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At least 91 records · Page 5

Design and performance of AI agents interfacing with an atomic layer deposition tool

In this work, we introduce the design of an atomic layer deposition (ALD) reactor augmented with an AI interface for autonomous materials synthesis. Our modular design encapsulates the particularities of the hardware behind a Python interface that communicates with the ALD control software via transmission control protocol. This interface is compatible with model context protocol interfaces used in agentic frameworks. We have integrated our tool with a simple AI agent that leverages a large language model to transform user-supplied queries into ALD processes that are then run in our reactor. Our approach uses a JavaScript object notation schema to encode ALD processes. Our experimental results show that the AI interface does not impose a significant overhead to our control software, at least within our fastest 10 ms scale. We also carried out a detailed evaluation of the agent performance using leading models in two classes of tasks: basic instruction and process discovery tasks, where the agent is presented with a target material and needs to identify the correct ALD process compatible with the reactor configuration. Despite the simplicity of our agent design, we observed that most of the advanced models excelled at the instruction tasks. However, only recent models, such as o1, o3, GPT-5, and Claude Opus 4, performed well in process discovery tasks. We also observed significant variability in the response for the hardest challenges. While the results obtained are promising, we identify areas where AI research could improve the performance of agents for ALD.

47 OTHER INSTRUMENTATION↗

Boosting the Oxygen Evolution Reaction by Tuning the Interfacial Iron Adsorption on Layered Double Hydroxide

Understanding the interaction between ions in the electrolyte and electrode materials plays an important role in optimizing the water electrolysis performance for hydrogen production. Herein, the synergistic effect of iron (Fe) in the electrolyte and interlayer anions within the layered structure on the oxygen evolution reaction (OER) has been investigated by combining material synthesis with controlled structure, multiple characterization techniques, and first-principles calculations. Nickel aluminum layered double hydroxides (NiAl-LDHs) with different interlayer anions (CO 3 2– , Cl – , and Br – ) show similar oxygen evolution activity in the absence of Fe species in the electrolyte. The addition of Fe into the electrolyte results in improved performance for all of the NiAl-LDHs, following the rank LDH-Br > LDH-Cl > LDH-CO 3 , under all of the conditions with varied concentration of Fe. X-ray absorption spectroscopy and identical location electron microscopy analyses show that the LDH structure remains unchanged after the OER activity test, while in situ stationary probe rotating disk electrode inductively coupled plasma mass spectrometry (SPRDE-ICP-MS) measurements show partial dissolution of the intercalating halide ions during cycling, with less dissolution for Br-intercalated materials. Insights from theoretical calculations demonstrate the thermodynamic preference of Br – to remain intercalated in the presence of Fe, while the stronger adsorption of Fe(OH) 3 species on the LDH-Br sample promotes the OER activity. In conclusion, these results provide mechanistic insights into the rational design of active layered materials with an enhanced OER performance for efficient water electrolysis.

58 GEOSCIENCES↗

In-Situ Atomic-Scale Revelation of Amorphous Metallic Iron Formation during Hydrogen-Driven Reduction of Iron Oxides

The transition to hydrogen as a green reductant in metal production is critical for decarbonizing the metallurgical industry, yet atomic-scale mechanisms governing reduction pathways and phase evolution remain unresolved. Using in-situ environmental transmission electron microscopy, we identify a hidden pathway that reveals dynamic formation of amorphous metallic iron (Fe) during the hydrogen-driven reduction of ferrous oxides of Fe 3 O 4 and FeO. Real-time imaging uncovers three coexisting transformation routes: (i) Fe 3 O 4 → FeO, (ii) Fe 3 O 4 → amorphous Fe, and (iii) FeO → amorphous Fe. The resulting amorphous Fe exhibits fluid-like mobility, enabling its rapid aggregation and crystallization into core-shell nanostructures, with a crystalline core enveloped by an amorphous shell. Complementary ab initio molecular dynamics simulations trace the amorphous Fe formation to interfacial strain at the metal/oxide interfaces, where large lattice mismatches destabilize the metal lattice during initial metallization. This interplay between thermodynamics and kinetics governs phase evolution: thermodynamics favors a self-limiting amorphous Fe overlayer, while rapid oxide reduction kinetics drives amorphous overgrowth. Our findings demonstrate that amorphous intermediates bypass rate-limiting crystalline steps, providing mechanistic insights to optimize H 2 -based processes for sustainable steelmaking. In conclusion, these insights bridge the gap between macroscopic process engineering and atomic-scale dynamics, with broader implications for catalysis and nanostructured material synthesis, where oxide reduction pathways critically shape functional phases and microstructures.

36 MATERIALS SCIENCE↗

Multifunctional Catalysts for the Tandem Reactions of Oxygenates

Industrially-relevant catalytic reactions rarely consist of a simple sequence of elementary steps. Moreover, kinetic coupling of multiple reactions on a catalyst surface is highly desired for process intensification and improved energy efficiency for large scale chemical transformations. The shifting landscape of hydrocarbon chemical feedstocks in the US also motivates research on the selective conversion of more complex molecules. One desirable type of catalytic reaction is the reduction of carboxylic acids that are produced from biomass feedstocks to their corresponding alcohols. The proposed research explores the fundamental importance of hydrogen spillover on a multifunctional catalyst for carboxylic acid reduction with H 2 composed of metal particles coupled to metal oxide particles. Recent work has demonstrated the excellent performance of supported tungsten oxide clusters for carboxylic acid reduction, but only after they are promoted with a late transition metal such as palladium. Elucidating the active state of the catalyst and the associated reaction mechanism for acid reduction on that active state are the overall goals of the proposed project and successful completion will enable future design of efficient multifunctional catalysts. The critically important role of the metal promoter is hypothesized to be its ability to dissociate H2 and spillover atomic H to the support. Although hydrogen spillover is a well-recognized phenomenon in catalysis, its role in both catalyst activation and catalytic turnover are still unresolved. The study combined materials synthesis, characterization, reactivity testing, and molecular simulations, to explore the effect of hydrogen chemical potential on the formation of the active catalytic sites and on the steady state catalytic reduction of carboxylic acid. Varying the hydrogen chemical potential through modification of the gas conditions, support composition, and metal loading to modulated the structure and catalytic performance of the reducible metal oxide. Dual function catalysts containing supported Pd and WO x species co-located on a non-reducible carrier (silica) and a reducible carrier (titania) were synthesized and characterized by electron microscopy, temperature-programmed reduction, and chemisorption. Spectroscopic methods such as X-ray absorption and UV-vis were also used to evaluate the catalysts, which were used in the reduction of propionic acid to aldehyde and alcohol. Quantum chemical calculations, including ab initio phase diagrams provided molecular insights into the H spillover phenomenon.

09 BIOMASS FUELS↗

Next-generation tunnel FETs: exploring material perspectives and areal tunneling configurations

The end of Dennard scaling, which facilitated proportional increases in computing power without added energy costs until the mid-2000s, has underscored the urgent need for innovative semiconductor devices that can enhance energy efficiency. Tunnel field-effect transistors (TFETs) have emerged as promising candidates to surpass the energy efficiency of conventional metal oxide semiconductor field-effect transistors (MOSFETs). Unlike MOSFETs, which rely on thermionic emission to overcome the source-channel potential barrier, TFETs operate through quantum tunneling, potentially enabling sub-60 mV dec −1 subthreshold swing (SS) for low-voltage operation. However, lateral TFETs have faced challenges in achieving adequate on-state current (I ON ) and a broad SS operation window, limiting their practical utility. This review article advocates for areal TFETs, which utilize face-to-face tunnel junctions that ideally offer step-function current turn-on characteristics and allow I ON to scale with device area rather than width. We highlight recent advancements in integrating 2D materials into tunneling structures, which could facilitate efficient band-to-band tunneling through atomically thin layers, while addressing challenges of gate field screening. We then discuss the nearer-term prospects of epitaxial areal TFETs comprising III–V compound semiconductors and group-IV semiconductors based on recent experimental progress. The review examines both quantum mechanical and semiclassical modeling approaches for TFETs, including techniques to reduce the computational complexity. The article delves into ongoing challenges in material synthesis, interface engineering, device fabrication, and integration pathways, concluding with recommendations for future research directions to overcome the fundamental power density limitations of conventional transistor technology.

2D materials↗

Epitaxial Metal Electrodeposition Controlled by Graphene Layer Thickness

Control over material structure and morphology during electrodeposition is necessary for material synthesis and energy applications. One approach to guide crystallite formation is to take advantage of epitaxy on a current collector to facilitate crystallographic control. Single-layer graphene on metal foils can promote “remote epitaxy” during Cu and Zn electrodeposition, resulting in growth of metal that is crystallographically aligned to the substrate beneath graphene. However, the substrate–graphene–deposit interactions that allow for epitaxial electrodeposition are not well understood. Here, we investigate how different graphene layer thicknesses (monolayer, bilayer, trilayer, and graphite) influence the electrodeposition of Zn and Cu. Scanning transmission electron microscopy and electron backscatter diffraction are leveraged to understand metal morphology and structure, demonstrating that remote epitaxy occurs on mono- and bilayer graphene but not trilayer or thicker. Density functional theory (DFT) simulations reveal the spatial electronic interactions through thin graphene that promote remote epitaxy. This work advances our understanding of electrochemical remote epitaxy and provides strategies for improving control over electrodeposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mesocrystal growth through oriented sliding and attachment of nanoplates

Oriented attachment is a critical, yet poorly understood, crystal growth pathway based on the self-assembly of nanocrystals. During oriented attachment, solvent-separated particles align and coalesce through forces that enable precise rotation and translation. While prior studies emphasized intragap forces driving crystallographic alignment, the forces enabling uniform stacking and superlattice formation remain unclear. Here, we demonstrate how macroscopic gibbsite mesocrystals emerge from nanoplates guided into staggered positions by directional sliding. Electron microscopy and X-ray scattering reveal the monoclinic superlattice structure, based on nanoplate stacking with a uniform ≈50° stagger along the gibbsite [010] direction. In situ liquid-cell TEM captures preferential sliding along the gibbsite [010] direction, decelerating with increasing particle overlap. Molecular dynamics simulations reveal that this staggered arrangement corresponds to a global free-energy minimum, rather than full alignment. The simulations also confirm that sliding along the [010] direction is energetically favored and provide insight into the role of interfacial water in achieving long-range ordered assemblies. These insights highlight the energy landscape’s role in oriented attachment, with implications for material synthesis and hierarchical structures in nature.

36 MATERIALS SCIENCE↗

Selective Electrochemical Reduction of CO 2 to Metal Oxalates in Nonaqueous Solutions Using Trace Metal Pb on Carbon Supports Enhanced by a Tailored Microenvironment

In this work, the electroreduction of carbon dioxide (CO 2 ) to oxalate is enabled by incorporating trace metallic lead (Pb) on carbon‐based supports (CBS) with polymer overlayers. These composite materials serve as an efficient electrocatalytic system for the facile conversion and storage of CO 2 , a pernicious atmospheric pollutant. Results from controlled potential electrolysis experiments indicate that 1) trace metallic Pb on the ppb scale is active toward the reductive coupling of CO 2 to oxalate at comparable Faradaic efficiencies to bulk metallic Pb and 2) polymer encapsulation of this trace metallic Pb leads to promotion of CO 2 reduction (CO 2 R) selectively to metal oxalates over other products such as CO. Importantly, metal oxalates are important alternative cementitious materials and precursors for other materials’ synthesis applications. The solid products undergo rigorous spectroscopic characterization, including 13 CO 2 labeling experiments, to ensure the metal oxalates are in fact produced from CO 2 R. These findings serve as a model for leveraging microenvironment effects to enhance activity and selectivity for CO 2 R using trace‐metal catalysts for carbon utilization and storage technologies.

alternative cementitious materials↗

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗

Real-Time Atomic-Scale Structural Analysis Resolves the Amorphous to Crystalline CaCO 3 Mechanism Controversy

Amorphous calcium carbonate (ACC) occurs as a precursor to geological and biogenic calcium carbonate (CaCO 3 ), yet its transformation pathways and reaction mechanisms remain inconsistent and controversial. In this study, we investigated the transformation of ACC to calcite under both solution and dry conditions, in the presence and absence of impurity ions, utilizing operando time-resolved synchrotron X-ray diffraction (TRXRD) and reactive transport modeling. Results demonstrate that TRXRD techniques allow us to differentiate dissolution-reprecipitation versus solid-state transformation mechanisms for amorphous to crystalline phase transitions. Specifically, we observe that in environments with abundant water, ACC transforms to calcite through a dissolution-reprecipitation mechanism. This features an activation energy of 63 ± 2 kJ/mol and unit cell volume contraction during calcite crystal growth. Conversely, under water-limited conditions, ACC to calcite transformation proceeds via a solid-state transformation mechanism, with an activation energy of 210 ± 2 kJ/mol, three times greater than the dissolution-reprecipitation route, and a unit cell expansion during crystalline calcite growth. Further, to illustrate the magnitude of these effects, the rates of calcite growth were similar during dissolution-reprecipitation at 3 °C [0.00207(35) s –1 ] and solid-state transformation at 280 °C [0.00134(11) s –1 ]. Moreover, the incorporation of an impurity, strontium, significantly retards the rate of calcite growth while expanding its unit cell but whose incorporation is history dependent. Reactive transport modeling of the dissolution–precipitation kinetics suggests that ACC must be dissolving as compact aggregates. These various transformation mechanisms drive diverse geological and biological carbonate formations, impacting their use as paleoenvironmental markers and functional materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unusual Li 2 O sublimation promotes single-crystal growth and sintering

Li 2 O is rarely used for cathode material synthesis due to its high melting point (1,438 °C). Here we discover that Li 2 O can sublimate at 800-1,000 °C under ambient pressure, opening new possibilities for cathode synthesis. We propose a mechanism that enables synthesis of single crystals-such as LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) or LiNi 0.9 Mn 0.05 Co 0.05 O 2 (NMC90)-without direct contact with Li 2 O salts. We show that Li 2 O vapour successfully converts spent polycrystalline NMC811 into segregated single crystals without milling or post-treatment. The Li 2 O vapour, derived from Li 2 O solids, diffuses rapidly and reacts with precursors, mimicking a molten-salt environment, which facilitates single-crystal growth. The chemical lithiation process continuously drives Li 2 O sublimation, sintering the crystals. Single crystals derived from Li 2 O and fresh precursors or spent polycrystals exhibit outstanding cycling after 1,000 cycles in full cells. The demonstrated Li 2 O sublimation and its universal role in promoting single-crystal growth provides an effective approach for single-crystal synthesis, scale-up and recycling.

25 ENERGY STORAGE↗

A multimodal large language model for materials science

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.

Tang, Yingheng [Lawrence Berkeley National Laborat↗

K–Co–Mo–S x chalcogel: high-capacity removal of Pb 2+ and Ag + and the underlying mechanisms

Chalcogenide-based aerogels, known as chalcogels, represent a novel class of nanoparticle-based porous amorphous materials characterized by high surface polarizability and Lewis base properties, exhibiting promising applications in clean energy and separation science. This work presents a K–Co–Mo–S x (KCMS) chalcogel as a highly efficient sorbent for heavy metal ions and details its sorption mechanisms. Its incoherent structure comprises Mo 2 V (S 2 ) 6 and Mo 3 IV S(S 6 ) 2 anion-like clusters with four- and six-coordinated Co–S polyhedra, forming a Co–Mo–S covalent network that hosts K + ions through electrostatic attraction. The interactions of KCMS with heavy metal ions, particularly Pb 2+ and Ag + , reveal that KCMS is exceptionally effective in removing these ions from ppm concentrations down to trace levels (≤5 ppb). KCMS rapidly removes Ag + (≈81.7%) and Pb 2+ (≈99.5%) within five minutes, achieving >99.9% removal within an hour, with a distribution constant K d ≥10 8 mL g -1 . KCMS exhibits an impressive removal capacity of 1378 mg g -1 for Ag + and 1146 mg g -1 for Pb 2+ , establishing it as one of the most effective materials known to date for heavy metal removal. This material is also effective for the removal of Ag + and Pb 2+ along with Hg 2+ , Ni 2+ , Cu 2+ , and Cd 2+ from various water sources even in the presence of highly concentrated and chemically diverse cations, anions, and organic species. Analysis of the post-interacted KCMS by synchrotron X-ray pair distribution function (PDF), X-ray photoelectron spectroscopy (XPS) and energy dispersive X-ray spectroscopy (EDS) revealed that the sorption of Pb 2+ , Ag + , and Hg 2+ mainly occurs by the exchange of K + and Co 2+ . Despite being amorphous, this material exhibits unprecedented ion-exchange mechanisms both for the ionically and covalently bound K + and Co 2+ , respectively. In conclusion, this discovery advances our knowledge of amorphous gels and guides material synthesis principles for the highly selective and efficient removal of heavy metal ions from water.

54 ENVIRONMENTAL SCIENCES↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter (WDM) physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the WDM physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations & experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments of and contemporary challenges for theoretical methods and experimental techniques needed to describe, create and diagnose WDM. A large part of this roadmap is dedicated to specific WDM systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

dense astrophysical objects↗

Synergizing human expertise and AI efficiency with language model for microscopy operation and automated experiment design

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

97 MATHEMATICS AND COMPUTING↗

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Toward the origins of binding energy shifts and “satellites” formation during plasma-XPS measurements

In-plasma x-ray photoelectron spectroscopy (plasma-XPS) emerges as a powerful platform for real-time, in situ chemical analysis under conditions relevant to semiconductor processing and other plasma-enabled technologies. This study investigates the origins of binding energy (BE) shifts and the formation of “satellite” peaks observed during plasma-XPS measurements across conductive, dielectric, and gas-phase systems. Using a standard laboratory-based ambient pressure XPS apparatus coupled with an alternating current (AC)-driven capacitively coupled plasma source, we demonstrate that metastable surface species, such as transient Au oxides, can be detected during plasma exposure, revealing chemical states that are hardly accessible using conventional ultrahigh vacuum (UHV) XPS. In dielectric samples (e.g., undoped diamond, sapphire), we observe pressure- and plasma-type-dependent BE shifts of more than 50 eV, attributed to x-ray-induced and plasma-mediated surface charging. These shifts are mitigated at higher pressures/plasmas or in electronegative plasmas (e.g., O 2 ), the latter due to enhanced charge compensation mechanisms involving slow negative ions. For gas-phase species, AC-plasma excitation leads to spectral broadening and the emergence of “satellite” peaks with energy separations of a few electron volts, linked to oscillating local plasma potentials in the probing volume. Furthermore, these findings highlight the complex and important interplay between plasma parameters, surface charging, and local electric fields in shaping XPS spectra. Overall, plasma-XPS emerges as a critical metrological tool for probing transient surface chemistry, with implications for semiconductor processing, material synthesis, and plasma diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic and Mechanistic Understanding of Boron-Containing Catalysts for the Production of Light Olefins through Selective Oxidation

In recent years, an abundance of natural gas obtained from shale deposits has created opportunities for the US chemical industry to establish new and more efficient processes for the production of chemical intermediates and polymers. For example, the replacement of petroleum-derived naphtha as a to shale-derived ethane as feedstocks has made the production of ethylene/polyethylene less costly. However, this shift in feedstock has led to lower production of propylene from steam crackers, and new “on-purpose” light olefin production technologies have been implemented to bridge the gap between propylene supply and demand. The most important of these processes is direct propane dehydrogenation (PDH), but catalyst deactivation and high temperatures lead to high capital and operating costs. Oxidative dehydrogenation of propane (ODHP) is an efficient alternative to PDH, but high selectivity to CO2 from previous metal oxide catalyst prevents implementation. Hexagonal boron nitride (hBN) and other boron-containing materials have been recently developed as highly selective catalysts for both ODHP and oxidative cracking, surpassing previous systems. Much is still unknown in regard to the mechanism and the dynamic surface changes that occur under reaction conditions. This research project aims to combine in situ/operando spectroscopic investigation and kinetic studies to elucidate the interplay between the proposed gas-phase mechanism and the surface structures on the working catalyst. These insights will be leveraged to create a framework for optimizing reaction conditions and material synthesis for the next generation of boron-containing selective oxidation catalysts.

02 PETROLEUM↗