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Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics. Bayesian optimization is a strategy of efficient global optimization that has proved successful in similar regimes in a wide variety of beamline alignment applications, though it has typically been implemented for particular beamlines and optimization tasks. In this paper, we present a basic formulation of Bayesian inference and Gaussian process models as they relate to multi-objective Bayesian optimization, as well as the practical challenges presented by beamline alignment. We show that the same general implementation of Bayesian optimization with special consideration for beamline alignment can quickly learn the dynamics of particular beamlines in an online fashion through hyperparameter fitting with no prior information. We present the implementation of a concise software framework for beamline alignment and test it on four different optimization problems for experiments on X-ray beamlines at the National Synchrotron Light Source II and the Advanced Light Source, and an electron beam at the Accelerator Test Facility, along with benchmarking on a simulated digital twin. We discuss new applications of the framework, and the potential for a unified approach to beamline alignment at synchrotron facilities.

Here, a recently commissioned five-analyzer Johann spectrometer at the Inner Shell Spectroscopy beamline (8-ID) at the National Synchrotron Light Source II (NSLS-II) is presented. Designed for hard X-ray photon-in/photon-out spectroscopy, the spectrometer achieves a resolution in the 0.5–2 eV range, depending on the element and/or emission line, providing detailed insights into the local electronic and geometric structure of materials. It serves a diverse user community, including fields such as physical, chemical, biological, environmental and materials sciences. This article details the mechanical design, alignment procedures and data-acquisition scheme of the spectrometer, with a particular focus on the continuous asynchronous data-acquisition approach that significantly enhances experimental efficiency.

Abstract Balancing kinetics, a crucial priority in catalysis, is frequently achieved by sacrificing activity of elementary steps to suppress side reactions and enhance catalyst stability. Dry reforming of methane (DRM), a process operated at high temperature, usually involves fast C-H activation but sluggish carbon removal, resulting in coke deposition and catalyst deactivation. Studies focused solely on catalyst innovation are insufficient in addressing coke formation efficiently. Herein, we develop coke-free catalysts that balance kinetics of elementary steps for overall thermodynamics optimization. Beginning from a highly active cobalt aluminum oxide (CoAl2O4) catalyst that is susceptible to severe coke formation, we substitute aluminum (Al) with gallium (Ga), reporting a CoAl0.5Ga1.5O4-R catalyst that performs DRM stably over 1000 hours without observable coke deposition. We find that Ga enhances DRM stability by suppressing C-H activation to balance carbon removal. A series of coke-free DRM catalysts are developed herein by partially substituting Al from CoAl2O4 with other metals.

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant Kβ XES of 3d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 (AXEAP2), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3d electron spin state, 3d–3p electron exchange force and Kβ emission core-hole lifetime.

The Inner Shell Spectroscopy (ISS) beamline on the 8-ID station at the National Synchrotron Light Source II (NSLS-II), Upton, NY, USA, is a high-throughput X-ray absorption spectroscopy beamline designed for in situ, operando, and time-resolved material characterization using high monochromatic flux and scanning speed. This contribution discusses the technical specifications of the beamline in terms of optics, heat load management, monochromator motion control, and data acquisition and processing. Results of the beamline tests demonstrating the quality of the data obtainable on the instrument, possible energy scanning speeds, as well as long-term beamline stability are shown. The ability to directly control the monochromator trajectory to define the acquisition time for each spectral region is highlighted. Examples of studies performed on the beamline are presented. The paper is concluded with a brief outlook for future developments.

Abstract In this study, we demonstrate three-dimensional (3D) hollow nanosphere electrocatalysts for CO2 conversion into formate with excellent H-Cell performance and industrially-relevant current density in a 25 cm2 membrane electrode assembly electrolyzer device. Varying calcination temperature maximized formate production via optimizing the crystallinity and particle size of the constituent SnO2 nanoparticles. The best performing SnO2 nanosphere catalysts contained ~ 7.5 nm nanocrystals and produced 71–81% formate Faradaic efficiency (FE) between −0.9 V and −1.3 V vs. the reversible hydrogen electrode (RHE) at a maximum formate partial current density of 73 ± 2 mA cmgeo −2 at −1.3 V vs. RHE. The higher performance of nanosphere catalysts over SnO2 nanoparticles and commercially-available catalyst could be ascribed to their initial structure providing higher electrochemical surface area and preventing extensive nanocrystal growth during CO2 reduction. Our results are among the highest performance reported for SnO2 electrocatalysts in aqueous H-cells. We observed an average 68 ± 8% FE over 35 h of operation with multiple on/off cycles. In situ Raman and time-dependent X-ray diffraction measurements identified metallic Sn as electrocatalytic active sites during long-term operation. Further evaluation in a 25 cm2 electrolyzer cell demonstrated impressive performance with a sustained current density of 500 mA cmgeo −2 and an average 75 ± 6% formate FE over 24 h of operation. Our results provide additional design concepts for boosting the performance of formate-producing catalysts.

Single atom catalysts have exhibited high selectivity for hydrogenation, yet improved selectively is often accompanied by loss of activity. Here the authors report that synergistic interactions of neighboring Pd single atoms lead to both high activity and selectivity for hydrodehalogenation catalysis.

As machine learning (ML) methods continue to be applied to a broad scope of problems in the physical sciences, uncertainty quantification is becoming correspondingly more important for their robust application. Uncertainty-aware machine learning methods have been used in select applications, but largely for scalar properties. In this work, we showcase an exemplary study in which neural network ensembles are used to predict the x-ray absorption spectra of small molecules, as well as their pointwise uncertainty, from local atomic environments. The performance of the resulting surrogate clearly demonstrates quantitative correlation between errors relative to ground truth and the predicted uncertainty estimates. Significantly, the model provides an upper bound on the expected error. Specifically, an important quality of this uncertainty-aware model is that it can indicate when the model is predicting on out-of-sample data. This allows for its integration with large-scale sampling of structures together with active learning or other techniques for structure refinement. Additionally, our models can be generalized to larger molecules than those used for training, and also successfully track uncertainty due to random distortions in test molecules. While we demonstrate this workflow on a specific example, ensemble learning is completely general. We believe it could have significant impact on ML-enabled forward modeling of a broad array of molecular and materials properties.

A capacitance increase phenomenon is observed for MoO3 electrodes synthesized via a sol-gel process in the presence of dopamine hydrochloride (Dopa HCl) as compared to α-MoO3 electrodes in 5M ZnCl2 aqueous electrolyte. The synthesis approach is based on a hydrogen peroxide-initiated sol-gel reaction to which the Dopa HCl is added. The powder precursor (Dopa)xMoOy, is isolated from the metastable gel using freeze-drying. Hydrothermal treatment (HT) of the precursor results in the formation of MoO3 accompanied by carbonization of the organic molecules; designated as HT-MoO3/C. HT of the precipitate formed in the absence of dopamine in the reaction produced α-MoO3, which was used as a reference material in this study (α-MoO3-ref). Scanning electron microscopy (SEM) images show a nanobelt morphology for both HT-MoO3/C and α-MoO3-ref powders, but with distinct differences in the shape of the nanobelts. The presence of carbonaceous content in the structure of HT-MoO3/C is confirmed by FTIR and Raman spectroscopy measurements. X-ray diffraction (XRD) and Rietveld refinement analysis demonstrate the presence of α-MoO3 and h-MoO3 phases in the structure of HT-MoO3/C. The increased specific capacitance delivered by the HT-MoO3/C electrode as compared to the α-MoO3-ref electrode in 5M ZnCl2 electrolyte in a −0.25–0.70 V vs. Ag/AgCl potential window triggered a more detailed study in an expanded potential window. In the 5M ZnCl2 electrolyte at a scan rate of 2 mV s−1, the HT-MoO3/C electrode shows a second cycle capacitance of 347.6 F g−1. The higher electrochemical performance of the HT-MoO3/C electrode can be attributed to the presence of carbon in its structure, which can facilitate electron transport. Our study provides a new route for further development of metal oxides for energy storage applications.

Reacting CO2 and ethane to achieve value-added C3 oxygenates offers opportunities to simultaneously reduce CO2 emissions and upgrade underutilized ethane in shale gas. Here, the authors report a successful oxygenate production strategy enabled by inserting CO2-derived CO into ethane-derived ethylene using a tandem reactor.

Hydrogen peroxide can be produced alternatively using green inputs such as air, water, and sunlight but this requires a selective catalyst. Here the authors report an iron single atom catalyst that can convert oxygen into hydrogen peroxide with a selectivity of above 95% in both alkaline and neutral pH.

Mixed-valence cerium oxide nanoparticles (nanoceria) have been investigated with pronounced interest due to a wide range of biomedical and industrial applications that arises from its remarkable redox catalytic properties. However, there is no understanding of how to control the formation of these two types of nanoceria to obtain Ce3+/Ce4+ ratios required in various applications. In this work, using a soluble borate glass, nanoceria with specific ratios of Ce3+/Ce4+ are created and extracted via controlled glass-melting parameters. Glass embedded with nanoceria as well as nanoceria extracted from the glass were studied via XANES and fitted with the Multivariate Curve Resolution (MCR) technique to calculate the ratio of Ce3+/Ce4+. Results show that mixed-valence nanoceria with specific ratios are hermetically sealed within the glass for long durations. When the glass dissolves, the mixed-valence nanoceria are released, and the extracted nanoceria have unchanged Ce3+/Ce4+ ratios. Furthermore, TEM investigation on released nanoceria show that the nanoceria consist of several different structures. Although nanocrystal structures of Ce7O12, Ce11O20, and Ce2O3 contribute to the reduced state, a new quasi-stable phase of CeO1.66 has been observed as well.

We report ferromagnetism in 2H-Co_{0.22}TaS_{2} single crystals where Co atoms are intercalated in the van der Waals gap, and a systematic study of its magnetic critical behavior in the vicinity of T_{c}∼28 K. The obtained critical exponents β=0.43(2), γ=1.15(1), and δ=3.54(1) fulfill the Widom scaling relation δ=1+γ/β and follow the scaling equation. This indicates that the spin coupling in 2H-Co_{0.22}TaS_{2} is of three-dimensional Heisenberg type coupled with long-range magnetic interaction, and that the exchange interaction decays with distance as J(r)≈r^{−4.69}. 2H-Co_{0.22}TaS_{2} exhibits a weak temperature-dependent metallic behavior in resistivity and negative values of thermopower with dominant electron-type carriers, in which obvious anomalies were observed below T_{c} as well as the anomalous Hall effect (AHE). The linear scaling behavior between the modified anomalous Hall resistivity ρ_{xy}/μ_{0}H and longitudinal resistivity ρ_{xx}^{2}M/μ_{0}H implies that the origin of the AHE in 2H-Co_{0.22}TaS_{2} should be dominated by the extrinsic side-jump mechanism.

The extent of reduction of unsupported iron-based high-temperature water-gas shift catalysts with small (

Rechargeable sodium-ion batteries with earth-abundant Fe/Mn based cathodes are a promising choice for grid-scale applications. However, the key candidate, P2-type Fe-based materials, suffers from severe voltage decay during battery operation due to Fe3+ migration to the neighboring tetrahedral sites. In this study, two Fe-based layered oxides, Na0.7[Cu0.15Fe0.3Mn0.55]O2 and Na0.7[Cu0.2Fe0.2Mn0.6]O2, were prepared. With a combination of in situ XRD, X-ray PDF, and hard and soft X-ray absorption, we demonstrate that the voltage decay in Fe-based layered oxides has dynamic origins. Drastic phase transition can be triggered by higher upper voltage limit, while partially irreversible Fe migration leads to voltage fading. With excess Cu doped into the crystal lattice, Fe migration can be considerably mitigated and therefore, structural stability can be maintained. Furthermore, Cu introduction brings about extra capacity via the correlation between transition metal elements and ligand oxygen, which may well compensate for capacity loss from inert impurity doping. Possible strategies for suppressing the detrimental voltage decay in battery cathodes can be proposed accordingly. [ABSTRACT FROM AUTHOR]