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Biphasic Janus Particles Explain Self-Healing in Pt–Pd Diesel Oxidation Catalysts

The addition of Pd to Pt-based diesel oxidation catalysts is known to enhance performance and restrict the anomalous growth of Pt nanoparticles when subjected to aging at high temperatures in oxidative environments. To gain a mechanistic understanding, we studied the transport of the mobile Pt and Pd species to the vapor phase, since vapor phase transport is the primary route for sintering in these catalysts. The results are surprising: there is a 30-fold drop in the effective vapor pressure of Pt in the Pt-Pd catalysts compared to monometallic Pt. At the same time, there is a significant enhancement in the vapor pressure of Pd, compared to PdO, which otherwise has a negligible vapor pressure at the aging temperature. Such behavior cannot be explained simply by alloying Pt and Pd in the metallic phase, or a core-shell morphology where a PdO shell covers a Pt core. Transmission electron microscopic examination of catalysts aged up to 50 h in air at 800 °C shows that the particles exhibit a biphasic “Janus”-like structure. The metal and oxide phases are conjoined, exposing a metal and an oxide face to the gas phase. The high mobility of the Pt and Pd allows them to be partitioned into the metal and oxide phases, in apparent thermodynamic equilibrium. The PdO helps to trap mobile PtO2 and as a result contains high concentrations of Pt oxide, consistent with its role in mitigating the transport of Pt to the vapor phase and preventing the growth of anomalously large particles. In turn, Pt allows Pd to remain metallic, allowing the catalyst to retain both metal and oxide functionality for catalysis. The regeneration of deactivated catalysts typically requires an external input, such as a change in the working environment from reducing to oxidizing or vice-versa. Here, we show that the mobile species, which are primary contributors to catalyst sintering are effectively returned to the active site, hence our use of the term “selfhealing”. The detailed insights into the inner workings of the Pt-Pd diesel oxidation catalysts can help provide clues to the design of robust and durable heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Surface Chemistry of Methanol on TiO 2 (110): Effects of Pressure and Temperature on the Stability of C–O and C–H Bonds

Synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the surface chemistry of methanol on TiO 2 (110), examining the effects of methanol pressure, oxide temperature, and coadsorption with H 2 . At 300 K, the adsorption of methanol on TiO 2 (110) leads to the formation of CH 3 O on the surface with a minor amount of CH 3 OH present. The easy cleavage of the O–H bond in the alcohol agrees with the predictions of theoretical calculations, and most of the adsorbed CH 3 O was not associated with the presence of Ti 3+ sites in the oxide substrate. The adsorbed CH 3 O was removed from the TiO 2 (110) surface by heating to 600 K without the deposition of CH x fragments or C on the oxide. The results of temperature-programmed desorption (TPD) showed the evolution of methanol and formaldehyde at 360 and 490 K as a result of a disproportionation reaction: 2CH 3 O → CH 3 OH + CH 2 O. This surface chemistry, where there is no rupture of the C–O bond, and only selective cleavage of O–H and C–H bonds, is very different from that found on metals used in catalysts for methanol reforming, where massive conversion of the alcohol into CO, CH x and C species is seen. Furthermore, the TPD data indicate that any CH 3 O formed on the oxide surface can be hydrogenated and desorbed as CH 3 OH at temperatures below 550 K. In this respect, titania is an ideal support for catalysts employed to achieve methanol synthesis through CO 2 hydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

36 MATERIALS SCIENCE↗

Growth and structural studies of In/Au(111) alloys and InO x /Au(111) inverse oxide/metal model catalysts

Indium oxide has received attention as an exciting candidate for catalyzing the CO 2 hydrogenation to methanol due to its high selectivity (>80%). Compared to the extent of research on the activity of indium oxide-based powder catalysts, very little is known about the phenomena associated with the formation of surface alloys involving indium or the growth mechanism for indium oxide nanoparticles. In this report, scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS) were employed to elucidate the growth mode, structure, and chemical state of In/Au(111) alloys and InO x /Au(111) inverse model catalysts. Here, our study reveals distinct morphological differences between In/Au(111) and InO x /Au(111), and the InO x structure also depends strongly on the preparation conditions. In/Au surface alloy systems with extremely low coverage (0.02 ML) form islands preferentially on the elbow sites of reconstructed Au(111) herringbone, regardless of hcp and fcc stacking. At higher coverage (0.1 ML), the In islands expand over the herringbone in the <110> direction and create two dimensional domain structures over the entire surfaces. Moreover, this 2D domain structure is disturbed by temperature with high dispersion of indium atoms observed during the annealing process. Oxidation of the In/Au(111) surface alloys with O 2 at 550 K produces InO x /Au(111) systems which contain various sizes of InO x aggregates (from 0.7 to 10 nm). On the other hand, InO x /Au(111) surfaces prepared by vapor deposition of In at 550 K in an O 2 background exhibit highly dispersed and uniformly small InO x particles (~1 nm). Both InO x systems were confirmed to be partially oxidized by XPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrocarbon, Oxidation, Dehydrogenation and Coupling Over Model Metal Oxide Surfaces

Final report for a 24.5 year single investigator project aimed at understanding structure/function relationships in adsorption and reaction on metal oxide surfaces for understanding heterogeneous catalysis. An experimental surface science approach was taken using single crystal surfaces as model catalysts and supplemented by density functional theory (DFT) calculations. Materials studied experimentally and computationally include the base metal oxide SnO 2 and transition metal oxides α-Cr 2 O 3 , α-Fe 2 O 3 and MnO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metallic Pd–Cu Alloy Phases Drive Selective Heterogeneous Electrochemical Ketonization of 1-Butene

Electrification of 2-butanone synthesis via ketonization of 1-butene offers a viable pathway to reduce emissions associated with its production as a commodity chemical and enhance its prospects as a clean carbon-based synthetic fuel. However, the direct electrochemical ketonization of alkenes remains underexplored, with previous studies largely limited to epoxides and glycols. Herein, we report an electrochemical heterogeneous system optimized for 1-butene ketonization, converting 1-butene to 2- butanone using a bimetallic PdCu catalyst in aqueous electrolytes. The system achieves a Faradaic efficiency of 20% and a partial current density of 0.6 mA/cm 2 at 1.8 V RHE . In comparison to monometallic Pd and oxidized PdCu analogs, the PdCu catalyst doubles the ketonization Faradaic efficiency and quadruples the production rate. Postelectrolysis characterization reveals that PdCu preserves the surface metallic alloy phase under anodic polarization, which likely accounts for the enhanced ketonization activity. This work demonstrates the significance of the Pd−Cu speciation dynamics and provides a framework for designing selective electrocatalysts for alkene ketonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stabilizing LiCoO 2 at 4.6 V by regulating anti-oxidative solvents

For LiCoO 2 (LCO) operating at high voltages (>4.5 V vs. Li/Li + ), the intensive side reactions between LCO and traditional ethylene carbonate (EC)-based electrolytes with LiPF 6 salts can produce plenty of corrosive species (such as HF and HPO 2 F 2 ), causing severe surface degradation. Herein, anti-oxidative fluoroethylene carbonate (FEC) and difluoroethylene carbonate (DFEC) were selected as co-solvents to reduce the generation of corrosive species. Besides, PF 6 − anions enrich the Helmholtz plane of the LCO/electrolyte interface and promote the formation of a robust cathode/electrolyte interphase (CEI) featuring LiF/Li x PO y F z /Li 3 PO 4 inorganics and P-containing organics under the synergy of fluorinated solvents, which significantly inhibits the catalysis of highly oxidative Co 4+ /O n− (0 < n < 2). Benefiting from the reduced corrosive species and reinforced CEI, the layered structure of the LCO surface is well preserved during long-term cycling, with a highly reversible O3/H1-3 phase transition. Consequently, a LCO||graphite pouch cell exhibits a remarkable capacity retention of 85.7% after 500 cycles in 3.0–4.55 V. Furthermore, this work provides a new insight into developing advanced functional electrolytes for high-voltage lithium-ion batteries.

Co/O loss↗

Heavy Versus Light Lanthanide Selectivity for Graphene Oxide Films is Concentration Dependent

Rare earths are important materials in various technologies such as catalysis and optoelectronics. Graphene oxide (GO) is a promising material for separation applications, including the isolation of lanthanides from complex mixtures. Previous works using fatty acid monolayers have demonstrated preferential heavy versus light lanthanide adsorption, which has been attributed to differences in lanthanide ion size. In this work, we used interfacial X-ray fluorescence measurements to reveal that GO thin films at the air/water interface have no lanthanide selectivity for dilute subphases. However, at high subphase concentrations, ~8 times more Lu is adsorbed than La. By comparing the GO results with an ideal monolayer with a carboxylic acid headgroup, arachidic acid (AA), we demonstrate that the number of Lu ions adsorbed to GO is significantly higher than the number expected to compensate for the surface charge. Vibrational sum frequency generation (SFG) spectroscopy results on both GO thin films and AA monolayers reveal a red-shifted SFG signal in the OH region, which we attribute to partial dehydration of the adsorbed ions and carboxylic acid headgroups. Liquid surface X-ray reflectivity data show that the GO thin film structure does not significantly change between the very dilute and concentrated subphases. We speculate that the functional groups of both GO and AA facilitate cation dehydration, which is essential for ion adsorption. Heavy lanthanide Lu has stronger ion–ion correlations that can overcome the electrostatic repulsion between cations at higher concentrations compared to light lanthanide La, meaning GO and AA can exhibit apparent overcharge with Lu. Lastly, the layered structure of the GO films and reactive chemical nature of GO itself can accommodate ion adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Node-Solution Microenvironment Governs the Selectivity of Thioanisole Oxidation within Catalytic Zr-Based Metal–Organic Framework

Lewis acidic metal oxides, including zirconia (ZrO 2 ), are catalytically active toward oxidative reactions in the presence of sacrificial oxidants like t-butyl hydroperoxide (TBHP). The structural ambiguity and heterogeneity of the ZrO 2 surface impose challenges to chemists in understanding the reaction mechanism down to atomic-level precision. The inorganic, Zr-oxo nodes of many crystalline metal–organic frameworks (MOFs) structurally mimic ZrO 2 . Herein, we report three novel findings: (A) Zr-based MOF, Zr-MOF-808 is catalytically competent in activating TBHP to induce oxygen atom transfer (OAT) reactions to a model substrate, thioanisole, at room temperature, (B) its reaction mechanism can be derived with greater structural precision owing to the crystallinity of the MOF, and (C) the node-binding agent and other reaction conditions significantly impact the selectivity between the singly oxidized methyl phenyl sulfoxide vs the doubly oxidized sulfone. These findings suggest that both the activity and selectivity of OAT reactions within Zr-MOF-808 are governed by the chemistry occurring at the interface of the node and the surrounding reaction medium. Implications of these findings in OAT reactions and other MOF/metal oxide-catalyzed relevant catalysis are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlled electron transfer by molecular wires embedded in ultrathin insulating membranes for driving redox catalysis

Organic bilayers or amorphous silica films of a few nanometer thickness featuring embedded molecular wires offer opportunities for chemically separating while at the same time electronically connecting photo- or electrocatalytic components. Such ultrathin membranes enable the integration of components for which direct coupling is not sufficiently efficient or stable. Photoelectrocatalytic systems for the generation or utilization of renewable energy are among the most prominent ones for which ultrathin separation layers open up new approaches for component integration for improving efficiency. Recent advances in the assembly and spectroscopic, microscopic, and photoelectrochemical characterization have enabled the systematic optimization of the structure, energetics, and density of embedded molecular wires for maximum charge transfer efficiency. The progress enables interfacial designs for the nanoscale integration of the incompatible oxidation and reduction catalysis environments of artificial photosystems and of microbial (or biomolecular)-abiotic systems for renewable energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interfacial Charge Transfer Pathways in Photoelectrochemical H 2 Evolution by a Single-Component Molecular Catalyst on a Conductive Metal Oxide

Dye-sensitized photoelectrosynthesis cells traditionally combine a photosensitizing dye to harvest light and a catalyst to generate chemical fuels on a semiconductor. Here, in this work, a photoactive catalyst capable of both light absorption and fuel formation, [Cp*Ir(4,4′-Y 2 -bpy)Cl][Cl] (Cp* = pentamethylcyclopentadienyl, bpy = 2,2′-bipyridine, Y = CH 2 PO 3 H 2 ), is anchored to a mesoporous tin-doped indium oxide (ITO) electrode and facilitates photoelectrochemical H 2 evolution in water without the need for additional photosensitizers or sacrificial reductants. Spectroelectrochemistry indicates a single-site H 2 evolution mechanism involving charge injection to ITO, in contrast to the bimetallic mechanism observed in solution. Cyclic voltammetry and variable-potential chronoamperometry under illumination probe competing pathways via interfacial electron transfer between the Ir hydride excited state and the conductive ITO electrode. A Marcus theory framework provides reorganization energies for competing interfacial electron transfer pathways from potential-dependent quantum yield measurements. The light-driven H 2 evolution catalysis on conducting oxide proceeds with high Faradaic efficiency and current densities comparable to photoelectrodes utilizing p-type semiconductors. By uncovering the principal electron transfer pathways that govern photocatalytic efficiency, this study establishes design principles for hybrid molecular photoelectrocatalysts.

catalysts↗

A General Approach for Metal Nanoparticle Encapsulation Within Porous Oxides

Abstract Encapsulation of metal nanoparticles within oxide materials has been shown as an effective strategy to improve activity, selectivity, and stability in several catalytic applications. Several approaches have been proposed to encapsulate nanoparticles, such as forming core‐shell structures, growing ordered structures (zeolites or metal‐organic frameworks) on nanoparticles, or directly depositing support materials on nanoparticles. Here, a general nanocasting method is demonstrated that can produce diverse encapsulated metal@oxide structures with different compositions (Pt, Pd, Rh) and multiple types of oxides (Al 2 O 3 , Al 2 O 3 ‐CeO 2 , ZrO 2 , ZnZrO x , In 2 O 3 , Mn 2 O 3 , TiO 2 ) while controlling the size and dispersion of nanoparticles and the porous structure of the oxide. Metal@polymer structures are first prepared, and then the oxide precursor is infiltrated into such structures and the resulting material is calcined to form the metal@oxide structures. Most Pt@oxides catalysts show similar catalytic activity, demonstrating the availability of surface Pt sites in the encapsulated structures. However, the Pt@Mn 2 O 3 sample showed much higher CO oxidation activity, while also being stable under aging conditions. This work demonstrated a robust nanocasting method to synthesize metal@oxide structures, which can be utilized in catalysis to finely tune metal‐oxide interfaces.

Zhou, Chengshuang↗

Gallionella and Sulfuricella populations are dominant during the transition of boreal potential to actual acid sulfate soils

Acid sulfate soils release metal laden, acidic waters that affect the environment, buildings, and human health. In this study, 16S rRNA gene amplicons, metagenomes, and metatranscriptomes all demonstrated distinct microbial communities and activities in the unoxidized potential acid sulfate soil, the overlying transition zone, and uppermost oxidized actual acid sulfate soil. Assembled genomes and mRNA transcripts also suggested abundant oxidized acid sulfate soil populations that aligned within the Gammaproteobacteria and Terracidiphilus. In contrast, potentially acid tolerant or moderately acidophilic iron oxidizing Gallionella and sulfur metabolizing Sulfuricella dominated the transition zone during catalysis of metal sulfide oxidation to form acid sulfate soil. Finally, anaerobic oxidation of methane coupled to nitrate, sulfate, and ferric reduction were suggested to occur in the reduced parent sediments. In conclusion, despite comparable metal sulfide dissolution processes e.g., biomining, Gallionella and Sulfuricella dominated the community and activities during conversion of potential to actual acid sulfate soils.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrothermally stable Pd/SiO 2 @Zr Core@Shell catalysts for diesel oxidation applications

Hydrothermally stable diesel oxidation catalysts (DOCs) with improved low-temperature activity are desired for the abatement of emissions from diesel vehicles. Herein, novel palladium(Pd)/SiO 2 (core)@Zr(shell) structured DOCs were developed. SiO 2 was completely covered by an 8.4 nm thickness Zr-based shell using a hard template method. The SiO 2 @Zr support was decorated by Pd and evaluated under a simulated diesel exhaust stream. Degreened 1 wt% Pd/SiO 2 @Zr achieved 90% CO and total hydrocarbon conversion at 178 and 372 °C, respectively (feed: 6% CO 2 , 12% O 2 , 6% H 2 O, 400 ppm H 2 , 2000 ppm CO, 100 ppm NO, 1667 ppm C 2 H 4 , 1000 ppm C 3 H 6 , 333 ppm C 3 H 8 ; HCs in C 1 basis and GHSV = 113,000 h –1 ). After hydrothermal aging, only a minor deactivation was observed, while the surface area of 1 wt% Pd/SiO 2 @Zr was as high as 104 m 2 /g. The hydrothermal stability of 1 wt% Pd/SiO 2 @Zr was attributed to the poor crystallinity of SiO 2 @Zr, possibly due to the formation of Si-O-Zr bonds. Lastly, this work highlights the promising potential of utilizing durable Pd/SiO 2 @Zr catalysts for diesel oxidation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lithium promotion of Pt/m-ZrO 2 catalysts for low temperature water-gas shift

Low temperature water-gas shift (LTS) is an important reaction occurring in a fuel processor for producing and purifying hydrogen. Platinum supported on m-ZrO 2 belongs to a family of catalysts consisting of metal nanoparticles and an active partially reducible oxide, with the catalysis proposed to occur at the boundary between metal particles and the support. In this investigation, increasing the loading of lithium dopant increased the LTS rate up to 0.54 wt % lithium, where conversion was 2.4 times that of the unpromoted catalyst at 260°C. Further increases in lithium loading up to 1.5 wt % decreased the rate, although it remained higher than that of the unpromoted catalyst. Infrared spectroscopy and CO 2 temperature programmed desorption experiments showed three effects with increasing lithium loading: (1) lithium promoter weakened the C–H bond of formate, the proposed rate limiting step of the interfacial surface formate mechanism; (2) high levels of lithium suppressed the platinum site capacity required for hydrogen transfer; and (3) high levels of lithium increased catalyst basicity. Aspects (2) and (3) tended to inhibit desorption of product CO 2 , an acidic molecule the removal of which is metal-catalyzed. XANES and XPS experiments revealed that electron transfer to enrich Pt nanoparticles is unlikely the root cause of C–H bond weakening in formate. However, other electronic effects (e.g., electrostatic effects or molecular rearrangement due to enhanced basicity) were not ruled out.

08 HYDROGEN↗

Structure of a monomeric photosystem II core complex from a cyanobacterium acclimated to far-red light reveals the functions of chlorophylls $d$ and $f$

Far-red light (FRL) photoacclimation (FaRLiP) in cyanobacteria provides a selective growth advantage for some terrestrial cyanobacteria by expanding the range of photosynthetically active radiation to include far-red/near-infrared light (700 to 800 nm). During this photoacclimation process, photosystem II (PSII), the water:plastoquinone photooxidoreductase involved in oxygenic photosynthesis, is modified. The resulting FRL-PSII is comprised of FRL-specific core subunits and binds chlorophyll (Chl) d and Chl f molecules in place of several of the Chl a molecules found when cells are grown in visible light. These new Chls effectively lower the energy canonically thought to define the “red limit” for light required to drive photochemical catalysis of water oxidation. Changes to the architecture of FRL-PSII were previously unknown, and the positions of Chl d and Chl f molecules had only been proposed from indirect evidence. Here, we describe the 2.25-Å resolution cryo-EM structure of a monomeric FRL-PSII core complex from Synechococcus sp. PCC 7335 cells that were acclimated to FRL. We identify one Chl d molecule in the Chl D1 position of the electron transfer chain, and four Chl f molecules in the core antenna. We also make observations that enhance our understanding of PSII biogenesis, especially on the acceptor side of the complex where a bicarbonate molecule is replaced by a glutamate sidechain in the absence of the assembly factor Psb28. In conclusion, these results provide a structural basis for the lower energy limit required to drive water oxidation, which is the gateway for most solar energy utilization on Earth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The interplay between surface facet and reconstruction on isopropanol conversion over SrTiO 3 nanocrystals

Strontium titanate (SrTiO 3 ) is an extensively investigated perovskite for various applications due to its optical, electrical and chemical properties. To gain an in-depth understanding of the active sites involved in heterogeneous catalysis over the broadly used SrTiO 3 (STO), we studied a model reaction, isopropanol conversion, on three differently shape-controlled nanocrystals: cube, truncated cube and dodecahedra. SEM, XRD and XPS confirmed the morphology, phase and composition of STO shapes. Low energy ion scattering (LEIS) revealed the occurrence of surface reconstruction over STO shapes during O 2 pretreatment at different temperatures. Based on the catalytic activities, scanning transmission electron microscopy images and density functional theory calculations, the step sites on STO derived from surface reconstruction were proposed to be the active sites for isopropanol conversion. This was further confirmed by steady state isotopic kinetic analysis (SSITKA) which demonstrated similar intrinsic turnover frequencies (TOFs) for the differently reconstructed STO shapes. It is concluded that the crystal facets impose an indirect effect on the catalysis of STO via controlling the degrees of surface reconstruction: the less stable STO (1 1 0) facet (dodecahedra) leads to more step sites after reconstruction and hence higher overall reaction rate than the more stable (1 0 0) facet (cube). This work highlights the important interplay between the crystal facet and surface reconstruction in controlling the nature and density of active sties and thus catalysis over complex oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗