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DOE OSTI2024

Invariant Molecular Representations for Heterogeneous Catalysis

Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used. This study introduces a novel machine learning (ML) method to learn adsorption energies from multiple DFT functionals by using invariant molecular representations (IMRs). To do this, we first extract molecular fingerprints for the reaction intermediates and later use a Siamese-neural-network-based training strategy to learn invariant molecular representations or the IMR across all available functionals. Our Siamese network-based representations demonstrate superior performance in predicting adsorption energies compared with other molecular representations. Notably, when considering mean absolute values of adsorption energies as 0.43 eV (PBE-D3), 0.46 eV (BEEF-vdW), 0.81 eV (RPBE), and 0.37 eV (scan+rVV10), our IMR method has achieved the lowest mean absolute errors (MAEs) of 0.18 0.10, 0.16, and 0.18 eV, respectively. These results emphasize the superior predictive capacity of our Siamese network-based representations. The empirical findings in this study illuminate the efficacy, robustness, and dependability of our proposed ML paradigm in predicting adsorption energies, specifically for propane dehydrogenation on a platinum catalyst surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Molecular approaches to heterogeneous catalysis

Not Available

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Oxidation of Ammonia Catalyzed by a Molecular Iron Complex: Translating Chemical Catalysis to Mediated Electrocatalysis

Abstract Ammonia is a promising candidate in the quest for sustainable, clean energy. With its capacity to serve as an energy carrier, the oxidation of ammonia opens avenues for carbon‐neutral approaches to address worldwide growing energy needs. We report the catalytic chemical oxidation of ammonia by an Earth‐abundant transition metal complex, trans ‐ [LFe II (MeCN) 2 ][PF 6 ] 2 , where L is a macrocyclic ligand bearing four N ‐heterocyclic carbene (NHC) donors. Using triarylaminium radical cations in MeCN, up to 182 turnovers of N 2 per Fe were obtained from chemical catalysis with an extremely low loading of the Fe catalyst (0.043 mM, 0.004 mol % catalyst). This chemical catalysis was successfully transitioned to mediated electrocatalysis for the oxidation of ammonia. Molecular electrocatalysis by the Fe catalyst and the mediator ( p ‐MeOC 6 H 4 ) 3 N exhibited a catalytic half‐wave potential ( E cat/2 ) of 0.18 V vs [Cp 2 Fe] +/0 in MeCN, and achieved 9.3 turnovers of N 2 at an applied potential of 0.20 V vs [Cp 2 Fe] +/0 at −20 °C in controlled‐potential electrolysis, with a Faradaic efficiency of 75 %. Based on computational results, the catalyst undergoes sequential oxidation and deprotonation steps to form [LFe IV (NH 2 ) 2 ] 2+ , and thereafter bimetallic coupling to form an N−N bond.

Liu, Liang↗

DOE OSTI2024

Oxidation of Ammonia Catalyzed by a Molecular Iron Complex: Translating Chemical Catalysis to Mediated Electrocatalysis

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Compartmentalisation of molecular catalysts for nonorthogonal tandem catalysis

The development of nonorthogonal tandem catalysis enables the use of a combination of arbitrary catalysts to rapidly synthesize complex products in a substainable, efficient, and timely manner. The key is to compartmentalise the molecular catalysts, thereby overcoming inherent incompatibilities between individual catalysts or reaction conditions. This tutorial review analyses the development of the past two decades in the field of nonorthogonal tandem catalysis with an emphasis on compartmentalisation strategies. Here, we highlight design principles of functional materials for compartmentalisation and suggest future directions in the field of nonorthogonal tandem catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Energy catalysis needs ligands with high oxidative stability

Replacing fossil fuel-based energy by renewable sources is a transition that society needs to make to meet future energy demand and simultaneously address climate change. Coupling renewable energy sources with electrochemical catalysis provides a promising path to carbon-neutral fuels and chemicals when the necessary reducing equivalents and protons are harvested from water. Developing highly active, stable, and inexpensive electrocatalysts for the oxygen evolution reaction (OER) is accordingly a centerpiece of a renewable energy portfolio. Whereas viable OER catalysts are heterogeneous in nature, owing to their oxidative stability, the realization of stable molecular OER catalysts greatly expands the horizon of energy science with the ability to tune OER energetics and mechanisms with fidelity. In this perspective, current challenges in the field of molecular OER catalysis are addressed with promising lines of research that are directed to designing ligands that can withstand the harsh oxidizing environment of OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

On the integration of molecular dynamics, data science, and experiments for studying solvent effects on catalysis

Computational workflows that combine molecular dynamics (MD) simulations and emerging data-centric (DC) methods can accelerate the screening and analysis of solvent systems experimentally and computationally. Here, MD simulations provide atomic positions and velocities of reactant, solvent, and catalyst materials that can be manipulated into data representations that in turn can be used by DC techniques to conduct predictive modeling, feature extraction, and experimental design. For liquid-phase catalytic applications, emerging DC techniques such as Convolutional and Graph Neural Networks (CNN/GNN), Topological Data Analysis (TDA), and Active Learning (AL) can leverage MD and experimental data to quickly predict solvent effects on reaction outcomes. For instance, in recent studies, 3D solvent environments obtained with MD have been exploited by CNNs to predict experimental reaction rates for homogeneous acid-catalyzed lignocellulosic processes. In this perspective, we discuss basic principles of DC methods and how these can be combined with MD to enable high-throughput screening of solvent selection for diverse catalysis applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Porosity as a Design Element for Developing Catalytic Molecular Materials for Electrochemical and Photochemical Carbon Dioxide Reduction

The catalytic reduction of carbon dioxide (CO 2 ) using sustainable energy inputs is a promising strategy for upcycling of atmospheric carbon into value-added chemical products. This goal has inspired the development of catalysts for selective and efficient CO 2 conversion using electrochemical and photochemical methods. Among the diverse array of catalyst systems designed for this purpose, two- and three-dimensional platforms that feature porosity offer the potential to combine carbon capture and conversion. Included are covalent organic frameworks (COFs), metal-organic frameworks (MOFs), porous molecular cages, and other hybrid molecular materials developed to increase active site exposure, stability, and water compatibility while maintaining precise molecular tunability. This mini-review showcases catalysts for the CO 2 reduction reaction (CO 2 RR) that incorporate well-defined molecular elements integrated into porous materials structures. Selected examples provide insights into how different approaches to this overall design strategy can augment their electrocatalytic and/or photocatalytic CO 2 reduction activity. This article is protected by copyright. All rights reserved.

36 MATERIALS SCIENCE↗

DOE OSTI2022

1 H chemical shift anisotropy: a high sensitivity solid-state NMR dynamics probe for surface studies?

We report dynamics play significant roles in chemistry and biochemistry-molecular motions impact both large- and small-scale chemical reactions in addition to biochemical processes. In many systems, including heterogeneous catalysts, the characterization of dynamics remains a challenge. The most common approaches involve the solid-state NMR measurement of anisotropic interactions, in particular 2 H quadrupolar coupling and 1 H–X dipolar coupling, which generally require isotope enrichment. Due to the high sensitivity of 1 H NMR, 1 H chemical shift anisotropy (CSA) is a particularly enticing, and underexplored, dynamics probe. We carried out 1 H CSA and 1 H– 13 C dipolar coupling measurements in a series of model supported complexes to understand how 1 H CSA can be leveraged to gain dynamic information for heterogeneous catalysts. Mathematical descriptions are given for the dynamic averaging of the CSA tensor, and its dependence on orientation and asymmetry. The variability of the orientation of the tensor in the molecular frame, in addition to its magnitude and asymmetry, negatively impacts attempts to extract quantitative dynamic information. Nevertheless, 1 H CSA measurements can reveal useful qualitative insights into the motions of a particularly dilute site, such as from a surface species.

1H chemical shift anisotropy↗

DOE OSTI2026

Frontiers in divalent $f$-block chemistry

Divalent f-block chemistry has undergone rapid expansion in recent years, driven by advances in the stabilization of low-valent lanthanide and actinide complexes. Although f-elements were historically accessed in the +3 or higher oxidation states, the isolation of +2 species has revealed unusual spectroscopic signatures, distinct bonding motifs, and multiple accessible electronic configurations that influence their chemical and physical properties. These developments have generated opportunities in areas including quantum information science, molecular magnetism, catalysis, and luminescence. Computational chemistry has played a pivotal role in interpreting the electronic structure and reactivity of these systems. However, accurately modeling divalent f-block complexes remains challenging because of strong electronic correlation, multiconfigurational character, and the presence of close-in-energy competing electronic states. As experimental capabilities and theoretical methodologies continue to advance, a comprehensive assessment of divalent chemistry is both timely and needed. In this Review, we integrate experimental and theoretical perspectives to provide a systematic analysis of divalent lanthanide and actinide complexes across the f-block series. We critically assess the role of ligands in determining competing ground-state configurations (f n d 1 vs. f n+1 ) resulting in their distinct spectroscopic, magnetic, and bonding properties. Finally, we discuss emerging strategies for predictive modeling and rational design of low-valent f-block molecular systems, with potential applications ranging from dinitrogen reduction to quantum technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Heterogenized Pyridine-Substituted Cobalt(II) Phthalocyanine Yields Reduction of CO2 by Tuning the Electron Affinity of the Co Center

Conversion of CO 2 to reduced products is a promising route to alleviate irreversible climate change. In this paper we report the synthesis of a Co-based phthalocyanine with pyridine moieties (CoPc-Pyr), which is supported on a carbon electrode and shows Faradaic efficiency ~90% for CO at 490 mV of overpotential (-0.6 V vs reversible hydrogen electrode (RHE)). In addition, its catalytic activity at -0.7 V versus RHE surpasses other Co-based molecular and metal-organic framework catalysts for CO 2 reduction at this bias. Density functional theory calculations show that pyridine moieties enhance CO 2 adsorption and electron affinity of the Co center by an inductive effect, thus lowering the overpotential necessary for CO 2 conversion. Our study shows that CoPc-Pyr reduces CO 2 at lower overpotential and with higher activity than noble metal electrodes, such as silver.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Confinement effects and acid strength in zeolites

Chemical reactivity and sorption in zeolites are coupled to confinement and—to a lesser extent—to the acid strength of Brønsted acid sites (BAS). In presence of water the zeolite Brønsted acid sites eventually convert into hydronium ions. The gradual transition from zeolite Brønsted acid sites to hydronium ions in zeolites of varying pore size is examined by ab initio molecular dynamics combined with enhanced sampling based on Well-Tempered Metadynamics and a recently developed set of collective variables. While at low water content (1–2 water/BAS) the acidic protons prefer to be shared between zeolites and water, higher water contents (n > 2) invariably lead to solvation of the protons within a localized water cluster adjacent to the BAS. At low water loadings the standard free energy of the formed complexes is dominated by enthalpy and is associated with the acid strength of the BAS and the space around the site. Conversely, the entropy increases linearly with the concentration of waters in the pores, favors proton solvation and is independent of the pore size/shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Confinement of Lewis Acid–Base Sites by Microporous Silica Layers on Titania for Enhanced Alkanol Dehydration Reactivity

Alkanol dehydration offers a pathway to upgrade biomass-derived short-chain oxygenates into alkenes, essential chemical building blocks widely used in industrial applications. Transition metal oxides with Lewis acid-base site pairs are attractive catalysts due to their high reactivity and cost-effectiveness. This work demonstrates a synthetic pathway to manipulate local environments around active Lewis acid-base pairs in anatase TiO 2 to enhance their reactivity in alkanol dehydration. Microporous SiO 2 layers with an average pore diameter of ~0.6 nm and a controlled thickness of 0.8-33 nm are deposited on anatase TiO 2 powders by using a molecular templated SiO 2 deposition method. The Lewis acid-base strength of accessible Ti-O pairs remains unchanged, as shown by temperature-programmed surface reactions of surface-bound formic acid-derived species and temperature-programmed desorption of pyridine. However, measured alkanol dehydration rates on confined Ti-O pairs are much higher (by up to 7-fold) than those on TiO 2 . The extent of rate enhancements depends on the reactant size and functional group positioning, suggesting that the rate enhancements reflect the interactions between the guest molecules (reactants and transition states) and the surrounding SiO 2 micropore environments. By providing a detailed synthetic procedure to tailor the local environments around active sites in bulk oxides, this approach offers an additional avenue for enhancing catalytic performance.

09 BIOMASS FUELS↗

DOE OSTI2025

Rigid Supramolecular Aramid Nanotubes as Catalyst Supports

Solution‐phase heterogeneous catalysts benefit from nanoscale dimensions, which maximize specific surface area and enhance catalytic activity. However, the ease of recovering such nanocatalysts depends on the design of the support materials, which are often particle‐like. Rigid 1D nanomaterials are proposed as supports that can enhance separability while offering high volumetric specific surface area for greater catalyst loading and activity. Here, aramid amphiphiles (AAs) are designed to spontaneously self‐assemble in water into high‐aspect‐ratio supramolecular nanotubes with tunable surface chemistry. These AA nanotubes exhibit high persistence lengths (P = 750 ± 340 µm) and mechanical stiffnesses (3 N/m). Incorporating surface thiol groups enables immobilization of catalytic gold nanoparticles. The resulting AA nanotube‐gold nanoparticle complexes exhibit high catalytic activity, efficient recoverability via simple microfiltration, and sustained reusability over ten reaction cycles. This study demonstrates the utility of molecular self‐assembled 1D nanomaterials as versatile scaffolds for the reuse and recovery of nanoscale catalysts.

1D nanomaterials↗

DOE OSTI2020

Does Selectivity of Molecular Catalysts Change with Time? Polymerization Imaged by Single-Molecule Spectroscopy

The chemoselectivity of molecular catalysts underpins much of modern synthetic organic chemistry. However, little is known about the selectivity of individual catalysts because this single-catalyst-level behavior is hidden by the bulk catalytic behavior. In this work, for the first time, the selectivity of individual molecular catalysts for two different reactions is imaged in real time at the single-catalyst level. This imaging is achieved through fluorescence microscopy paired with spectral probes that produce a snapshot of the instantaneous chemoselectivity of a single catalyst for either a single-chain-elongation or a single-chain-termination event during ruthenium-catalyzed polymerization. Superresolution imaging of multiple selectivity events, each at a different single-molecular ruthenium catalyst, indicates that catalyst selectivity may be unexpectedly spatially and time-variable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Cylindrical C 96 Fullertubes: A Highly Active Metal-Free O 2 -Reduction Electrocatalyst

A new isolation protocol was recently reported for highly purified metallic Fullertubes D 5h -C 90 , D 3d -C 96 , and D 5d -C 100 , which exhibit unique electronic features. Here, we report the oxygen reduction electrocatalytic behavior of C 60 , C 70 (spheroidal fullerenes), and C 90 , C 96 , and C 100 (tubular fullerenes) using a combination of experimental and theoretical approaches. C 96 (a metal-free catalyst) displayed remarkable oxygen reduction reaction (ORR) activity, with an onset potential of 0.85 V and a halfway potential of 0.75 V, which are close to the state-of-the-art Pt/C benchmark catalyst values. Here we achieved an excellent power density of 0.75 W cm −2 using C 96 as a modified cathode in a proton-exchange membrane fuel cell, comparable to other recently reported efficient metal-free catalysts. Combined band structure (experimentally calculated) and free-energy (DFT) investigations show that both favorable energy-level alignment active catalytic sites on the carbon cage are responsible for the superior activity of C 96 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets

Peptoids (N-substituted glycines) are a class of tailorable synthetic peptidomic polymers. Amphiphilic diblock peptoids have been engineered to assemble 2D crystalline lattices with applications in catalysis and molecular separations. Assembly is induced in an organic solvent/water mixture by evaporating the organic phase, but the assembly pathways remain uncharacterized. We conduct all-atom molecular dynamics simulations of Nbrpe6Nc6 as a prototypical amphiphilic diblock peptoid comprising an NH 2 -capped block of six hydrophobic N-((4-bromophenyl)ethyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail. We identify a thermodynamically controlled assembly mechanism by which monomers assemble into disordered aggregates that self-order into 1D chiral helical rods then 2D achiral crystalline sheets. We support our computational predictions with experimental observations of 1D rods using small-angle X-ray scattering, circular dichroism, and atomic force microscopy and 2D crystalline sheets using X-ray diffraction and atomic force microscopy. Furthermore, this work establishes a new understanding of hierarchical peptoid assembly and principles for the design of peptoid-based nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗