Search NASA⌕ Search

SEARCH · Search NASA

Results for “plastic oxidation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

332 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

X-Ray Photoelectron Spectroscopy

The interaction of photon and the electron goes back to the early part of 19th century emanating from the photo-electric effect depicted by none other than Albert Einstein (Ref 1) described in 1905, and the redistribution of kinetic energy resulting from the interaction of x-ray and solids reported during early part of the century (Ref.2). The spectrum resolutions obtained at that time was not sufficient to observe distinct peaks in spectra for materials. Thus, these phenomena hardly attracted any attention for many years following these discoveries. The modern X-ray Photoelectron Spectroscopy (XPS) has been possible by the extensive and significant contribution from Kai Siegbahn and others (Ref.3, 4) of Uppsala University. Siegbahn developed and employed a high-resolution electron spectrometer that revealed electron peaks in a spectrum emerging from the interaction of x-rays and solids. Eventually, Kai Siegbahn received Nobel Prize in 1981 for his contributions to XPS. Around 1958, shifts in elemental peaks were realized in compounds when the same elements are bound to other but different elements. This discovery resulted in the chemical state identification in various chemicals as well as the oxidation states of atoms in compounds. Because of these useful physical effects, the Uppsala group named XPS with a synonymous name of ESCA (Electron Spectroscopy for Chemical Analysis) used widely today and will be used here alternatively. Therefore, XPS or ESCA not only identifies the element, but also the compound these elements form, from their chemical shifts. Compared to other micro-analytical techniques such as Energy Dispersive (EDS) or Wavelength Dispersive (WDS) techniques, XPS analyzes only few atomic layers present on the surface. This was discovered early in 1966 (Ref. 5). While this has awarded a merit to the analytical technique to analyze very thin layers such as films and coatings, it often analyzes the adsorbed superficial gases and contaminations on a sample introduced to its analytical chamber. This necessitates the surface is cleaned and the underlying material, material of interest, is exposed in a clean environment such that the material of interest is analyzed. The cleaning is accomplished by a scanning ion gun within the analytical chamber of the instrument. Ion gun uses an argon gas and is commonly attached in most modern machines. Reliable and efficient vacuum systems employed in modern machines does not allow adsorbed layers to rebuild after the surface is cleaned. Development of efficient and reliable vacuum pumps over these developmental years is yet another important step in the commercialization of XPS machines. Vacuum levels of better than 10-7 torr are essential to increase the mean free path of electrons released from the sample surface. Thus, modern machines are equipped with high capacity ion, turbo or cryogenic pumps in their analytical chambers. Today, XPS has advanced from an applied physics laboratory to industry for use in quality control as well as analysis of contaminants and has taken a dominant role in microanalysis. Its uniqueness arises from the fact that it is considered non-destructive compared to other common micro-analytical techniques using the electron and ion excitation sources. Polymers and plastics could be analyzed since the binding energies of saturated and unsaturated bonds in atoms could be separated. Extremely thin layers could be analyzed including materials with layered structures. The technique, though did not advance for many years, has now opened a new window for research as well as applications in industry due to its ability to separate and measure the chemical shifts in bound elements. Principles

Panda, Binayak↗
DOE OSTI2025

Technoeconomic Analysis of Microwave-Assisted Dry Reforming Integrated with Chemical Looping for Production of Methanol

Methanol is a key component in producing formaldehyde, acetic acid, and methyl tert -butyl ether (MTBE) and supports a wide array of industries, including plastics, textiles, and automotive. It also plays a growing role in renewable energy solutions. However, the conventional production of methanol involves steam reforming of methane, which is very energy-intensive and produces significant quantities of the greenhouse gas carbon dioxide. In this research, a chemical looping scheme is combined with dry reforming of natural gas in a novel microwave reactor to produce an industrial quantity of methanol. A heat exchanger network is developed to substantially reduce hot and cold utility usage. The effect of the cost of purchasing carbon dioxide from an external source for dry reforming, the capital cost of the microwave reactor, and the cost of electricity on the net present value is analyzed. Technoeconomic comparison with the conventional industrial process that produces methanol via steam reforming of methane indicates that the chemical looping generates a significant positive net present value along with a substantial reduction in carbon dioxide emissions while producing methanol significantly below the U.S. Department of Energy’s goal of $800/ton.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

The response of thermally and optically stimulated luminescence from Al2O3:C to high-energy heavy charged particles

The thermoluminescence (TL) and optically stimulated luminescence (OSL) response of Al2O3 dosimeters to high-energy heavy charged particles (HCP) has been studied using the heavy ion medical accelerator at Chiba, Japan. The samples were Al2O3 single-crystal chips, of the type usually known as TLD-500, and Luxel(TM) dosimeters (Al2O3:C powder in plastic) from Landauer Inc. The samples were exposed to 4He (150 MeV/u), 12C (400 MeV/u), 28Si (490 MeV/us) and 56Fe (500 MeV/u) ions, with linear energy transfer values covering the range from 2.26 to 189 keV/micrometers in water and doses from 1 to 100 mGy (to water). A 90Sr/90Y beta source, calibrated against a 60Co secondary standard, was used for calibration purposes. For OSL, we used both continuous-wave OSL measurements (CW-OSL, using green light stimulation at 525 nm) and pulsed OSL measurements (POSL, using 532 nm stimulation from a Nd:YAG Q-switched laser). The efficiencies (eta HCP, gamma) of the different HCPs at producing OSL or TL were observed to depend not only upon the linear energy transfer (LET) of the HCP, but also upon the sample type (single crystal chip or Luxel(TM)) and the luminescence method used to define the signal--i.e. TL, CW-OSL initial intensity, CW-OSL total area, or POSL. Observed changes in shape of the decay curve lead to potential methods for extracting LET information of unknown radiation fields. A discussion of the results is given, including the potential use of OSL from Al2O3 in the areas of space radiation dosimetry and radiation oncology. c2004 Elsevier Ltd. All rights reserved.

Heavy Ions↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2024

Upcycling linear low-density polyethylene waste to turbostratic graphene for high mass loading supercapacitors

Linear low-density polyethylene (LLDPE) waste is difficult to upcycle into more valuable carbon materials because it tends to completely decompose into small molecules during thermal processing. In this work, LLDPE is upcycled into a high quality turbostratic graphene using a pre-treatment step to oxidatively crosslink the polymer with the assistance of solid additives (KCl and K 2 CO 3 ) that improve crosslinking by increasing the effective surface area of the polymer melt during processing. After this pretreatment step, the crosslinked polymer could then be carbonized and catalytically graphenized between 400–950°C without decomposition of the polymer feedstock. The LLDPE derived graphene (LLDPE-G) obtained from this process has a Brunauer–Emmett–Teller (BET) specific surface area, up to 1800m 2 g -1 and average Raman I D /I G and I 2D /I G ratios of 0.85 and 0.57, respectively, indicating high quality graphene. When used as an electrode material in symmetric supercapacitors, LLDPE-G possesses a specific capacitance up to 175Fg -1 at a mass loading of 20mgcm -2 , which is two times the commercial requirement, yielding an areal capacitance of 3.5 Fcm -2 . Moreover, LLDPE-G exhibits exceptional cycling stability with a capacitance retention of 95.8 % after 100,000 cycles at a current density of 4.0 Ag -1 . Additionally, the KCl and K 2 CO 3 solids are recycled and reused over 3 complete reaction cycles to make new LLDPE-G with the material quality and electrocapacitive performance retained and verified after each cycle. Our approach creates new opportunities for upcycling waste LLDPE and other varieties of polyethylene into a higher value graphene used for electrochemical energy storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Data-Driven Discovery of Bimetallic Nanoparticles Catalysts for the Hydrogenolysis of Polyethylene

Supported platinum nanoparticles are known to convert polyolefins to high-quality liquid hydrocarbons with hydrogen under relatively mild conditions. However, no systematic study has been undertaken using bimetallic catalysts for polyethylene upcycling. Specifically, a total of 98 monometallic and bimetallic combinations (Ag, Cr, Co, Cu, Fe, Ga, In, Mn, Ni, Pd, Pt, Rh, Ru, Zr) on alumina were synthesized utilizing surface organometallic chemistry (SOMC) technique via robotic platform. These were investigated at a small scale (10 mg of catalyst and 50 mg of polyethylene) for their activity for the hydrogenolysis of polyethylene in a high-throughput batch reactor. Combinations of Ni and Co were selected as candidates with high activity toward conversion into paraffin oils. Reaction conditions were optimized with Ni/Co/Al 2 O 3 catalyst at a larger scale (300 mg catalyst and 3 g polyethylene) to obtain a high yield (93.1%) of paraffin wax with desired properties (M n = 380 Da) and low polydispersity (Đ = 1.2). Ni/Co/Al 2 O 3 was compared against Co/Ni/Al 2 O 3 to understand the role of the deposition sequence. When Co is deposited before Ni, a layer of cobalt aluminate is formed upon reduction, stabilizing the deposition of 5 nm metallic Ni particles. When nickel is deposited before Co, particles are larger (average >20 nm) and more oxidized (Ni δ+ in NiAl 2 O 4 ), decreasing the availability of the catalytically active metallic Ni. In conclusion, the difference in electronic environments was also described by DFT calculations, which revealed that smaller 3D clusters of Ni are preferred on CoAl2O4 over the 3D clusters on NiAl 2 O 4 and that these smaller clusters are more reducible, as confirmed experimentally.

Polymer↗
DOE OSTI2024

Polystyrene Hydrogenolysis to High-Quality Lubricants Using Ni/SiO 2

Pyrolytic and light-activated oxidation processes are leading technologies for utilizing polystyrene (PS) wastes. These approaches exhibit poor selectivities, use complex reactors, and require solvents. Hydrogenolysis is effective for deconstructing polyolefins, but its application to PS feedstocks has been limited. Herein, we demonstrate Ni/SiO 2 catalysts to facilitate PS (M w ≈ 97 kDa) hydrogenolysis to produce lubricant base oils possessing group IV properties, achieving maximum yields of 70% within 6 h at 300 °C and 70 bar of H 2 . Gas, liquid, and oil product yields are stable across reaction conditions, whereas hydrogenation of the PS aromaticity and reduction of the molecular weight benefit from higher temperatures and H 2 pressures. Time-dependent experiments underscore the importance of elevated H 2 pressure, revealing that PS hydrogenolysis occurs sequentially, with aromatic ring hydrogenation preceding degradation of the C–C backbone. Kinetic measurements with 1,2-diphenylethane as a probe molecule demonstrate that ring hydrogenation pis 3 orders of magnitude faster than internal C–C bond cleavage over Ni/SiO 2 . Ni/SiO 2 proves to be effective in the hydrogenolysis of heavier PS polymers and rigid commercial PS products. Conversely, flexibility and foam PS feeds result in Ni/SiO 2 deactivation, attributed to performance additives. Unlike polyolefins, the process produces very little methane and other light hydrocarbons. Furthermore, these findings expand the applicability of hydrogenolysis to PS feedstocks, offering a versatile solution and broadening the range of high-value products from PS to include lubricant base oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Yield strength of CeO 2 measured from static compression in a radial diamond anvil cell

Cerium oxide (ceria, CeO 2 ) is frequently used as a standard in applications such as synchrotron and x-ray free electron lasers for calibrating x-ray wavelengths and offers the potential for understanding the high pressure properties and deformation mechanisms in a wide range of similar face centered cubic (fcc) materials. In this study, the pressure dependence of the strength of ceria was investigated up to 38 GPa using angle dispersive x-ray diffraction in a radial geometry in a diamond anvil cell. In this experiment, the difference in the stress along the axis of compression and perpendicular to the direction of compression can be determined, giving a quantity known as the differential stress. It was found that the differential stress (t), a measure of the lower bound for yield strength, initially increases rapidly from 0.35 ± 0.06 GPa to 2.2 ± 0.4 GPa at pressures of 1.8 and 3.8 GPa, respectively. Above 4 GPa, t increases more slowly to 13.8 ± 2.6 GPa at a pressure of 38 GPa. The changes in the preferred orientation (texture) of CeO 2 with pressure were also measured, allowing for the determination of active deformation mechanisms using an elasto-viscoplastic self-consistent model (EVPSC). It was found that as pressure increased, the [001] direction had a slight preferred orientation along the axis of compression. Our EVPSC model of experimental fiber (cylindrically symmetric) textures and lattice strains were most consistent with dominant slip activity along ${111}$ $\langle$$1\bar10$$\rangle$.

36 MATERIALS SCIENCE↗