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NASA NTRS1999

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Huang, Norden E.↗

NASA NTRS2013

Microbial Burden Approach : New Monitoring Approach for Measuring Microbial Burden

Advantages of new approach for differentiating live cells/ spores from dead cells/spores. Four examples of Salmonella outbreaks leading to costly destruction of dairy products. List of possible collaboration activities between JPL and other industries (for future discussion). Limitations of traditional microbial monitoring approaches. Introduction to new approach for rapid measurement of viable (live) bacterial cells/spores and its areas of application. Detailed example for determining live spores using new approach (similar procedure for determining live cells). JPL has developed a patented approach for measuring amount of live and dead cells/spores. This novel "molecular" method takes less than 5 to 7 hrs. compared to the seven days required using conventional techniques. Conventional "molecular" techniques can not discriminate live cells/spores among dead cells/spores. The JPL-developed novel method eliminates false positive results obtained from conventional "molecular" techniques that lead to unnecessary delay in the processing and to unnecessary destruction of food products.

microbial monitoring↗

NASA NTRS1998

A Geometry Based Infra-Structure for Computational Analysis and Design

The computational steps traditionally taken for most engineering analysis suites (computational fluid dynamics (CFD), structural analysis, heat transfer and etc.) are: (1) Surface Generation -- usually by employing a Computer Assisted Design (CAD) system; (2) Grid Generation -- preparing the volume for the simulation; (3) Flow Solver -- producing the results at the specified operational point; (4) Post-processing Visualization -- interactively attempting to understand the results. For structural analysis, integrated systems can be obtained from a number of commercial vendors. These vendors couple directly to a number of CAD systems and are executed from within the CAD Graphical User Interface (GUI). It should be noted that the structural analysis problem is more tractable than CFD; there are fewer mesh topologies used and the grids are not as fine (this problem space does not have the length scaling issues of fluids). For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. In most cases, the output from a CAD system could go to Initial Graphics Exchange Specification (IGES) or Standard Exchange Program (STEP) files. The output from Grid Generators and Solvers do not really have standards though there are a couple of file formats that can be used for a subset of the gridding (i.e. PLOT3D data formats). The user would have to patch up the data or translate from one format to another to move to the next step. Sometimes this could take days. Specifically the problems with this procedure are:(1) File based -- Information flows from one step to the next via data files with formats specified for that procedure. File standards, when they exist, are wholly inadequate. For example, geometry from CAD systems (transmitted via IGES files) is defined as disjoint surfaces and curves (as well as masses of other information of no interest for the Grid Generator). This is particularly onerous for modern CAD systems based on solid modeling. The part was a proper solid and in the translation to IGES has lost this important characteristic. STEP is another standard for CAD data that exists and supports the concept of a solid. The problem with STEP is that a solid modeling geometry kernel is required to query and manipulate the data within this type of file. (2) 'Good' Geometry. A bottleneck in getting results from a solver is the construction of proper geometry to be fed to the grid generator. With 'good' geometry a grid can be constructed in tens of minutes (even with a complex configuration) using unstructured techniques. Adroit multi-block methods are not far behind. This means that a million node steady-state solution can be computed on the order of hours (using current high performance computers) starting from this 'good' geometry. Unfortunately, the geometry usually transmitted from the CAD system is not 'good' in the grid generator sense. The grid generator needs smooth closed solid geometry. It can take a week (or more) of interaction with the CAD output (sometimes by hand) before the process can begin. One way Communication. (3) One-way Communication -- All information travels on from one phase to the next. This makes procedures like node adaptation difficult when attempting to add or move nodes that sit on bounding surfaces (when the actual surface data has been lost after the grid generation phase). Until this process can be automated, more complex problems such as multi-disciplinary analysis or using the above procedure for design becomes prohibitive. There is also no way to easily deal with this system in a modular manner. One can only replace the grid generator, for example, if the software reads and writes the same files. Instead of the serial approach to analysis as described above, CAPRI takes a geometry centric approach. This makes the actual geometry (not a discretized version) accessible to all phases of the analysis. The connection to the geometry is made through an Application Programming Interface (API) and NOT a file system. This API isolates the top-level applications (grid generators, solvers and visualization components) from the geometry engine. Also this allows the replacement of one geometry kernel with another, without effecting these top-level applications. For example, if UniGraphics is used as the CAD package then Parasolid (UG's own geometry engine) can be used for all geometric queries so that no solid geometry information is lost in a translation. This is much better than STEP because when the data is queried, the same software is executed as used in the CAD system. Therefore, one analyzes the exact part that is in the CAD system. CAPRI uses the same idea as the commercial structural analysis codes but does not specify control. Software components of the CAD system are used, but the analysis suite, not the CAD operator, specifies the control of the software session. This also means that the license issues (may be) minimized and individuals need not have to know how to operate a CAD system in order to run the suite.

Haimes, Robert↗

NASA NTRS2006

Marsviewer

Marsviewer is a multi-platform application designed to aid in quality control, browsing, and analysis of original science product images (Experiment Data Records, or EDRs) and derived image data products (Reduced Data Records, or RDRs) returned by the Mars Explorer Rover (MER) mission. Marsviewer offers an abstraction of the products organization via a file finder. For example, the application understands the file structure and filename conventions of the MER Operational Storage Server, helping the user to navigate this complex file system to find desired images. Marsviewer also works with a flat file system, remote-operations file systems, image-archive file systems, and others. All EDRs found for a given solar day (Sol) are displayed in a list, optionally with thumbnail images. Once the user selects an image from the list, a tabbed pane conveniently displays the original source image and all associated RDRs. Marsviewer provides the option of overlaying derived images upon the source image, resulting in an easier-to-interpret color representation of the data. Display manipulations such as zoom, data range adjustment, contrast enhancement, and contour control are available. Image metadata (labels) from the current image can be displayed and searched. The architecture of the program is extensible: new types of RDRs can be installed and new file finders can be added to adapt the program to different file structures and different filename conventions. This keeps the application flexible and provides an opportunity for reuse with future rover missions.

Toole, Nicholas↗

NASA NTRS1989

Computer image generation: Reconfigurability as a strategy in high fidelity space applications

The demand for realistic, high fidelity, computer image generation systems to support space simulation is well established. However, as the number and diversity of space applications increase, the complexity and cost of computer image generation systems also increase. One strategy used to harmonize cost with varied requirements is establishment of a reconfigurable image generation system that can be adapted rapidly and easily to meet new and changing requirements. The reconfigurability strategy through the life cycle of system conception, specification, design, implementation, operation, and support for high fidelity computer image generation systems are discussed. The discussion is limited to those issues directly associated with reconfigurability and adaptability of a specialized scene generation system in a multi-faceted space applications environment. Examples and insights gained through the recent development and installation of the Improved Multi-function Scene Generation System at Johnson Space Center, Systems Engineering Simulator are reviewed and compared with current simulator industry practices. The results are clear; the strategy of reconfigurability applied to space simulation requirements provides a viable path to supporting diverse applications with an adaptable computer image generation system.

Bartholomew, Michael J.↗

NASA NTRS1995

The multidimensional Self-Adaptive Grid code, SAGE, version 2

This new report on Version 2 of the SAGE code includes all the information in the original publication plus all upgrades and changes to the SAGE code since that time. The two most significant upgrades are the inclusion of a finite-volume option and the ability to adapt and manipulate zonal-matching multiple-grid files. In addition, the original SAGE code has been upgraded to Version 1.1 and includes all options mentioned in this report, with the exception of the multiple grid option and its associated features. Since Version 2 is a larger and more complex code, it is suggested (but not required) that Version 1.1 be used for single-grid applications. This document contains all the information required to run both versions of SAGE. The formulation of the adaption method is described in the first section of this document. The second section is presented in the form of a user guide that explains the input and execution of the code. The third section provides many examples. Successful application of the SAGE code in both two and three dimensions for the solution of various flow problems has proven the code to be robust, portable, and simple to use. Although the basic formulation follows the method of Nakahashi and Deiwert, many modifications have been made to facilitate the use of the self-adaptive grid method for complex grid structures. Modifications to the method and the simple but extensive input options make this a flexible and user-friendly code. The SAGE code can accommodate two-dimensional and three-dimensional, finite-difference and finite-volume, single grid, and zonal-matching multiple grid flow problems.

Davies, Carol B.↗

NASA NTRS2002

Satellites as Sentinels for Environment & Health

Satellites as Sentinels for Environment & Health Remotely-sensed data and observations are providing powerful new tools for addressing human and ecosystem health by enabling improved understanding of the relationships and linkages between health-related environmental parameters and society as well as techniques for early warning of potential health problems. NASA Office of Earth Science Applications Program has established a new initiative to utilize its data, expertise, and observations of the Earth for public health applications. In this initiative, lead by Goddard Space Flight Center, remote sensing, geographic information systems, improved computational capabilities, and interdisciplinary research between the Earth and health science communities are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global health issues. This presentation provides a number of recent examples of applications of advanced remote sensing and other technologies to health.and security issues related to the following: infectious and vector-borne diseases; urban, regional and global air pollution; African and Asian airborne dust; heat stress; UV radiation; water-borne disease; extreme weather; contaminant pathways (ocean, atmosphere, ice)

Maynard, Nancy G.↗

NASA NTRS1995

Applications of decision analysis and related techniques to industrial engineering problems at KSC

This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).

Evans, Gerald W.↗

NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental tool in numerous image processing and remote sensing applications. For example, unsupervised clustering is often used to obtain vegetation maps of an area of interest. This approach is useful when reliable training data are either scarce or expensive, and when relatively little a priori information about the data is available. Unsupervised clustering methods play a significant role in the pursuit of unsupervised classification. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points (or samples) in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute a set of cluster centers in d-space. Although there is no specific optimization criterion, the algorithm is similar in spirit to the well known k-means clustering method in which the objective is to minimize the average squared distance of each point to its nearest center, called the average distortion. One significant feature of ISOCLUS over k-means is that clusters may be merged or split, and so the final number of clusters may be different from the number k supplied as part of the input. This algorithm will be described in later in this paper. The ISOCLUS algorithm can run very slowly, particularly on large data sets. Given its wide use in remote sensing, its efficient computation is an important goal. We have developed a fast implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm, the filtering algorithm, by Kanungo et al.. They showed that, by storing the data in a kd-tree, it was possible to significantly reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm. For technical reasons, which are explained later, it is necessary to make a minor modification to the ISOCLUS specification. We provide empirical evidence, on both synthetic and Landsat image data sets, that our algorithm's performance is essentially the same as that of ISOCLUS, but with significantly lower running times. We show that our algorithm runs from 3 to 30 times faster than a straightforward implementation of ISOCLUS. Our adaptation of the filtering algorithm involves the efficient computation of a number of cluster statistics that are needed for ISOCLUS, but not for k-means.

Memarsadeghi, Nargess↗

NASA NTRS2005

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗

NASA NTRS2009

Achieving a Prioritized Research and Technology Development Portfolio for the Dust Management Project

Mission architectures for human exploration of the lunar surface continue to advance as well as the definitions of capability needs, best practices and engineering design to mitigate the impact of lunar dust on exposed systems. The NASA DMP has been established as the agency focal point for dust characterization, technology, and simulant development. As described in this paper, the DMP has defined a process for selecting and justifying its R&T portfolio. The technology prioritization process, which is based on a ranking system according to weighted criteria, has been successfully applied to the current DMP dust mitigation technology portfolio. Several key findings emerged from this assessment. Within the dust removal and cleaning technologies group, there are critical technical challenges that must be overcome for these technologies to be implemented for lunar applications. For example, an in-situ source of CO2 on the moon is essential to the CO2 shower technology. Also, significant development effort is required to achieve technology readiness level TRL 6 for the electrostatic cleaning system for removal of particles smaller than 50 pm. The baseline materials related technologies require considerable development just to achieve TRL 6. It is also a nontrivial effort to integrate the materials in hardware for lunar application. At present, there are no terrestrial applications that are readily adaptable to lunar surface applications nor are there any obvious leading candidates. The unique requirements of dust sealing systems for lunar applications suggest an extensive development effort will be necessary to mature dust sealing systems to TRL 6 and beyond. As discussed here, several alternate materials and technologies have achieved high levels of maturity for terrestrial applications and warrant due diligence in ongoing assessment of the technology portfolio. The present assessment is the initial step in an ongoing effort to continually evaluate the DMP technology portfolio and external non-NASA relevant technology developments efforts to maintain an optimal investment profile. At the same time, there is an ongoing review of agency-wide dust-related R&T activities. The results of these ongoing assessments will be reported in future publications.

Hyatt, Mark J.↗

NASA NTRS1981

Instrumentation applications to Space Shuttle models and thermal protection system tiles tested in NASA-AMES wind tunnels

The highlights of the many wind-tunnel tests conducted in the course of the Space Shuttle development program are presented with emphasis on instrumentation applications. The examples of tests discussed include airframe aerodynamics, aerodynamic heating, aerodynamic noise, tile dynamic response, and tile loads. Many of the tests were conducted with standard wind-tunnel instrumentation. Most of the more unusual instrumentation requirements were related to the thermal protection system, where some pressure-sensor concepts were adapted to measure airloads on tiles. These measurements provided the only quantitative data that could be used to confirm the airload analysis procedure. Limited applications of computers to experimental control, in conjunction with data taken during Shuttle tests, have resulted in substantial benefits in overall test efficiency.

Coe, C. F.↗

NASA NTRS1947

Rockets using Liquid Oxygen

It is my task to discuss rocket propulsion using liquid oxygen and my treatment must be highly condensed for the ideas and experiments pertaining to this classic type of rocket are so numerous that one could occupy a whole morning with a detailed presentation. First, with regard to oxygen itself as compared with competing oxygen carriers, it is known that the liquid state of oxygen, in spite of the low boiling point, is more advantageous than the gaseous form of oxygen in pressure tanks, therefore only liquid oxygen need be compared with the oxygen carriers. The advantages of liquid oxygen are absolute purity and unlimited availability at relatively small cost in energy. The disadvantages are those arising from the impossibility of absolute isolation from heat; consequently, allowance must always be made for a certain degree of vaporization and only vented vessels can be used for storage and transportation. This necessity alone eliminates many fields of application, for example, at the front lines. In addition, liquid oxygen has a lower specific weight than other oxygen carriers, therefore many accessories become relatively larger and heavier in the case of an oxygen rocket, for example, the supply tanks and the pumps. The advantages thus become effective only in those cases where definitely scheduled operation and a large ground organization are possible and when the flight requires a great concentration of energy relative to weight. With the aim of brevity, a diagram of an oxygen rocket will be presented and the problem of various component parts that receive particularly thorough investigation in this classic case but which are also often applicable to other rocket types will be referred to.

Busemann, Adolf↗

NASA NTRSDate not supplied

The Application of Artificial Intelligence Deep Learning to Visually Identify Micrometeoroid and Orbital Debris Impacts

Recent advances in Artificial Intelligence (AI) are changing the World. Novel approaches to training AI systems have led to dramatic reductions in the amount of time required. Training an AI system could take years and teams of people using traditional methods, but with the advancements of Deep Learning (DL) models this training can now be accomplished by an individual in a matter of minutes. The development of “fast AI” libraries has delivered AI to essentially everyone. Democratization of AI power has inspired many to revisit past problems that will benefit from DL approaches. For example, the application of AI has improved detection of breast cancer by 20% compared to traditional detection methods. Computer vision and machine learning are being used to identify soil deficiencies and provide planting recommendations to farmers. Success stories like these and many others have provided inspiration to see if AI can help improve one of our needed capabilities – that of visually identifying micrometeoroid and orbital debris (MMOD) impact damage to spacecraft from images of the spacecraft exterior. The need to visually locate and characterize spacecraft MMOD impact damage has been present since the early days of space travel. This is often done by either having a crew member take photographs of the spacecraft through a window using a hand-held camera or ground personnel directing externally-mounted cameras. The photographs are then transmitted back to Earth for visual analysis. This method of MMOD damage inspection works well and has been used on various spacecraft including the Space Shuttle and the International Space Station (ISS). One of the issues with the current method that we believe AI could improve is the speed and possibly the accuracy in identifying MMOD impacts. Note that detecting MMOD impacts in images can be very difficult. The visual appearance of an MMOD impact can change dramatically with lighting conditions, size of impact, depth of penetration, material types, surface waviness, fabric coverings, camera & lens, distance to surface, spacecraft orientation, analyst experience, and many other factors. Currently, this takes a team of highly-experienced specialists in both the fields of Image Analysis and MMOD impacts. This paper documents our initial research in training an AI DL model using the fast-AI library to identify actual and simulated MMOD impacts and perforations into exposed flat surfaces. While we recognize that this initial goal seems modest, it must be noted that what we have done would have taken teams of individuals and years of training just ten years ago. Our long-term goal is to add complexity and use-cases to the DL model being trained to expand the capabilities of this model so that it can be used to identify MMOD impacts on all types of spacecraft surfaces.

Cameron M Collins↗

NASA NTRS2014

Black Molecular Adsorber Coatings for Spaceflight Applications

The molecular adsorber coating is a new technology that was developed to mitigate the risk of on-orbit molecular contamination on spaceflight missions. The application of this coating would be ideal near highly sensitive, interior surfaces and instruments that are negatively impacted by outgassed molecules from materials, such as plastics, adhesives, lubricants, epoxies, and other similar compounds. This current, sprayable paint technology is comprised of inorganic white materials made from highly porous zeolite. In addition to good adhesion performance, thermal stability, and adsorptive capability, the molecular adsorber coating offers favorable thermal control characteristics. However, low reflectivity properties, which are typically offered by black thermal control coatings, are desired for some spaceflight applications. For example, black coatings are used on interior surfaces, in particular, on instrument baffles for optical stray light control. Similarly, they are also used within light paths between optical systems, such as telescopes, to absorb light. Recent efforts have been made to transform the white molecular adsorber coating into a black coating with similar adsorptive properties. This result is achieved by optimizing the current formulation with black pigments, while still maintaining its adsorption capability for outgassing control. Different binder to pigment ratios, coating thicknesses, and spray application techniques were explored to develop a black version of the molecular adsorber coating. During the development process, coating performance and adsorption characteristics were studied. The preliminary work performed on black molecular adsorber coatings thus far is very promising. Continued development and testing is necessary for its use on future contamination sensitive spaceflight missions.

adsorption↗

NASA NTRS2014

Black Molecular Adsorber Coatings for Spaceflight Applications

adsorption↗

NASA NTRS2019

Going Beyond Standard Ocean Color Observations: Lidar and Polarimetry

Passive ocean color images have provided a sustained synoptic view of the distribution of ocean optical properties and color and biogeochemical parameters for the past 20-plus years. These images have revolutionized our view of the ocean. Remote sensing of ocean color has relied on measurements of the radiance emerging at the top of the atmosphere, thus neglecting the polarization and the vertical components. Ocean color remote sensing utilizes the intensity and spectral variation of visible light scattered upward from beneath the ocean surface to derive concentrations of biogeochemical constituents and inherent optical properties within the ocean surface layer. However, these measurements have some limitations. Specifically, the measured property is a weighted-integrated value over a relatively shallow depth, it provides no information during the night and retrievals are compromised by clouds, absorbing aerosols, and low Sun zenithal angles. In addition, ocean color data provide limited information on the morphology and size distribution of marine particles. Major advances in our understanding of global ocean ecosystems will require measurements from new technologies, specifically lidar and polarimetry. These new techniques have been widely used for atmospheric applications but have not had as much as interest from the ocean color community. This is due to many factors including limited access to in-situ instruments and/or space-borne sensors and lack of attention in university courses and ocean science summer schools curricula. However, lidar and polarimetry technology will complement standard ocean color products by providing depth-resolved values of attenuation and scattering parameters and additional information about particle morphology and chemical composition. This review aims at presenting the basics of these techniques, examples of applications and at advocating for the development of in-situ and space-borne sensors. Recommendations are provided on actions that would foster the embrace of lidar and polarimetry as powerful remote sensing tools by the ocean science community.

Jamet, Cedric↗

NASA NTRS1991

Industrial Applications of Graphite Fluoride Fibers

Based on fluorination technology developed during 1934 to 1959, and the fiber technology developed during the 1970s, a new process was developed to produce graphite fluoride fibers. In the process, pitch based graphitized carbon fibers are at first intercalated and deintercalated several times by bromine and iodine, followed by several cycles of nitrogen heating and fluorination at 350 to 370 C. Electrical, mechanical, and thermal properties of this fiber depend on the fluorination process and the fluorine content of the graphite fluoride product. However, these properties are between those of graphite and those of PTFE (Teflon). Therefore, it is considered to be a semiplastic. The physical properties suggest that this new material may have many new and unexplored applications. For example, it can be a thermally conductive electrical insulator. Its coefficient of thermal expansion (CTE) can be adjusted to match that of silicon, and therefore, it can be a heat sinking printed circuit board which is CTE compatible with silicon. Using these fibers in printed circuit boards may provide improved electrical performance and reliability of the electronics on the board over existing designs. Also, since it releases fluorine at 300 C or higher, it can be used as a material to store fluorine and to conduct fluorination. This application may simplify the fluorination process and reduce the risk of handling fluorine.

Hung, Ching-Cheh↗