Demystifying the Chemical Ordering of Multimetallic Nanoparticles.

ConspectusMultimetallic nanoparticles (NPs) have highly tunable properties due to the synergy between the different metals and the wide variety of NP structural parameters such as size, shape, composition, and chemical ordering. The major problem with studying multimetallic NPs is that as the number of different metals increases, the number of possible chemical orderings (placements of different metals) for a NP of fixed size explodes. Thus, it becomes infeasible to explore NP energetic differences with highly accurate computational methods, such as density functional theory (DFT), which has a high computational cost and is typically applied to up to a couple of hundred metal atoms. Here, we demonstrate a methodology advancing NP simulations by effectively exploring the vast materials space of multimetallic NPs and accurately identifying the ones with the most thermodynamically preferred chemical orderings. With accuracies reaching that of DFT, our methodology is applicable to practically any NP size, shape, and metal composition. We achieve this by significantly advancing the bond-centric (BC) model, a physics-based model that has been previously shown to rapidly predict bimetallic NP cohesive energies (CEs). Specifically, the BC model is trained in a way to understand how the bimetallic bond strength changes under different coordination environments present on a NP and how the metal composition of every site affects the detailed coordination environment using fractional coordination numbers. This newly modified BC model leads to an improvement from 0.331 (original model) to 0.089 eV/atom in CE predictions when compared to DFT values on a robust data set of 90 different NPs consisting of PtPd, AuPt, and AuPd NPs with varying compositions and chemical orderings. By incorporating the modified BC model into an in-house-developed genetic algorithm (GA) we can effectively and accurately predict the most stable chemical orderings of large, realistic bimetallic NPs consisting of thousands of metal atoms. This is demonstrated on AuPd bimetallic NPs, a challenging system due to the similarity in the cohesion of the two metals. By training our BC model using a unique DFT calculation on a bimetallic NP (one calculation for two metals combining together), we expand to explore the chemical ordering of multimetallic NPs. We first demonstrate the application of our methodology on a AuPdPt NP and validate our stability predictions with literature data. Then, we effectively explore the vast materials space of multimetallic NPs consisting of combinations of Au, Pt, and Pd as a function of metal composition. Our thermodynamic stability trends are presented in a ternary diagram revealing detailed, and yet, unexpected chemical ordering trends. Our computational framework can aid both experimental and computational researchers toward effectively screening multimetallic NP stability. Moreover, we provide an outlook of how this framework can be applied to catalyst discovery, high-entropy alloys, and single-atom alloys.

Impact of Surface Ligand Identity and Density on the Thermodynamics of H Atom Uptake at Polyoxovanadate-Alkoxide Surfaces.

An understanding of how molecular structure influences the thermodynamics of H atom transfer is critical to designing efficient catalysts for reductive chemistries. Herein, we report experimental and theoretical investigations summarizing structure-function relationships of polyoxovanadate-alkoxides that influence bond dissociation free energies of hydroxide ligands located at the surface of the cluster. We evaluate the thermochemical descriptors of O-H bond strength for a series of clusters, namely [V6O13-x(OH)x(TRIOLR)2]-2 (x = 2, 4, 6; R = NO2, Me) and [V6O11-x(OMe)2(OH)x(TRIOLNO2)2]-2, via computational analysis and open circuit potential measurements. Our findings reveal that modifications to the TRIOL ligand (e.g., changing from the previously reported electron withdrawing nitro-backed ligand to the electron-donating methyl variant) have limited influence on the strength of surface O-H bonds as a result of near complete thermodynamic compensation in these systems (i.e., correlated changes in redox potential and cluster basicity). In contrast, changes in surface density of alkoxide ligands via direct alkoxylation of the polyoxovanadate-alkoxide surface result in measurable increases in bond dissociation free energies of surface O-H bonds for the mixed-valent derivatives. Our findings indicate that the extent of (de)localization of electron density across the cluster core has an impact on the bond dissociation free energies of surface O-H bonds across all oxidation states of the assembly.

Confined Ru Sites in a 13X Zeolite for Ultrahigh H2 Production from NH3 Decomposition.

Catalytic NH3 synthesis and decomposition offer a new promising way to store and transport renewable energy in the form of NH3 from remote or offshore sites to industrial plants. To use NH3 as a hydrogen carrier, it is important to understand the catalytic functionality of NH3 decomposition reactions at an atomic level. Here, we report for the first time that Ru species confined in a 13X zeolite cavity display the highest specific catalytic activity of over 4000 h-1 for the NH3 decomposition with a lower activation barrier, compared to most reported catalytic materials in the literature. Mechanistic and modeling studies clearly indicate that the N-H bond of NH3 is ruptured heterolytically by the frustrated Lewis pair of Ruδ+-Oδ- in the zeolite identified by synchrotron X-rays and neutron powder diffraction with Rietveld refinement as well as other characterization techniques including solid-state nuclear magnetic resonance spectroscopy, in situ diffuse reflectance infrared transform spectroscopy, and temperature-programmed analysis. This contrasts with the homolytic cleavage of N-H displayed by metal nanoparticles. Our work reveals the unprecedented unique behavior of cooperative frustrated Lewis pairs created by the metal species on the internal zeolite surface, resulting in a dynamic hydrogen shuttling from NH3 to regenerate framework Brønsted acid sites that eventually are converted to molecular hydrogen.

Global and Local Connectivities Describe Hydrogen Intercalation in Metal Oxides.

We introduce global connectivity, Ω, which quantifies the detailed connectivity of a material and accurately captures reactivity behavior. We demonstrate that combining global and local connectivity describes how metal oxides interact with hydrogen. Blending density functional theory, graph theory, and machine learning we built a reactivity model which accurately predicts hydrogen intercalation potentials of different metal oxides experimentally measured in the lab. The use of global connectivity can accelerate materials design through the development of novel structure-property relationships.

The Sensitivity of Metal Oxide Electrocatalysis to Bulk Hydrogen Intercalation: Hydrogen Evolution on Tungsten Oxide.

Metal oxides are attracting increased attention as electrocatalysts owing to their affordability, tunability, and reactivity. However, these materials can undergo significant chemical changes under reaction conditions, presenting challenges for characterization and optimization. Herein, we combine experimental and computational methods to demonstrate that bulk hydrogen intercalation governs the activity of tungsten trioxide (WO3) toward the hydrogen evolution reaction (HER). In contrast to the focus on surface processes in heterogeneous catalysis, we demonstrate that bulk oxide modification is responsible for experimental HER activity. Density functional theory (DFT) calculations reveal that intercalation enables the HER by altering the acid-base character of surface sites and preventing site blocking by hydration. First-principles microkinetic modeling supports that the experimental HER rates can only be explained by intercalated HxWO3, whereas nonintercalated WO3 does not catalyze the HER. Overall, this work underscores the critical influence of hydrogen intercalation on aqueous cathodic electrocatalysis at metal oxides.

Molecular modifiers reveal a mechanism of pathological crystal growth inhibition.

Crystalline materials are crucial to the function of living organisms, in the shells of molluscs, the matrix of bone, the teeth of sea urchins, and the exoskeletons of coccoliths. However, pathological biomineralization can be an undesirable crystallization process associated with human diseases. The crystal growth of biogenic, natural and synthetic materials may be regulated by the action of modifiers, most commonly inhibitors, which range from small ions and molecules to large macromolecules. Inhibitors adsorb on crystal surfaces and impede the addition of solute, thereby reducing the rate of growth. Complex inhibitor-crystal interactions in biomineralization are often not well elucidated. Here we show that two molecular inhibitors of calcium oxalate monohydrate crystallization--citrate and hydroxycitrate--exhibit a mechanism that differs from classical theory in that inhibitor adsorption on crystal surfaces induces dissolution of the crystal under specific conditions rather than a reduced rate of crystal growth. This phenomenon occurs even in supersaturated solutions where inhibitor concentration is three orders of magnitude less than that of the solute. The results of bulk crystallization, in situ atomic force microscopy, and density functional theory studies are qualitatively consistent with a hypothesis that inhibitor-crystal interactions impart localized strain to the crystal lattice and that oxalate and calcium ions are released into solution to alleviate this strain. Calcium oxalate monohydrate is the principal component of human kidney stones and citrate is an often-used therapy, but hydroxycitrate is not. For hydroxycitrate to function as a kidney stone treatment, it must be excreted in urine. We report that hydroxycitrate ingested by non-stone-forming humans at an often-recommended dose leads to substantial urinary excretion. In vitro assays using human urine reveal that the molecular modifier hydroxycitrate is as effective an inhibitor of nucleation of calcium oxalate monohydrate nucleation as is citrate. Our findings support exploration of the clinical potential of hydroxycitrate as an alternative treatment to citrate for kidney stones.

Dissecting Critical Factors for Electrochemical CO2 Reduction on Atomically Precise Au Nanoclusters.

This work investigates the critical factors impacting electrochemical CO2 reduction reaction (CO2 RR) using atomically precise Au nanoclusters (NCs) as electrocatalysts. First, the influence of size on CO2 RR is studied by precisely controlling NC size in the 1-2.5 nm regime. We find that the electrocatalytic CO partial current density increases for smaller NCs, but the CO Faradaic efficiency (FE) is not directly associated with the NC size. This indicates that the surface-to-volume ratio, i.e. the population of active sites, is the dominant factor for determining the catalytic activity, but the selectivity is not directly impacted by size. Second, we compare the CO2 RR performance of Au38 isomers (Au38 Q and Au38 T) to reveal that structural rearrangement of identical size NCs can lead to significant changes in both CO2 RR activity and selectivity. Au38 Q shows higher activity and selectivity towards CO than Au38 T, and density functional theory (DFT) calculations reveal that the average formation energy of the key *COOH intermediate on the proposed active sites is significantly lower on Au38 Q than Au38 T. These results demonstrate how the structural isomerism can impact stabilization of reaction intermediates as well as the overall CO2 RR performance of identical size Au NCs. Overall, this work provides important structure-property relationships for tailoring the NCs for CO2 RR.

Hydrogen Evolution Electrocatalyst Design: Turning Inert Gold into Active Catalyst by Atomically Precise Nanochemistry.

Electrocatalytic hydrogen evolution reaction (HER) holds promise in the renewable clean energy scheme. Crystalline Au and Ag are, however, poor in catalyzing HER, and the ligands on colloidal nanoparticles are generally another disadvantage. Herein, we report a thiolate (SR)-protected Au36Ag2(SR)18 nanocluster with low coverage of ligands and a core composed of three icosahedral (Ih) units for catalyzing HER efficiently. This trimeric structure, together with the monomeric Ih Au25(SR)18- and dimeric Ih Au38(SR)24, constitutes a unique series, providing an opportunity for revealing the correlation between the catalytic properties and the catalyst's structure. The Au36Ag2(SR)18 surprisingly exhibits high catalytic activity at lower overpotentials for HER due to its low ligand-to-metal ratio, low-coordinated Au atoms and unfilled superatomic orbitals. The current density of Au36Ag2(SR)18 at -0.3 V vs RHE is 3.8 and 5.1 times that of Au25(SR)18- and Au38(SR)24, respectively. Density functional theory (DFT) calculations reveal lower hydrogen binding energy and higher electron affinity of Au36Ag2(SR)18 for an energetically feasible HER pathway. Our findings provide a new strategy for constructing highly active catalysts from inert metals by pursuing atomically precise nanoclusters and controlling their geometrical and electronic structures.

A Classification Model to Identify Direct-Acting Mutagenic Polycyclic Aromatic Hydrocarbon Transformation Products.

Polycyclic aromatic hydrocarbons (PAHs) are a complex group of environmental contaminants, many having long environmental half-lives. As these compounds degrade, the changes in their structure can result in a substantial increase in mutagenicity compared to the parent compound. Over time, each individual PAH can potentially degrade into several thousand unique transformation products, creating a complex, constantly evolving set of intermediates. Microbial degradation is the primary mechanism of their transformation and ultimate removal from the environment, and this process can result in mutagenic activation similar to the metabolic activation that can occur in multicellular organisms. The diversity of the potential intermediate structures in PAH-contaminated environments renders hazard assessment difficult for both remediation professionals and regulators. A mixture of structural and energetic descriptors has proven effective in existing studies for classifying which PAH transformation products will be mutagenic. However, most existing studies of environmental PAH mutagens primarily focus on nitrogenated derivatives, which are prevalent in the atmosphere and not as relevant in soil. Additionally, PAH products commonly found in the environment can range from as large as five rings to as small as a single ring, requiring a broadly inclusive methodology to comprehensively evaluate mutagenic potential. We developed a combination of supervised and unsupervised machine learning methods to predict environmentally induced PAH mutagenicity with improved performance over currently available tools. K-means clustering with principal component analysis allows us to identify molecular clusters that we hypothesize to have similar mechanisms of action. Recursive feature elimination identifies the most influential descriptors. The cluster-specific regression outperforms available classifiers in predicting direct-acting mutagens resulting from the microbial biodegradation of PAHs and provides direction for future studies evaluating the environmental hazards resulting from PAH biodegradation.

CuZrO3: If it exists it should be a sandwich.

CuZrO3 has been hypothesized to be a catalytic material with potential applications for CO2 reduction. Unfortunately, this material has received limited attention in the literature, and to the best of our knowledge the exact crystal structure is still unknown. To address this challenge, we utilize several different structural prediction techniques in concert, including the Universal Structure Predictor: Evolutionary Xtallography (USPEX), the Materials Project Structure Predictor, and the Open Quantum Materials Database (OQMD). Leveraging these structural prediction techniques in conjunction with Density-Functional Theory (DFT) calculations, we determine a possible structure for CuZrO3, which resembles a "sandwich" morphology. Our calculations reveal that this new structure is significantly lower in energy than a previously hypothesized perovskite structure, albeit it still has a thermodynamic preference to decompose into CuO and ZrO2. In addition, we experimentally tried to synthesize CuZrO3 based on literature reports and compared computational to experimental X-ray Diffraction (XRD) patterns confirming that the final product is a mixture of CuO and ZrO2. Finally, we conducted a computational surface energetics and CO2 adsorption study on our discovered sandwich morphology, demonstrating that CO2 can adsorb and activate on the material. However, these CO2 adsorption results deviate from previously reported results further confirming that the CuZrO3 is a metastable form and may not be experimentally accessible as a well-mixed oxide, since phase segregation to CuO and ZrO2 is preferred. Taken together, our combined computational and experimental study provides evidence that the synthesis of CuZrO3 is extremely difficult and if this oxide exists, it should have a sandwich-like morphology.

Correlating structural rules with electronic properties of ligand-protected alloy nanoclusters.

Thiolate protected gold nanoclusters (TPNCs) are a unique class of nanomaterials finding applications in various fields, such as biomedicine, optics, and catalysis. The atomic precision of their structure, characterized through single crystal x-ray diffraction, enables the accurate investigation of their physicochemical properties through electronic structure calculations. Recent experimental efforts have led to the successful heterometal doping of TPNCs, potentially unlocking a large domain of bimetallic TPNCs for targeted applications. However, how TPNC size, bimetallic composition, and location of dopants influence electronic structure is unknown. To this end, we introduce novel structure-property relationships (SPRs) that predict electronic properties such as ionization potential (IP) and electron affinity (EA) of AgAu TPNCs based on physically relevant descriptors. The models are constructed by first generating a hypothetical AgAu TPNC dataset of 368 structures with sizes varying from 36 to 279 metal atoms. Using our dataset calculated with density functional theory (DFT), we employed systematic analyses to unravel size, composition, and, importantly, core-shell effects on TPNC EA and IP behavior. We develop generalized SPRs that are able to predict electronic properties across the AgAu TPNC materials space. The models leverage the same three fundamental descriptors (i.e., size, composition, and core-shell makeup) that do not require DFT calculations and rely only on simple atom counting, opening avenues for high throughput bimetallic TPNC screening for targeted applications. This work is a first step toward finely controlling TPNC electronic properties through heterometal doping using high throughput computational means.

Boosting CO2 Electrochemical Reduction with Atomically Precise Surface Modification on Gold Nanoclusters.

Thiolate-protected gold nanoclusters (NCs) are promising catalytic materials for the electrochemical CO2 reduction reaction (CO2 RR). In this work an atomic level modification of a Au23 NC is made by substituting two surface Au atoms with two Cd atoms, and it enhances the CO2 RR selectivity to 90-95 % at the applied potential between -0.5 to -0.9 V, which is doubled compared to that of the undoped Au23 . Additionally, the Cd-doped Au19 Cd2 exhibits the highest CO2 RR activity (2200 mA mg-1 at -1.0 V vs. RHE) among the reported NCs. This synergetic effect between Au and Cd is remarkable. Density-functional theory calculations reveal that the exposure of a sulfur active site upon partial ligand removal provides an energetically feasible CO2 RR pathway. The thermodynamic energy barrier for CO formation is 0.74 eV lower on Au19 Cd2 than on Au23 . These results reveal that Cd doping can boost the CO2 RR performance of Au NCs by modifying the surface geometry and electronic structure, which further changes the intermediate binding energy. This work offers insights into the surface doping mechanism of the CO2 RR and bimetallic synergism.

Atom-by-Atom Evolution of the Same Ligand-Protected Au21, Au22, Au22Cd1, and Au24 Nanocluster Series.

Atom-by-atom manipulation on metal nanoclusters (NCs) has long been desired, as the resulting series of NCs can provide insightful understanding of how a single atom affects the structure and properties as well as the evolution with size. Here, we report crystallizations of Au22(SAdm)16 and Au22Cd1(SAdm)16 (SAdm = adamantanethiolate) which link up with Au21(SAdm)15 and Au24(SAdm)16 NCs and form an atom-by-atom evolving series protected by the same ligand. Structurally, Au22(SAdm)16 has an Au3(SAdm)4 surface motif which is longer than the Au2(SAdm)3 on Au21(SAdm)15, whereas Au22Cd1(SAdm)16 lacks one staple Au atom compared to Au24(SAdm)16 and thus the surface structure is reconstructed. A single Cd atom triggers the structural transition from Au22 with a 10-atom bioctahedral kernel to Au22Cd1 with a 13-atom cuboctahedral kernel, and correspondingly, the optical properties are dramatically changed. The photoexcited carrier lifetime demonstrates that the optical properties and excited state relaxation are highly sensitive at the single atom level. By contrast, little change in both ionization potential and electron affinity is found in this series of NCs by theoretical calculations, indicating the electronic properties are independent of adding a single atom in this series. The work provides a paradigm that the NCs with continuous metal atom numbers are accessible and crystallizable when meticulously designed, and the optical properties are more affected at the single atom level than the electronic properties.

Elucidating the optical spectra of [Au25(SR)18]q nanoclusters.

Ligand-protected Au nanoclusters have attracted tremendous interest due to their atomically precise structural determination and controllable optical properties. However, the origin of their optical features is not well understood. Herein, we address the effects of charge state and type of ligands on the structural, electronic, and optical properties of the Au25(SR)18 nanocluster, using first principles calculations. In particular, we analyze in detail the optical absorption spectra of phenylethanethiol-capped [Au25(SCH2CH2Ph)18]q nanocluster (q = -1, 0, and 1) and demonstrate that the nanocluster undergoes geometric changes when increasing its charge state, yielding the development of additional photoabsorption features. Moreover, by comparing the properties of the anionic [Au25(SR)18]1- nanoclusters (with SR = -SCH2CH2Ph, -SCH3 and -SH) we demonstrate that accounting for full (-SCH2CH2Ph) compared to simplified (-SCH3 and -SH) ligands leads to significant modifications in the shape of the main absorption features, such as the emergence of step-like absorption shoulders. In addition, we show that the energy of the main absorption peaks of the [Au25(SR)18]1- significantly blue-shifts when using -SH as model ligands. Overall, our computational work aids the experimental characterization of optical properties of ligand-protected nanoclusters and highlights the importance of accounting for full ligands in optical spectra calculations.

Size-, Shape-, and Composition-Dependent Model for Metal Nanoparticle Stability Prediction.

Although tremendous applications for metal nanoparticles have been found in modern technologies, the understanding of their stability as related to morphology (size and shape) and chemical ordering (e.g., in bimetallics) remains limited. First-principles methods such as density functional theory (DFT) are capable of capturing accurate nanoalloy energetics; however, they are limited to very small nanoparticle sizes (<2 nm in diameter) due to their computational cost. Herein, we propose a bond-centric (BC) model able to capture cohesive energy trends over a range of monometallic and bimetallic nanoparticles and mixing behavior (excess energy) of nanoalloys, in great agreement with DFT calculations. We apply the BC model to screen the energetics of a recently reported 23 196-atom FePt nanoalloys ( Yang et al. Nature 2017 , 542 , 75 - 79 ), offering insights into both segregation and bulk-chemical ordering behavior. Because the BC model utilizes tabulated data (diatomic bond energies and bulk cohesive energies) and structural information on nanoparticles (coordination numbers), it can be applied to calculate the energetics of any nanoparticle morphology and chemical composition, thus significantly accelerating nanoalloy design.

Mechanistic Studies on the Michael Addition of Amines and Hydrazines To Nitrostyrenes: Nitroalkane Elimination via a Retro-aza-Henry-Type Process.

In this article we report on the mechanistic studies of the Michael addition of amines and hydrazines to nitrostyrenes. Under the present conditions, the corresponding N-alkyl/aryl substituted benzyl imines and N-methyl/phenyl substituted benzyl hydrazones were observed via a retro-aza-Henry-type process. By combining organic synthesis and characterization experiments with computational chemistry calculations, we reveal that this reaction proceeds via a protic solvent-mediated mechanism. Experiments in deuterated methanol CD3OD reveal the synthesis and isolation of the corresponding deuterated intermediated Michael adduct, results that support the proposed slovent-mediated pathway. From the synthetic point of view, the reaction occurs under mild, noncatalytic conditions and can be used as a useful platform to yield the biologically important N-methyl pyrazoles in a one-pot manner, simple starting with the corresponding nitrostyrenes and the methylhydrazine.

Reconstructing the Surface of Gold Nanoclusters by Cadmium Doping.

Atomically precise metal nanoclusters with tailored surface structures are important for both fundamental studies and practical applications. The development of new methods for tailoring the surface structure in a controllable manner has long been sought. In this work, we report surface reconstruction induced by cadmium doping into the [Au23(SR)16]- (R = cyclohexyl) nanocluster, in which two neighboring surface Au atomic sites "coalesce" into one Cd atomic site and, accordingly, a new bimetal nanocluster, [Au19Cd2(SR)16]-, is produced. Interestingly, a Cd(S-Au-S)3 "paw-like" surface motif is observed for the first time in nanocluster structures. In such a motif, the Cd atom acts as a junction which connects three monomeric -S-Au-S- motifs. Density functional theory calculations are performed to understand the two unique Cd locations. Furthermore, we demonstrate different doping modes when the [Au23(SR)16]- nanocluster is doped with different metals (Cu, Ag), including (i) simple substitution and (ii) total structure transformation, as opposed to surface reconstruction for Cd doping. This work greatly expands doping chemistry for tailoring the structures of nanoclusters and is expected to open new avenues for designing nanoclusters with novel surface structures using different dopants.

From Biomass-Derived Furans to Aromatics with Ethanol over Zeolite.

We report a novel catalytic conversion of biomass-derived furans and alcohols to aromatics over zeolite catalysts. Aromatics are formed via Diels-Alder cycloaddition with ethylene, which is produced in situ from ethanol dehydration. The use of liquid ethanol instead of gaseous ethylene, as the source of dienophile in this one-pot synthesis, makes the aromatics production much simpler and renewable, circumventing the use of ethylene at high pressure. More importantly, both our experiments and theoretical studies demonstrate that the use of ethanol instead of ethylene, results in significantly higher rates and higher selectivity to aromatics, due to lower activation barriers over the solid acid sites. Synchrotron-diffraction experiments and proton-affinity calculations clearly suggest that a preferred protonation of ethanol over the furan is a key step facilitating the Diels-Alder and dehydration reactions in the acid sites of the zeolite.

Description and Role of Bimetallic Prenucleation Species in the Formation of Small Nanoparticle Alloys.

We report the identification, description, and role of multinuclear metal-thiolate complexes in aqueous Au-Cu nanoparticle syntheses. The structure of these species was characterized by nuclear magnetic resonance spectroscopy, mass spectrometry, X-ray photoelectron spectroscopy, and X-ray absorption spectroscopy techniques. The observed structures were found to be in good agreement with thermodynamic growth trends predicted by first-principles calculations. The presence of metal-thiolate complexes is then shown to be critical for the formation of alloyed Au-Cu architectures in the small nanoparticle regime (diameter ∼2 nm). In the absence of mixed metal-thiolate precursors, nanoparticles form with a Cu-S shell and a Au-rich interior. Taken together, these results demonstrate that prenucleation species, which are discrete molecular precursors distinct from both initial reagents and final particle products, may provide an important new synthetic route to control final metal nanoparticle composition and composition architectures.

Informatics guided discovery of surface structure-chemistry relationships in catalytic nanoparticles.

A data driven discovery strategy based on statistical learning principles is used to discover new correlations between electronic structure and catalytic activity of metal surfaces. From the quantitative formulations derived from this informatics based model, a high throughput computational framework for predicting binding energy as a function of surface chemistry and adsorption configuration that bypasses the need for repeated electronic structure calculations has been developed.