efficiency of the treatment and increasing morbidity or mortality. Focusing on glomerular filtration, we propose in this study a simple and reproducible in vitro human model that is able to bring to light a functional podocyte injury, correlated with morphologic/phenotypic changes after drug exposure. This model was used for the evaluation of paracellular permeability of FITC-dextran molecules as well as FITC-BSA after different treatments. Puromycin aminonucleoside and adriamycin, compounds known to induce proteinuria in vivo and that serve here as positive nephrotoxic drug controls, were able to induce an important increase in fluorescent probe passage through the cell monolayer. Different molecules were then evaluated for their potential effect on podocyte filtration. Our results demonstrated that a drug effect could be time dependent, stable or scalable and relatively specific. Immunofluorescence studies indicated that these functional perturbations were due to cytoskeletal perturbations, monolayer disassembly or could be correlated with a decrease in nephrin expression and/or ZO-1 relocation. Taken together, our results demonstrated that this in vitro human model represents an interesting tool for the screening of the renal toxicity of drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Empirical correlations for prediction of minimum miscible pressure and near-miscible pressure interval for oil and CO 2 systems

Although near-miscible CO 2 flooding has recently received considerable attention, no criteria are available to predict its applicability to a specific reservoir. Evaluating the viability of near-miscible flooding requires experimental exploration of a specific region in pressure–temperature space. The near-miscible pressure field is bounded on one side in P, T space by the MMP (minimum miscible pressure). This paper provides robust empirical correlations to estimate the MMP for both pure and impure CO 2 and for prediction of the near-miscible pressure region for CO 2 -oil. Many slim tube analyses, lacking high density data points, systematically underestimate the MMP, when the near miscible region is not accounted for. They are based on 147 published data sets that include: slim tube experimental determination of MMP; interfacial tension (IFT) between oil and CO 2 ; concentration of solution gas; and purity of the CO 2 . This paper is the first to begin a systematic exploration of the pressure-temperature space within which near-miscible effects characterize CO 2 floods. Our new correlations provide a basis for identifying and investigating the nature of near miscible effects associated with existing CO 2 floods. For a case study of an offshore field we determined that lower and upper pressure boundaries for effective near-miscible flooding, are 0.87 MMP and 1.07 MMP at reservoir temperatures. The proposed model is the first empirical correlation for the prediction of near-miscible pressure region, it will provide the basis for both screening the relative potential of oil reservoirs for economically viable miscible or near-miscible CO 2 -flooding.

42 ENGINEERING↗
NASA NTRS2022

Uncertainty Models for the Hybrid Parametric Variation Method of Uncertainty Quantification; Analysis

There is some level of uncertainty in every finite element model (FEM), which flows to a level of uncertainty in predicted results. The purpose of uncertainty quantification (UQ) is to provide statistical bounds on prediction accuracy based on model uncertainty. This is distinct from model updating, which attempts to modify models to improve their accuracy. UQ does not improve the accuracy of models, but accepts that the models are inherently inaccurate and attempts to quantify the impact of that inaccuracy on predicted results. Previously, an alternate method for UQ, called the Hybrid Parametric Variation (HPV) method, was applied to Space Launch System (SLS) Hurty/Craig-Bampton (HCB) components to predict system-level statistics for launch vehicle attitude control transfer functions and core stage section loads due to buffet. The HPV method combines a parametric variation of the HCB fixed-interface (FI) modal frequencies with a nonparametric variation (NPV) method that randomly varies the HCB mass and stiffness matrices as Wishart random matrix distributions using random matrix theory (RMT). Alternatively, the most common method for modeling uncertainty in the structural dynamics community is a parametric approach, which varies physical parameters in the model. However, there are several disadvantages associated with the parametric method. Determining a reduced set of parameters that have a significant impact on the system response can be time consuming, and the selected parameter probability distributions are rarely reliably known. Therefore, in practice, the parameters are surrogates for the actual errors, and the link to parameter uncertainty is unknown. Another major drawback is that the uncertainty that can be represented is limited to the form of the nominal FEM. It is the experience of the authors that based on numerous aerospace programs, almost all FEM errors are in form rather than parameter values. This hypothesis is supported by the observation of the authors that it is almost never possible to ‘tune’ a FEM to match modal test results by only modifying model parameters. Model-form uncertainty cannot be directly represented by FEM input parameters nor included in a parametric approach. However, model-form uncertainty can be modeled using RMT, where a probability distribution is developed for the matrix ensemble of interest. The major advantage of the NPV method is that it covers errors in model form. The HPV method anchors uncertainty at the HCB component level to component modal test results by matching the HCB and test modes based on mode descriptions or other methods, and then applying differing levels of frequency variation. The specific variations depend on the confidence to which a component FEM has been validated through modal testing. The NPV method is layered on the frequency variation to match modal test self-orthogonality and cross-orthogonality (XO) results. Once the component uncertainty models are identified, they are assembled, and the uncertainty is propagated to the system level using a Monte Carlo (MC) analysis approach that generates statistics for system-level predictions This provides a UQ method that can be traced to test data, which can be updated as additional data and improved correlated models become available. The purpose of this paper is to collect and present all of the theory for HPV that has been previously published in reports and papers and to present examples of its application. Specifically, component uncertainty models based on the dispersion of corresponding mass and stiffness matrices using proposed test/analysis correlation metrics are investigated. The first example is purely academic so that the true answers are known, and the validity of the HPV method and the corresponding uncertainty models can be determined. The purpose of this paper is to collect and present all of the theory for HPV that has been previously published in reports and papers and to present examples of its application. Specifically, component uncertainty models based on the dispersion of corresponding mass and stiffness matrices using proposed test/analysis correlation metrics are investigated. The first example is purely academic so that the true answers are known, and the validity of the HPV method and the corresponding uncertainty models can be determined. The second example is an application to a component that is design specific to the SLS. Based on this work and other assessments, the HPV method provides another tool to the toolset used for complex system UQ analysis. From experience gathered to date using the HPV method, additional design specific applications must be investigated to provide further confidence in the validity of the HPV method of UQ analysis.

Uncertainty quantification↗
DOE OSTI2015

Transcriptome-Wide Cleavage Site Mapping on Cellular mRNAs Reveals Features Underlying Sequence-Specific Cleavage by the Viral Ribonuclease SOX

Many viruses express factors that reduce host gene expression through widespread degradation of cellular mRNA. An example of this class of proteins is the mRNA-targeting endoribonuclease SOX from the gamma-herpesvirus Kaposi’s sarcoma-associated herpesvirus (KSHV). Previous studies indicated that cleavage of messenger RNAs (mRNA) by SOX occurs at specific locations defined by the sequence of the target RNA, which is at odds with the down-regulation of a large portion of cellular transcripts. In this study, we address this paradox by using high-throughput sequencing of cleavage intermediates combined with a custom bioinformatics-based analysis pipeline to identify SOX cleavage sites across the mRNA transcriptome. These data, coupled with targeted mutagenesis, reveal that while cleavage sites are specific and reproducible, they are defined by a degenerate sequence motif containing a small number of conserved residues rather than a strong consensus sequence. This degenerate element is well represented in both human and KSHV mRNA, and its presence correlates with RNA destabilization by SOX. This represents a new endonuclease targeting strategy, in which use of a degenerate targeting element enables RNA cleavage at specific locations without restricting the range of targets. Furthermore, it shows that strong target selectivity can be achieved without a high degree of sequence specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Nature of peptide wrapping onto metal nanoparticle catalysts and driving forces for size control

Colloidal metal nanocrystals find many applications in catalysis, energy conversion devices, and therapeutics. However, the nature of ligand interactions and implications on shape control have remained uncertain at the atomic scale. Large differences in peptide adsorption strength and facet specificity were found on flat palladium surfaces versus surfaces of nanoparticles of 2 to 3 nm size using accurate atomistic simulations with the Interface force field. Folding of longer peptides across many facets explains the formation of near-spherical particles with local surface disorder, in contrast to the possibility of nanostructures of higher symmetry with shorter ligands. The average particle size in TEM correlates inversely with the surface coverage with a given ligand and with the strength of ligand adsorption. The role of specific amino acids and sequence mutations on the nanoparticle size and facet composition is discussed, as well as the origin of local surface disorder that leads to large differences in catalytic reactivity.

Chemistry↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗
DOE OSTI2025

Role of Electron Correlation beyond the Active Space in Achieving Quantitative Predictions of Spin-Phonon Relaxation

Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as temperature rises, interactions between electronic states and lattice vibrations accelerate spin relaxation, significantly limiting their practical applications. Recently, ab initio simulations have made it possible to advance our understanding of phonon-induced magnetic relaxation, but significant deviations from experiments have often been observed. The description of molecules’ electronic structure has been mostly based on complete active space self-consistent field (CASSCF) calculations, and the impact of electron correlation beyond the active space remains largely unexplored. In this study, we provide the first systematic investigation of spin-phonon relaxation in SMMs with post-CASSCF multiconfigurational methods, specifically CAS followed by second-order perturbation theory and multiconfiguration pair-density functional theory. Taking Co(II)- and Dy(III)-based SMMs as case studies, we analyze how electron correlation influences spin-phonon relaxation rates across a range of temperatures, comparing theoretical predictions with experimental observations. Our findings demonstrate that post-CASSCF treatments make it possible to achieve quantitative predictions for Co(II)-based SMMs. For Dy(III)-based systems, however, accurate predictions require consideration of additional effects, underscoring the urgent necessity of further advancing the study of the effects of electronic correlation in these complex systems.

Energy↗
DOE OSTI2020

Unveiling the strong interaction among hadrons at the LHC

One of the key challenges for nuclear physics today is to understand from first principles the effective interaction between hadrons with different quark content. First successes have been achieved using techniques that solve the dynamics of quarks and gluons on discrete space-time lattices. Experimentally, the dynamics of the strong interaction have been studied by scattering hadrons off each other. Such scattering experiments are difficult or impossible for unstable hadrons and so high-quality measurements exist only for hadrons containing up and down quarks. Here we demonstrate that measuring correlations in the momentum space between hadron pairs produced in ultrarelativistic proton–proton collisions at the CERN Large Hadron Collider (LHC) provides a precise method with which to obtain the missing information on the interaction dynamics between any pair of unstable hadrons. Specifically, we discuss the case of the interaction of baryons containing strange quarks (hyperons). We demonstrate how, using precision measurements of proton–omega baryon correlations, the effect of the strong interaction for this hadron–hadron pair can be studied with precision similar to, and compared with, predictions from lattice calculations. The large number of hyperons identified in proton–proton collisions at the LHC, together with accurate modelling of the small (approximately one femtometre) inter-particle distance and exact predictions for the correlation functions, enables a detailed determination of the short-range part of the nucleon-hyperon interaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Crystallographic analyses illustrate significant plasticity and efficient recoding of meganuclease target specificity

The retargeting of protein–DNA specificity, outside of extremely modular DNA binding proteins such as TAL effectors, has generally proved to be quite challenging. Here, we describe structural analyses of five different extensively retargeted variants of a single homing endonuclease, that have been shown to function efficiently in ex vivo and in vivo applications. The redesigned proteins harbor mutations at up to 53 residues (18%) of their amino acid sequence, primarily distributed across the DNA binding surface, making them among the most significantly reengineered ligand-binding proteins to date. Specificity is derived from the combined contributions of DNA-contacting residues and of neighboring residues that influence local structural organization. Changes in specificity are facilitated by the ability of all those residues to readily exchange both form and function. The fidelity of recognition is not precisely correlated with the fraction or total number of residues in the protein–DNA interface that are actually involved in DNA contacts, including directional hydrogen bonds. The plasticity of the DNA-recognition surface of this protein, which allows substantial retargeting of recognition specificity without requiring significant alteration of the surrounding protein architecture, reflects the ability of the corresponding genetic elements to maintain mobility and persistence in the face of genetic drift within potential host target sites.

Biochemistry & Molecular Biology↗
NASA NTRS2016

Hall Thruster Thermal Modeling and Test Data Correlation

The life of Hall Effect thrusters are primarily limited by plasma erosion and thermal related failures. NASA Glenn Research Center (GRC) in cooperation with the Jet Propulsion Laboratory (JPL) have recently completed development of a Hall thruster with specific emphasis to mitigate these limitations. Extending the operational life of Hall thursters makes them more suitable for some of NASA's longer duration interplanetary missions. This paper documents the thermal model development, refinement and correlation of results with thruster test data. Correlation was achieved by minimizing uncertainties in model input and recognizing the relevant parameters for effective model tuning. Throughout the thruster design phase the model was used to evaluate design options and systematically reduce component temperatures. Hall thrusters are inherently complex assemblies of high temperature components relying on internal conduction and external radiation for heat dispersion and rejection. System solutions are necessary in most cases to fully assess the benefits and/or consequences of any potential design change. Thermal model correlation is critical since thruster operational parameters can push some components/materials beyond their temperature limits. This thruster incorporates a state-of-the-art magnetic shielding system to reduce plasma erosion and to a lesser extend power/heat deposition. Additionally a comprehensive thermal design strategy was employed to reduce temperatures of critical thruster components (primarily the magnet coils and the discharge channel). Long term wear testing is currently underway to assess the effectiveness of these systems and consequently thruster longevity.

Hall thruster↗
DOE OSTI2024

Addressing Critical Problems in Materials Science Through Multiscale and Multimode Characterization (Project 1); Characterization and Optimization of Novel Triple-Conducting Oxide Materials for Energy Applications (Project 2) (CRADA Final Report)

PROJECT 1: Address critical problems in materials science and simultaneously advance the state-of-the-art in multiscale and multimode characterization using the combined advanced analytical capabilities and expertise of Colorado School of Mines (CSM) and the National Renewable Energy Laboratory (NREL). The primary effort of the Phase I of this CRADA is to establish the International Center for Multiscale Characterization using shared resources at both NREL and CSM. Phase II will focus on capability development and marketing, choosing candidate materials science issues in the areas of structure imaging, chemical composition mapping, and correlating properties and performance of materials for impact in energy-related, environmental and critical materials areas. The CRADA will be modified to include specific topics of concern in materials science to industry member partners. Advanced analytical capabilities and expertise at CSM and NREL will be used to advance materials understanding and performance through characterization of multiscale phenomena including structural imaging, chemical composition mapping, and other techniques correlating properties and performance of materials. PROJECT 2: As part of the International Center for Materials Characterization, work under Modification #1 will be led by Colorado School of Mines (CSM), working in collaboration with NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments. The purpose of the modification is to provide for NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments, including mentoring and advising the CSM-NREL team on proper Secondary Ion Mass Spectrometry (SIMS) data analysis as needed. SIMS measurements of 10-20 samples will be performed at NREL during the project duration.

08 HYDROGEN↗
DOE OSTI2015

Opposite correlations between cation disordering and amorphization resistance in spinels versus pyrochlores

Understanding and predicting radiation damage evolution in complex materials is crucial for developing next-generation nuclear energy sources. Here, using a combination of ion beam irradiation, transmission electron microscopy and X-ray diffraction, we show that, contrary to the behaviour observed in pyrochlores, the amorphization resistance of spinel compounds correlates directly with the energy to disorder the structure. Using a combination of atomistic simulation techniques, we ascribe this behaviour to structural defects on the cation sublattice that are present in spinel but not in pyrochlore. Specifically, because of these structural defects, there are kinetic pathways for the relaxation of disorder in spinel that are absent in pyrochlore. This leads to a direct correlation between amorphization resistance and disordering energetics in spinel, the opposite of that observed in pyrochlores. Furthermore, these results provide new insight into the origins of amorphization resistance in complex oxides beyond fluorite derivatives.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Magnetic properties of the spin-3/2 Blume-Capel model on a hexagonal Ising nanowire

Magnetic properties, such as magnetizations, internal energy, specific heat, entropy, Helmholtz free energy, and phase diagrams of the spin-3/2 Blume-Capel model on a hexagonal Ising nanowire with core-shell structure are studied by using the effective-field theory with correlations. The hysteresis behaviors of the system are also investigated and the effects of Hamiltonian parameters on hysteresis behaviors are discussed in detail. The obtained results are compared with some theoretical results and a qualitatively good agreement is found.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Preliminary Assessment of Spatial Competition in the Market for E85

The Preliminary Assessment of Spatial Competition in the Market for E85 presentation and supplementary report from the U.S. Department of Energy’s National Renewable Energy Laboratory examine how the spacing of E85 fueling stations impacts E85 retail pricing. The analysis finds an inverse correlation between station density and E85 prices, with local competition putting downward pressure on E85 prices. A gas station with E85 whose nearest competitor is within a 0.5 mile radius is associated with a lower E85 price per gallon than an otherwise identical station with E85 whose nearest competitor is farther away. The analysis also finds a higher level of correlation between E85 and both E10 and wholesale gasoline prices than with ethanol costs. This indicates that E85 may, in fact, be priced with respect to its substitute fuel, and not based on the cost of its inputs. These findings help identify key trends and barriers in E85 markets and highlight data gaps that, if addressed, could help enable competitive E85 markets. The analysis was released in February 2017 and uses national and Minnesota-specific price data.

E85, retail pricing, vehicles, fuels, fuel station↗
NASA NTRS1994

Associations of Methanotrophs With the Roots and Rhizomes of Aquatic Vegetation

Results of an in vitro assay revealed that root-associated methane consumption was a common attribute or diverse emergent wetland macrophytes from a variety of habitats. Maximum potential uptake rates (V(sub maxp)) varied between about 1 and 10 micro mol g/ (dry weight) h, with no obvious correlation between rate and gross morphological characteristics of the plants. The V(sub maxp) corresponded to about 2 x 10(exp 18) to 2 x 10(exp 9) methanotrophs g/ (dry weight), assuming that root-associated methanotrophs have cell-specific activities comparable to those of known isolates. V(sub maxp) varied seasonally for an aquatic grass, Calamogrostis canadensis, and for the cattail, Typha latifolia, with highest rates in late summer. V(sub maxp) was well correlated with ambient temperature for C. canadensis but weakly correlated for T. Wifolia. The seasonal changes in V(sub maxp), as well as inferences from apparent half-saturation constants for methane uptake (K(sub app); generally 3 to 6 micro M), indicated that oxygen availability might be more important than methane as a rate determinant. In addition, roots incubated under anoxic conditions showed little or no postanoxia aerobic methane consumption, indicating that root-associated metbanotrophic populations might not tolerate variable oxygen availability. Hybridization of oligodeoxynucleotide probes specific for group 1 or group 2 methylotrophs also varied seasonally. The group 2-specific probe consistently hybridized to a greater extent than the group 1 probe, and the relative amount of group 2 probe hybridization to C. canadensis root extracts was positively correlated with V(sub maxp).

King, Gary M.↗
DOE OSTI2026

Imaging from Macro to Nanoscale: Multimodal Advances in Chemical and Biomedical Imaging

Imaging increasingly serves as a multiscale framework for linking molecular mechanisms to cellular behavior, tissue architecture, and organ phenotypes in biology and unraveling fundamental processes in chemistry, physics and materials science. This Perspective highlights recent advances in chemical and biomedical imaging across macro-, micro-, and nanoscales, using representative examples published in Chemical and Biomedical Imaging (CBMI). At the macroscale, we discuss chemically selective MRI, including endogenous and exogenous CEST strategies, together with photoacoustic imaging as a hybrid modality with functional and chemical contrast. At the microscale, we consider fluorescence, label-free optical and vibrational imaging, and selected X-ray approaches that expand sensitivity, specificity, and temporal resolution in biological and materials systems. At the nanoscale, we highlight super-resolution fluorescence microscopy, single-molecule methods, tip-enhanced Raman spectroscopy, and correlative imaging strategies that resolve local heterogeneity and molecular organization. Across scales, a common theme emerges that advances in probes, contrast mechanisms, instrumentation, and sample handling are enabling chemically informed imaging that connects molecular specificity with biological context.

multiscale imaging↗