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At least 253 records · Page 14

Evaluating the carbon footprint of the integrated DBD‐plasma bi‐reforming unit via laboratory scale experiments and scaled‐up process modeling

Catalytic dielectric barrier discharge (DBD) plasma reactor experiments were performed in a tubular glass reactor with a 2 mm gap at 550°C to facilitate the reaction kinetics of steam added dry reforming or bireforming. The best specific energy input obtained was 11.2 eV/molecule feed at CO 2 :CH 4 :H 2 O of 4.5:1:4.5 ratio and gas hour space velocity (GHSV) = 432 h −1 . This value was used to design a conceptual process and assess the environmental impact of methane steam reforming-based H 2 production 18.4 kmol/h CO 2 emission processing into H 2 :CO = 2 syngas, with an emphasis on the carbon footprint.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

System code evaluation of near-term accident tolerant claddings during pressurized water reactor station blackout accidents

Following the Fukushima Daiichi nuclear accident in 2011, researches on Accident-tolerant fuels (ATFs) are currently of high interest in not only the nuclear industry but also governmental and international organizations. In this work, a quantitative evaluation of the performance of monolithic FeCrAl cladding and Cr-coated Zircaloy cladding has been performed for Pressurized Water Reactor (PWR) Station Blackout (SBO) accidents. A generic PWR model has been built in system thermal-hydraulics code TRACE based on the Surry Nuclear Power Station with counter-current natural circulation modelling capability for hotleg and steam generator U-tube components during the accidents. The base model results are then compared to MELCOR and RELAP simulations to verify the system component implementation in TRACE. Two PWR SBO scenarios were investigated, including: short-term SBO and long-term SBO with early reactor coolant pump (RCP) seal failure. These scenarios are defined to be very similar to the accidents studied in the State-of-the-Art Reactor Consequence Analysis (SOARCA) project. TRACE code is modified to reflect the oxidation kinetics of FeCrAl and Cr-coating. Larson-Miller creep rupture model is also implemented in TARCE using its built-in control systems to simulate the creep rupture of hotlegs. Additionally, the comparison between the TRACE models with and without the counter-current flow modeling resulted in significant difference when comparing ATF cladding to Zircaloy for short term SBO, while it marginal impacted the performance during long term SBO with RCP seal failure. For short term SBO, both ATF cladding underwent hot leg creep rupture ~20 min after Zircaloy cladding. While Zircaloy and Cr-coated cladding had generated significant amount of hydrogen gas (>10 kg) before the creep rupture event, FeCrAl cladding had only generated <0.5 kg of hydrogen gas. For long term SBO with RCP seal failure, significant hydrogen generation and fuel melting was predicted before hot leg creep rupture for the ATF cladding while providing only 10–20 min additional coping time compared to Zircaloy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimization of Hydrogen Production from Pyrolysis of Biomass Waste [Poster]

We developed an CFD aided ML-based tool for rapid assessment and optimization of different compositions of biomass in a fluidized bed reactor. First, we use CFD to simulate fluidized bed reactors with known inlet biomass mixtures and obtain corresponding syngas yields. A lumped kinetic mechanisms represents the conversion of cellulose, hemicellulose, and lignin, as well as subsequent cracking of tars into non-condensable gases (H 2 , CO, CO 2 , CH 4 ). We use Bayesian analysis/optimization to obtain the ideal operational and mass flow conditions for hydrogen production.

08 HYDROGEN↗

Modeling Isothermal Reduction of Iron Ore Pellet Using Finite Element Analysis Method: Experiments & Validation

Iron ore pellet reduction experiments were performed with pure hydrogen (H2) and mixtures with carbon monoxide (CO) at different ratios. For direct reduction processes that switch dynamically between reformed natural gas and hydrogen as the reductant, it is important to understand the effects of the transition on the oxide reduction kinetics to optimize the residence time of iron ore pellets in a shaft reactor. Hence, the reduction rates were studied by varying experimental parameters such as the temperature (800, 850 & 900 °C), reactant gas flow rate (100, 150 & 200 cm3/min), pellet size and composition of the reactant gas mixture. The rate of reduction was observed to increase with an increase in temperature and reactant gas flow rate, but it decreased with an increase in pellet size. SEM greyscale analysis was performed to analyze the porosity and phase composition of partially reduced pellets. The porosity of the pellets was observed to increase from 0.3 for unreacted pellet to 0.42 for a completely reduced pellet. Energy-dispersive X-ray spectroscopy (EDAX) analysis was performed to identify the phases observed in the SEM images. The fraction of iron phase was observed to increase from the shell region of the pellet to the core region with an increase in the degree of reduction. A 2D-axisymmetric numerical model was developed on COMSOL Multiphysics, and it was validated using the conversion (X) vs. time curves obtained from each experiment. The model was able to accurately predict the total time needed for the complete conversion of a single iron ore pellet for multiple experiments. Effects of changes in the porosity and tortuosity of the pellet on the model were also studied and the rate of reduction was observed to be sensitive to changes in both porosity and tortuosity. The SEM analysis and the model results show that tortuosity is higher for pellets reduced with H2 than for pellets reduced with H2-CO gas mixtures.

08 HYDROGEN↗

Low- and intermediate-temperature oxidation of dimethyl ether up to 100 atm in a supercritical pressure jet-stirred reactor

Understanding the low- and intermediate-temperature oxidation chemistry of oxygenated fuels like dimethyl ether (DME) at high pressure is paramount to the development of advanced engines with low carbon emissions. The supercritical pressure jet-stirred reactor (SP-JSR) recently developed at Princeton provides a new platform for conducting kinetic studies at low and intermediate temperatures at extremely high pressures with a uniform temperature distribution and a short flow residence time. This paper uses the SP-JSR to investigate DME oxidation at equivalence ratios of 0.175, 1.0, and 1.72, for pressures of 10 and 100 atm, and temperatures ranging from 400 to 900 K. The results demonstrate weakened NTC behavior at 100 atm relative to 10 atm due to increased flux through QOOH + O 2 = O 2 QOOH relative to QOOH = 2 CH 2 O + OH at 100 atm. Furthermore, the intermediate-temperature oxidation window is shifted to lower temperatures at 100 atm. The experimental data are compared with several chemical kinetic models from the literature. The existing models are seen to agree quite well with the experimental data at 10 atm. However, the models fail to properly capture the NTC behavior at 100 atm. Reaction pathway analyses indicate that both the low- and intermediate-temperature chemistries are controlled by RO 2 consumption pathways. The reaction rates for several of the important reactions, such as DME + OH = CH 3 OCH 2 + H 2 O, H 2 O 2 (+M) = 2 OH (+M), and 2 HO 2 = 2 OH + O 2 are updated in this work. Furthermore, the updated model improves the predictability for all key species compared to the original model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microkinetic Modeling of the Transient CO 2 Methanation with DFT–Based Uncertainties in a Berty Reactor

The transient operation of methanation reactors can become desirable when coupled with fluctuating renewable energies in Power-to-Gas scenarios, which requires suitable kinetic approaches that can describe the transient catalytic phenomena. A combined experimental and theoretical investigation of the transient CO 2 methanation is conducted using concentration forcing to derive a suitable microkinetic model. Methanation experiments are performed with a Ni/SiO 2 catalyst in a Berty-type reactor at industrially relevant conditions. The microkinetics are based on previous work and were automatically constructed for the Ni(111) facet using the Reaction Mechanism Generator. A feasible set of energetic parameters of the microkinetic models was identified in a theory-constrained optimization procedure within the DFT uncertainty space that can accurately reproduce the experimental results on a first-principles basis. The microkinetic model unravels that the formation of H 2 O* and CH 3 * control the activity and selectivity of Ni(111) under the investigated conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupling of Pronghorn and RELAP-7 for a Pebble Bed Reactor

High temperature gas cooled reactors (HTGR) are a candidate for timely Gen-IV reactor technology deployment because of high technology readiness and walk-away safety. Among HTGRs, pebble bed reactors (PBRs) have attractive features such as low excess reactivity and online refueling. Pebble bed reactors pose unique challenges to analysts and reactor designers such as continuous burnup distribution depending on pebble motion and recirculation, radiative heat transfer across a variety of gas-filled gaps, and long design basis transients such as pressurized and depressurized loss of forced circulation. Modeling and simulation is essential for both the PBR’s safety case and design process. In order to verify and validate the new generation codes the Nuclear Energy Agency (NEA) Data bank provide a set of benchmarks data together with solutions calculated by the participants using the state of the art codes of that time. An important milestone to test the new PBR simulation codes is the OECD NEA PBMR-400 benchmark which includes thermal hydraulic and neutron kinetic standalone exercises as well as coupled exercises and transients scenarios. In this work, the reactor multiphysics code MAMMOTH and the thermal hydraulics code Pronghorn, both developed by the Idaho National Laboratory (INL) within the multiphysics object-oriented simulation environment (MOOSE), have been used to solve Phase 1 exercises 1 and 2 of the PBMR-400 benchmark. The steady state results are in agreement with the other participants’ solutions demonstrating the adequacy of MAMMOTH and Pronghorn for simulating PBRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experimental Investigation of Uranium Volatility during Vapor Condensation

The predictive models that describe the fate and transport of radioactive materials in the atmosphere following a nuclear incident (explosion or reactor accident) assume that uranium-bearing particulates would attain chemical equilibrium during vapor condensation. Here, we show that kinetically driven processes in a system of rapidly decreasing temperature can result in substantial deviations from chemical equilibrium. This can cause uranium to condense out in oxidation states (e.g., UO 3 vs UO 2 ) that have different vapor pressures, significantly affecting uranium transport. To demonstrate this, we synthesized uranium oxide nanoparticles using a flow reactor under controlled conditions of temperature, pressure, and oxygen concentration. The atomized chemical reactants passing through an inductively coupled plasma cool from ~5000 to 1000 K within milliseconds and form nanoparticles inside a flow reactor. The ex situ analysis of particulates by transmission electron microscopy revealed 2–10 nm crystallites of fcc-UO 2 or α-UO 3 depending on the amount of oxygen in the system. α-UO 3 is the least thermodynamically preferred polymorph of UO 3 . The absence of stable uranium oxides with intermediate stoichiometries (e.g., U 3 O 8 ) and sensitivity of the uranium oxidation states to local redox conditions highlight the importance of in situ measurements at high temperatures. Therefore, we developed a laser-based diagnostic to detect uranium oxide particles as they are formed inside the flow reactor. Our in situ measurements allowed us to quantify the changes in the number densities of the uranium oxide nanoparticles (e.g., UO 3 ) as a function of oxygen gas concentration. Our results indicate that uranium can prefer to be in metastable crystal forms (i.e., α-UO 3 ) that have higher vapor pressures than the refractory form (i.e., UO 2 ) depending on the oxygen abundance in the surrounding environment. This demonstrates that the equilibrium processes may not dominate during rapid condensation processes, and thus kinetic models are required to fully describe uranium transport subsequent to nuclear incidents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimal Chloride Salt Mixture for a Fusion Blanket

Deuterium-tritium fusion reactors cannot operate for a significant period without a closed tritium fuel cycle, according to a recent National Academies of Sciences (NAS) report on bringing fusion reactors to the US electrical grid. This fact places breeder blankets as one of the foundational systems for self-sustained fusion reactor operation. The typical functional requirements for a breeder blanket system include producing tritium, absorbing kinetic energy, transporting thermal energy, and being environmentally attractive. State-of-the-art research on liquid blankets has converged to primarily focus on (LiF) 2 and BeF 2 (FLiBe) molten salts and a metallic eutectic of lead and lithium (PbLi), but “virtually all of the technologies related to the tritium fuel cycle are at a low technological readiness level”. This work sought to explore optimum blanket configurations as it aligned with the Oak Ridge National Laboratory (ORNL) FY 2023 Laboratory Directed Research and Development Program’s research priority of developing and expanding the current understanding of fusion blanket science and technology. This purpose of this work was to address ORNL research priorities and NAS recommendations by investigating novel liquid blanket materials that could provide self-sustaining operation and draw on experience from research on molten salts used for advanced fission reactors, concentrated solar, and thermal energy storage. The hypothesis when proposing this research was that there could be chloride-based blanket designs that can exceed the tritium breeding ratios of (FLiBe) molten salt blankets while reducing the use of Be (FLiBe), avoiding the generation of HF (FLiBe), and minimizing magnetohydrodynamic (MHD)-perturbed flow fields (PbLi). The fastest and most cost-effective path to deploying liquid fusion breeder blankets could be from maximizing the synergistic technological overlap between fusion, fission, concentrated solar, and thermal energy storage industries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Condensed Phase Guerbet Reactions of Ethanol/Isoamyl Alcohol Mixtures

The self-condensation and cross-condensation reactions of ethanol and isoamyl alcohol are examined to better understand the potential routes to value-added byproducts from fuel ethanol production. Reactions have been carried out in both batch autoclave and continuous condensed-phase reactors using a lanthanum-promoted, alumina-supported nickel catalyst at near-critical condensed phase conditions. Analysis of multiple candidate kinetic models led to a Langmuir–Hinshelwood rate expression that is first-order in alcohol with water as the strongly adsorbed species. This model provides the best fit of data from both batch and continuous reactor experiments. Activation energies for primary condensation reactions increase as carbon chain lengths increase. Selectivities to higher alcohols of 94% and 87% for ethanol and isoamyl alcohol, respectively, were observed at different operating conditions.

Nezam, Iman (ORCID:0000000277598069)↗

A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks

For turbulent reacting flow systems, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale simulations. Principal component analysis (PCA), and its variants, are a widely employed class of methods. Recently, an alternative technique that focuses on higher-order statistical interactions, co-kurtosis PCA (CoK-PCA), has been shown to effectively provide a low-dimensional representation by capturing the stiff chemical dynamics associated with spatiotemporally localized reaction zones. While its effectiveness has only been demonstrated based on a priori analyses with linear reconstruction, in this work, we employ nonlinear techniques to reconstruct the full thermo-chemical state and evaluate the efficacy of CoK-PCA compared to PCA. Specifically, we combine a CoK-PCA-/PCA-based dimensionality reduction (encoding) with an artificial neural network (ANN) based reconstruction (decoding) and examine, a priori, the reconstruction errors of the thermo-chemical state. In addition, we evaluate the errors in species production rates and heat release rates, which are nonlinear functions of the reconstructed state, as a measure of the overall accuracy of the dimensionality reduction technique. We employ four datasets to assess CoK-PCA/PCA coupled with ANN-based reconstruction: zero-dimensional (homogeneous) reactor for autoignition of an ethylene/air mixture that has conventional single-stage ignition kinetics, a dimethyl ether (DME)/air mixture which has two-stage (low and high temperature) ignition kinetics, a one-dimensional freely propagating premixed ethylene/air laminar flame, and a two-dimensional dataset representing turbulent autoignition of ethanol in a homogeneous charge compression ignition (HCCI) engine. Finally, results from the analyses demonstrate the robustness of the CoK-PCA based low-dimensional manifold with ANN reconstruction in accurately capturing the data, specifically from the reaction zones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The RAPTR furnace: a rapid heating and cooling sample furnace for in situ X-ray scattering studies of temperature-induced reactions

In situX-ray scattering provides valuable insights into the mechanisms and kinetics of reactions and structural transformations. For reactions and structural transformations primarily driven by temperature, and not coupled to chemical/electrochemical triggers, our ability to initiate and quench processes thermally is a practical limit for probing fast reactive phenomena. Meaningful quantitative analysis requires the dynamic phenomena to be triggered on fast time scales relative to the reaction/transformation kinetics. This article describes a new sample furnace, the Rapid-Actuating Pneumatic Thermal Reactor or RAPTR, for time-resolvedin situX-ray scattering studies initiated by temperature. The RAPTR quickly heats and cools samples by translating them into and out of a pre-heated hot zone. Using diffraction thermometry, it is shown that the samples can be heated/cooled in 10 s or less, with temperatures up to ∼1000°C being accessible. The application of the RAPTR furnace is demonstrated by exploring a fast solid-state reaction: the synthesis of scheelite-type lead tungstate, PbWO 4 , from PbO and WO 3 for which Pb 3 WO 6 is identified as a previously unrecognized reaction intermediate.

Chemistry↗

Substrate-explicit Modeling Tutorial

This tutorial Narrative demonstrates how to apply thermodynamic theory, also known as lambda theory, to convert molecular formulas of compounds (derived from FTICR-MS peaks using Formulatiry and R codes) into stoichiometric and kinetic forms of biogeochemical reactions and how to use the resulting kinetic equations to simulate dynamic conversion of compounds in batch and continuous stirred tank reactors. It will address under what conditions respiration rates are driven by thermodynamics, and how respiration rates respond to the variations in parameters and input variables and how to interpret the results.

54 ENVIRONMENTAL SCIENCES↗

Field Testing of an Affordable Zero-Liquid-Discharge Arsenic-Removal Technology for a Small-Community Drinking Water System in Rural California

Arsenic contamination in groundwater threatens public health, particularly in small, low-income communities lacking affordable treatment solutions. This study investigated the field implementation of novel air cathode assisted iron electrocoagulation (ACAIE) technology for arsenic removal in Allensworth, California, where groundwater arsenic concentrations exceeded 250 µg/L. Over four months, a pilot-scale ACAIE system, operating at 600 L/h, consistently reduced arsenic levels to below the EPA’s maximum contaminant level of 10 µg/L. Laboratory experiments informed the optimization of charge dosage and flow rates, which were validated during field testing of the ACAIE 600 L/h system. The in-situ generation of hydrogen peroxide at the cathode speeded up the reaction kinetics, ensuring high arsenic removal efficiency while allowing high throughput, even with a compact reactor size. An economic analysis demonstrated a treatment cost of USD 0.02/L excluding labor, highlighting the system’s affordability compared to conventional methods. Adding labor costs increased the treatment cost to USD 0.09/L. The regeneration of air cathodes extended their operational life, addressing a key maintenance challenge, thus reducing the costs slightly. Intermittent challenges were encountered with filtration and secondary contaminant removal; these issues highlight opportunities for further operational improvements. Despite these challenges, ACAIE’s low operational complexity, scalability, and cost-effectiveness make it a promising solution for underserved small communities. These findings provide critical insights into deploying sustainable arsenic remediation technologies that are tailored to the needs of rural, low-resource communities.

Bandaru, Siva R S↗

Data for Catalyst and Reactor Design Considerations for Selective Production of Acids by Oxidative Cleavage of Alkenes with H2O2

Oxidative cleavage of alkenes and unsaturated fatty acids with hydrogen peroxide gives an efficient and sustainable process to obtain mono- and di-acids for polymers and lubricants with fewer safety risks and less environmental impact than processes that utilize ozone or other inorganic oxidizers (e.g., permanganate, dichromate, etc.). Guided by insight into the mechanisms for competing reaction pathways (i.e., epoxidation of alkene on W–(η2-O2) complexes vs. H2O2 decomposition) and the apparent kinetics derived from kinetic experiments, here, we postulate that W-based heterogeneous catalysts can provide high performance and stable operations at low H2O2 concentrations. Semi-batch reactors with continuous introduction of H2O2 solutions offer the means to maintain low H2O2 concentrations while providing sufficient quantities of H2O2 to satisfy the reaction stoichiometry. We derived simple kinetic model equations for the epoxidation, ring-opening, oxidative cleavage, and oxidation steps and fit theses equations to batch experimental data to obtain kinetic parameters. This kinetic model describes the concentration profiles of reactant, oxidant, and products well as shown by agreement with experimental data. Further predictions of the optimal H2O2 feed rate for semi-batch operation utilized by the proposed rate expressions and the reactor design equations suggest that low H2O2 feed rate increases selectivity towards oxidative cleavage products and selective use of H2O2 for oxidative cleavage pathway. Comparisons of oxidative cleavage of 4-octene in batch and semi-batch reactors show that semi-batch reactors with optimized molar feed rates of H2O2 increased oxidative cleavage product selectivities (76% to 99%; with an increase in butyric acid selectivity from 1% to 55%) and H2O2 selectivity (3% to 30%). In addition, semi-batch reaction conditions used avoid H2O2-mediated dissolution of W-atoms from the catalyst. Analysis of these findings suggest that solid oxide catalysts will be effective for continuous oxidative cleavage reactions if deployed within fixed-bed reactors that allow for distributed introduction of reactants and therefore low in situ concentrations of H2O2.

Catalysis↗

Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Nuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs in monitoring of RTs for operator support requires near real-time model performance. However, as with all machine learning models, development of a PINN involves time-consuming model training. Here, we show that a transfer learning (TL-PINN) approach achieves significant performance gain, as measured by reduction of the number of iterations for model training. Using point kinetic equations (PKEs) model with six neutron precursor groups, constructed with experimental parameters of the Purdue University Reactor One (PUR-1) research reactor, we generated different RTs with experimentally relevant range of variables. The RTs were characterized using Hausdorff and Fréchet distance. We have demonstrated that pre-training TL-PINN on one RT results in up to two orders of magnitude acceleration in prediction of a different RT. The mean error for conventional PINN and TL-PINN models prediction of neutron densities is smaller than 1%. We have developed a correlation between TL-PINN performance acceleration and similarity measure of RTs, which can be used as a guide for application of TL-PINNs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Catalytic production of δ-valerolactone (DVL) from biobased 2-hydroxytetrahydropyran (HTHP) – Combined experimental and modeling study

δ-Valerolactone (DVL) is a five-carbon (C5) cyclic ester that can undergo ring-opening polymerization to yield high-performance, biocompatible polyesters. But current market prices of C5 chemicals like DVL are very high due to poor availability of C5 feedstock in petroleum. Herein, we demonstrate a novel route to DVL synthesis via dehydrogenation of biomass-derived 2-hydroxytetrahydropyran (HTHP) over Cu/SiO 2 without the use of toxic reagents. Since HTHP exists in thermal equilibrium with 3,4-dihydropyran (DHP) via dehydration, and with 2,2’-oxybis(tetrahydropyran) and 5-(tetrahydropyran-2-yloxy)pentanal via acetalization, we have also determined the thermochemistry (ΔH rxn and ΔG rxn ) of each competing reaction using density functional theory (DFT) calculations at the M06-2X/cc-pVTZ level. Finally, by developing a kinetic model of all 8 reactions involved, we have achieved 84% selectivity to DVL at 150°C in a packed bed reactor for over 72 hours of time on stream.

42 ENGINEERING↗

Consequences of product inhibition in the quantification of kinetic parameters

While the potential for product inhibition in catalytic reactions is well known, the impact of neglected inhibition on measured kinetic parameters is often overlooked. The presence of product inhibition, most often caused by the competitive adsorption of products with reactants on catalytic active sites, is difficult to determine a priori for an arbitrary catalytic system. The significance of product inhibition relies on the concentration of the products, their adsorption thermodynamics on catalytically relevant sites, and process parameters such as temperature and pressure. When inhibition is significant, however, apparent activation energies and reaction orders vary from the differential-reactor apparent activation energy by a factor of 1/(1 - δ), where δ is the total inhibition order (e.g., the factor (1 - δ) = 1.6 for a system with product inhibition of -0.6 order). This is illustrated here with the kinetics of NO oxidation over Cu ion clusters (Cu x O y ) in Cu-SSZ-13, for which the product NO 2 inhibits the forward reaction. Furthermore, in the presence of inhibition, when only reactants are fed to a flow reactor or placed in a batch reactor, there is often no practical conversion that is low enough to guarantee differential behavior. Inclusion of products in the feed solves this problem, allowing accurate determination of kinetic parameters such as apparent reaction orders and activation energies. We also demonstrate that evaluation of the necessity of co-feeding products to assure measurement of differential-reactor data in a given catalytic system is straightforward from a plot of the log of the rate (or conversion) versus the log of the space time in a flow reactor or elapsed time in a batch reactor. We encourage inclusion of this test in all kinetic analyses that are reasonably approximated by power law rate expressions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗