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At least 163 records · Page 9

AI-assisted discovery of high-temperature dielectrics for energy storage

Abstract Electrostatic capacitors play a crucial role as energy storage devices in modern electrical systems. Energy density, the figure of merit for electrostatic capacitors, is primarily determined by the choice of dielectric material. Most industry-grade polymer dielectrics are flexible polyolefins or rigid aromatics, possessing high energy density or high thermal stability, but not both. Here, we employ artificial intelligence (AI), established polymer chemistry, and molecular engineering to discover a suite of dielectrics in the polynorbornene and polyimide families. Many of the discovered dielectrics exhibit high thermal stability and high energy density over a broad temperature range. One such dielectric displays an energy density of 8.3 J cc −1 at 200 °C, a value 11 × that of any commercially available polymer dielectric at this temperature. We also evaluate pathways to further enhance the polynorbornene and polyimide families, enabling these capacitors to perform well in demanding applications (e.g., aerospace) while being environmentally sustainable. These findings expand the potential applications of electrostatic capacitors within the 85–200 °C temperature range, at which there is presently no good commercial solution. More broadly, this research demonstrates the impact of AI on chemical structure generation and property prediction, highlighting the potential for materials design advancement beyond electrostatic capacitors.

25 ENERGY STORAGE↗

A flexible and scalable scheme for mixing computed formation energies from different levels of theory

Abstract Computational materials discovery efforts are enabled by large databases of properties derived from high-throughput density functional theory (DFT), which now contain millions of calculations at the generalized gradient approximation (GGA) level of theory. It is now feasible to carry out high-throughput calculations using more accurate methods, such as meta-GGA DFT; however recomputing an entire database with a higher-fidelity method would not effectively leverage the enormous investment of computational resources embodied in existing (GGA) calculations. Instead, we propose here a general procedure by which higher-fidelity, low-coverage calculations (e.g., meta-GGA calculations for selected chemical systems) can be combined with lower-fidelity, high-coverage calculations (e.g., an existing database of GGA calculations) in a robust and scalable manner. We then use legacy PBE(+ U ) GGA calculations and new r 2 SCAN meta-GGA calculations from the Materials Project database to demonstrate that our scheme improves solid and aqueous phase stability predictions, and discuss practical considerations for its implementation.

36 MATERIALS SCIENCE↗

Multiscale modeling of metal-hydride interphases—quantification of decoupled chemo-mechanical energies

Abstract The quantification of interphase properties between metals and their corresponding hydrides is crucial for modeling the thermodynamics and kinetics of the hydrogenation processes in solid-state hydrogen storage materials. In particular, interphase boundary energies assume a pivotal role in determining the kinetics of nucleation, growth, and coarsening of hydrides, alongside accompanying morphological evolution during hydrogenation. The total interphase energy arises from both chemical bonding and mechanical strains in these solid-state systems. Since these contributions are usually coupled, it is challenging to distinguish via conventional computational approaches. Here, a comprehensive atomistic modeling methodology is developed to decouple chemical and mechanical energy contributions using first-principles calculations, of which feasibility is demonstrated by quantifying chemical and elastic strain energies of key interfaces within the FeTi metal-hydride system. Derived materials parameters are then employed for mesoscopic micromechanical analysis, predicting crystallographic orientations in line with experimental observations. The multiscale approach outlined verifies the importance of the chemo-mechanical interplay in the morphological evolution of growing hydride phases, and can be generalized to investigate other systems. In addition, it can streamline the design of atomistic models for the quantitative evaluation of interphase properties between dissimilar phases and allow for efficient predictions of their preferred phase boundary orientations.

36 MATERIALS SCIENCE↗

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy

Abstract The majority of computational catalyst design focuses on the screening of material components and alloy composition to optimize selectivity and activity for a given reaction. However, predicting the metastability of the alloy catalyst surface at realistic operating conditions requires an extensive sampling of possible surface reconstructions and their associated kinetic pathways. We present CatGym, a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions. We showcase our agent by predicting the surface reconstruction pathways of a ternary Ni 3 Pd 3 Au 2 (111) alloy catalyst. Our results show that the DRL agent can not only explore more diverse surface compositions than the conventional minima hopping method, but also generate the kinetic surface reconstruction pathways. We further demonstrate that the kinetic pathway to a global minimum energy surface composition and its associated transition state predicted by our agent is in good agreement with the minimum energy path predicted by nudged elastic band calculations.

36 MATERIALS SCIENCE↗

Mechanistic Studies of a Primitive Homolog of Nitrogenase Involved in Coenzyme F430 Biosynthesis

Methyl-coenzyme M reductase (MCR) is the key enzyme in the biological formation and anaerobic oxidation of methane (AOM). Methane is a potent greenhouse gas and the major component of natural gas. Given the abundance of natural gas reserves in remote areas, there is great current interest in a scalable bio-based process for the conversion of methane to liquid fuel or other high-value commodity chemicals. MCR holds much promise for use in such a methane bioconversion strategy. However, MCR cannot currently be produced in an active form in a heterologous host, due in large part to the lack of genetic and biochemical information about the production of holo MCR. In an effort to overcome this deficiency, our laboratory elucidated the biosynthetic pathway of the unique nickel-containing coenzyme of MCR, F430. The key step in coenzyme F430 biosynthesis (Cfb) was found to involve an unprecedented reductive cyclization reaction that converts Ni-sirohydrochlorin a , c -diamide to 15,17 3 -seco-F430-17 3 -acid. This remarkable transformation, which involves a 6-electron reduction of the isobacteriochlorin ring system, cyclization of the c -acetamide side chain to form a γ-lactam ring, and the formation of 7 stereocenters, is catalyzed by a primitive homolog of nitrogenase (CfbCD). Nitrogenase is a two-component metalloenzyme that catalyzes the ATP-dependent reduction of dinitrogen to ammonia (nitrogen fixation). Homologs of nitrogenase are also involved in the biosynthesis of the photosynthetic pigments chlorophyll and bacteriochlorophyll. Phylogenetic analysis of the CfbCD complex suggests that it is representative of a more ancient lineage of the nitrogenase superfamily, and a thorough investigation of its structure and function is likely to shed light on the mechanisms and evolution of these important metalloenzymes that catalyze multi-electron redox reactions. Moreover, a detailed understanding of the mechanism of the CfbCD complex may aid in the development of specific inhibitors to help reduce natural greenhouse gas emissions and can be exploited for the heterologous production of MCR for methane bioconversion. Towards these goals, the following Specific Aims will be pursued to determine the: 1) Identity of the CfbCD reaction product. The exact reaction catalyzed by CfbCD, including the number of electrons transferred and whether it involves enzymatic cyclization, is unclear. Several approaches, including reaction stoichiometry measurements, spectroelectrochemistry, and magnetic resonance spectroscopy will be applied to elucidate the structure of the reaction product and establish whether CfbCD is a reductase or reductive cyclase. 2) Structure, conformational dynamics, and oligomerization state changes of CfbCD. Significant insight into the mechanism and allosteric regulation of CfbCD can be obtained by assessing changes in the structure and dynamics of the complex during the catalytic cycle. To accomplish this, a combination of size-exclusion chromatography, hydrogen-deuterium exchange mass spectrometry, molecular dynamics simulations, and high-resolution structural methods will be employed. 3) Source, order, and stereochemistry of proton additions during CfbCD catalysis. Details regarding the order and stereochemistry of proton additions during the CfbCD reaction will be uncovered using a combined spectroscopic and computational approach. Complementary mechanistic studies employing site-directed mutagenesis and substrate analogs will establish the identity of active site acid residues and the possible involvement of substrate-assisted catalysis during the CfbCD reaction.

09 BIOMASS FUELS↗

A Solar Fuels Nexus: Molecules and Materials for Light-Driven Catalysis

The American Chemical Society (ACS) selects two groups of graduate students each year to plan and host a one-day symposium at each national meeting (both fall and spring).This year our Graduate Student Symposium Planning Committee (GSSPC), composed of seven students from four universities, proposal entitled “A Solar Fuels Nexus: Molecules and Materials for Light-Driven Catalysis” was selected for the “Crossroads in Chemistry” ACS Meeting that will take place March 23-26, 2023 in Indianapolis, IN. All members of our GSSPC are affiliated with the DOE Fuels from Sunlight Energy Innovation Hub, with two from the Liquid Sunlight Alliance (LiSA) and five from the Center for Hybrid Approaches in Solar Energy to Liquid Fuels (CHASE). Here we request funds to support this symposium. This symposium will highlight research progress and perspectives in the solar fuels generation field and seeks to advance the four priority research objectives (PROs) established by the Department of Energy’s Office of Basic Energy Sciences (DOE-BES) Roundtable Report that are also central to many research goals within LiSA and CHASE. The symposium will consist of research presentations from 10 invited senior researcher speakers on topics such as molecular catalyst design, computational modeling of electron transfer systems, microenvironmental effects on CO2 reduction and H2O oxidation catalysis, and intelligent design of semiconductor interfaces with ample time for discussions. These research topics fit very well with the Solar Photochemistry supported research areas of “light-driven electron and energy transfer in condensed phase and interfacial molecular systems,” “electrocatalysis and photocatalysis of solar fuels reactions,” and “semiconductor photoelectrochemistry.” More broadly, this symposium seeks to advance the DOE-BES’s mission to: “support fundamental research to understand, predict, and ultimately control matter and energy at the level of electrons, atoms, and molecules” by providing a diverse atmosphere where such research will be disseminated, discussed, and debated. There will be a strong focus on Diversity, Equity, and Inclusivity (DEI) in our symposium. Of our 10 speakers, 7 will be from underrepresented demographics in STEM, including 5 who identify as women. Furthermore, we have representatives from academia accompanied by one national lab scientist and one officer from the Office of Fossil Energy and Carbon Management at the DOE. All speakers will be holding a short DEI moment ahead of their talks. In order to support the career development of attending early career scientists, we will also be hosting a luncheon specifically for graduate students and postdocs to provide them opportunities to network with the distinguished speakers and other attendees. DOE funds for this symposium will be used to support the attendance and participation of 15 graduate students from US institutions by defraying travel and registration costs. These funds will promote engagement and conversation between early career scientists in the solar fuels field, while disseminating solar fuels research funded by and relevant to the DOE.

30 DIRECT ENERGY CONVERSION↗

Analytic Corrections to CFD Heating Predictions Accounting for Changes in Surface Catalysis

A new approach for combining the insight afforded by integral boundary-layer analysis with comprehensive (but time intensive) computational fluid dynamic (CFD) flowfield solutions of the thin-layer Navier-Stokes equations is described. The approach extracts CFD derived quantities at the wall and at the boundary layer edge for inclusion in a post-processing boundary-layer analysis. It allows a designer at a work-station to address two questions, given a single CFD solution. (1) How much does the heating change for a thermal protection system (TPS) with different catalytic properties than was used in the original CFD solution? (2) How does the heating change at the interface of two different TPS materials with an abrupt change in catalytic efficiency? The answer to the second question is particularly important, because abrupt changes from low to high catalytic efficiency can lead to localized increase in heating which exceeds the usually conservative estimate provided by a fully catalytic wall assumption. Capabilities of this approach for application to Reusable Launch Vehicle (RLV) design are demonstrated. If the definition of surface catalysis is uncertain early in the design process, results show that fully catalytic wall boundary conditions provide the best baseline for CFD design points.

Gnoffo, Peter A.↗

Site heterogeneity and broad surface-binding isotherms in modern catalysis: Building intuition beyond the Sabatier principle

Learning the science of heterogeneous catalysis and electrocatalysis always starts with the simple case of a flat, uniform surface with an ideal adsorbate. It has of course been recognized for a century that real catalysts are more complicated. For the increasingly complex catalysts of the 21st century, this Perspective argues that surface heterogeneity and non-ideal binding isotherms are central features, and their implications need to be incorporated in current thinking. A variety of systems are described herein where catalyst complexity leads to broad, non-Langmuirian surface isotherms for the binding of hydrogen atoms – and this occurs even for ideal, flat Pt(111) surfaces. Modern catalysis employs nanoscale materials whose surfaces have substantial step, edge, corner, impurity, and other defect sites, and they increasingly have both metallic and non-metallic elements M n X m , including metal oxides, chalcogenides, pnictides, carbides, doped carbons, etc. The surfaces of such catalysts are often not crystal facets of the bulk phase underneath, and they typically have a variety of potential active sites. Catalytic surfaces in operando are often non-stoichiometric, amorphous, dynamic, and impure, and often vary from one part of the surface to another. Understanding of the issues that arise at such nanoscale, multi-element catalysts is just beginning to emerge. Yet these catalysts are widely discussed using Brønsted/Bell-Evans-Polanyi (BEP) relations, volcano plots, Tafel slopes, the Butler-Volmer equation, and other linear free energy relations (LFERs), which all depend on the implicit assumption that the active sites are “similar” and that surface adsorption is close to ideal. These assumptions underly the ubiquitous intuition based on the Sabatier Principle, that the fastest catalysis will occur when key intermediates have free energies of adsorption that are not too strong nor too weak. Current catalysis research often aims to minimize the complexity of non-ideal isotherms through experimental and computational design (e.g., the use of single crystal surfaces), and these studies are the foundation of the field. In contrast, this Perspective argues that the heterogeneity of binding sites and binding energies is an inherent strength of these catalysts. Here, this diversity makes many nanoscale catalysts inherently a high-throughput screen wrapped in a tiny package. Only by making the heterogeneity part of the foundation of catalysis models, sorting the types of active sites and dissecting non-ideal binding isotherms, will modern catalysis learn to harness the inherent diversity of real catalysts. Controlling and exploiting diversity rather than avoiding it will help to optimize complex modern catalysts and catalytic conditions.

Mayer, James M.↗

Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson–Boltzmann continuum solvation methods with ab initio molecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. Additionally, we show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. Therefore, this work provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing CO 2 -Loaded Aqueous Amine Solutions for Higher Electrocatalytic CO 2 Reduction Activity

The activity of aqueous-based carbon dioxide reduction (CO 2 R) reactions is often limited by the solubility of CO 2 . The addition of amines can increase the total dissolved carbon in water through the formation of bicarbonate and carbamate species, which has been used to a great effect to capture CO 2 from dilute streams. Here, in this study, we explore the effect of 12 primary and secondary amines of varying Brønsted basicity, steric profile, and hydrogen-bonding capabilities on the aqueous CO 2 R to CO activity of a molecular Ni(cyclam)Cl 2 catalyst with a Hg electrode. Addition of some of the amines results in greater activity and selectivity for CO production compared to equivalent aqueous solutions without added amines. Under optimal conditions (0.4 M 3-amino-propionitrile), there is an over sevenfold increase in partial current density and greater selectivity for CO compared to equivalent conditions with no amine. Interestingly, the increase in activity did not correlate to any single property across the 12 amines. To elucidate the effect of the amine additives on catalysis, we used vapor–liquid equilibrium modeling (VLE), 13 C NMR spectroscopy, and computational analysis to determine the carbon speciation of the solutions. These results indicate that for amines without ethylalcohol functionalities, CO 2 R activity correlates with carbamate concentration, which is in turn governed by amine basicity and steric effects. However, this correlation does not persist for amines with ethylalcohol functionalities, which can form more stable carbamates through intramolecular-hydrogen bonding. These studies demonstrate that amine additives can enhance aqueous CO 2 R activity and selectivity and describe amine properties that lead to these higher performance metrics.

Amines↗

Nanoparticle self-assemblies with modern complexity

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

36 MATERIALS SCIENCE↗

Modeling of the HiPco process for carbon nanotube production. II. Reactor-scale analysis

The high-pressure carbon monoxide (HiPco) process, developed at Rice University, has been reported to produce single-walled carbon nanotubes from gas-phase reactions of iron carbonyl in carbon monoxide at high pressures (10-100 atm). Computational modeling is used here to develop an understanding of the HiPco process. A detailed kinetic model of the HiPco process that includes of the precursor, decomposition metal cluster formation and growth, and carbon nanotube growth was developed in the previous article (Part I). Decomposition of precursor molecules is necessary to initiate metal cluster formation. The metal clusters serve as catalysts for carbon nanotube growth. The diameter of metal clusters and number of atoms in these clusters are some of the essential information for predicting carbon nanotube formation and growth, which is then modeled by the Boudouard reaction with metal catalysts. Based on the detailed model simulations, a reduced kinetic model was also developed in Part I for use in reactor-scale flowfield calculations. Here this reduced kinetic model is integrated with a two-dimensional axisymmetric reactor flow model to predict reactor performance. Carbon nanotube growth is examined with respect to several process variables (peripheral jet temperature, reactor pressure, and Fe(CO)5 concentration) with the use of the axisymmetric model, and the computed results are compared with existing experimental data. The model yields most of the qualitative trends observed in the experiments and helps to understanding the fundamental processes in HiPco carbon nanotube production.

Validation Studies↗

Best practices in catalysis: A perspective

Catalysis, from its roots in petrochemical refining and conversion, has emerged as a transdisciplinary field that now encompasses synthesis of materials and molecules that enable applications in energy conversion and storage, environmental remediation, medicine, plastics, and fertilizer production, among numerous others. A handful of disciplines can claim relevance and success over such an extended period of time and continue to claim a preeminent role in defining the state-of-the-art in science and technology. Syncretic and rapid advancements in formulation and spectroscopic characterization of materials and molecules useful as catalysts, high-level density functional and molecular orbital theory calculations, and a strong foundation in concepts of physical chemistry, thermodynamics, and chemical kinetics offer new and abundant opportunities at the present day for addressing the grand challenge of controlling chemical transformations using catalysis. Here, we examine what we have learned of concepts that underpin heterogeneous catalysis but more importantly, how we learned to archive our knowledge in context of a set of best practices and standards that have emerged in the course of our learnings—ones we seek to highlight herein. Our perspective emphasizes concepts in synthesis, characterization, kinetics, and theory, because these four elements combined enable description of molecular acts that happen on surfaces and how fast they occur. In revisiting best practices in heterogeneous catalysis in these sub-fields and in authorship and peer review we aspire to augment clarity, reproducibility, and rigor in the science and practice of catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding dynamic properties of materials using neutron spectroscopy and atomistic simulation

Recent developments in first-principles lattice dynamics and classical force field based molecular dynamics are revolutionising the field of neutron spectroscopy. Herein we present a short review of these methods, their critical role in the supporting of cutting-edge experiments, and how they are improved by matching experimental data. We begin with a brief overview of how lattice dynamics calculations can be compared to inelastic neutron scattering (INS) and molecular dynamics simulations to both INS and quasi-elastic neutron scattering (QENS). We then provide a series of exemplar applications where lattice dynamics and molecular dynamics have been used in conjunction with neutron spectroscopy to bring significant understanding to topical areas of materials science namely: (i) lattice dynamics and INS for the study of hybrid organic-inorganic perovskites (ii) lattice dynamics and INS for the study of flexible porous solids and (iii) molecular dynamics and QENS for probing molecular behaviour in zeolite catalysis. In all three cases, the understanding gained through the synergy of experiment and computation would have been significantly reduced using either in isolation. Finally, we consider the current state of the art, describing outstanding challenges and suggesting future directions in this exciting and fertile area of physical science.

36 MATERIALS SCIENCE↗

Pd(II) and Rh(I) Catalytic Precursors for Arene Alkenylation: Comparative Evaluation of Reactivity and Mechanism Based on Experimental and Computational Studies

We combine experimental and computational investigations to compare and understand catalytic arene alkenylation using the Pd(II) and Rh(I) precursors Pd(OAc) 2 and [(η 2 -C 2 H 4 ) 2 Rh(µ-OAc)] 2 with arene, olefin and Cu(II) carboxylate at elevated temperature (> 120 °C). Under specific conditions, previous computational and experimental efforts have identified heterotrimetallic cyclic PdCu 2 (η 2 -C 2 H 4 ) 3 (μ-OPiv) 6 and [(η 2 -C 2 H 4 ) 2 Rh(µ-OPiv) 2 ] 2 (µ-Cu) (OPiv = pivalate) species as likely active catalysts for these processes. Further studies of catalyst speciation suggest a complicated equilibrium between Cu(II)-containing complexes containing one Rh or Pd atom with complexes containing two Rh or Pd atoms. At 120 °C, Rh catalysis produces styrene > 20-fold more rapidly than Pd. Also, at 120 °C, Rh is ~98% selective for styrene formation while Pd is ~82% selective. Furthermore, our studies indicate that Pd catalysis has a higher predilection toward olefin functionalization to form undesired vinyl ester, while Rh catalysis is more selective for arene/olefin coupling. However, at elevated temperatures, Pd converts vinyl ester and arene to vinyl arene, which is proposed to occur through low valent Pd(0) clusters that are formed in situ. Regardless of arene functionality, the regioselectivity for alkenylation of mono-substituted arenes with the Rh catalyst gives an approximate 2:1 meta:para ratio with minimal ortho C–H activation. In contrast, Pd selectivity is significantly influenced by arene electronics with electron-rich arenes giving an approximate 1:2:2 ortho:meta:para ratio while the electron deficient (α,α,α)-trifluorotoluene gives a 3:1 meta:para ratio with minimal ortho functionalization. Kinetic intermolecular arene ethenylation competition experiments find that Rh reacts most rapidly with benzene, and the rate of mono-substituted arene alkenylation does not correlate with arene electronics. In contrast, with Pd catalysis, electron-rich arenes react more rapidly than benzene while electron-deficient arenes react less rapidly than benzene. These experimental findings, in combination with computational results, are consistent with the arene C–H activation step for Pd catalysis involving significant η 1 -arenium character due to Pd-mediated electrophilic aromatic substitution character. In contrast, the mechanism for Rh catalysis is not sensitive to arene substituent electronics, which we propose indicates less electrophilic aromatic substitution character for the Rh-mediated arene C–H activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fe‐Triazolate Metal–Organic Frameworks as Water Oxidation Catalysts with Dual Photoanode Functionality

Artificial photosynthesis is an emerging technology that achieves renewable fuels, such as hydrogen, from sunlight. Its realization depends on finding highly active and stable catalysts of water splitting and photoactive materials for light absorption. To be scalable, these should contain only abundant elements. Here, for the first time, Fe-triazolate (Fe(ta) 2 ) and its metal substituted derivatives (Fe-Metal(ta) 2 ) Metal-organic frameworks (MOFs) are characterized as new dual-function materials for photo-absorption and water oxidation catalysis in acidic media. The materials were studied by a range of structural, spectroscopic, and computational density functional theory (DFT) techniques. Fe(ta) 2 and Fe-Mn(ta) 2 were found to be highly active and stable in chemical and photochemical water oxidation, and in addition function as photoanodes, with photo-electrocatalytic currents (∼2.00 x 10 −3 Acm −2 at + 1.4 V vs. Ag/AgCl) at pH = 1. The possibility of a unique catalytic mechanism where O─O bond formation is possible from the coupling of two adjacent Fe IV = O fragments was demonstrated by DFT analysis. Thus, Fe-triazolate MOF has been established as a new, stable, scalable, versatile, and efficient platform for sustainable energy conversion in the realm of artificial photosynthesis.

Artificial photosynthesis↗

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗