Results for “soft structural materials” — Page 4

NASA NTRSDate not supplied

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

NASA NTRS2023

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

NASA NTRS1998

Mechanistic Models of Friction Stir Welding

Friction stir welding is a welding process developed at The Welding Institute (TWI) in England. The method uses very large strain plastic deformation of the material to join two pieces of metal together. The material is deformed using a tool which is forced between the two pieces which rotates causing a bond. Beyond this, very little is actually known although many people working in the field are willing to speculate on the detailed mechanisms involved. Some measurements made using sacrificial thermocouples at the weld joint indicate that the maximum temperature during the weld process is on the order of 370C - well below the melting temperature of the material. However, at this temperature, the material properties are highly temperature dependent, and the yield stress is approximately an order of magnitude less at this temperature than it is at room temperature. As expected, there are many interpretations of the physical mechanisms occurring during the weld process. Although there is very little published concerned with FSW, some of the anecdotal theories will be described. One describes the primary mechanism as frictional heating at the front of the tool caused by slip between the tool and the material. At elevated temperatures, the weld material becomes soft and deforms around the tool but not essentially altered by the tool rotation, similar to an extrusion. As the material meets again at the rear of the tool, the temperatures and pressures are sufficient to cause the material to bond. All other structures seen are secondary and unimportant. Another theory examined last summer at NASA's Marshall Space Flight Center (MSFC) was that there was no slip between the tool and the material resulting in a rotating mass of plastic weld material traveling at a variety of angular velocities - the greatest at the tool surface diminishing to zero at the outer edge of the plastic mass surrounding the tool. This conceptual model was followed by simplified calculations which showed that the balance of moments through the weld plug was not possible under steady state conditions and realistic temperature profiles. This led to some consideration of a quasi-steady oscillating process. Later when force measurements became available some models were modified and new ones were proposed.

Stewart, Michael B.↗

NASA NTRS2016

Soft-Robotic Rover with Electrodynamic Power Scavenging: NIAC Final Report - Phase 1

The purpose of studying the capabilities of Electrodynamic Tethers (EDT) and Soft Robotics is to ascertain the feasibility of using cross-cutting EDT and soft robotics technologies to achieve future NASA mission objectives with mass and power budgets orders of magnitude lower than conventional spacecraft. In this context, the Phase I study focuses on three technological elements: the design of a soft-robotic rover that can operate in extraterrestrial oceans, demonstrating feasibility of electrodynamic tethers for power scavenging in the Europa environment, and utilizing electrolysis to power biomimetic propulsion.The Phase I results show that a soft robotic, underwater rover has many advantages over a traditional view of autonomous underwater vehicles. Many of these advantages stem from its ability to collapse or expand the body, which carries two key benefits: (i) cost savings in transport and (ii) buoyancy control. Furthermore, this rover's material offers properties that enable it to survive most oceanic conditions, withstand a likely radiation environment, and retard ice formation. The use of these soft robots under water is very attractive because buoyancy enables very large robots without the need for skeletal structures that limit their shape-changing ability. The prime limitation of soft robots for underwater exploration is their nascent state of development, an issue that this study has begun to address and that we hope to continue in Phase II. The theoretical calculations and experimental investigation on electrodynamic tethers discussed in this report show that their use in saltwater environments is feasible. However, magneto hydrodynamic effects require attention, which will be a priority in Phase II. A possible approach involves magnetic shielding of a portion of the EDT array to generate significant current from imposed alternating magnetic fields. The Phase I experiments show that this approach may enable enough power to be generated for a soft robotic rover of the scale contemplated here. This power is in the range of 1mW to 1W and determines the time required to collect and transmit science data.

Soft Robotics↗

NASA NTRS1979

O VI absorption in interstellar cloud surfaces

The velocity profiles of O VI absorption lines of 24 stars, observed in early Copernicus surveys, have been compared with the line profiles of Si III (1206.51 A) and N II (1083.99 A). The velocity structures of the O VI lines appear to be correlated with those of the material in the lower ionization stages. It is argued that the O VI absorption arises in the coronal gas of the conductive interface between hot gas, responsible for extended, soft X-ray emission, and cooler interstellar clouds. The velocity broadening of both sets of lines is attributed to motions of the cloud surfaces induced by pressure fluctuations in the interstellar medium.

Cowie, L. L.↗

NASA NTRS2008

Deployable Crew Quarters

The deployable crew quarters (DCQ) have been designed for the International Space Station (ISS). Each DCQ would be a relatively inexpensive, deployable boxlike structure that is designed to fit in a rack bay. It is to be occupied by one crewmember to provide privacy and sleeping functions for the crew. A DCQ comprises mostly hard panels, made of a lightweight honeycomb or matrix/fiber material, attached to each other by cloth hinges. Both faces of each panel are covered with a layer of Nomex cloth and noise-suppression material to provide noise isolation from ISS. On Earth, the unit is folded flat and attached to a rigid pallet for transport to the ISS. On the ISS, crewmembers unfold the unit and install it in place, attaching it to ISS structural members by use of soft cords (which also help to isolate noise and vibration). A few hard pieces of equipment (principally, a ventilator and a smoke detector) are shipped separately and installed in the DCQ unit by use of a system of holes, slots, and quarter-turn fasteners. Full-scale tests showed that the time required to install a DCQ unit amounts to tens of minutes. The basic DCQ design could be adapted to terrestrial applications to satisfy requirements for rapid deployable emergency shelters that would be lightweight, portable, and quickly erected. The Temporary Early Sleep Station (TeSS) currently on-orbit is a spin-off of the DCQ.

Izenson, Michael G.↗

NASA NTRS1983

X-ray spectra of Orion OB supergiants

The spectra are at a higher energy resolution than earlier X-ray observations of OB supergiants, and this allows stronger constraints to be placed on the location of the emission source in the outer atmosphere. The spectra of all three stars are found to be consistent with thermal sources which are only slightly attenuated by stellar wind opacity and have temperatures of approximately 10 to the (6.5 + or - 0.2) power K. A number of explanations of the soft X-ray flux distributions of early-type stars are tested. A model with the X rays coming only from a corona in a slab at the base of the wind does not seem a possibility unless the ionization or density structure of the overlying material is significantly different from that usually assumed for a cool wind. A model where the X rays are produced by radiatively driven shocks, some of which must be strong, can explain the X-ray luminosity and satisfy upper limits on the absorption by oxygen derived from the data. A high-energy (greater than 1 keV) contribution from a base coronal zone is considered possible. The spectrum of Zeta Ori shows emission near 2 keV, wich can be interpreted as line emission of Si XIII and S XV from a very hot source component with T = 1.5 x 10 to the 7th K.

Cassinelli, J. P.↗

NASA NTRS1982

Poly(aryl ethers) and related polysiloxane copolymer molecular coatings: Preparation and radiation degradation

The radiation degradation of poly(arylene ether sulfones) and related materials is studied. These basic studies are important both as a means to developing stronger, more stable matrix resins for composite materials, as well as to improve the data base in regard to chemical structure-physical property relationships. Thirty homo and copolymers were synthesized, at least partially characterized and, in several cases suitable film casting techniques were developed. Four samples were chosen for initial radiation degradation. Poly(dimethyl siloxane) soft bocks/segments can preferentially migrate to the surface of copolymer films. Since siloxanes are utilized as thermal control coatings, this form of 'molecular' coating is of interest. The chemistry for preparing such copolymers with any of the polymers described was demonstrated.

Mcgrath, J. E.↗

NASA NTRS1990

Vertical bloch line memory

Vertical Bloch Line (VBL) memory is a recently conceived, integrated, solid-state, block-access, VLSI memory which offers the potential of 1Gbit/sq cm real storage density, gigabit per second data rates, and sub-millisecond average access times simultaneously at relatively low mass, volume, and power values when compared to alternative technologies. VBL's are micromagnetic structures within magnetic domain walls which can be manipulated using magnetic fields from integrated conductors. The presence or absence of VBL pairs are used to store binary information. At present, efforts are being directed at developing a single-chip memory using 25Mbit/sq cm technology in magnetic garnet material which integrates, at a single operating point, the writing, storage, reading, and amplification functions needed in a memory. This paper describes the current design architecture, functional elements, and supercomputer simulation results which are used to assist the design process. The current design architecture uses three metal layers, two ion implantation steps for modulating the thickness of the magnetic layer, one ion implantation step for assisting propagation in the major line track, one NiFe soft magnetic layer, one CoPt hard magnetic layer, and one reflective Cr layer for facilitating magneto-optic observation of magnetic structure. Data are stored in a series of elongated magnetic domains, called stripes, which serve as storage sites for arrays of VBL pairs. The ends of these stripes are placed near conductors which serve as VBL read/write gates. A major line track is present to provide a source and propagation path for magnetic bubbles. Writing and reading, respectively, are achieved by converting magnetic bubbles to VBL's and vice versa. The output function is effected by stretching a magnetic bubble and detecting it magnetoresistively. Experimental results from the past design cycle created four design goals for the current design cycle. First, the bias field ranges for the stripes and the major line needed to be matched. Second, the magnetic field barrier between the stripe and the read/write gates needed to be reduced. Third, current conductor routing needed to be improved to reduce occurrences of open-circuiting, short-circuiting, and eddy-current shielding. Fourth, a modified Co-alloy was needed with an increased coercivity and controlled magnetization to allow VBL stabilization to occur without affecting stripe stability.

Katti, R.↗

NASA NTRS1986

Perspective on the local interstellar medium

Theoretical local-interstellar-medium (LISM) models designed to explain the observed soft-X-ray background (SXRB) are reviewed. Consideration is given to the LISM in the immediate solar vicinity (the Local Fluff, extending 3-10 pc), the local bubble (a large irregularly shaped cavity filled with very-low-density gas at 10 to the 6th K and surrounded by denser material), the three-dimensional structure of the SXRB emitting region, the thermal nature of the SXRB, and the implications of process time scales for LISM theories. A number of possible mechanisms are discussed in the context of a model in which the LISM hot gas is a remnant from the creation of the local bubble about 20 Myr ago and/or the product of supernova reheating as recently as 150 kyr ago.

Cox, D. P.↗

NASA NTRSDate not supplied

Auxetic Thermo-Responsive Shape-Memory Polyurethane Aerogels

Shape memory polymer aerogels are stimuli-responsive aerogel materials that incorporate polymer aerogel characteristics such as flexibility at low density, and high porosity with shape-changing capabilities upon exposure to external stimuli. By designing the structure of these materials at meso- to macroscale, their shape memory response can be efficiently engineered to show an auxetic response such as a negative Poisson’s ratio, leading to an active and tunable metamaterial. We present a material technology based on a shape memory polyurethane aerogel derived from aliphatic triisocyanate and triethylene glycol, which demonstrates and remembers an auxetic shape change through a thermomechanical cycle first below, and then back again above the glass transition temperature of the polyurethane. Our auxetic shape memory polyurethane aerogels exhibit a significant auxetic response with a negative Poisson’s ratio of approximately -0.8 at 15% compressive strain. This technology is expected to impact multiple areas of interest in relation to commercial, aeronautic, and aerospace industries. Potential applications include minimally invasive medical technologies, soft robotics, and self-deployable structures and habitats. Structure-property relationships of the auxetic shape memory polymer aerogels will be discussed.

Sadeq Malakooti↗

NASA NTRS1994

Formation and chemical reactivity of carbon fibers prepared by defluorination of graphite fluoride

Defluorination of graphite fluoride (CFX) by heating to temperatures of 250 to 450 C in chemically reactive environments was studied. This is a new and possibly inexpensive process to produce new carbon-based materials. For example, CF 0.68 fibers, made from P-100 carbon fibers, can be defluorinated in BrH2C-CH = CH-CH2Br (1,4-dibromo-2butene) heated to 370 C, and graphitized to produce fibers with an unusually high modulus and a graphite layer structure that is healed and cross-linked. Conversely, a sulfur-doped, visibly soft carbon fiber was produced by defluorinating CF 0.9 fibers, made from P-25, in sulfur (S) vapor at 370 C and then heating to 660 C in nitrogen (N2). Furthermore, defluorination of the CF 0.68 fibers in bromine (Br2) produced fragile, structurally damaged carbon fibers. Heating these fragile fibers to 1100 C in N2 caused further structural damage, whereas heating to 150 C in bromoform (CHBr3) and then to 1100 C in N2 healed the structural defects. The defluorination product of CFX, tentatively called activated graphite, has the composition and molecular structure of graphite, but is chemically more reactive. Activated graphite is a scavenger of manganese (Mn), and can be intercalated with magnesium (Mg). Also, it can easily collect large amounts of an alloy made from copper (Cu) and type 304 stainless steel to form a composite. Finally, there are indications that activated graphite can wet metals or ceramics, thereby forming stronger composites with them than the pristine carbon fibers can form.

Hung, Ching-Cheh↗

NASA NTRS2009

Thermal Performance Testing of Order Dependancy of Aerogels Multilayered Insulation

Robust multilayer insulation systems have long been a goal of many research projects. Such insulation systems must provide some degree of structural support and also mechanical integrity during loss of vacuum scenarios while continuing to provide insulative value to the vessel. Aerogel composite blankets can be the best insulation materials in ambient pressure environments; in high vacuum, the thermal performance of aerogel improves by about one order of magnitude. Standard multilayer insulation (MU) is typically 50% worse at ambient pressure and at soft vacuum, but as much as two or three orders of magnitude better at high vacuum. Different combinations of aerogel and multilayer insulation systems have been tested at Cryogenics Test Laboratory of NASA Kennedy Space Center. Analysis performed at Oak Ridge National Laboratory showed an importance to the relative location of the MU and aerogel blankets. Apparent thermal conductivity testing under cryogenic-vacuum conditions was performed to verify the analytical conclusion. Tests results are shown to be in agreement with the analysis which indicated that the best performance is obtained with aerogel layers located in the middle of the blanket insulation system.

Johnson, Wesley L.↗

NASA NTRS2017

Predictive Modeling of Fast-Curing Thermosets in Nozzle-Based Extrusion

This work presents an approach to modeling the dynamic spreading and curing behavior of thermosets in nozzle-based extrusions. Thermosets cover a wide range of materials, some of which permit low-temperature processing with subsequent high-temperature and high-strength working properties. Extruding thermosets may overcome the limited working temperatures and strengths of conventional thermoplastic materials used in additive manufacturing. This project aims to produce technology for the fabrication of thermoset-based structures leveraging advances made in nozzle-based extrusion, such as fused deposition modeling (FDM), material jetting, and direct writing. Understanding the synergistic interactions between spreading and fast curing of extruded thermosetting materials will provide essential insights for applications that require accurate dimensional controls, such as additive manufacturing [1], [2] and centrifugal coating/forming [3]. Two types of thermally curing thermosets -- one being a soft silicone (Ecoflex 0050) and the other being a toughened epoxy (G/Flex) -- served as the test materials in this work to obtain models for cure kinetics and viscosity. The developed models align with extensive measurements made with differential scanning calorimetry (DSC) and rheology. DSC monitors the change in the heat of reaction, which reflects the rate and degree of cure at different crosslinking stages. Rheology measures the change in complex viscosity, shear moduli, yield stress, and other properties dictated by chemical composition. By combining DSC and rheological measurements, it is possible to establish a set of models profiling the cure kinetics and chemorheology without prior knowledge of chemical composition, which is usually necessary for sophisticated mechanistic modeling. In this work, we conducted both isothermal and dynamic measurements with both DSC and rheology. With the developed models, numerical simulations yielded predictions of diameter and height of droplets, along with width and height of extruded lines cured at varied temperatures. Experimental results carried out on a goniometric platform and a nozzle-based 3D printer showed agreement with the numerical simulations. Finally, this presentation will show how the models are adaptable to the planning of tool paths and designs in additive manufacturing.

Xie, Jingjin↗

NASA NTRS1997

Study of the Source Regions of Coronal Mass Ejections Using Yohkoh SXT Data

The scientific objective of the program was to better understand how CMEs (Coronal Mass Ejections) are initiated at the sun by examining structures on the disk which are related to the origins of CMEs. CMEs represent important disruptions of large-scale structures of closed magnetic fields in the corona, and result in significant disturbances of the interplanetary medium and near-Earth space. The program pertained to NASA's objectives of understanding the physics of solar activity and the structured and evolution of the corona, and the results are being applied to understanding CMEs currently being observed by SOHO near the sun and by WIND and Ulysses in the heliosphere. Three general areas of research were pursued in the program. One was to use Yohkoh soft X-ray telescope (SXT) images of eruptive events visible against the solar disk to examine the coronal structures and the boundaries of the large-scale magnetic fields considered to be involved in coronal mass ejections (CMEs). The second area involved a survey and study of SXT X-ray arcade events which exhibit dimming, or the possible depletion of coronal material above and possibly before onset of the bright long-duration event (LDE). Finally, we studied the SXT data during periods when white light CMEs were observed the HAO Mauna Loa K-coronameter and, conversely, we examined the white light data during periods when expanding X-ray loops were observed at the limb.

Webb, David F.↗

NASA NTRS2005

A K-BKZ Formulation for Soft-Tissue Viscoelasticity

A viscoelastic model of the K-BKZ (Kaye 1962; Bernstein et al. 1963) type is developed for isotropic biological tissues, and applied to the fat pad of the human heel. To facilitate this pursuit, a class of elastic solids is introduced through a novel strain-energy function whose elements possess strong ellipticity, and therefore lead to stable material models. The standard fractional-order viscoelastic (FOV) solid is used to arrive at the overall elastic/viscoelastic structure of the model, while the elastic potential via the K-BKZ hypothesis is used to arrive at the tensorial structure of the model. Candidate sets of functions are proposed for the elastic and viscoelastic material functions present in the model, including a regularized fractional derivative that was determined to be the best. The Akaike information criterion (AIC) is advocated for performing multi-model inference, enabling an objective selection of the best material function from within a candidate set.

Freed, Alan D.↗

NASA NTRS1972

Program for the exploitation of unused NASA patents

The program to exploit unused NASA patents through the use of a multidisciplinary approach involving faculty students, and research staff is reported. NASA patents were screened for their applicability outside the space program, specific applications were identified, and the technical and commercial feasibility of these applications was established. Also application of this technology by governmental agencies outside the space program was sought. The program was specifically interested in energy absorbing devices such as those developed for lunar soft landings. These energy absorbing devices absorb large amounts of mechanical energy but are, in general, not reusable. Some of these devices can also operate as structural elements until their structural load capacity is exceeded and they become activated as energy absorbers. The capability of these devices to operate as structural elements and as energy absorbing devices makes them candidates for many applications in the fields of transportation and materials handling safety where accidents take a large toll in human injury and property damage.

Fay, R. J.↗

NASA NTRS2001

Self-assembly of mesoscopically ordered chromatic polydiacetylene/silica nanocomposites

Nature abounds with intricate composite architectures composed of hard and soft materials synergistically intertwined to provide both useful functionality and mechanical integrity. Recent synthetic efforts to mimic such natural designs have focused on nanocomposites, prepared mainly by slow procedures like monomer or polymer infiltration of inorganic nanostructures or sequential deposition. Here we report the self-assembly of conjugated polymer/silica nanocomposite films with hexagonal, cubic or lamellar mesoscopic order using polymerizable amphiphilic diacetylene molecules as both structure-directing agents and monomers. The self-assembly procedure is rapid and incorporates the organic monomers uniformly within a highly ordered, inorganic environment. Polymerization results in polydiacetylene/silica nanocomposites that are optically transparent and mechanically robust. Compared to ordered diacetylene-containing films prepared as Langmuir monolayers or by Langmuir-Blodgett deposition, the nanostructured inorganic host alters the diacetylene polymerization behaviour, and the resulting nanocomposite exhibits unusual chromatic changes in response to thermal, mechanical and chemical stimuli. The inorganic framework serves to protect, stabilize, and orient the polymer, and to mediate its function. The nanocomposite architecture also provides sufficient mechanical integrity to enable integration into devices and microsystems.

NASA Discipline Life Support Systems↗