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

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At least 127 records · Page 7

Design Basis Document / Owner’s Technical Specification for Nitrate Salt Systems in CSP Projects (Final Technical Report)

The number of commercial coal, gas, and nuclear projects built over the past 100 years number in the thousands. As such, there is a large database, available to a wide range of commercial engineering contractors, on proven designs. In essence, unsuccessful designs have, through generations of iterations, been identified and then deleted from further consideration. In contrast, the number of commercial parabolic trough projects using nitrate salt for the thermal storage media is perhaps 60. Further, the number of commercial central receiver projects using nitrate salt as the working fluid is on the order of 20, including estimates for China. Given the relative immaturity of salt technology, and commercial pressures to successfully bid new solar projects into a mature electricity market, solar projects often promise more than has been delivered. The Design Basis Document / Owner’s Technical Specification is a first step in the iteration process. The report describes the successful features of commercial projects, outlines a range equipment and system failures in projects that didn’t operate as intended, and provides a draft set of design changes intended to correct the known problems. The product of the study is 3 volumes of technical material; one volume is on parabolic trough technologies; a second is on central receiver technologies, and the third is on potential design changes to parabolic trough and central receiver projects. The 3 volumes, which total some 590 pages, can be found at https://www.solardynllc.com/csp-plant-technologies. One of the principal topics in the report is the use of functional or prescriptive specifications. Functional specifications describe what the equipment needs to do, consistent with the minimum legal requirements of the local jurisdictions. The details of how this is to be accomplished is developed by the engineering contractor. Prescriptive specifications, which are developed by the Owner, prescribe to the engineering contractor how the functional requirements are to be met. This arrangement ensures that the favorable experience from a previous project is repeated. One example is the design code for the hot salt tank in central receiver projects. The closest design basis is API Standard 650 Welded Steel Tanks for Oil Storage. However, the maximum design temperature in API 650 is 260 °C. As such, solar projects have typically adopted a hybrid Code approach, in which allowable material stresses are taken from ASME Section II Materials. Further, since the tanks experience daily changes in temperature and in (static) pressure, and since portions of the tank can operate at stresses beyond the elastic range, the low cycle fatigue life of the tank is conducted using the rules of Section VIII Division 2. However, in a recent study by NREL, the principal damage mechanism was identified as creep rather than fatigue. Further, design stresses permitted under Section VIII Division 2, corresponding to a fatigue life of 30 years, result in projected creep lifetimes of only 2 to 5 years. An alternate design approach, prescribed by the Owner, would be based on Code sections intended for high temperature service in the creep regime. A candidate is Section III Division 5. Granted, this is a nuclear code section, and it’s use would not likely be mandated by local jurisdictions. However, the effects of creep have been deemed to be of sufficient importance that one nuclear project developer, and one central receiver project developer, have stipulated in the tank design specification that the equipment be designed to the requirements of Section III Division 5.

14 SOLAR ENERGY↗

Long-time integration of parametric evolution equations with physics-informed DeepONets

Ordinary and partial differential equations (ODEs/PDEs) play a paramount role in analyzing and simulating complex dynamic processes across all corners of science and engineering. In recent years machine learning tools are aspiring to introduce new effective ways of simulating such equations, however existing approaches are not able to reliably return stable and accurate predictions across long temporal horizons. We aim to address this challenge by introducing an effective framework for learning evolution operators that map random initial conditions to associated ODE/PDE solutions within a short time interval. Such operators can be parametrized by deep neural networks that are trained in an entirely self-supervised manner without requiring one to generate any paired input-output observations. Global long-time predictions across a range of initial conditions can be then obtained by iteratively evaluating the trained model using each prediction as the initial condition for the next evaluation step. Here, this introduces a new approach to temporal domain decomposition that is shown to be effective in performing accurate long-time simulations for a wide range of parametric ODE and PDE systems, from wave propagation, to reaction-diffusion dynamics and stiff chemical kinetics, introducing a new way of rapidly emulating non-equilibrium processes in science and engineering.

97 MATHEMATICS AND COMPUTING↗

Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO 2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including E. coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate limiting steps in biological ethylene production. We employed a combination of genome scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to the EFE enzyme (WT vs mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.

59 BASIC BIOLOGICAL SCIENCES↗

Magnetic Proximity Effects in Iron Germanium Telluride/Platinum Heterostructures

Van der Waals (vdW) magnetic materials have attracted considerable attention for use in spintronic devices such as those controlled by spin–orbit torque (SOT). Such SOT-driven devices are typically fabricated by bringing a vdW magnet in proximity to a spin–charge conversion layer to achieve current-driven magnetization switching. Here, we show that such structures fabricated with iron germanium telluride (FGT) and platinum can exhibit emergent magnetic properties, which we attribute to magnetic proximity effects at the FGT/Pt interface. These changes manifest as increased perpendicular magnetic anisotropy and the emergence of additional magnetization reversal steps as probed by magneto-transport, with the most significant changes appearing in thinner flakes. The behavior was found to be robust and consistently appeared in samples made with crystals from different vendors. In conclusion, our results demonstrate the potential for engineering vdW spintronic systems through magnetic proximity effects.

2D magnet↗

Grid-scale Energy Storage Hazard Analysis & Design Objectives for System Safety

Battery based energy storage systems are becoming a critical part of a modernized, resilient power system. However, batteries have a unique combination of hazards that can make design and engineering of battery systems difficult. This report presents a systematic hazard analysis of a hypothetical, grid scale lithium-ion battery powerplant to produce sociotechnical "design objectives" for system safety. We applied system's theoretic process analysis (STPA) for the hazard analysis which is broken into four steps: purpose definition, modeling the safety control structure, identifying unsafe control actions, and identifying loss scenarios. The purpose of the analysis was defined as to prevent event outcomes that can result in loss of battery assets due to fires and explosions, loss of health or life due to battery fires and explosions, and loss of energy storage services due to non- operational battery assets. The STPA analysis resulted in identification of six loss scenarios, and their constituent unsafe control actions, which were used to define a series of design objectives that can be applied to reduce the likelihood and severity of thermal events in battery systems. These design objectives, in all or any subset, can be utilized by utilities and other industry stakeholders as "design requirements" in their storage request for proposals (RFPs) and for evaluation of proposals. Further, these design objectives can help to protect firefighters and bring a system back to full functionality after a thermal event. We also comment on the hazards of flow battery technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Rise of Intelligent Materials Science: Unleashing the Power of Machine Intelligence in Characterization

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

autonomous↗

Phase Contrast X‐Ray Imaging of the Collapse of an Engineered Void in Single‐Crystal HMX

Abstract Imaging the collapse of a single void that creates a hot spot initiation site in an otherwise defect‐free explosive is challenging given the spatial and temporal scales involved in explosive systems. This work presents our attempt to examine a single hot spot mode (void collapse) in single‐crystal octahydro‐l,3,5,7‐tetranitro‐l,3,5,7‐tetrazocine (HMX) embedded in Sylgard. The hot spot heating mechanisms involved with pore collapse include adiabatic heating, jetting, and viscoplastic dissipation. Quantifying the dynamics of a pore collapse is a crucial step to understanding which mechanisms dominate during ignition events. Our experiments were conducted with a single‐stage, light‐gas gun at Argonne National Laboratory's Advanced Photon Source, applying the phase contrast imaging technique while collecting high‐speed video. The details of HMX single crystal production, defect (pore) engineering, and sample construction, along with experimental results are presented here. These results demonstrate that detailed collapse dynamics can be obtained from homogeneous, single‐crystal explosives with this approach. Qualitative comparisons are made with simulation data which show good agreement in the transition between a quasi‐symmetric pore collapse and an asymmetric collapse with jetting across the pore as measured with normalized pore area and pore circularity.

42 ENGINEERING↗

Cold start strategy and system for gasoline direct injection compression ignition engine

A method for starting a compression ignition engine having at least one cylinder with a reciprocating piston located therein, an intake valve configured to control the intake of air to an intake port of the cylinder and an exhaust valve configured to control the expulsion of gas from an exhaust port of the cylinder. The method includes the steps of: cranking the engine, conditioning intake air at the intake port of the cylinder to raise the temperature of air in the cylinder, controlling a valve timing the intake valve and/or the exhaust valve to allow the piston to compress the air within the cylinder, thereby increasing the temperature of the air within the cylinder, and injecting fuel into the cylinder when the air within the cylinder has been heated to a temperature sufficient to support compression ignition of a gasoline and air mixture within the cylinder.

Sellnau, Mark C.↗

Rapid and robust squashed spore/colony PCR of industrially important fungi

Fungi have been utilized for centuries in medical, agricultural, and industrial applications. Development of systems biology techniques has enabled the design and metabolic engineering of these fungi to produce novel fuels, chemicals, and enzymes from renewable feedstocks. Many genetic tools have been developed for manipulating the genome and creating mutants rapidly. However, screening and confirmation of transformants remain an inefficient step within the design, build, test, and learn cycle in many industrial fungi because extracting fungal genomic DNA is laborious, time-consuming, and involves toxic chemicals. In this study we developed a rapid and robust technique called “Squash-PCR” to break open the spores and release fungal genomic DNA as a template for PCR. The efficacy of Squash-PCR was investigated in eleven different filamentous fungal strains. Clean PCR products with high yields were achieved in all tested fungi. Spore age and type of DNA polymerase did not affect the efficiency of Squash-PCR. However, spore concentration was found to be the crucial factor for Squash-PCR in Aspergillus niger, with the dilution of starting material often resulting in higher PCR product yield. We then further evaluated the applicability of the squashing procedure for nine different yeast strains. We found that Squash-PCR can be used to improve the quality and yield of colony PCR in comparison to direct colony PCR in the tested yeast strains. The developed technique will enhance the efficiency of screening transformants and accelerate genetic engineering in filamentous fungi and yeast.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗

sCO2 Primary Power Large-Scale Pilot Plant FEED Summary

Echogen Power Systems and its project partners the Electric Power Research Institute, CDM Smith, Riley Power Inc. (a Babcock Power Inc. company), and the University of Missouri completed the Front-End Engineering Design (FEED) study of a nominal 10 MWe supercritical carbon dioxide (sCO2) large-scale pilot plant based on Recompression Brayton Cycle (RCBC) architecture. The FEED study was completed under Phase II of the U.S. Department of Energy Fossil Fuel Large-Scale Pilots program. The FEED study scope included the preliminary design of the combustion and environmental control systems, the primary heater, the sCO2 power cycle and its associated turbomachinery, and the balance of plant equipment to determine accurate cost and schedule requirements for fabrication and installation of the system at the University of Missouri’s Combined Cooling, Heat, and Power Plant, located in Columbia, Missouri. The RCBC sCO2 cycle presents superior thermodynamic efficiency compared to steam-Rankine cycles and is adaptable to a broad range of heat sources. The risk aversion of the power generation industry requires a successful large-scale pilot plant demonstration to enable financing and deployment of commercial-scale plants. Therefore, successful construction and demonstration of a 10 MWe RCBC sCO2 power plant would empower a transformational step forward for the efficiency of the next generation of utility power plants. This paper provides details on the primary heater, environmental control systems, and sCO2 power cycle design and performance.

01 COAL, LIGNITE, AND PEAT↗

Coupling of CTF and RELAP5-3D Within an Enhanced Fidelity Nuclear Power Plant Simulator

A robust and accurate multiphysics engineering simulator is being developed to model the core behavior and system response of pressurized water reactors. This simulator relies on the NESTLE and CTF computer codes to model the neutronics and thermal hydraulics (TH), respectively, inside the core on a nodal scale and on the Reactor Excursion and Leak Analysis Program—Three Dimensional (RELAP5-3D) to model the entire nuclear steam supply system. The RELAP5-3D model includes highly detailed nodalization and multidimensional flow modeling throughout the vessel. Previously, pin-resolved data generated via the Virtual Environment for Reactor Analysis core simulator were used to improve the accuracy of the NESTLE core predictions. The engineering simulator being developed as part of this work uses the 3KEYMASTER platform to couple the enhanced NESTLE model to a nodal-fidelity CTF model to balance run time with accuracy; NESTLE provides node-dependent powers to CTF, and CTF provides node-dependent coolant densities and fuel temperatures to NESTLE.An overlapping domain approach is used for the core TH in which RELAP5-3D provides core boundary conditions based on the system response and CTF provides a node-dependent coolant heating rate to the RELAP5-3D core solution. In the preliminary TH demonstration discussed in this paper, CTF and RELAP5-3D provided similar steady-state core predictions, indicating the hydraulic compatibility between the codes, as well as reasonable and expected behavior under hypothetical transient conditions. This provides an initial step in ongoing efforts toward a robust, multiscale TH/neutronics engineering simulator capability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stopping criteria for ending autonomous, single detector radiological source searches

While the localization of radiological sources has traditionally been handled with statistical algorithms, such a task can be augmented with advanced machine learning methodologies. The combination of deep and reinforcement learning has provided learning-based navigation to autonomous, single-detector, mobile systems. However, these approaches lacked the capacity to terminate a surveying/search task without outside influence of an operator or perfect knowledge of source location (defeating the purpose of such a system). Two stopping criteria are investigated in this work for a machine learning navigated system: one based upon Bayesian and maximum likelihood estimation (MLE) strategies commonly used in source localization, and a second providing the navigational machine learning network with a “stop search” action. A convolutional neural network was trained via reinforcement learning in a 10 m × 10 m simulated environment to navigate a randomly placed detector-agent to a randomly placed source of varied strength (stopping with perfect knowledge during training). The network agent could move in one of four directions (up, down, left, right) after taking a 1 s count measurement at the current location. During testing, the stopping criteria for this navigational algorithm was based upon a Bayesian likelihood estimation technique of source presence, updating this likelihood after each step, and terminating once the confidence of the source being in a single location exceeded 0.9. A second network was trained and tested with similar architecture as the previous but which contained a fifth action: for self-stopping. The accuracy and speed of localization with set detector and source initializations were compared over 50 trials of MLE-Bayesian approach and 1000 trials of the CNN with self-stopping. The statistical stopping condition yielded a median localization error of ~1.41 m and median localization speed of 12 steps. The machine learning stopping condition yielded a median localization error of 0 m and median localization speed of 17 steps. This work demonstrated two stopping criteria available to a machine learning guided, source localization system.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Dynamic Atomistic Polar Structure Underpins Ultrahigh Linear Electro-Optic Coefficient in Transparent Ferroelectric Ceramics

Transparent ferroelectrics with high linear electro-optic (EO) coefficients are critical for advanced electro-optical devices. However, achieving optical transparency in ferroelectric ceramics remains challenging due to visible light scattering caused by defects such as domain walls, grain boundaries, and pores. Here, we report the successful fabrication of transparent ferroelectric ceramics through innovative chemical composition design and an advanced two-step sintering process in the La-doped Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 system. The optical transparency, which is near the theoretical upper limit, can be attributed to the wide band gap and the minimization of light scattering of defects. By minimizing porosity and engineering grain/domain sizes to differ significantly from the wavelengths of visible light, we suppress scattering, achieving optical transparency near the theoretical upper limit. Strikingly, these ceramics exhibit an ultrahigh linear EO coefficient of ∼1417 pm/V, over 65 times greater than that of LiNbO 3 single crystals, the current industry standard. We attribute this exceptional performance to dynamic atomistic polar structures within switchable, thermally stable domains, which enhance electronic polarization sensitivity. This mechanism is corroborated by dielectric spectroscopy, high-resolution transmission electron microscopy and simulation. Our findings offer insights into the design of cost-effective transparent materials with exceptional EO properties, paving the way for next-generation electro-optical devices.

36 MATERIALS SCIENCE↗

Synthesis of Si-Fe Chondrule-like Dust Analogues in RF Discharge Plasmas

Chondrules are tiny particles that occur in stony meteorites and are considered as the building blocks of early asteroids and planets. It is believed that they were formed by the fast heating of the dust in the solar nebula. To date, there is no lab-scale experimental study of the formation of chondrules from the initial gas phase precursors following fast heating and crystallisation. The motivation of this work is a pre-trial study of the formation of chnodrule-like particles. The formation of meteorites in the space environment is associated with the aggregation of small particles or molecular clouds under the influence of shock waves or high-energy gas discharges in the solar nebula. In this work, the properties of product formation at the nanoscale-level were investigated using different feedstock materials which are the dominant elements in the meteorite. The structural and morphological properties of the synthesised Si-Fe nanomaterials were analysed by scanning/transmission electron microscopy (SEM/TEM), and chemical composition was analysed by X-ray energy-dispersive spectroscopy (EDS). The identification of crystalline phases was carried out by X-ray diffraction (XRD), whereas the presence of an Fe-Si system in the synthesised particles was demonstrated by Mössbauer spectroscopy. The obtained materials were exposed to the relatively high-energy pulsed plasma beam on the substrate with the aim to emulate the possible fast heating and melting of the formed nanoparticles. The formation steps of growing synthetic (engineered) chondro-like particles and nanostructures in laboratory conditions is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development of a Modular, Crushed-Rock Thermal Energy Storage Pilot Design

The goal of this project, primarily funded by the U.S. Department of Energy, is to design a next-step pilot to advance near-term energy storage integrated with a fossil plant to provide a facility capable of being viable and effective in a market with growing penetration of variable renewable energy (VRE). Thermal energy storage (TES) represents an ideal technology for this purpose. The current effort will complete a feasibility study to prepare for the Phase II pre-front end engineering design (pre-FEED) for implementing a crushed-rock TES system integrated with a natural gas combined cycle (NGCC) plant. The crushed rock storage technology, which is being developed by Brenmiller Energy, is a modular TES system termed bGen™, which can accommodate both thermal and electrical inputs and output steam, hot water, or hot air. For this application, the estimated efficiency is 80% thermal to thermal. The TES technology is being designed to operate on a slipstream from NYPA’s Eugene W. Zeltmann Power Project (Zeltmann) natural gas combined cycle (NGCC) plant. The projected size of the system will be up to 4 MWe with at least 4 hours of storage duration, or 16 MWh-e total. Final sizing is being determined during the ongoing feasibility study. The next-step pilot being designed as part of the current project will represent a 5-fold increase in scale for this TES technology, and will be used to validate the technology’s ability to provide effective and economical energy storage. This pilot would represent the next-to-last demonstration scale before the technology could be commercial ready at GWh-e scales in the 2030 timeframe. This project is expected to design the critical next-step pilot, which will be undertaken in real-world operating conditions to better determine the crushed rock TES technology’s ability to be integrated with an NGCC plant and assess degradation over transient cycling at rates befitting various marketplaces. The crushed-rock TES pilot design is a technically feasible next step in the development of the technology and is built upon years of prior testing and demonstration. The proposed TES technology was developed by Brenmiller over the last 8 years and has been tested in 3 generations of demonstration units at various sites, globally. During this field testing, different characteristics and performance of the technology were validated, including the following key features: energy storage capacity, energy storage charge/discharge rate, energy storage loses, energy storage mechanical testing. This presentation will provide an update on the results of the conceptual design study for the modular crushed-rock TES system, integrated with a NGCC power plant.

03 NATURAL GAS↗

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Microwave catalytic conversion of acetylene for co-production of hydrogen and carbon nanotubes

Natural gas conversion to hydrogen and solid carbon can drastically reduce the carbon footprint. Microwave plasma pyrolysis is an emerging process for chemical industries to directly convert methane (CH 4 ), the major component of natural gas, to hydrogen and carbon, which offers benefits such as fast process dynamics, flexibility, and high product yield. However, the formation of unwanted by-products, like acetylene (C 2 H 2 ), will require extra cost for gas separation. Plasma pyrolysis of CH 4 produces large amount of acetylene at downstream, which is currently used mainly for welding. Here, to avoid gas separation and upgrade acetylene from the downstream of methane plasma reactor, a novel approach toward its transformation to carbon nanotubes (CNT) and pure hydrogen (H 2 ) over Ni-based bimetallic catalyst driven by microwave irradiation has been reported in this work. The dominant gas product was hydrogen. Low concentrations of methane, ethane, and ethylene were observed in the product stream. Catalytic acetylene decomposition was carried out at 400 °C over Al 2 O 3 supported Ni catalyst. The results showed that, at 400 °C, acetylene was dehydrogenated to CNT and hydrogen was the dominant gas in product stream over 10Ni-1Pd-Al 2 O 3 catalyst. Characterizations of spent catalysts was conducted using Raman spectroscopy and transmission electron microscopy (TEM) to investigate the properties of carbon deposited over the catalyst during the catalytic acetylene decomposition. The results highlight that methane can be efficiently converted to hydrogen and CNT through 2-step process, microwave plasma and microwave catalytic conversion of intermediate acetylene, operated in a single reactor system driven by microwave.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗