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At least 433 records · Page 24

Proton Conducting Silicon Oxide Membranes as a Fluorine Free Alternative to Nafion for Low Temperature Water Electrolysis

Driven by environmental and health concerns related to per- and polyfluoroalkyl substances (PFAS), there has been growing interest in developing fluorine-free proton (H + ) exchange membrane (PEM) materials for fuel cells and water electrolyzers. In this study, we present a side-by-side comparison of the key transport properties of submicron thick, PFAS-free amorphous silicon dioxide (SiO 2 ) membranes to Nafion, a fluorinated polymer electrolyte membrane that represents the industry standard for PEM fuel cells and electrolyzers. Here, measurements of proton (H + ) conductivity (σ H + ), hydrogen (H 2 ) permeability (P H 2 ), and electrical resistivity (ρ e – ) were conducted using model thin films comprised of SiO 2 membranes deposited by atomic layer deposition (ALD). Although the H + conductivity of the SiO 2 membranes is 2–3 orders of magnitude lower than Nafion, the addition of phosphorus dopants (PO x ) improves H + conductivity such that the area specific membrane resistance of thin (<50 nm) PO x -doped SiO 2 membranes is more than an order of magnitude lower than Nafion-117. Importantly, the safe operation of such nanoscale membranes within a PEM electrolyzer is feasible thanks to the low H 2 permeability of dense SiO 2 -based membranes, which are predicted to limit H 2 crossover rates to acceptable levels for pressures up to ≈ 100 bar. As a proof-of-principle demonstration, a chip-scale water electrolyzer based on 100 nm thick PO x -SiO 2 membrane is shown to achieve a current density of 2 A cm –2 at a potential of 2.5 V. If this technology can be successfully scaled up, H + conducting oxide membranes offer an attractive PFAS-free alternative to Nafion for efficient and durable water electrolysis and fuel cell technologies.

Nafion↗

Pore-Confined Polymers Enhance the Thermal Conductivity of Polymer Nanocomposites

In this work, molecularly confined polymer fillers in nanopores were found to give superior mechanical properties of polymer nanocomposites. In this work, we study the thermal conductivity of such nanocomposites and unveil the effect of polymer confinement on thermal conductivity. Using the time-domain thermoreflectance method, we measure the cross-plane thermal conductivity of polymer nanocomposites that consist of polystyrene fillers confined within a nanoporous organosilicate matrix. Compared to unconfined bulk polystyrene fillers, we find that pore-confined polystyrene fillers enhance the thermal conductivity of the polymer nanocomposites. This enhancement is attributed to the better aligned and less entangled chains in the confined phase, where chain–chain phonon scatterings are reduced. Our work provides essential insights into the thermal conductivity of polymer nanocomposites for multifunctional thermal and mechanical applications.

36 MATERIALS SCIENCE↗

Critical Role of Framework Flexibility and Disorder in Driving High Ionic Conductivity in LiNbOCl 4

Understanding Li-ion transport is key for the rational design of superionic solid electrolytes with exceptional ionic conductivities. LiNbOCl 4 is reported to be one of the most highly conducting materials in the recently realized new class of soft oxyhalide solid electrolytes, exhibiting an ionic conductivity of ~11 mS·cm -1 . Here, we apply X-ray/neutron diffraction and pair distribution function analysis - coupled with density functional theory/ab-initio molecular dynamics - to determine a structural model that provides a rationale for the high conductivity that we observe experimentally in this nanocrystalline solid. We show that it arises from unusually high framework flexibility at room temperature. This owes to isolated 1-D [NbOCl 4 ] - anionic chains which exhibit energetically favorable orientational disorder that is - in turn - correlated to multiple, disordered and equi-energetic Li + sites in the lattice. As the Li-ions sample the 3-D energy landscape with a fast predicted diffusion coefficient of 5.1 x 10 -7 cm 2 /s at room temperature (σ i calc = 17.4 mS·cm -1 ), the inorganic polymer chains can reorient or vice versa. The activation energy barrier for Li migration through the frustrated energy landscape is especially reduced by the elastic nature of the NbO 2 Cl 4 octahedra evident from very widely dispersed Cl-Nb-Cl bond angles in AIMD snapshots at 300 K. The phonon spectra are predominantly influenced by Cl vibrations in the low energy range, and there is strong overlap between the framework (Cl, Nb) and Li partial pDOS in the region between 1.2 - 4.0 THz. The framework flexibility is also reflected in a relatively low bulk modulus of 22 GPa. In conclusion, our findings pave the way for investigation of future “flex-ion” inorganic solids and open up a new direction for the design of high conductivity, soft solid electrolytes for all-solid-state batteries.

AIMD↗

A New Class of Ionically Conducting Fluorinated Ether Electrolytes with High Electrochemical Stability

Increasing battery energy density is greatly desired for applications such as portable electronics and transportation. However, many next-generation batteries are limited by electrolyte selection because high ionic conductivity and poor electrochemical stability are typically observed in most electrolytes. For example, ether-based electrolytes have high ionic conductivity but are oxidatively unstable above 4 V, which prevents the use of high-voltage cathodes that promise higher energy densities. In contrast, hydrofluoroethers (HFEs) have high oxidative stability but do not dissolve lithium salt. Here, we synthesize a new class of fluorinated ether electrolytes that combine the oxidative stability of HFEs with the ionic conductivity of ethers in a single compound. We show that conductivities of up to 2.7 × 10 –4 S/cm (at 30 °C) can be obtained with oxidative stability up to 5.6 V. The compounds also show higher lithium transference numbers compared to typical ethers. Furthermore, we use nuclear magnetic resonance (NMR) and molecular dynamics (MD) to study their ionic transport behavior and ion solvation environment, respectively. Finally, we demonstrate that this new class of electrolytes can be used with a Ni-rich layered cathode (NMC 811) to obtain over 100 cycles at a C/5 rate. The design of new molecules with high ionic conductivity and high electrochemical stability is a novel approach for the rational design of next-generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗

A comprehensive conductivity model for drift and micro-tearing modes

The parallel electrical conductivity is a crucial parameter in the study of the linear stability of drift-modes like the micro-tearing mode (MTM). The conductivity enters by closing the electromagnetic tearing layer equations. Recent progress in the understanding of the pedestal suggests that the MTM could play an important role in its structure and evolution. For this reason, we revisit and improve previous model conductivities. This parameter is generally derived from the linearized drift kinetic equation. In the past literature, it has been computed using either simplified collision operators or neglecting the spatial dependence away from the rational surface. Here, a fully consistent expression for the conductivity that would accurately model the pedestal has not been available. By applying a novel variational procedure and with the full Fokker Plank collision operator, including electron–electron collisions, we compute a closed expression for the parallel electrical conductivity in the form of a rational function.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Observation of a highly conductive warm dense state of water with ultrafast pump–probe free-electron-laser measurements

The electrical conductivity of water under extreme temperatures and densities plays a central role in modeling planetary magnetic fields. Experimental data are vital to test theories of high-energy-density water and assess the possible development and presence of extraterrestrial life. These states are also important in biology and chemistry studies when specimens in water are confined and excited using ultrafast optical or free-electron lasers (FELs). Here we utilize femtosecond optical lasers to measure the transient reflection and transmission of ultrathin water sheet samples uniformly heated by a 13.6 nm FEL approaching a highly conducting state at electron temperatures exceeding 20 000 K. The experiment probes the trajectory of water through the high-energy-density phase space and provides insights into changes in the index of refraction, charge carrier densities, and AC electrical conductivity at optical frequencies. At excitation energy densities exceeding 10 MJ/kg, the index of refraction falls to n = 0.7, and the thermally excited free-carrier density reaches ne = 5 × 1027 m−3, which is over an order of magnitude higher than that of the electron carriers produced by direct photoionization. Significant specular reflection is observed owing to critical electron density shielding of electromagnetic waves. The measured optical conductivity reaches 2 × 104 S/m, a value that is one to two orders of magnitude lower than those of simple metals in a liquid state. At electron temperatures below 15 000 K, the experimental results agree well with the theoretical calculations using density-functional theory/molecular-dynamics simulations. With increasing temperature, the electron density increases and the system approaches a Fermi distribution. In this regime, the conductivities agree better with predictions from the Ziman theory of liquid metals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simultaneous determination of electrical conductivity and thickness of nonmagnetic metallic foils using two-sided multifrequency eddy current techniques

Here, in this paper, we describe a simple method for performing multifrequency eddy current characterization of free-standing uniform-thickness metallic foils using a forked inductive coil arrangement. The method involves measuring the mutual inductance between two coils when a foil is present between the coils, and when it is not present; the ratio of these mutual inductances is compared with an analytical solution, and foil conductivity, thickness, and sheet resistance are simultaneously estimated using numerical inversion and least-squares fitting. This method was used to characterize 34 non-ferrous metallic samples with thicknesses between 50 and 640 μm and with conductivities between 0.8 × 10 7 and 5.8 × 10 7 S/m. The estimated thicknesses from eddy current characterization agreed well with those measured using confocal optical techniques; the two approaches agreed to within 1 μm for samples that were thinner than 200 μm, and to within 0.5% for samples that had a thickness of 200 μm or greater. The estimated conductivities from eddy current characterization were in close agreement with expected values, given knowledge of the materials used. A particular strength of this approach is that the instrumentation needed is broadly available in research and development laboratories and the associated fixturing is easy to manufacture and assemble. A calibration procedure is described that can be used to reduce errors from geometric uncertainties. This calibration requires a sample that has only a known conductivity or thickness; both do not need to be known. The method described herein is likely extensible to conductivities and thickness well outside the ranges measured as part of this work.

47 OTHER INSTRUMENTATION↗

Enhancement of Thermal Conductivity of Bentonite Buffer Materials with Copper Wires/Meshes for High-Level Radioactive Waste Disposal

In high-level radioactive waste disposal, a heat-generating waste canister is generally encased with a layer of bentonite-based buffer material acting as an engineered barrier to limit water percolation and radionuclide release. The low thermal conductivity of bentonite (~0.5 W/m∙K) combined with a high thermal loading waste package may result in a high surface temperature on the package that can potentially impact the structural integrity of the package itself as well as the surrounding buffer material. We show in this paper that the thermal conductivity of bentonite can be effectively enhanced by embedding copper wires/meshes across the buffer layer to form fully connected high heat conduction pathways. A simple calculation based on Rayleigh’s model shows that a required thermal conductivity of 5 W/m∙K for effective heat dissipation can be achieved simply by adding ~1 vol % of copper wires/meshes into bentonite. As a result, the peak surface temperature on a large waste package such as a dual-purpose canister can be reduced by up to 300°C, leading to a significant reduction in the surface storage time for waste cooling and therefore the overall cost for direct disposal of such waste packages. Because of the ensured full thermal percolation across the buffer layer, copper wires/meshes turn out to be much more effective than any other materials currently suggested (such as graphene or graphite) in enhancing the thermal conductivity of buffer material. Furthermore, the embedded copper wires/meshes can help reinforce the mechanical strength of the buffer material, thus preventing the material from a potential erosion by a possible intrusion of dilute groundwater.

36 MATERIALS SCIENCE↗

Implications of phonon anisotropy on thermal conductivity of fluorite oxides

Abstract Fluorite oxides are attractive ionic compounds for a range of applications with critical thermal management requirements. In view of recent reports alluding to anisotropic thermal conductivity in this face-centered cubic crystalline systems, we perform a detailed analysis of the impact of direction-dependent phonon group velocities and lifetimes on the thermal transport of fluorite oxides. We demonstrate that the bulk thermal conductivity of this class of materials remains isotropic despite notable anisotropy in phonon lifetime and group velocity. However, breaking the symmetry of the phonon lifetime under external stimuli including boundary scattering present in nonequilibrium molecular dynamics simulations of finite size simulation cell gives rise to apparent thermal conductivity anisotropy. We observe that for accurate determination of thermal conductivity, it is important to consider phonon properties not only along high symmetry directions commonly measured in inelastic neutron or x-ray scattering experiments but also of those along lower symmetry. Our results suggests that certain low symmetry directions have a larger contribution to thermal conductivity compared to high symmetry ones.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

SnSe 2 thermal conductivity from optothermal Raman and Stokes/anti-Stokes thermometry

The optothermal Raman method is useful in determining the in-plane thermal conductivity of two-dimensional (2D) materials that are either suspended or supported on a substrate. We compare this method with the Stokes/anti-Stokes scattering thermometry method, which can play a role in both calibration of Raman peak positions as well as extraction of the local phonon temperature. This work demonstrates that the Stokes/anti-Stokes intensity ratio plays an important role in determining the in-plane thermal conductivity of 2D tin diselenide (SnSe 2 ) dry-transferred onto a polished copper (Cu) substrate. The statistically-averaged thermal conductivity of the 108 ± 24 nm-thick SnSe 2 yielded 5.4 ± 3.5 Wm −1 K −1 for the optothermal Raman method, and 2.40 ± 0.81 Wm −1 K −1 for the Stokes/anti-Stokes thermometry method, indicating that the Stokes/anti-Stokes thermometry method to calculate the thermal conductivity of a material can simultaneously increase both precision and accuracy. The uncertainty value was also lowered by a factor of 1.9 from the traditional optothermal Raman method to the Stokes/anti-Stokes thermometry method. The low in-plane thermal conductivity of 2D SnSe 2 , 1.3–2.9 times lower than bulk, is useful for applications in thermal and electrical energy conversion and thermoelectric devices.

2D materials↗

Space-time dependent thermal conductivity in nonlocal thermal transport

Nonlocal thermal transport is generally described by the Peierls-Boltzmann transport equation (PBE). However, solving the PBE for a general space-time dependent problem remains a challenging task due to the high dimensionality of the integro-differential equation. In this work, we present a direct solution to the space-time dependent PBE with a linearized collision matrix using an eigendecomposition method. We show that there exists a generalized Fourier-type relation that links heat flux to the local temperature, and this constitutive relation defines a thermal conductivity that depends on both time and space. Combining this approach with ab initio calculations of phonon properties, we demonstrate that the space-time dependent thermal conductivity gives rise to an oscillatory response in temperature in a transient grating geometry in high thermal conductivity materials. The present solution method allows us to extend the reach of our computational capability for heat conduction to space-time dependent nondiffusive transport regimes. Here, this capability will not only enable a more accurate interpretation of thermal measurements that observe nonlocal thermal transport, but also enhance our physical understanding of nonlocal thermal transport in high thermal conductivity materials that are promising candidates for nanoscale thermal management applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Helical Covalent Polymers with Unidirectional Ion Channels as Single Lithium-Ion Conducting Electrolytes

Single-ion conducting polymer electrolytes have attracted great attention as safe alternatives to liquid electrolytes in high energy density lithium-ion batteries. Herein, we report the first example of a crystalline anionic helical polymer as a single lithium-ion conducting solid polymer electrolyte (SPE). Single-crystal X-ray analysis shows that the polymer folds into densely packed double helices, with bundles of unidirectional negatively charged channels formed that can facilitate lithium-ion transportation. Such a helical covalent polymer ( HCP) exhibits excellent room temperature lithium-ion conductivity (1.2 x 10 -3 S cm -1 ) in the absence of external lithium salts, a high transference number (0.84), low activation energy (0.14 eV), and a wide electrochemical stability window (0.2-5 V). We found that nonflammable, nonvolatile ionic liquid can serve as a solvating medium and excellent conductivity enhancer (>1000 times increase). These ion-conducting properties are comparable to the best polyethylene oxide-based polymer electrolytes mixed with lithium salts. Finally, we show that the solvated HCP SPE enables the reversible cycling of an all-solid-state cell prepared with a high-voltage NMC 811 cathode. Our study opens up new possibilities for developing next-generation high-performance solid-state electrolytes.

25 ENERGY STORAGE↗

Projecting the Thermal Response in a HTGR-Type System during Conduction Cooldown Using Graph-Laplacian Based Machine Learning

Accurate prediction of an off-normal event in a nuclear reactor is dependent upon the availability of sensory data, reactor core physical condition, and understanding of the underlying phenomenon. This work presents a method to project the data from some discrete sensory locations to the overall reactor domain during conduction cooldown scenarios similar to High Temperature Gas-cooled Reactors (HTGRs). The existing models for conductive cooldown in a heterogeneous multi-body system, such as an assembly of prismatic blocks or pebble beds relies on knowledge of the thermal contact conductance, requiring significant knowledge of local thermal contacts and heat transport possibilities across those contacts. With a priori knowledge of bulk geometry features and some discrete sensors, a machine learning approach was devised. The presented work uses an experimental facility to mimic conduction cooldown with an assembly of 68 cylindrical rods initially heated to 1200 K. High-fidelity temperature data were collected using an infrared (IR) camera to provide training data to the model and validate the predicted temperature data. The machine learning approach used here first converts the macroscopic bulk geometry information into Graph-Laplacian, and then uses the eigenvectors of the Graph-Laplacian to develop Kernel functions. Support vector regression (SVR) was implemented on the obtained Kernels and used to predict the thermal response in a packed rod assembly during a conduction cooldown experiment. The usage of SVR modeling differs from most models today because of its representation of thermal coupling between rods in the core. When trained with thermographic data, the average normalized error is less than 2% over 400 s, during which temperatures of the assembly have dropped by more than 500 K. The rod temperature prediction performance was significantly better for rods in the interior of the assembly compared to those near the exterior, likely due to the model simplification of the surroundings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Surface and Bulk Oxygen Kinetics of BaCo 0.4 Fe 0.4 Zr 0.2-X Y X O 3-δ Triple Conducting Electrode Materials

Triple ionic-electronic conductors have received much attention as electrode materials. In this work, the bulk characteristics of oxygen diffusion and surface exchange were determined for the triple-conducting BaCo 0.4 Fe 0.4 Zr 0.2-X Y X O 3-δ suite of samples. Y substitution increased the overall size of the lattice due to dopant ionic radius and the concomitant formation of oxygen vacancies. Oxygen permeation measurements exhibited a three-fold decrease in oxygen permeation flux with increasing Y substitution. The DC total conductivity exhibited a similar decrease with increasing Y substitution. These relatively small changes are coupled with an order of magnitude increase in surface exchange rates from Zr-doped to Y-doped samples as observed by conductivity relaxation experiments. The results indicate that Y-doping inhibits bulk O 2- conduction while improving the oxygen reduction surface reaction, suggesting better electrode performance for proton-conducting systems with greater Y substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Gas-Exchange Model for C4 Leaves Comparing Stomatal Conductance Models

Plant simulation models are abstractions of plant physiological processes that are useful for investigating the responses of plants to changes in the environment. Because photosynthesis and transpiration are fundamental processes that drive plant growth and water relations, a leaf gas-exchange model that couples their interdependent relationship through stomatal control is a prerequisite for explanatory plant simulation models. Here, we present a coupled gas-exchange model for C4 leaves incorporating two widely used stomatal conductance submodels: Ball–Berry and Medlyn models. The output variables of the model includes steady-state values of CO2 assimilation rate, transpiration rate, stomatal conductance, leaf temperature, internal CO2 concentrations, and other leaf gas-exchange attributes in response to light, temperature, CO2, humidity, leaf nitrogen, and leaf water status. We test the model behavior and sensitivity, and discuss its applications and limitations. The model was implemented in Julia programming language using a novel modeling framework. Our testing and analyses indicate that the model behavior is reasonably sensitive and reliable in a wide range of environmental conditions. The behavior of the two model variants differing in stomatal conductance submodels deviated substantially from each other in low humidity conditions. The model was capable of replicating the behavior of transgenic C4 leaves under moderate temperatures as found in the literature. The coupled model, however, underestimated stomatal conductance in very high temperatures. This is likely an inherent limitation of the coupling approaches using Ball–Berry type models in which photosynthesis and stomatal conductance are recursively linked as an input of the other.

59 BASIC BIOLOGICAL SCIENCES↗

The delayed rectifier, IKI, is the major conductance in type I vestibular hair cells across vestibular end organs

Hair cells were dissociated from the semicircular canal, utricle, lagena and saccule of white king pigeons. Type I hair cells were identified morphologically based on the ratios of neck width to cuticular plate width (NPR < 0.72) as well as neck width to cell body width (NBR < 0.64). The perforated patch variant of the whole-cell recording technique was used to measure electrical properties from type I hair cells. In voltage-clamp, the membrane properties of all identified type I cells were dominated by a predominantly outward potassium current, previously characterized in semicircular canal as IKI. Zero-current potential, activation, deactivation, slope conductance, pharmacologic and steady-state properties of the complex currents were not statistically different between type I hair cells of different vestibular end organs. The voltage dependence causes a significant proportion of this conductance to be active about the cell's zero-current potential. The first report of the whole-cell activation kinetics of the conductance is presented, showing a voltage dependence that could be best fit by an equation for a single exponential. Results presented here are the first data from pigeon dissociated type I hair cells from utricle, saccule and lagena suggesting that the basolateral conductances of a morphologically identified population of type I hair cells are conserved between functionally different vestibular end organs; the major conductance being a delayed rectifier characterized previously in semicircular canal hair cells as IKI.

NASA Discipline Number 40-99↗

Changes in nerve conduction and Pi/PCr ratio during denervation-reinnervation of the gastrocsoleus muscles of rats

The purpose of this investigation was to study the changes in nerve conduction and phosphate metabolites of the gastrocsoleus muscles of rats during denervation-reinnervation. Sixteen male Sprague-Dawley rats underwent unilateral crush-denervation of the left sciatic nerves at the sciatic notch. Six rats were used for measurement of motor conduction latency and action potential amplitude of the gastrocsoleus muscle by stimulating the sciatic nerve at one, two and eight weeks after nerve crush. The other ten rats were designated for evaluation of the ratio of inorganic phosphorous (Pi) to phosphocreatine (PCr) by a 31P-phosphoenergetic spectrometer at two weeks and eight weeks after nerve crush. None of the sciatic nerves showed conduction to the gastrocsoleus at one or two weeks after nerve crush. At eight weeks postcrush, the motor conduction latency returned to within normal limits, whereas the action potential amplitude was only 55% of the normal. For the eight-week period of study, the Pi/PCr ratio of the normal control muscles ranged between 0.09 +/- 0.02 and 0.11 +/- 0.02 (mean +/- SD). The denervated muscles showed an increase of Pi/PCr ratio by 54% at two weeks postcrush, compared to the respective contralateral control sides. The ratios returned to the normal value by eight weeks postcrush. In summary, these data suggested that the metabolic recovery of the crush-denervated muscle followed the same pattern as the parameters of nerve conduction.

NASA Center JSC↗