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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Biomechanical drivers of the evolution of butterflies and moths with a coilable proboscis

Current biomechanical models suggest that butterflies and moths use their proboscis as a drinking straw pulling nectar as a continuous liquid column. Our analyses revealed an alternative mode for fluid uptake: drinking bubble trains that help defeat drag. We combined X-ray phase-contrast imaging, optical video microscopy, micro-computed tomography, phylogenetic models of evolution and fluid mechanics models of bubble-train formation to understand the biomechanics of butterfly and moth feeding. Our models suggest that the bubble-train mechanism appeared in the early evolution of butterflies and moths with a proboscis long enough to coil. We propose that, in addition to the ability to drink a continuous column of fluid from pools, the ability to exploit fluid films by capitalizing on bubble trains would have expanded the range of available food sources, facilitating diversification of Lepidoptera.

Palaoro, Alexandre V.↗
DOE OSTI2025

The Second Skin: A Wearable Sensor Suite that Enables Real-Time Human Biomechanics Tracking Through Deep Learning

Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.

Casey, Ryan T. F. [Georgia Institute of Technology↗
DOE OSTI2024

Harnessing quantum light for microscopic biomechanical imaging of cells and tissues

The biomechanical properties of cells and tissues play an important role in our fundamental understanding of the structures and functions of biological systems at both the cellular and subcellular levels. Recently, Brillouin microscopy, which offers a label-free spectroscopic means of assessing viscoelastic properties in vivo, has emerged as a powerful way to interrogate those properties on a microscopic level in living tissues. However, susceptibility to photodamage and photobleaching, particularly when high-intensity laser beams are used to induce Brillouin scattering, poses a significant challenge. This article introduces a transformative approach designed to mitigate photodamage in biological and biomedical studies, enabling nondestructive, label-free assessments of mechanical properties in live biological samples. By leveraging quantum-light-enhanced stimulated Brillouin scattering (SBS) imaging contrast, the signal-to-noise ratio is significantly elevated, thereby increasing sample viability and extending interrogation times without compromising the integrity of living samples. The tangible impact of this methodology is evidenced by a notable three-fold increase in sample viability observed after subjecting the samples to three hours of continuous squeezed-light illumination, surpassing the traditional coherent light-based approaches. The quantum-enhanced SBS imaging holds promise across diverse fields, such as cancer biology and neuroscience where preserving sample vitality is of paramount significance. By mitigating concerns regarding photodamage and photobleaching associated with high-intensity lasers, this technological breakthrough expands our horizons for exploring the mechanical properties of live biological systems, paving the way for an era of research and clinical applications.

Li, Tian↗
DOE OSTI2024

A MPET 2 -mPBPK model for subcutaneous injection of biotherapeutics with different molecular weights: From local scale to whole-body scale

Subcutaneous injection of biotherapeutics has attracted considerable attention in the pharmaceutical industry. However, there is limited understanding of the mechanisms underlying the absorption of drugs with different molecular weights and the delivery of drugs from the injection site to the targeted tissue. Here, we propose the MPET 2 -mPBPK model to address this issue. This multiscale model couples the MPET 2 model, which describes subcutaneous injection at the local tissue scale from a biomechanical view, with a post-injection absorption model at injection site and a minimal physiologically-based pharmacokinetic (mPBPK) model at whole-body scale. Utilizing the principles of tissue biomechanics and fluid dynamics, the local MPET 2 model provides solutions that account for tissue deformation and drug absorption in local blood vessels and initial lymphatic vessels during injection. Additionally, we introduce a model accounting for the molecular weight effect on the absorption by blood vessels, and a nonlinear model accounting for the absorption in lymphatic vessels. The post-injection model predicts drug absorption in local blood vessels and initial lymphatic vessels, which are integrated into the whole-body mPBPK model to describe the pharmacokinetic behaviors of the absorbed drug in the circulatory and lymphatic system. We establish a numerical model which links the biomechanical process of subcutaneous injection at local tissue scale and the pharmacokinetic behaviors of injected biotherapeutics at whole-body scale. With the help of the model, we propose an explicit relationship between the reflection coefficient and the molecular weight and predict the bioavalibility of biotherapeutics with varying molecular weights via subcutaneous injection. The considered drug absorption mechanisms enable us to study the differences in local drug absorption and whole-body drug distribution with varying molecular weights. This model enhances the understanding of drug absorption mechanisms and transport routes in the circulatory system for drugs of different molecular weights, and holds the potential to facilitate the application of computational modeling to drug formulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Genetically Controlled Iron Oxide Biomineralization in Encapsulin Nanocompartments for Magnetic Manipulation of a Mammalian Cell Line

Magnetic nanoparticles have proven invaluable for biomechanical investigations due to their ability to exert localized forces. However, cellular delivery of exogenous magnetic agents often results in endosomal entrapment, thereby limiting their utility for manipulating subcellular structures. This study characterizes and exploits fully genetically controlled biomineralization of iron-oxide cores inside encapsulin nanocompartments to enable magnetic-activated cell sorting (MACS) and magnetic cell manipulation. The fraction of MACS-retained cells showed substantial overexpression of encapsulins and exhibited both para- and ferrimagnetic responses with magnetic moments of 10 -15 A m 2 per cell, comparable to standard exogenous labels for MACS. Electron microscopy revealed that MACS-retained cells contained densely packed agglomerates of ≈30 nm iron oxide cores consisting of ultrafine quasicrystalline ordered nuclei within an amorphous matrix of iron, oxygen, and phosphorus. Scanning transmission X-ray microscopy, X-ray absorption spectroscopy, and Raman microspectroscopy confirmed that the iron-oxide species are consistent with ferric oxide (Fe 2 O 3 ). In addition, the encapsulin-overexpressing MACS-retained cells can be manipulated by a magnetic needle and regrown in patterns determined by magnetic gradients. This study demonstrates that the formation of quasicrystalline iron oxide with mixed para/ferrimagnetic behavior in the cytosol of mammalian cells enables magnetic manipulation without the delivery of exogenous agents.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Molecular Insights Into the Ionic Assembly of Poly-Galacturonic Acid Oligomers - Impact of Charge, Ionic Radius, and Polymer Functionalization

Pectin, a major class of matrix polysaccharides present in plant cell walls (PCW), contains widespread anionic saccharides that cross-link in the presence of cations. It modulates important functions such as cell-cell adhesion and determines the PCW's biomechanical properties. It is known that mono-, di-, and tri-valent cations facilitate cross-linking; however, significant knowledge gaps remain in understanding the structure and mechanism of pectin cross-linking. In this study, replica-exchange molecular dynamics (REMD) simulations were employed to elucidate the role of ionic charge, ionic radii, and functional groups on the cross-linking of homogalacturonan (HG), the most abundant pectin molecule. Our enhanced sampling approach in fully solvated environments suggests more effective cross-linking with higher-valent and smaller ions, and that the "zipper" conformation is more favorable than the prevalent "egg-box" conformation. These findings advance our fundamental understanding of pectin matrix structure in PCWs and provide a solid foundation to probe structure-property relationships in pectic polysaccharides.

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

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗
DOE OSTI2025

The molecular architecture distinctions between compression, opposite and normal wood of Pinus radiata

In gymnosperms compression wood is a specialised type of structural cell wall formed in response to biomechanical stresses. The differences in terms of gross structure, ultrastructure and chemistry are well-known. However, the differences between compression wood, normal wood, and opposite wood regarding the arrangements and interactions of the various polymers and water within their cell walls still needs to be established. The analysis of 13 C-labelled Pinus radiata by solid-state NMR spectroscopy and other complementary techniques revealed several new aspects of compression and opposite wood molecular architecture. Compared to normal wood, compression wood has a lower water content, its overall nanoporosity is reduced, and the water and matrix polymers have a lower molecular mobility. Galactan, which is a specific marker of compression wood, is broadly distributed within the cell wall, disordered, and not aligned with cellulose, and is found to be in close proximity to xylan. Dehydroabietic acid (a resin acid) is immobilised and close to the H-lignin only in compression wood. Although the overall molecular mobility of normal wood and opposite wood are similar, opposite wood has different arabinose conformations, a large increase in the amount of chain ends, contains significantly more galactan and has additional unassigned mobile components highlighting the different molecular arrangement of cell wall polymers in opposite and normal wood.

59 BASIC BIOLOGICAL SCIENCES↗