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At least 217 records · Page 12

Metabolic engineering of oleaginous yeast Rhodotorula toruloides for overproduction of triacetic acid lactone

Abstract The plant‐sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2‐pyrone synthase gene from Gerbera hybrida ( GhPS ) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl‐CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP‐citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl‐CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12‐ ACL1‐ACC1 using fed‐batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl‐CoA‐derived polyketides from low‐cost carbon sources.

2‐pyrone synthase↗

Effect of particle size on the capture of uranium oxide colloidal particles from aqueous suspensions via high-gradient magnetic filtration

The effectiveness of High Gradient Magnetic Filtration (HGMF) in capturing uranium oxide particles from suspensions was investigated in this study. Two sets of experiments were performed to evaluate the importance of size on the capture of uranium oxide particles. The first considered two batches sieved into size bins of< 5, 5–10, 10–15, and 15–20 µm, while the second was performed using two suspensions with diameters smaller than 1.0 µm and between 1.0 and 1.5 µm. Iron oxide experiments, with particles between 0.3 and 0.8 µm, were performed for calibration purposes. In all experiments, a surfactant (Triton-X100 or sodium dodecyl sulfate) was used to prevent particle aggregation and limit the influence of non-magnetic capture mechanisms. A magnetic field of approximately 1.1 Tesla was generated using a water cooled electromagnet. HGMF was performed using tubular filters packed with ferromagnetic stainless-steel wool. Of the initial four uranium oxide particle sizes, magnetic capture was only observed for particles with a diameter of less than 5 µm, while larger particles experienced no magnetic and minimal total capture. For particles with diameters smaller than 1.0 µm and between 1.0 and 1.5 µm, capture efficiencies increased by 39 ± 9% and 34 ± 6% respectively, solely due to the magnetic field. Although the magnetic force is proportional to particle diameter, the capture efficiency decreased as diameter increased. So these results suggest that Brownian diffusion, which is influential for micron sized particles and increases with decreasing particle size, is acting in conjunction with the magnetic force to influence the efficacy of HGMF for uranium oxide. This important finding underscores the effectiveness of Brownian diffusion in increasing the rate of collision between particles and collector fibers. A stochastic trajectory model was developed to incorporate the influence of Brownian motion on particle behavior and filter removal efficiency. Modeling results are discussed and compared for uranium and iron oxide particles.

42 ENGINEERING↗

Data for Metabolic Engineering of Oleaginous Yeast Rhodotorula toruloides for Overproduction of Triacetic Acid Lactone

The plant-sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2-pyrone synthase gene from Gerbera hybrida (GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl-CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP-citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl-CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12-ACL1-ACC1 using fed-batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl-CoA-derived polyketides from low-cost carbon sources.

Conversion↗

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference

Efficient machine learning implementations optimized for inference in hardware have wide-ranging benefits, depending on the application, from lower inference latency to higher data throughput and reduced energy consumption. Two popular techniques for reducing computation in neural networks are pruning, removing insignificant synapses, and quantization, reducing the precision of the calculations. In this work, we explore the interplay between pruning and quantization during the training of neural networks for ultra low latency applications targeting high energy physics use cases. Techniques developed for this study have potential applications across many other domains. We study various configurations of pruning during quantization-aware training, which we term quantization-aware pruning, and the effect of techniques like regularization, batch normalization, and different pruning schemes on performance, computational complexity, and information content metrics. We find that quantization-aware pruning yields more computationally efficient models than either pruning or quantization alone for our task. Further, quantization-aware pruning typically performs similar to or better in terms of computational efficiency compared to other neural architecture search techniques like Bayesian optimization. Surprisingly, while networks with different training configurations can have similar performance for the benchmark application, the information content in the network can vary significantly, affecting its generalizability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Oxidation of n-alkanes using TS-1 and H 2 O 2 : Effects of chain length and solvents

The selective oxidation of n-C 8 H 18 , n-C 12 H 26 , n-C 16 H 34 , n-C 20 H 42 , and n-C 36 H 74 was studied with a goal of using these as models to provide insight into how to functionalize polyolefins. Reactions were carried out using a TS-1 catalyst and H 2 O 2 in a batch reactor with different cosolvents, including methanol, acetone, acetonitrile, methyl ethyl ketone, and methyl butyl ketone. Rates decreased with increasing alkane size, possibly due to the reduced solubility of larger alkanes into the water-rich phases. Cosolvents that promote the partitioning of alkanes in the aqueous phase increased the rates. 1 H NMR spectroscopy demonstrated that ketones were the primary products, although some alcohols also formed. There was preferential reaction at the 2 position in the alkanes, but reaction at central carbons was also observed. The results of this study suggest strategies for using this catalytic chemistry to functionalize polyolefins.

Alkane oxidation↗

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗

Mineral and fluid transformation of hydraulically fractured shale: case study of Caney Shale in Southern Oklahoma

This study explores the geochemical reactions that can cause permeability loss in hydraulically fractured reservoirs. The experiments involved the reaction of powdered-rock samples with produced brines in batch reactor system at temperature of 95 °C and atmospheric pressure for 7-days and 30-days respectively. Results show changes in mineralogy and chemistry of rock and fluid samples respectively, therefore confirming chemical reactions between the two during the experiments. The mineralogical changes of the rock included decreases of pyrite and feldspar content, whilst carbonate and illite content showed an initial stability and increase respectively before decreasing. Results from analyses of post-reaction fluids generally corroborate the results obtained from mineralogical analyses. Integrating the results obtained from both rocks and fluids reveal a complex trend of reactions between rock and fluid samples which is summarized as follows. Dissolution of pyrite by oxygenated fluid causes transient and localized acidity which triggers the dissolution of feldspar, carbonates, and other minerals susceptible to dissolution under acidic conditions. The dissolution of minerals releases high concentrations of ions, some of which subsequently precipitate secondary minerals. On the field scale, the formation of secondary minerals in the pores and flow paths of hydrocarbons can cause significant reduction in the permeability of the reservoir, which will culminate in rapid productivity decline. This study provides an understanding of the geochemical rock–fluid reactions that impact long term permeability of shale reservoirs.

58 GEOSCIENCES↗

Time-Temperature-Transformation (TTT) Diagram for a Sludge Batch 9 Glass Composition Based on Coupled-Operation with the Salt Waste Processing Facility

The amorphous structure of a glass waste form has the potential to rearrange into crystalline phases at temperatures between the liquidus temperature and the glass transition temperature (Tg). Certain phases that can form will be detrimental to the durability of the glass and it is important to know the conditions that promote devitrification. The canister-centerline-cooling (CCC) profile is used to replicate the area within the center of the Defense Waste Processing Facility (DWPF) canister with the slowest cooling during the initial cool down after pouring, which has the greatest potential for crystallization. Other time-temperature conditions that cause significant changes in either phase structure or phase composition are identified by a time-temperature-transformation (TTT) study. The phase stability of a waste form must be determined as a part of the Waste Acceptance Product Specifications (WAPS) if it is to eventually be stored in a geologic repository. This requires the creation of a TTT diagram and analysis of the Tg, as defined by the Department of Energy (DOE). The previous TTT study for a DWPF glass waste form was completed in 2010 prior to coupled operation with the Salt Waste Processing Facility (SWPF). SWPF transfers two high activity waste streams to DWPF for vitrification: a cesium-containing strip effluent and a stream containing monosodium titanate/sludge solids. These SWPF streams were first transferred to DWPF for vitrification during Sludge Batch 9 (SB9) in 2021. The impact of these SWPF streams on crystallization behavior was not determined in previous studies and the need for data to satisfy WAPS Specification 1.4 for SB9 was identified.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optimized production of a bioactive human recombinant protein from the microalgae Chlamydomonas reinhardtii grown at high density in a fed-batch bioreactor

Microalgae have been identified as an alternative platform to produce high-quality biomass and subsequent bioproducts, such as foods, feeds, nutritional supplements, recombinant proteins, and biofuels. Traditional biotechnological hosts for therapeutic proteins, such as the bacteria Escherichia coli and mammalian CHO cells, have long been established as the dominate platforms, but recent advances have shown that microalgae can potentially serve as an alternative platform. In the present study, we examine the potential of the microalga Chlamydomonas reinhardtii to produce a complex human recombinant protein in a high-density heterotrophic culture. The recombinant human protein, ICAM-1, was targeted for secretion to the extracellular media of the culture from cells grown in a bioreactor using a fed-batch strategy to achieve high cell density. Ultimately, this resulted in a maximum biomass titer of 40 g/L and a recombinant protein titer of 50 mg/L. The algal-produced ICAM-1 protein showed comparable bioactivity to mammalian cell culture produced ICAM-1, as measured using binding assays for its native ligand LFA-1. This work shows that C. reinhardtii is a viable option to produce complex recombinant proteins, with native biological activity, at high concentrations using a fed batch heterotrophic growth strategy.

60 APPLIED LIFE SCIENCES↗

Improved reproducibility of metal halide perovskite solar cells via automated gas quenching

Achieving reproducible perovskite solar cell fabrication is crucial for making it a scalable technology. We demonstrate an automated gas quenching system to improve perovskite solar cell reproducibility at the lab-scale. We use in situ photoluminescence to monitor the perovskite film formation as a function of the atmosphere in the glove box and find that antisolvent quenching is more sensitive to lingering precursor solvents than the gas quenching method. We observe a better reproducibility with gas quenching than with antisolvent quenching because it maintains a more consistent atmosphere in the glove box. The automated gas quenching process leads to high performing devices that are reproducible both batch to batch and researcher to researcher. The insights into gas quenching film formation as a function of solvent atmosphere and quench velocity will help inform future studies on large scale fabrication systems.

14 SOLAR ENERGY↗

Sequencing and analysis of 131 SARS-CoV-2 isolates in previously sampled and unsampled regions of Jordan from 2020 to 2023

The Hashemite Kingdom of Jordan remains an understudied country for next generation sequencing analysis of SARS-CoV-2 genomes collected during the 2019 pandemic. Here we provide 131 additional reference genomes collected between 2020–2023 from SARS-CoV-2-positive patients across Jordan. Phylogenetic analysis supports existing pandemic narratives of changing clade dominance over time and adds genomes in novel Jordanian locations and timepoints to make Jordan SARS-CoV-2 databases more comprehensive. Samples from the less-sequenced cities of Ajloun, Jaresh, Karak, and Madaba identified previously unreported lineages while Amman, Irbid, and Zarqa have existing sequencing efforts bolstered. Despite many incomplete patient records and a relatively small sample size, we observe interesting symptom patterns that support existing global and Jordanian pandemic narratives. We note how in-country COVID-19 pandemic genomic studies showcase Jordan’s efforts to expand next generation sequencing capabilities, especially through the leveraging of EDGE COVID-19, a bioinformatics platform for performing rapid, batched analysis of SARS-CoV-2 sequencing that streamlines sample processing prepared from a network of hospital locations.

60 APPLIED LIFE SCIENCES↗

Investigation of the Effect of Injected CO 2 on the Morrow B Sandstone through Laboratory Batch Reaction Experiments: Implications for CO 2 Sequestration in the Farnsworth Unit, Northern Texas, USA

About one million tons of CO 2 have been injected into the Farnsworth unit to date. The target reservoir for CO 2 injection is the Morrow B Sandstone, which is primarily made of quartz with lesser amounts of albite, calcite, chlorite, and clay minerals. The impact of CO 2 injection on the mineralogy, porosity, and pore water composition of the Morrow B Sandstone is a major concern. Although numerical modeling studies suggest that porosity changes will be minimal, significant alterations to mineralogy and pore water composition are expected. Given the implications for CO 2 storage effectiveness and risk assessment, it is crucial to verify the accuracy of theoretical model predictions through laboratory experiments. To this end, batch reaction experiments were conducted to model conditions near an injection well in the Morrow B Sandstone and at locations further away, where the CO 2 has been diluted by formation water. The laboratory experiments involved submerging thin sections of both coarse- and fine-grained facies of the Morrow B Sandstone in formation water samples with varying levels of CO 2 . The experiments were conducted at the reservoir temperature of 75 °C. Two experimental runs were conducted, one lasting for 61 days and the other for 72 days. The initial fluid composition used in the second run was the same as in the first. The mineralogy changes in the thin sections were analyzed using SEM and the Tescan Integrated Mineral Analyzer (TIMA), while changes in the composition of the formation water were determined using ICP-AES. During each experiment, a thin layer of white fine-grained particles consisting mainly of dolomite and silica formed on the surface of the thin sections, leading to significant reductions in Ca, Mg, and Sr in the formation water. This outcome is consistent with numerical model predictions that dolomite would be the primary mineral that would react with injected CO 2 and that silica would be oversaturated in the formation water. Changes in mineral abundance in the thin sections themselves were much less systematic than in the theoretical modeling experiments, perhaps reflecting heterogeneities in the mineral grain size surface area to volume ratios and mineral distributions in the thin sections not considered in the numerical models.

58 GEOSCIENCES↗

Fed-batch production of deuterated protein in Escherichia coli for neutron scattering experimentation

Neutron scattering is a powerful technique for determining the structure and dynamics of biological materials in a variety of environmental conditions. A distinguishing property of the neutron is its sensitivity to detecting hydrogen and distinguishing it from its isotope deuterium. This enables unique types of experiments that take advantage of this differential sensitivity called isotopic contrast variation. Using this approach, the chemistry of the system is not changed, but the visibility of individual sample components can be tuned by varying the deuterium content of the system under investigation. Deuterated proteins are commonly produced in bacterial systems that are adapted to growth in D2O minimal media. To maximize the yield of deuterium-labeled protein and efficiently utilize D2O and occasionally the deuterated substrate, fed-batch processes are routinely used to maximize biomass production without compromising cell viability. A step-by-step procedure will be described along with a case study of the production of deuterated green fluorescent protein. Limitations of the process will also be discussed.

Weiss, Kevin L.↗

Effects of HZ-PAN Sorbent Irradiation on Kr Adsorption

Idaho National Laboratory (INL) has developed and studied an engineered form hydrogen mordenite in polyacrylonitrile matrix (HZ-PAN) for krypton (Kr) adsorption. Adsorption studies to date have successfully separated and captured Kr from carrier gas streams, but those studies have used non-radioactive gases for testing. However, if utilized in a used nuclear fuel (UNF) reprocessing facility, this sorbent will be exposed to the potential deleterious effects of radiation. This report explores Kr adsorption behavior on HZ PAN after the sorbent was exposed to gamma radiation. A batch of HZ-PAN was divided into five segments, a control segment that was not exposed to radiation, and the other four segments that were exposed to progressively increased levels of radiation dose, up to 5 MGy. Samples were then analyzed to determine total surface area as well as their capacity to capture Kr. This study reveals HZ PAN retains its initial surface area and Kr-capture capacity after radiation exposure, indicating viability for service in radioactive gases.

42 - ENGINEERING↗

Characterization of the Sulfur-Saturated Melt Versions of the HFG1 Study Glasses

The U.S. Department of Energy (DOE) is responsible for building the Hanford Tank Waste Treatment and Immobilization Plant (WTP) at the Hanford Site in Washington to remediate 55 million gallons of radioactive waste that is temporarily stored in 177 underground tanks. The Office of River Protection (ORP) has requested that the Savannah River National Laboratory (SRNL) contribute to current glass studies to support successful startup of the WTP, due to SRNL’s recognized capabilities and expertise for glass waste form development. As part of this effort, the Pacific Northwest National Laboratory (PNNL) is developing, batching, and fabricating simulated high-level waste (HLW) glasses to generate the associated property data needed to validate or identify areas of potential characterization improvements in the current glass property/ composition models. Currently, the models cover only a small fraction of the waste compositions projected in the Hanford tank farm; therefore, the models must be expanded to include high fluoride compositions to successfully complete the WTP mission. SRNL support of this work is defined in the Task Technical and Quality Assurance Plan (TTQAP). This report provides results from the chemical analyses of a series of sulfur-saturated melt (SSM) versions of simulated nuclear waste glasses fabricated at PNNL. The glasses were selected as part of a broader study of the influence of glass composition on chemical durability, sulfur retention, and other properties. The glasses were designated the High Fluoride Glasses-1 (HLG1).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Effect of dietary fiber fermentation on short‐chain fatty acid production and microbial composition in vitro

Abstract BACKGROUND The efficient utilization of fiber‐rich co‐products is important for optimizing feed resource utilization and animal health. This study was conducted to evaluate the fermentation characteristics of fiber‐rich co‐products, which had equal quantities of total dietary fiber (TDF), at different time points using batch in vitro methods. It considered their gas production, short‐chain fatty acid (SCFA) production, and microbial composition. RESULTS The fermentation of wheat bran (WB) and oat bran (OB) showed higher and faster ( P < 0.05) gas and SCFA production than corn bran (CB), sugar beet pulp (SBP), and soybean hulls (SH). The α ‐diversity was higher in the CB, SBP, and SH groups than in the WB and OB groups ( P < 0.05). At the phylum level, OB and WB fermentation showed lower ( P < 0.05) relative abundance of Actinobacteria than the CB, SBP, and SH groups. At the genus level, OB and WB fermentation increased the Enterococcus population in comparison with the CB, SBP, and SH groups, whereas CB and SBP fermentation improved the relative abundance of the Christensenellaceae R‐7 group more than the WB, OB, and SH groups ( P < 0.05). CONCLUSION Overall, WB and OB were rapidly fermented by fecal microbiota, in contrast with SBP, SH, and CB. Fermentation of different fiber‐rich co‐products with an equal TDF content gives different responses in terms of microbial composition and SCFA production due to variations in their physicochemical properties and molecular structure. © 2020 Society of Chemical Industry

Bai, Yu↗

Ultrasound-Assisted Nonthermal, Nonequilibrium Separation of Organic Molecules from Their Binary Aqueous Solutions: Effect of Solute Properties on Separation

The separation of organic molecules in downstream processes, such as distillation, plays a vital role in biobased chemical production. A comprehensive study was performed here using ultrasonic energy to separate 11 organic molecules from their binary aqueous solutions under nonthermal, nonequilibrium, and phase-change free conditions. A batch sonoseparator with a three-stage mist collection unit allowed direct analysis of ultrasound-generated mist with an HPLC/GC and differentiation and quantification of the vapor and mist. The results showed that the alcohols (1-butanol, ethanol, 1-propanol, and methanol) and acetone were enriched in the ultrasound-generated mist with enrichment ratios of 3.2–5. On the other hand, ethylene glycol, glycerol, γ-valerolactone (GVL), glucose, and sucrose were diluted with dilution ratios in the range of 2.04–15.7 in the mist and vapor generated by ultrasound (or concentrated in the bulk solution). No enrichment nor dilution of acetic acid was observed. The role of various physicochemical parameters such as dynamic viscosity, surface tension, Henry’s law of solubility constant, vapor pressure, and octanol–water partition coefficient in the enrichment was examined. Furthermore, the hydrophobicity of the organic molecules represented by the octanol–water partition coefficient was found to play a crucial role in determining the separation characteristics of the molecules in ultrasound-generated mist and vapor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Steering the methanol steam reforming reactivity of intermetallic Cu–In compounds by redox activation: stability vs . formation of an intermetallic compound–oxide interface

To compare the inherent methanol steam reforming properties of intermetallic compounds and a corresponding intermetallic compound–oxide interface, we selected the Cu–In system as a model to correlate the stability limits, self-activation and redox activation properties with the catalytic performance. Three distinct intermetallic Cu–In compounds – Cu 7 In 3 , Cu 2 In and Cu 11 In 9 – were studied both in an untreated and redox-activated state resulting from alternating oxidation–reduction cycles. The stability of all studied intermetallic compounds during methanol steam reforming (MSR) operation is essentially independent of the initial stoichiometry and all accordingly resist substantial structural changes. The inherent activity under batch MSR conditions is highest for Cu 2 In, corroborating the results of a Cu 2 In/In 2 O 3 sample accessed through reactive metal–support interaction. Under flow MSR operation, Cu 7 In 3 displays considerable deactivation, while Cu 2 In and Cu 11 In 9 feature stable performance at simultaneously high CO 2 selectivity. Here, the missing significant self-activation is most evident in the operando thermogravimetric experiments, where no oxidation is detected for any of the intermetallic compounds. In situ X-ray diffraction allowed us to monitor the partial decomposition and redox activation of the Cu–In intermetallic compounds into Cu 0.9 In 0.1 /In 2 O 3 (from Cu 7 In 3 ), Cu 7 In 3 /In 2 O 3 (from Cu 2 In) and Cu 7 In 3 /Cu 0.9 In 0.1 /In 2 O 3 (from Cu 11 In 9 ) interfaces with superior MSR performance compared to the untreated samples. Although the catalytic profiles appear surprisingly similar, the latter interface with the highest indium content exhibits the least deactivation, which we explain by formation of stabilizing In 2 O 3 patches under MSR conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗