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At least 1,243 records · Page 69

The STAR Forward Silicon Tracker

The Forward Silicon Tracker (FST) is a pivotal component of the forward upgrade of the Solenoidal Tracker at RHIC (STAR), designed to discern hadron charge signs with a momentum resolution better than 30% for 0.2 < p T < 2GeV/c in the 2.5 < η < 4 pseudorapidity range. Its compact design features three disks along the beam direction, minimized material budget, and scattering effects. The FST uses Hamamatsu’s p-in-n silicon strip sensors with a double metal layer that enables efficient signal routing to the readout electronics, enhancing overall detector performance. The flexible hybrid boards, essential for the readout system, are constructed with Kapton and copper layers to optimize signal handling and power distribution. These boards connect silicon strips to analogue pipeline ASIC APV25-S1 chips, which read up to 128 channels each. A cooling system with nonconducting, volatile NOVEC 7200 coolant at 22.2 °C mitigates ASIC-generated heat. Furthermore, the FST enhances forward tracking performance at STAR as an integral part of the forward upgrade.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Characterization of the optical model of the T2K 3D segmented plastic scintillator detector unit cube

The magnetized near detector (ND280) of the T2K long-baseline neutrino oscillation experiment has been recently upgraded aiming to satisfy the requirement of reducing the systematic uncertainty from measuring the neutrino–nucleus interaction cross section, which is the largest systematic uncertainty in the search for leptonic charge-parity symmetry violation. A key component of the upgrade is SuperFGD, a 3D segmented plastic scintillator detector made of approximately 2,000,000 optically-isolated 1 cm 3 cubes. The SuperFGD cube unit shows promising optical performance, including a high light yield of about 40 photoelectrons (p.e.) per channel, a low cube-to-cube crosstalk rate below 3%, and a sub-nanosecond time resolution of 0.96 ns. By combining tracking and stopping power measurements of final state particles, this novel detector enables precise 3D-imaging of GeV neutrino interactions with reduced systematic uncertainties. A detailed Geant4 based optical simulation of the SuperFGD building block, i.e. a plastic scintillating cube read out by three wavelength shifting fibers, has been developed and validated with the different datasets collected in various beam tests. In this manuscript the description of the optical model as well as the comparison with data are reported.

Neutrino oscillations↗

Process design for recovering rare-earth elements from mine tailings with low rare-earth concentrations via sequential leaching and solvent extraction

Rare earth elements (REEs) are essential for advanced technologies and yet face significant supply chain risks due to their concentrated global production and limited domestic availability. Addressing this challenge requires efficient processes capable of upgrading low-grade secondary resources such as mine tailings. In this study, we developed a novel separation flowsheet that integrates sequential leaching and 2-stage solvent extraction (SX) processes to recover high-purity heavy REEs (HREEs) and light REEs (LREEs) from a simulated mine-tailing concentrate containing 2.4 wt% total REEs (TREEs; 0.6 wt% LREEs and 1.8 wt% HREEs). Sequential leaching with controlled pH adjustment selectively precipitated REEs while retaining the large amount of impurities in the solution, producing an REE-enriched leachate by following leaching processes with roughly twice the REE concentration and half the impurity concentration compared to that of single-step leaching. The optimized SX flowsheet employed Cyanex 572 to extract HREEs and Fe over LREEs, followed by Fe removal using tributyl phosphate (TBP), while the raffinate stream was processed by SX with di(2-ethylhexyl)phosphoric acid (D2EHPA) to recover LREEs under optimized conditions balancing both extraction efficiency and purity. Although increased extractant availability in the organic phase improved LREE recovery, it also increased co-extraction of Ca, underscoring trade-offs in process optimization. Both HREE- and LREE-rich solutions were subsequently precipitated into solid products via oxalate precipitation, resulting in high-purity REE solids containing ∼92.0 wt% HREEs (∼95.7 wt% TREEs) and ∼92.8 wt% LREEs (∼94.0 wt% TREEs). In conclusion, this proof-of-concept study using simulated mine tailings demonstrates a promising approach for upgrading low-grade REE resources, while highlighting the need for future validation with real materials.

Mine tailings↗

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗

Pilot microbial electrolysis cell closes the hydrogen loop for hydrothermal wet waste conversion to jet fuel

The global shift toward net-zero emissions necessitates resource recovery from wet waste. In this study, we demonstrate the first feasibility of combining pilot-scale microbial electrolytic cells (MECs) with hydrothermal liquefaction (HTL) for simultaneous post-hydrothermal liquefaction wastewater (PHW) treatment and efficient hydrogen (H₂) production to meet biocrude upgrading requirements. Long-term single reactor operation revealed that fixed anode potential enabled rapid startup, and low catholyte pH and high salinity were effective in suppression of cathodic methanogenesis and acetogenesis – resulting in high current density of 16.6 A m –2 and 9.3 A m –2 when feeding synthetic wastewater and PHW respectively. Additionally, the anode biofilm exhibited spatial variations in response to local environmental conditions. In conclusion, onsite parallel or serial operations of multiple MECs showed good performance using actual PHW with a record-high H 2 production rate of 0.5 L L R day –1 for MEC over 10 liters scale, and the optimal chemical oxygen demand (COD)-to-H 2 yield reached 0.127 kg-H 2 per kg-COD, supporting a self-sufficient, closed-loop upgrade to jet fuel.

08 HYDROGEN↗

Prediction of dynamic behavior of a system undergoing an exchange of components using a transmission simulator method

In systems with modular design, it is of interest to perform component exchanges to upgrade components and explore new system configurations. If the dynamics of the components are known, then dynamic substructuring can be used to obtain a prediction of system performance for the new configuration. The transmission simulator method is a substructuring technique that utilizes an additional fixture to apply an elastic boundary condition to a test article such that an appropriate dynamic response can be obtained for a given substructuring application, and the technique has been used widely for performing coupling and decoupling operations. Here, in this work, a modified transmission simulator method is proposed that allows a direct exchange of components to be performed. In a numerical demonstration, the proposed method is shown to accurately predict the dynamics of an assembly that has undergone a component exchange in which the exchanged components have different material properties and different geometric properties. This approach can be applied to dynamic qualification frameworks in which structures undergo modifications or upgrades rather than complete redesigns.

Component exchange↗

Molten-Phase Unsaturation Enhanced Pyrolytic Upcycling of Polyolefins

Fast pyrolysis is a robust deconstruction technology for chemically upcycling waste plastics without losing significant carbon to noncondensable gases. However, fast pyrolysis of polyolefins often produces hydrocarbons with broad molecular weight distributions, mainly waxes, which can also negatively affect the commercial reactor operation and downstream upgrading of the products. We discovered that combining molten-phase thermal treatment with subsequent fast pyrolysis offers a facile method to enhance polyolefin pyrolysis and catalytic upgrading. The molten-phase thermal treatment increased unsaturated C–C bonds in the treated polyolefins. During subsequent pyrolysis, the preheated polyolefins significantly reduced wax range hydrocarbons in the condensable products without an increase in gas formation. Here, the wax yields from pyrolysis of high-density polyethylene (HDPE) preheated to 295 °C and low-density polyethylene (LDPE) preheated to 275 °C were 20.5% and 26.5%, respectively, compared to 38.6% and 46% produced from pyrolyzing untreated polyolefins. When catalytically pyrolyzed using a zeolite catalyst, the preheated polyolefins promoted higher yields of olefins during ex-situ catalytic pyrolysis and higher yields of aromatic hydrocarbons during in-situ catalytic pyrolysis. During ex-situ catalytic pyrolysis, ethylene yields were 23.3% and 24.7% for the preheated HDPE and LDPE compared to 16.7% and 9.3% for untreated HDPE and LDPE, respectively.

Aromatic compounds↗

Load-Shifting Strategies for Cost-Effective Emission Reductions at Wastewater Facilities

Significant hourly variation in the carbon intensity of electricity supplied to wastewater facilities introduces an opportunity to lower emissions by shifting the timing of their energy demand. This shift could be accomplished by storing wastewater, biogas from sludge digestion, or electricity from on-site biogas generation. However, the life cycle emissions and cost implications of these options are not clear. Here, we present a multiobjective optimization framework for comparing cost- and emission-minimizing load-shifting strategies at a California case study facility with a relatively low carbon intensity grid and high spread in peak and off-peak electricity prices. We evaluate cost and emission trade-offs from the optimal flexible operation of both existing infrastructure and optimally sized energy flexibility upgrades. We estimate energy-related emission reductions of up to 9.0% with flexible operation of existing infrastructure and up to 16.8% with optimally sized storage upgrades. Only a fraction of these potential savings are realized under actual industrial energy tariffs and the EPA’s recommended social cost of carbon. Energy flexibility may hold promise as a short-term emission-saving solution for the wastewater sector, but the extent of savings is heavily dependent on the cost of carbon, electricity tariffs, and emission intensity of the regional electricity grid.

climate↗

Selective butene formation in direct ethanol-to-C3+-olefin valorization over Zn-Y/Beta and single-atom alloy composite catalysts using in situ generated hydrogen

The selective production of C3+ olefins from renewable feedstocks, especially via C1 and C2 platform chemicals, is a critical challenge for obtaining economically viable low-carbon middle distillate transportation fuels (i.e., jet and diesel). Here, we report a multifunctional catalyst system composed of Zn-Y/Beta and “single-atom” alloy (SAA) Pt-Cu/Al2O3 which selectively catalyzes ethanol-to-olefins (C3+, ETO) valorization in the absence of cofed hydrogen, forming butenes as the primary olefin products. Beta zeolites containing predominately isolated Zn and Y metal sites catalyze ethanol upgrading steps (588 K, 3.1 kPa ethanol, ambient pressure) regardless of cofed hydrogen partial pressure (0-98.3 kPa H2), forming butadiene as the primary product (60% selectivity at 87% conversion). The Zn-Y/Beta catalyst possesses site-isolated Zn and Y Lewis acid sites (at ~7 wt% Y) and Brønsted acidic Y sites, the latter of which has been previously uncharacterized. A secondary bed of SAA Pt-Cu/Al2O3 selectively hydrogenates butadiene to butene isomers at a consistent reaction temperature using hydrogen generated in situ from ethanol-to-butadiene (ETB) conversion. This unique hydrogenation reactivity at near-stoichiometric hydrogen and butadiene partial pressures is not observed over monometallic Pt or Cu catalysts, highlighting these operating conditions as a critical SAA catalyst application area for conjugated diene selective hydrogenation at high reaction temperatures (>573 K) and low H2/diene ratios (e.g., 1:1). Single-bed steady state selective hydrogenation rates, associated apparent hydrogen and butadiene reaction orders, and DFT calculations of the Horiuti-Polanyi reaction mechanisms indicate that the unique butadiene selective hydrogenation reactivity over SAA Pt-Cu/Al2O3 reflects lower hydrogen scission barriers relative to monometallic Cu surfaces and limited butene binding energies relative to monometallic Pt surfaces. DFT calculations further indicate the preferential desorption of butene isomers over SAA Pt-Cu(111) and Cu(111) surfaces while Pt(111) surface favors subsequent butene hydrogenation reactions to form butane over butene desorption events. Under operating conditions without of hydrogen cofeeding, this combination of Zn-Y/Beta and SAA Pt-Cu catalysts can selectively form butenes (65% butenes, 78% C3+ selectivity at 94% conversion) and avoid butane formation using only in situ generated hydrogen, avoiding costly hydrogen cofeeding requirements that hinder many renewable energy processes.

Cordon, Michael↗

Understanding Electrochemical Alcohol Hydrogenolysis Enabled by Carbonyl Reduction in Lignocellulosic Biomass-Derived Aromatic Oxygenates

Molecules derived from lignocellulosic biomass are oxygenates with multiple oxygen-containing functional groups, such as hydroxyl and carbonyl groups. Therefore, the ability to selectively reduce a specific oxygenate group is essential for the reductive upgrading of such molecules. Previous studies on electrochemical biomass conversion have shown that alcohol hydrogenolysis, which involves cleavage of the σ(C–O alcohol ) bond, is extremely challenging for furfural and 5-hydroxymethylfurfural (HMF) derivatives, including furfuryl alcohol, 5-methylfurfuryl alcohol (MFA), and 2,5-bis(hydroxymethyl)furan (BHMF). In contrast, HMF itself undergoes alcohol hydrogenolysis relatively easily in acidic aqueous media. Considering that the only structural difference between HMF and BHMF or MFA is the presence of a carbonyl group, this observation raises the question of whether the carbonyl group in HMF facilitates alcohol hydrogenolysis. In this study, we designed systematic experiments to provide a coherent explanation of when and how a carbonyl group enables hydrogenolysis of a copresent alcohol group. Specifically, we show that alcohol hydrogenolysis in HMF proceeds via reduction of the carbonyl group to a ketyl radical, followed by a spin-center shift (SCS) through extended π conjugation. We also elucidate the effect of pH on the selectivity between carbonyl hydrogenation and alcohol hydrogenolysis, both of which share the ketyl radical intermediate. This mechanistic understanding enhances our ability to predict and control alcohol hydrogenolysis in the reductive upgrading of biomass-derived oxygenates.

alcohols↗

A unifying equation for fermentation sustainability across the titer-rate-yield landscape

Industrial fermentation is central to the sustainable production of fuels and chemicals, yet commercial viability of emerging technologies hinges on improving fermentation titer, rate, and yield (TRY). How these metrics shape system cost remains difficult to generalize due to complex interactions among feedstocks, fermentation, separations, catalytic upgrading, waste management, and facility design. Here, we systematically map theoretical fermentation performance spaces (formed by all potential TRY combinations) for 32 representative biomanufacturing facilities—spanning distinct choices for feedstocks, fermentation regimes and products, separations, and catalytic upgrading—by simulating and evaluating them (via techno-economic analysis, TEA) under uncertainty (600,000 Monte Carlo simulations) and across TRY combinations (7500 TRY combinations for each of 32 configurations). Across this wide design and thermodynamic simulation space, we find the relationship between fermentation TRY and system cost is captured by a simple, generalizable mathematical equation (R 2 of 0.992 − 1.000 across our simulations; 0.954 − 1.000 when validated against prior studies that used different tools). We use this equation to elucidate key drivers that shape cost sensitivity to fermentation performance, generating widely applicable insights. By demonstrating a unifying relationship governs the impact of fermentation on biomanufacturing economics, this work establishes a foundation for agile, holistically predictive, resource-efficient strategies to prioritize fermentation research and development needs and accelerate commercialization of emerging biomanufacturing technologies.

applied mathematics↗

Opportunities for retrieval and tool augmented large language models in scientific facilities

Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of materials across the spectrum of the physical sciences, from life sciences to microelectronics. However, these facility and instrument upgrades come with a significant increase in complexity. Driven by more exacting scientific needs, instruments and experiments become more intricate each year. This increased operational complexity makes it ever more challenging for domain scientists to design experiments that effectively leverage the capabilities of and operate on these advanced instruments. Large language models (LLMs) can perform complex information retrieval, assist in knowledge-intensive tasks across applications, and provide guidance on tool usage. Using x-ray light sources, leadership computing, and nanoscience centers as representative examples, we describe preliminary experiments with a Context-Aware Language Model for Science (CALMS) to assist scientists with instrument operations and complex experimentation. With the ability to retrieve relevant information from facility documentation, CALMS can answer simple questions on scientific capabilities and other operational procedures. With the ability to interface with software tools and experimental hardware, CALMS can conversationally operate scientific instruments. By making information more accessible and acting on user needs, LLMs could expand and diversify scientific facilities’ users and accelerate scientific output.

97 MATHEMATICS AND COMPUTING↗

Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems

Major technological advancements and recent policy support are improving the outlook for heavy-duty truck electrification in the United States. In particular, short-haul operations (=200 miles (=322 km)) are prevalent and early candidates for plug-in electric vehicles (EVs) given their short, predictable routes and return-to-base applications, which allows vehicles to recharge when off shift at their depots. Although previous studies investigated the impacts of added electrical loads on distribution systems, which included light-duty EVs, the implications for heavy-duty EV charging are underexplored. Here we summarize the causes, costs and lead times of distribution system upgrades anticipated for depot charging. We also developed synthetic depot charging load profiles for heavy-duty trucks from real-world operating schedules, and found that charging requirements are met at common light-duty EV charging rates (=100 kW per vehicle). Finally, we applied depot charging load profiles to 36 distribution real-world substations, which showed that most can accommodate high levels of heavy-duty EV charging without upgrades.

47 OTHER INSTRUMENTATION↗

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Biogas sequestration to carbon nanofibers via tandem catalytic strategies

Upgrading decentralized biogas represents a sustainable route to produce valuable products while mitigating two potent greenhouse gases, namely, methane (CH 4 ) and carbon dioxide (CO 2 ). Conventional dry reforming of CH 4 with CO 2 yields syngas with low H 2 /CO ratios (≤1) and requires high temperatures (>800 °C) to overcome equilibrium constraints and abate coke deposition, which limits commercial implementation. Here we demonstrate the conversion of biogas into value-added carbon nanofibers via reaction integration in tandem reactors, while reducing the reaction temperature, shifting equilibrium limits and yielding H 2 -enriched syngas (H 2 /CO = 2–3) as a byproduct. Experimental and theoretical insights reveal that potassium (K) modification enhances carbon nanofiber formation due to synergistic effects via a balanced interplay between KO x -induced cobalt facets and cobalt carbide species. In conclusion, the energy cost and CO 2 footprint analyses highlight the potential advantages of tandem processes for the sustainable upgrading of biogas into valuable solid carbon products.

09 BIOMASS FUELS↗

A Hybrid Pathway to Biojet Fuel via 2,3-Butanediol

Production of biomass-derived sustainable alternative jet fuels (SAJF) has been considered as an important approach to decarbonize the aviation industry but still possesses various challenges in technology advancement, particularly in achieving high carbon efficiency. Here we report a hybrid pathway to SAJF from 2,3-butanediol (2,3-BDO), integrating biologically converting biomass to 2,3-BDO with catalytically upgrading of 2,3-BDO to jet-range hydrocarbons. This pathway is demonstrated to have a high carbon recovery to liquid hydrocarbons from corn stover (25–28%) (74–82% of the theoretical maximum efficiency). The catalytic conversion steps involve 2,3-BDO to C3+ olefins, oligomerization, and hydrogenation where the first two steps are the focus of this study. Under optimum reaction conditions (523 K, 115 kPa, 1.0 h-1 weight hourly space velocity), 2,3-BDO conversion and C3+ olefin selectivity are >97% and 94–98% during 40 h time on stream, respectively. To demonstrate the adaptability of this technology with bio-derived 2,3-BDO, we also investigated the impact of water and other organic coproducts (acetoin and acetic acid) inherited from the fermentation broth on the catalyst performance and product selectivities. We have shown that the catalyst can handle a significant amount of water in the liquid feed (40 wt% water/60 wt% 2,3-BDO) and maintain catalyst stability for ~40 h. Acetoin can be converted to similar C3+ olefins as 2,3-BDO with complete conversion of acetoin. Co-feeding 10 wt% acetoin with 2,3-BDO is found to have no impact on 2,3-BDO conversion, C3+ olefin selectivity, and catalyst stability. The utilization of organic coproduct like acetoin can help to improve overall carbon conversion efficiency when using real biomass-derived 2,3-BDO. On the other hand, the presence of 10 wt% acetic acid is shown to drastically inhibit methyl ethyl ketone (MEK) hydrogenation and butene oligomerization as revealed by the increased MEK and butene selectivities, implying the importance of separating organic acids when feeding bio-derived 2,3-BDO. The formed C3–C6 olefins from 2,3-BDO are further oligomerized over Amberlyst-36 catalyst to longer-chain hydrocarbons with >70 wt% jet-range hydrocarbons including predominantly iso-olefins/iso-paraffins. The overall carbon efficiency for the jet-range hydrocarbons is 19–22%, exceeding most of the reported biojet pathways, which makes it a promising approach for SAJF production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Predicting Thermal Excursions During in situ Oxidative Regeneration of Packed Bed Catalytic Fast Pyrolysis Catalyst

Ex situ catalytic fast pyrolysis (CFP) uses a secondary reactor to upgrade biomass pyrolysis vapors to stabilized CFP oils with reduced oxygen content. In one configuration, the secondary reactor is operated as a packed-bed swing reactor system which allows coke-deactivated beds to be decarbonized in situ while other beds remain online for vapor upgrading. In situ decarbonization must be done carefully to avoid irreversible deactivation and/or physical degradation of catalyst pellets. Given that packed bed reactors are well known to have poor heat transfer characteristics, this is a critical issue impacting scaleability and commercial viability of the technology. To predict thermal excursions during regeneration, finite element computational models have been built to assist in scaling up oxidative decarbonization of a Pt/TiO2 CFP catalyst (0.5 mm spheres) from a bench scale packed bed with 100 g of catalyst to a pilot scale packed bed with 2 kg of catalyst and internal cooling tubes. Based on transient measurements of outlet temperature and effluent CO2 concentration, and using an assumed coke profile and activation energy, this paper demonstrates that specific combinations of effective thermal conductivity and wall heat transfer coefficient can fit bench scale oxidative regeneration data equally well. For the upscaled 2 kg bed, four bench-scale “best fit” parameter pairs give different predictions for location and magnitude of thermal excursions, with the maximum computed bed temperature gradients ranging from 30 °C cm-1 to as high as 3000 °C cm-1. The larger the fraction of heat removal by conduction through the cooling tubes, the greater the differences between the parameter pairs. The modelling results presented in this paper cast doubt on the industrial viability of the proposed combination of catalyst, bed and regeneration process, and point to the need for alternate reactor designs. However, there is considerable uncertainly in some of the key model parameters. The reliability of model predictions can be increased by adding more temperature measurements at key bed locations, testing additional variations in process conditions, performing careful bed dissections to determine the true coke profile, and perhaps most importantly, directly measuring the effective thermal conductivity of the catalyst pellets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗