Energies of Adsorbed Catalytic Intermediates on Transition Metal Surfaces: Calorimetric Measurements and Benchmarks for Theory

Capitalistic Chemistry

The concept of "bond strength" is of essence for modeling every kind of reactive chemistry. Particularly within the field of catalysis and surface science, the interaction strength of adsorbates to surfaces affects the activity, selectivity, and stability of intermediates and transition states. Here, we introduce a simple approach to chemical reactions through an analogy with business. We regard rehybridization as the investment a molecule makes to prepare its electronic and geometrical structure to form new bonds. The resulting bond strength is the total proceeds from bond formation, and the difference (exothermicity) is the profit. The predictive power lies in the fact that any change in the electronic structure to prepare for bond formation requires the involvement of specific excited states. Thus, with knowledge of the energy needed for this excitation (investment) and the strength of the resulting interaction one can predict whether a specific reaction or bonding mode will be favored. We apply this concept to rationalize observed binding modes at surfaces and the often observed large structural changes even for "weakly" chemisorbed systems and finally to justify using small metal clusters to correct chemisorption energies from periodic DFT calculations.

Unifying thermochemistry concepts in computational heterogeneous catalysis

Thermophysical properties of adsorbates and gas-phase species define the free energy landscape of heterogeneously catalyzed processes and are pivotal for an atomistic understanding of the catalyst performance. These thermophysical properties, such as the free energy or the enthalpy, are typically derived from density functional theory (DFT) calculations. Enthalpies are species-interdependent properties that are only meaningful when referenced to other species. The widespread use of DFT has led to a proliferation of new energetic data in the literature and databases. However, there is a lack of consistency in how DFT data is referenced and how the associated enthalpies or free energies are stored and reported, leading to challenges in reproducing or utilizing the results of prior work. Additionally, DFT suffers from exchange-correlation errors that often require corrections to align the data with other global thermochemical networks, which are not always clearly documented or explained. In this review, we introduce a set of consistent terminology and definitions, review existing approaches, and unify the techniques using the framework of linear algebra. This set of terminology and tools facilitates the correction and alignment of energies between different data formats and sources, promoting the sharing and reuse of ab initio data. Standardization of thermochemistry concepts in computational heterogeneous catalysis reduces computational cost and enhances fundamental understanding of catalytic processes, which will accelerate the computational design of optimally performing catalysts.

High Temperature Solid Oxide Electrolysis for Green Hydrogen Production

Global warming and energy crises have motivated the development of renewable energy and its energy carriers. Green hydrogen is the most promising renewable energy carrier and will be fundamental to future energy conversion and storage systems. Solid Oxide Electrolysis Cells (SOECs) are a promising green hydrogen production technology featuring high electrical efficiency, no noble metal catalyst usage, and reversible operation. This review provides a timely summary of the latest SOEC progress, covering developments at various levels, from cells to stacks to systems. Cell/stack components, configurations, advanced electrode material/fabrication, and novel characterization methods are discussed. Electrochemical and durable performance for each cell/stack configuration is reviewed, focusing on degradation mechanisms and associated mitigation strategies. SOEC system integration with renewable energy and downstream users is outlined, showing flexibility, robustness, scalability, viability, and energy efficiency. Challenges of cost and durability are expected to be overcome by innovation in material, fabrication, production, integration, and operation. Overall, this comprehensive review identifies the SOEC commercialization bottleneck, encourages further technology development, and envisions a future green hydrogen society with net-zero carbon emissions.

Spiers Memorial Lecture: New directions in molecular scattering

The field of molecular scattering is reviewed as it pertains to gas-gas as well as gas-surface chemical reaction dynamics. We emphasize the importance of collaboration of experiment and theory, from which new directions of research are being pursued on increasingly complex problems. We review both experimental and theoretical advances that provide the modern toolbox available to molecular-scattering studies. We distinguish between two classes of work. The first involves simple systems and uses experiment to validate theory so that from the validated theory, one may learn far more than could ever be measured in the laboratory. The second class involves problems of great complexity that would be difficult or impossible to understand without a partnership of experiment and theory. Key topics covered in this review include crossed-beams reactive scattering and scattering at extremely low energies, where quantum effects dominate. They also include scattering from surfaces, reactive scattering and kinetics at surfaces, and scattering work done at liquid surfaces. The review closes with thoughts on future promising directions of research.

Benchmarking water adsorption on metal surfaces with ab initio molecular dynamics

Solid-water interfaces are ubiquitous in nature and technology. In particular, technologies evolving in the green transition, such as electrocatalysis, heavily rely on the junction of an electrolyte and an electrode as a central part of the device. For the understanding of atomic-scale processes taking place at the electrolyte-electrode interface, density functional theory (DFT) has become the de facto standard. The validation of DFT's ability to simulate the interfacial solid/water interaction is crucial, and ideal simulation setups need to be identified in order to prevent avoidable systematic errors. Here, we develop a rigorous sampling protocol for benchmarking the adsorption/desorption energetics of water on metallic surfaces against experimental temperature programmed desorption, single crystal adsorption calorimetry, and thermal energy atom scattering. We screened DFT's quality on a series of transition metal surfaces, applying three of the most common exchange-correlation approximations: PBE-D3, RPBE-D3, and BEEF-vdW. We find that all three xc-functionals reflect the pseudo-zeroth order desorption of water rooted in the combination of attractive adsorbate-adsorbate interactions and their saturation at low and intermediate coverages, respectively. However, both RPBE-D3 and BEEF-vdW lead to more accurate water adsorption strengths, while PBE-D3 clearly overbinds near-surface water. We relate the variations in binding strength to specific variations in water-metal and water-water interactions, highlighting the structural consequences inherent in an uninformed choice of simulation parameters. Our study gives atomistic insight into water's complex adsorption equilibrium. Furthermore, it represents a guideline for future DFT-based simulations of solvated solid interfaces by providing an assessment of systematic errors in specific setups.

Unsupervised machine learning reveals eigen reactivity of metal surfaces

The reactivity of metal surfaces is a cornerstone concept in chemistry, as metals have long been used as catalysts to accelerate chemical reactions. Although fundamentally important, the reactivity of metal surfaces has hitherto not been explicitly defined. For example, in order to compare the activity of two metal surfaces, a particular probe adsorbate, such as O, H, or CO, has to be specified, as comparisons may vary from probe to probe. Here we report that the metal surfaces actually have their own intrinsic/eigen reactivity, independent of any probe adsorbate. By employing unsupervised machine learning algorithms, specifically, principal component analysis (PCA), two dominant eigenvectors emerged from the binding strength dataset formed by 10 commonly used probes on 48 typical metal surfaces. According to their chemical characteristics revealed by vector decomposition, these two eigenvectors can be defined as the covalent reactivity and the ionic reactivity, respectively. Whereas the ionic reactivity turns out to be related to the work function of the metal surface, the covalent reactivity cannot be indexed by simple physical properties, but appears to be roughly connected with the valence-electron number normalized density of states at the Fermi level. Our findings expose that the metal surface reactivity is essentially a two-dimensional vector rather than a scalar, opening new horizons for understanding interactions at the metal surface.

How Precisely Can Individual Molecules Be Analyzed? A Case Study on Locally Quantifying Forces and Energies Using Scanning Probe Microscopy

Recent advances in scanning probe microscopy methodology have enabled the measurement of tip-sample interactions with picometer accuracy in all three spatial dimensions, thereby providing a detailed site-specific and distance-dependent picture of the related properties. This paper explores the degree of detail and accuracy that can be achieved in locally quantifying probe-molecule interaction forces and energies for adsorbed molecules. Toward this end, cobalt phthalocyanine (CoPc), a promising CO2 reduction catalyst, was studied on Ag(111) as a model system using low-temperature, ultrahigh vacuum noncontact atomic force microscopy. Data were recorded as a function of distance from the surface, from which detailed three-dimensional maps of the molecule's interaction with the tip for normal and lateral forces as well as the tip-molecule interaction potential were constructed. The data were collected with a CO molecule at the tip apex, which enabled a detailed visualization of the atomic structure. Determination of the tip-substrate interaction as a function of distance allowed isolation of the molecule-tip interactions; when analyzing these in terms of a Lennard-Jones-type potential, the atomically resolved equilibrium interaction energies between the CO tethered to the tip and the CoPc molecule could be recovered. Interaction energies peaked at less than 160 meV, indicating a physisorption interaction. As expected, the interaction was weakest at the aromatic hydrogens around the periphery of the molecule and strongest surrounding the metal center. The interaction, however, did not peak directly above the Co atom but rather in pockets surrounding it.

Infrared Spectroscopy of Liquid Solutions as a Benchmarking Tool of Semiempirical QM Methods: The Case of GFN2-xTB

The accurate description of large molecular systems has triggered the development of new computational methods. Due to the computational cost of modeling large systems, the methods usually require a trade-off between accuracy and speed. Therefore, benchmarking to test the accuracy and precision of the method is an important step in their development. The typical gold standard for evaluating these methods is isolated molecules, because of the low computational cost. However, the advent of high-performance computing has made it possible to benchmark computational methods using observables from more complex systems such as liquid solutions. To this end, infrared spectroscopy provides a suitable set of observables (i.e., vibrational transitions) for liquid systems. Here, IR spectroscopy observables are used to benchmark the predictions of the newly developed GFN2-xTB semiempirical method. Three different IR probes (i.e., N-methylacetamide, benzonitrile, and semiheavy water) in solution are selected for this purpose. The work presented here shows that GFN2-xTB predicts central frequencies with errors of less than 10% in all probes. In addition, the method captures detailed properties of the molecular environment such as weak interactions. Finally, the GFN2-xTB correctly assesses the vibrational solvatochromism for N-methylacetamide and semiheavy water but does not have the accuracy needed to properly describe benzonitrile. Overall, the results indicate not only that GFN2-xTB can be used to predict the central frequencies and their dependence on the molecular environment with reasonable accuracy but also that IR spectroscopy data of liquid solutions provide a suitable set of observables for the benchmarking of computational methods.

Linking Experimental and Ab Initio Thermochemistry of Adsorbates with a Generalized Thermochemical Hierarchy

Enthalpies of formation of adsorbates are crucial parameters in the microkinetic modeling of heterogeneously catalyzed reactions since they quantify the stability of intermediates on the catalyst surface. This quantity is often computed using density functional theory (DFT), as more accurate methods are computationally still too expensive, which means that the derived enthalpies have a large uncertainty. In this study, we propose a new error cancellation method to compute the enthalpies of formation of adsorbates from DFT more accurately through a generalized connectivity-based hierarchy. The enthalpy of formation is determined through a hypothetical reaction that preserves atomistic and bonding environments. The method is applied to a data set of 60 adsorbates on Pt(111) with up to 4 heavy (non-hydrogen) atoms. Enthalpies of formation of the fragments required for the bond balancing reactions are based on experimental heats of adsorption for Pt(111). The comparison of enthalpies of formation derived from different DFT functionals using the isodesmic reactions shows that the effect of the functional is significantly reduced due to the error cancellation. Thus, the proposed methodology creates an interconnected thermochemical network of adsorbates that combines experimental with ab initio thermochemistry in a single and more accurate thermophysical database.

Transition-state correlations for predicting thermochemistry of adsorbates and surface reactions

Estimating thermochemical properties from linear correlations may provide a pathway to circumvent expensive density functional theory (DFT) calculations for quantities such as pre-exponentials and temperature corrections to DFT energies. Here, we construct thermochemical scaling relations between C₁-C₆n-alkanes in the gas phase and adsorbed alkyl chains extending from several transition metal surfaces, and examine changes in the slope and fit between metals and adsorption sites. We subsequently add -OH, -NH₂, CO, and CC functional groups to the C₁-C₆ molecules and demonstrate strong linear correlations for thermochemistry across all species. We broaden the correlations to incorporate transition states of C₁-C₆n-alkane dehydrogenation reactions, where thermochemistry for computationally prohibitive transition-state calculations can be quickly assessed. Additionally, we rationalize the linearity of thermochemical correlations based on the composition of the homologous series and theoretical assessments. As an application of the correlations, we estimate pre-exponentials for elementary surface reactions of ethane and propane hydrogenolysis on Ru(0001), which is of relevance to plastic hydrogenolysis. Depending on kinetically important steps, entropic contributions may be necessary to include in certain reaction mechanisms; in contrasting examples, entropies are found to be relatively insignificant for ethane hydrogenolysis but pertinent for propane hydrogenolysis.

Adsorption energies on transition metal surfaces: towards an accurate and balanced description

Density functional theory predictions of binding energies and reaction barriers provide invaluable data for analyzing chemical transformations in heterogeneous catalysis. For high accuracy, effects of band structure and coverage, as well as the local bond strength in both covalent and non-covalent interactions, must be reliably described and much focus has been put on improving functionals to this end. Here, we show that a correction from higher-level calculations on small metal clusters can be applied to improve periodic band structure adsorption energies and barriers. We benchmark against 38 reliable experimental covalent and non-covalent adsorption energies and five activation barriers with mean absolute errors of 2.2 kcal mol^-1, 2.7 kcal mol^-1, and 1.1 kcal mol^-1, respectively, which are lower than for functionals widely used and tested for surface science evaluations, such as BEEF-vdW and RPBE.

Liquid-Phase Effects on Adsorption Processes in Heterogeneous Catalysis

Aqueous solvation free energies of adsorption have recently been measured for phenol adsorption on Pt(111). Endergonic solvent effects of ∼1 eV suggest solvents dramatically influence a metal catalyst's activity with significant implications for the catalyst design. However, measurements are indirect and involve adsorption isotherm models, which potentially reduces the reliability of the extracted energy values. Computational, implicit solvation models predict exergonic solvation effects for phenol adsorption, failing to agree with measurements even qualitatively. In this study, an explicit, hybrid quantum mechanical/molecular mechanical approach for computing solvation free energies of adsorption is developed, solvation free energies of phenol adsorption are computed, and experimental data for solvation free energies of phenol adsorption are reanalyzed using multiple adsorption isotherm models. Explicit solvation calculations predict an endergonic solvation free energy for phenol adsorption that agrees well with measurements to within the experimental and force field uncertainties. Computed adsorption free energies of solvation of carbon monoxide, ethylene glycol, benzene, and phenol over the (111) facet of Pt and Cu suggest that liquid water destabilizes all adsorbed species, with the largest impact on the largest adsorbates.

How to extract adsorption energies, adsorbate-adsorbate interaction parameters and saturation coverages from temperature programmed desorption experiments

We present a scheme to extract the adsorption energy, adsorbate interaction parameter and the saturation coverage from temperature programmed desorption (TPD) experiments. We propose that the coverage dependent adsorption energy can be fit using a functional form including the configurational entropy and linear adsorbate-adsorbate interaction terms. As one example of this scheme, we analyze TPD of CO desorption on Au(211) and Au(310) surfaces. We determine that under atmospheric CO pressure, the steps of both facets adsorb between 0.4-0.9 ML coverage of CO*. We compare this result against energies obtained from five density functionals, RPBE, PBE, PBE-D3, RPBE-D3 and BEEF-vdW. We find that the energies and equilibrium coverages from RPBE-D3 and PBE are closest to the values determined from the TPD.

Water and Carbon Dioxide Adsorption on CaO(001) Studied via Single Crystal Adsorption Calorimetry

A new method to analyze microcalorimetry data was employed to study the adsorption energies and sticking probabilities of D2O and CO2 on CaO(001) at several temperatures. This method deconvolutes the line shapes of the heat detector response into an instrument response function and exponential decay functions, which correspond to the desorption of distinct surface species. This allows for a thorough analysis of the adsorption, dissociation, and desorption processes that occur during our microcalorimetry experiments. Our microcalorimetry results, show that D2O adsorbs initially with an adsorption energy of 85–90 kJ/mol at temperatures ranging from 120 to 300 K, consistent with prior spectroscopic studies that indicate dissociation. This adsorption energy decreases with increasing coverage until either D2O multilayers are formed at low temperatures (120 K) or the surface is saturated (> 150 K). Artificially producing defects on the surface by sputtering prior to dosing D2O sharply increases this adsorption energy, but these defects may be healed after annealing the surface to 1300 K. CO2 adsorbs on CaO(001) with an initial adsorption energy of ~ 125 kJ/mol, and decreases until the saturation coverage is reached, which is a function of surface temperature. The results showed that pre-adsorbed water blocks adsorption sites, lowers the saturation coverage, and lowers the measured adsorption energy of CO2. The calorimetry data further adds to our understanding of D2O and CO2 adsorption on oxide surfaces.

Structural, electronic, and magnetic properties of Ni nanoparticles supported on the TiC(001) surface

Metals supported on transition metal carbides are known to exhibit good catalytic activity and selectivity, which is interpreted in terms of electron polarization induced by the support. In the present work we go one step further and investigate the effect that a titanium carbide (TiC) support has on the structural, electronic, and magnetic properties of a series of Ni nanoparticles of increasing size exhibiting a two- or three-dimensional morphology. The obtained results show that three-dimensional nanoparticles are more stable and easier to form than their homologous two-dimensional counterparts. Also, comparison to previous results indicates that, when used as the support, transition metal carbides have a marked different chemical activity with respect to oxides. The analysis of the magnetic moments of the supported nanoparticles evidences a considerable quenching of the magnetic moment that affects mainly the Ni atoms in close contact with the TiC substrate indicating that these atoms are likely to be responsible for the catalytic activity reported for these systems. The analysis of the electronic structure reveals the existence of chemical interactions between the Ni nanoparticles and the TiC support, even if the net charge transfer between both systems is negligible.

Silver Adsorption on Calcium Niobate(001) Nanosheets: Calorimetric Energies That Explain Sinter-Resistant Support

Metal nanoparticles deposited on oxide supports are essential to many technologies, including catalysts, fuel cells, and electronics. Therefore, understanding the chemical bonding strength between metal nanoparticles and oxide surfaces is of great interest. The adsorption energetics, adhesion energy, and adsorbate structure of Ag on dehydrated HCa₂Nb₃O₁₀(001) nanosheets at 300 K have been studied using metal adsorption calorimetry and surface spectroscopies. These dehydrated ("dh") calcium niobate nanosheets (dh-HCa₂Nb₃O₁₀(001)) have the stoichiometry Ca₄Nb₆O₁₉. They impart unusual stability to metal nanoparticles when used as catalyst supports and are easy-to-prepare by Langmuir-Blodgett (LB) techniques, highly ordered, and essentially single-crystal surfaces of mixed oxides with a huge ratio of terrace to edge sites. Below the monolayer coverage, Ag grows on dh-HCa₂Nb₃O₁₀(001) as 2D islands of thickness ∼2 layers. The differential heat of Ag adsorption is initially ∼303 kJ/mol, increasing slowly to ∼338 kJ/mol by 0.8 ML. At higher coverages, Ag atoms mainly add on top of these 2D islands, growing 3D nanoparticles of increasing thickness, as the heat decreases asymptotically toward silver's heat of sublimation (285 kJ/mol). The adhesion energy of Ag(s) to this Ca niobate surface is estimated to be 4.33 J/m², larger than that on any oxide surface previously measured. This explains the sinter resistance reported for metal nanoparticles on this support. Electron transfer from Ag into the calcium niobate is also measured. These results demonstrate an easy way to do single-crystal-type surface science studies-and especially thermochemical measurements-on the complex surfaces of mixed oxides: using LB-deposited perovskite nanosheets and ultrahigh-vacuum annealing in O₂.

Single-Atom Catalysts in Catalytic Biomedicine

The intrinsic deficiencies of nanoparticle-initiated catalysis for biomedical applications promote the fast development of alternative versatile theranostic modalities. The catalytic performance and selectivity are the critical issues that are challenging to be augmented and optimized in biological conditions. Single-atom catalysts (SACs) featuring atomically dispersed single metal atoms have emerged as one of the most explored catalysts in biomedicine recently due to their preeminent catalytic activity and superior selectivity distinct from their nanosized counterparts. Herein, an overview of the pivotal significance of SACs and some underlying critical issues that need to be addressed is provided, with a specific focus on their versatile biomedical applications. Their fabrication strategies, surface engineering, and structural characterizations are discussed briefly. In particular, the catalytic performance of SACs in triggering some representative catalytic reactions for providing the fundamentals of biomedical use is discussed. A sequence of representative paradigms is summarized on the successful construction of SACs for varied biomedical applications (e.g., cancer treatment, wound disinfection, biosensing, and oxidative-stress cytoprotection) with an emphasis on uncovering the intrinsic catalytic mechanisms and understanding the underlying structure-performance relationships. Finally, opportunities and challenges faced in the future development of SACs-triggered catalysis for biomedical use are discussed and outlooked.

Including dispersion in density functional theory for adsorption on flat oxide surfaces, in metal-organic frameworks and in acidic zeolites

We examine the performance of nine commonly used methods for including dispersion interactions in density functional theory (DFT): three different parametrizations of damped 1/Rn terms (n = 6, 8, …) added to the DFT energy (Grimme's D2 and D3 parameterizations as well as that of Tkatchenko and Scheffler), three different implementations of the many-body dispersion approach (MBD, MBD/HI and MBD/FI), the density-dependent energy correction, called dDsC, and two "first generation" van der Waals density functionals, revPBE-vdW and optB86b-vdW. As test set we use eight molecule-surface systems for which agreement has been reached between experiment and hybrid QM:QM calculations within chemical accuracy limits (±4.2 kJ mol-1). It includes adsorption of carbon monoxide and dioxide in the Mg2(2,5-dioxido-1,4-benzenedicarboxylate) metal-organic framework (Mg-MOF-74, CPO-27-Mg), adsorption of carbon monoxide as well as of monolayers of methane and ethane on the MgO(001) surface, as well as adsorption of methane, ethane and propane in H-chabazite (H-CHA). D2 with Ne parameters for Mg2+, D2(Ne), MBD/HI and MBD/FI perform best. With the PBE functional, the mean unsigned errors are 6.1, 5.6 and 5.4 kJ mol-1, respectively.

Assessment of van der Waals inclusive density functional theory methods for adsorption and selective dehydrogenation of formic acid on Pt(111) surface

In this work, we studied the adsorption and catalytic dehydrogenation of formic acid (HCOOH) on Pt(111) surface using different van der Waals inclusive density functional theory (DFT) methods.