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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Full circle mechanical dynamic characterization including experimental modal analysis and finite element analysis

During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. Finally, a qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

42 ENGINEERING↗
DOE OSTI2022

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Development and validation of a second-order thermal network model for residential buildings

Heating, Ventilation, and Air Conditioning (HVAC) systems can maintain the space air temperature of residential buildings, either directly by heating/cooling the air, or indirectly via heat transfer to and from the building structure that acts as a thermal mass. Hence, HVAC systems can help achieve load shifting, peak load reduction, and/or energy cost saving, thus enabling grid-interactive HVAC operation. A home thermal model that can accurately reflect the dynamics of the space air and interior wall surface temperatures, is therefore valuable. This paper develops such a model using the standard RC (resistance-capacitance) approach. The model contains a virtual envelope node and an internal space node and is thus second-order. A hybrid parameter identification scheme, made up of the least-squares and optimal search methods, is also developed. The proposed model and scheme were validated using data collected from a test home. It was found that a modest amount of training data was sufficient to yield reliable parameter estimates and accurate prediction. It was also found that when making 24-hour-ahead prediction of the space air temperature, both methods had comparable performances when the training data began in a transition season. However, when they began in an HVAC season, the optimal search method performed better. Furthermore, the least-squares method is recommended during a transition season due to its lower computational burden, while the optimal search method is recommended during an HVAC season due to its better estimation performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Sub-grid scale model classification and blending through deep learning

In this article we detail the use of machine learning for spatio-temporally dynamic turbulence model classification and hybridization for large eddy simulations (LES) of turbulence. Here, our predictive framework is devised around the determination of local conditional probabilities for turbulence models that have varying underlying hypotheses. As a first deployment of this learning, we classify a point on our computational grid as that which requires the functional hypothesis, the structural hypothesis or no modelling at all. This ensures that the appropriate model is specified from a priori knowledge and an efficient balance of model characteristics is obtained in a particular flow computation. In addition, we also utilize the conditional-probability predictions of the same machine learning to blend turbulence models for another hybrid closure. Our test case for the demonstration of this concept is given by Kraichnan turbulence, which exhibits a strong interplay of enstrophy and energy cascades in the wavenumber domain. Our results indicate that the proposed methods lead to robust and stable closure and may potentially be used to combine the strengths of various models for complex flow phenomena prediction.

42 ENGINEERING↗
DOE OSTI2020

A Positive Charge in the Outer Coordination Sphere of an Artificial Enzyme Increases CO 2 Hydrogenation

The protein scaffold around the active site of enzymes is known to influence catalytic activity, but specific scaffold features responsible for favorable influences are often not known. This study focuses on using an artificial metalloenzyme to probe one specific feature of the scaffold, the position of a positive charge in the outer coordination sphere around the active site. Previous work showed that a small molecular complex, [Rh(P Et 2 N glycine P Et 2 )2 ] – , immobilized covalently within a protein scaffold was activated for CO 2 hydrogenation. In this work, using an iterative design where the effect of arginine, histidine, or lysine residues placed in the outer coordination sphere of the catalytic active site were evaluated, we tested the hypothesis that positively charged groups facilitate CO 2 hydrogenation with seven unique constructs. Single-, double-, and triple-point mutations were introduced to directly compare catalytic activity, as monitored by turnover frequencies (TOFs) measured in real time with 1 H NMR spectroscopy, and evaluate related structural and electronic properties. Two of the seven constructs showed a 2- and 3-fold increase relative to the wild type, with overall rates ranging from 0.2 to 0.7 h –1 , and a crystal structure of the fastest of these shows the positive charge positioned next to the active site. A crystal structure of the arginine-containing complex shows that the arginines are positioned near the metal. Molecular dynamics (MD) studies also suggest that the positive charge is oriented next to the active site in the two constructs with faster rates but not in the others and that the positive charge near the active site holds the CO 2 near the metal, all consistent with a positive charge appropriately positioned in the scaffold benefiting catalysis. The MD studies also suggest that changes in the water distribution around the active site may contribute to catalytic activity, while modest structural changes and movement of the complex within the scaffold do not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Aerosol jet printed capacitive strain gauge for soft structural materials

Soft structural textiles, or softgoods, are used within the space industry for inflatable habitats, parachutes and decelerator systems. Evaluating the safety and structural integrity of these systems occurs through structural health monitoring systems (SHM), which integrate non-invasive/non-destructive testing methods to detect, diagnose, and locate damage. Strain/load monitoring of these systems is limited while utilizing traditional strain gauges as these gauges are typically stiff, operate at low temperatures, and fail when subjected to high strain that is a result of high loading classifying them as unsuitable for SHM of soft structural textiles. For this work, a capacitance based strain gauge (CSG) was fabricated via aerosol jet printing (AJP) using silver nanoparticle ink on a flexible polymer substrate. Printed strain gauges were then compared to a commercially available high elongation resistance-based strain gauge (HE-RSG) for their ability to monitor strained Kevlar straps having a 26.7?kN (6?klbf) load. Dynamic, static and cyclic loads were used to characterize both types of strain monitoring devices. Printed CSGs demonstrated superior performance for high elongation strain measurements when compared to commonly used HE-RSGs, and were observed to operate with a gauge factor of 5.2 when the electrode arrangement was perpendicular to the direction of strain.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control

Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to decentralized paradigm, LFC needs to consider the decentralized scheme that considers limited information from the information-exchange graph for the generator control of each interconnected area. This paper aims to solve a data-driven constrained LQR problem with mean-variance risk constraints and output structured feedback, and applies this framework to solve the LFC problem in multi-area power systems. By reformulating the constrained optimization problem into a minimax problem, the stochastic gradient descent max-oracle (SGDmax) algorithm with zero-order policy gradient (ZOPG) is adopted to find the optimal feedback gain from the learning, while guaranteeing the convergence. In addition, to improve the adaptation of the proposed learning method to new or varying models, we construct an emulator grid that approximates the dynamics of a physical grid and performs training based on this model. Once the feedback gain is obtained from the emulator grid, it is applied to the physical grid with a robustness test to check whether the controller from the approximated emulator applies to the actual system. Numerical tests show that the obtained feedback controller can successfully control the frequency of each area, while mitigating the uncertainty from the loads, with reliable robustness that ensures the adaptability of the obtained feedback gain to the actual physical grid.

Kwon, Kyung-bin↗
DOE OSTI2017

Numerical simulation of vortex-induced motion of a deep-draft paired-column semi-submersible offshore platform

Understanding and predicting vortex-induced motion (VIM) of offshore systems for deep seawater applications is crucial to improve the system safety and integrity. In this paper, we report on experimental tow-tank measurements and numerical simulations of VIM of a deep-draft offshore platform, specifically Paired-Column Semisubmersible (PC-Semi). The study is carried out in model scale (1:54), at subcritical flow regime with Re~10 4 . Motion of the floating structure has three degrees of freedom: in-line, cross-flow, and yaw. Large periodic cross-flow motion is measured for headings 0°, 11.25°, and 22.5°, for reduced velocities (U r ) between 5 and 10. Considerably smaller cross-flow amplitude is recorded at 45° heading across the U r range considered. An extensive sensitivity study is performed using computational fluid dynamics (CFD) to capture the transient displacement history of VIM (in-line, cross-flow, and yaw motion components). Amplitude and period of cross-flow (transverse) motion are obtained from statistical analysis of VIM time history and subsequently used as the validation criterion between the CFD simulation and the model tests. Satisfactory agreement between the CFD results and tow-tank measurements is achieved with a Delayed Detached Eddy Simulation – Shear Stress Transport (DDES-SST) formulation. Finally, this work provides experimental results and serves as a practical starting point to set up a CFD problem to estimate amplitude and period of cross-flow VIM motion for offshore engineering applications.

42 ENGINEERING↗
DOE OSTI2026

Brittle-to-Ductile Transition Temperature Decreases at the Microscale in Muscovite Mica

Characterizing the structural and chemical transitions of muscovite mica across various scales and thermal profiles is essential for ensuring the reliability of high-voltage power insulation, aerospace thermal barriers, and nanoscale semiconductor substrates under extreme operational stress. Here, we investigate notch fracture toughness $K^{n}_{Ic}$ of muscovite mica as a function of feature size w and temperature T with microscale shear testing. $K^{n}_{Ic}$ decreased and then stayed constant as w increased, likely from fabrication-induced changes to the microstructure and roughness. Moreover, $K^{n}_{Ic}$ initially decreased and then increased as temperature T increased, with the reversal in trend indicative of a brittle-to-ductile transition. Complementary Raman spectroscopy and molecular dynamics showed that the observed trends were due to an increase in bond lengths and a decrease in critical stresses/strains. In comparing the microscale results to macroscale counterparts, it was surmised that the decrease in brittle-to-ductile transition temperature was due to an increase in the dehydroxylation rate.

DelRio, Frank W. [Sandia National Laboratories (SN↗
DOE OSTI2025

De Novo Design of Proteins That Bind Naphthalenediimides, Powerful Photooxidants with Tunable Photophysical Properties

De novo protein design provides a framework to test our understanding of protein function and build proteins with cofactors and functions not found in nature. Here, we report the design of proteins designed to bind powerful photooxidants and the evaluation of the use of these proteins to generate diffusible small-molecule reactive species. Because excited-state dynamics are influenced by the dynamics and hydration of a photooxidant’s environment, it was important to not only design a binding site but also to evaluate its dynamic properties. Thus, we used computational design in conjunction with molecular dynamics (MD) simulations to design a protein, designated NBP (NDI Binding Protein), that held a naphthalenediimide (NDI), a powerful photooxidant, in a programmable molecular environment. Solution NMR confirmed the structure of the complex. We evaluated two NDI cofactors in this de novo protein using ultrafast pump–probe spectroscopy to evaluate light-triggered intra- and intermolecular electron transfer function. Moreover, we demonstrated the utility of this platform to activate multiple molecular probes for protein labeling.

carbonyls↗
DOE OSTI2018

Understanding the Scale of the Single Ion Free Energy: A Critical Test of the Tetra-Phenyl Arsonium and Tetra-Phenyl Borate Assumption

Free energies, enthalpies and entropies of ions in solution can be experimentally determined for neutral pairs. For individual ions however, determining these properties requires additional assumptions, which can and should be theoretically tested. The tetra-phenyl arsonium and tetra-phenyl borate (TATB) assumption is a commonly used extra-thermodynamic assumption, which allows these values to be split into cationic and anionic contributions. The assumption is that the values for the TATB salt can be divided equally. This is justified by arguing that these large hydrophobic ions will cause a symmetric response in water. Experimental and classical simulation work has raised potential flaws with this assumption, indicating that hydrogen bonding with the phenyl ring may favor the solvation of the TB-anion. In this study, we perform ab initio molecular dynamics (AIMD) simulations of these ions in bulk water demonstrating that there are significant structural differences. We quantify our findings by reproducing the experimentally observed vibrational shift for the TB-anion and confirm that this is associated with hydrogen bonding with the phenyl rings. Finally, we demonstrate that this results in a substantial energetic preference of the water to solvate the anion. In conclusion, our results suggest that the validity of the TATB assumption, which is still widely used today, should be reconsidered experimentally in order to properly reference single ion solvation free energy, enthalpy and entropy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Robustness and printed sensor qualification

A limiting factor of additive manufactured (AM) sensors for in-pile applications is the development of appropriate interconnection and packaging strategies that can maintain reliable performance in extreme environments. Failure mechanisms in these harsh conditions could include, but not limited to, materials interaction (i.e., intermetallic formation) and coefficient of thermal expansion (CTE) mismatch between the individual components of the sensors. To mitigate premature failure and enable the successful sustained operation of AM sensors, non-destructive qualification tests are used as an intermediate process control step used for verifying robustness and reliability of the sensor before they are deployed. A materials system of interest is the use of barium strontium titanium oxide (BST) films on stainless steel 316L (SS316L) substrate. Due to BST’s high dielectric constant and tunable dielectric properties, there is an interest for its application as an insulation/encapsulation layer for capacitive strain gauges when printed on structural materials. Previous work on the BST/SS316L material system, however, showed that the BST cracks when exposed to temperatures up to 600 °C due to CTE mismatch between the printed BST film and the metallic substrate. When comparing different fabrication techniques, less surface cracking was observed in the samples that deposited thinner (i.e., 2-20 μm) than samples that were thicker (i.e., 135 µm – 300 µm). The objective of this report is to establish a qualification process that will determine and address any challenges (i.e., mechanical failure of thick prints) of the AM sensor prior to its application in experimental tests. To demonstrate the qualification process in this report, laser spallation and uniaxial tensile tests using dynamic and quasi-static loading, respectively, will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2016

Determination of Coronal Mass Ejection physical parameters from a combination of polarized visible light and UV Lyα observations

Visible-light observations of Coronal Mass Ejections (CMEs) performed with coronagraphs and heliospheric imagers (in primis on board the Solar and Heliospheric Observatory and STEREO missions) have offered the best way to study the kinematics and geometrical structure of these fundamental events so far. Nevertheless, it has been widely demonstrated that only combination of multi-wavelength data (including X-ray spectra, EUV images, EUV-UV spectra, and radio dynamic spectra) can provide complete information on the plasma temperature and density distributions, non-thermal motions, magnetic fields, and other physical parameters, for both CMEs and CME-related phenomena. In this work, we analyze three CMEs by combining simultaneous data acquired in the polarized visible light by the LASCO-C2 coronagraph and in the UV H i Lyα line (1216 Å) by the UVCS spectrometer, in order to estimate the CME plasma electron density (using the polarization-ratio technique to infer the 3D structure of the CME) and temperature (from the comparison between the expected and measured Lyα intensities) along the UVCS field of view. This analysis is primarily aimed at testing the diagnostic methods that will be applied to coronagraphic observations of CMEs delivered by the Metis instrument on board the next ESA-Solar Orbiter mission. We find that CME cores are usually associated with cooler plasma (T∼10{sup 6} K), and that a significant increase of the electron temperatures is observed from the core to the front of the CME (where T>10{sup 6.3} K), which seems to be correlated, in all cases, with the morphological structure of the CME as derived from visible-light images.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Enhancement of Structural Health Monitoring Framework by Optimizing Vibro-Acoustic Modulation Technique to Localize Alkali-Silica Reaction Degradation in Medium-Sized Concrete Samples

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed to understand the current condition of a structure based on heterogeneous measurements and then produce high confidence actionable information regarding structural integrity. This information can then be used to support operational and maintenance decisions. The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, wells, placitas, and spratt) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Vibro-acoustic methods were used on these slabs to locate large pockets of ASR within the reactive samples and determine the effects of rebar using the non-reactive slabs. Vibro-acoustic modulation (VAM) is a vibration-based NDE method that utilizes signatures of nonlinear dynamic interactions on contact surfaces of crack or delamination damage to detect and localize the damage. VAM analysis was conducted on both Vanderbilt and Alabama’s samples using multiple variables for damage detection and localization. The results from the data analysis of the NDE vibro-acoustic techniques on concrete slabs cured at Vanderbilt University and the University of Alabama are discussed in detail in this report. The major outcome of the analysis suggests that the VAM method can be used to detect damage within the concrete samples by comparing the results found in different sections of the samples. Results for damage localization are dependent on multiple variables used in the vibro-acoustic modulation experiments. Digital image correlation (DIC) is a three-dimensional, full-field, optical NDE technique to measure contour, deformation, vibration, and strain. The application of the digital image correlation technique to study ASR-related degradation on a large concrete sample at the University of Tennessee Knoxville is discussed and observations are presented in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Comparison of interlaminar damage modeling strategies for hybrid composite/aluminum laminates subjected to low-velocity impact

Low-velocity impact of hybrid metal-composite structures was investigated experimentally and computationally. Composite laminates consisting of 2D woven glass fiber reinforced polymer (GFRP) and carbon fiber reinforced polymer (CFRP) were joined with a 6061-T6 aluminum plate using an epoxy adhesive. Two variations of the structure were studied; one consisting of all plies oriented at 0° and one consisting of all plies oriented at 45°. A drop tower was used to impact structures at a range of energies, including energies above and below the threshold at which the aluminum layer was perforated. Numerical simulations were implemented using Sierra/SM, an in-house transient dynamics finite element code developed at Sandia National Laboratories. A Hosford plasticity model was used to describe the response of the aluminum layer. A newly implemented orthotropic continuum damage mechanics (CDM) constitutive model was used to represent the composite laminate. This 3D-CDM model was compared to a cohesive zone model (2D-CDM/CZM) to investigate efficacy of aluminum perforation energy prediction, delamination prediction, and computational cost. Accuracy of each model was evaluated using the experimental results. Each showed good agreement with the tests for both the force and velocity histories, as well as the observed damage mechanisms. The 2D-CDM/CZM model was marginally more accurate in capturing both the composite and aluminum behavior — this model averaged error percentages of -11.2% and 10.8% for residual velocity and peak force, respectively. Meanwhile, the 3D-CDM model predictions yielded average error percentages of -35.5% (velocity) and 22.6% (force). However, the 3D-CDM model generally resulted in a decreased computational cost; the average run time was 14% shorter than the 2D-CDM/CZM model and 3x as many timesteps per hour were computed using the same computational resources. In conclusion, new experimental data on the impact and perforation resistance of metal-composite laminates is presented in addition to numerical predictions of the impact behavior.

Carbon fiber↗
DOE OSTI2022

Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization

Abstract Accurate earthquake location and magnitude estimation play critical roles in seismology. Recent deep learning frameworks have produced encouraging results on various seismological tasks (e.g., earthquake detection, phase picking, seismic classification, and earthquake early warning). Many existing machine learning earthquake location methods utilize waveform information from a single station. However, multiple stations contain more complete information for earthquake source characterization. Inspired by recent successes in applying graph neural networks (GNNs) in graph‐structured data, we develop a Spatiotemporal Graph Neural Network (STGNN) for estimating earthquake locations and magnitudes. Our graph neural network leverages geographical and waveform information from multiple stations to construct graphs automatically and dynamically by adaptive message passing based on graphs' edges. Using a recent graph neural network and a fully convolutional neural network as baselines, we apply STGNN to earthquakes recorded by the Southern California Seismic Network from 2000 to 2019 and earthquakes collected in Oklahoma from 2014 to 2015. STGNN yields more accurate earthquake locations than those obtained by the baseline models and performs comparably in terms of depth and magnitude prediction, though the ability to predict depth and magnitude remains weak for all tested models. Our work demonstrates the potential of using GNNs and multiple stations for better automatic estimation of earthquake epicenters.

58 GEOSCIENCES↗
DOE OSTI2023

Nanoscale simulation of the thylakoid membrane response to extreme temperatures

Abstract The thylakoid membrane is in a temperature‐sensitive equilibrium that shifts repeatedly during the life cycle in response to ambient temperature or solar irradiance. Plants respond to seasonal temperature variation by changing their thylakoid lipid composition, while a more rapid mechanism for short‐term heat exposure is required. The emission of the small organic molecule isoprene has been postulated as one such possible rapid mechanism. The protective mechanism of isoprene is unknown, but some plants emit isoprene at high temperature. We investigate the dynamics and structure for lipids within a thylakoid membrane across temperatures and varied isoprene content using classical molecular dynamics simulations. The results are compared with experimental findings for temperature‐dependent changes in the lipid composition and shape of thylakoids. The surface area, volume, and flexibility of the membrane, as well as the lipid diffusion, increase with temperature, while the membrane thickness decreases. Saturated thylakoid 34:3 glycolipids derived from eukaryotic synthesis pathways exhibit altered dynamics relative to lipids from prokaryotic synthesis paths, which could explain the upregulation of specific lipid synthesis pathways at different temperatures. Increasing isoprene concentration was not observed to have a significant thermoprotective effect on the thylakoid membranes, and that isoprene readily permeated the membrane models tested.

59 BASIC BIOLOGICAL SCIENCES↗