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1.
Phys Chem Chem Phys ; 22(35): 19454-19458, 2020 Sep 16.
Artigo em Inglês | MEDLINE | ID: mdl-32856642

RESUMO

Various databases of density functional theory (DFT) calculations for materials and adsorption properties are currently available. Using the Materials Project and GASpy databases of material stability and binding energies (H* and CO*), respectively, we evaluate multiple aspects of catalysts to discover active, stable, CO-tolerant, and cost-effective hydrogen evolution and oxidation catalysts. Finally, we suggest a few candidate materials for future experimental validations. We highlight that the stability analysis is easily obtainable but provides invaluable information to assess thermodynamic and electrochemical stability, bridging the gap between simulations and experiments. Furthermore, it reduces the number of expensive DFT calculations required to predict catalytic activities of surfaces by filtering out unstable materials.

2.
J Am Chem Soc ; 142(36): 15386-15395, 2020 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-32786758

RESUMO

The oxygen reduction reaction (ORR) is central in carbon-neutral energy devices. While platinum group materials have shown high activities for ORR, their practical uses are hampered by concerns over deactivation, slow kinetics, exorbitant cost, and scarce nature reserve. The low cost yet high tunability of metal-organic frameworks (MOFs) provide a unique platform for tailoring their characteristic properties as new electrocatalysts. Herein, we report a new concept of design and present stable Zr-chain-based MOFs as efficient electrocatalysts for ORR. The strategy is based on using Zr-chains to promote high chemical and redox stability and, more importantly, tailor the immobilization and packing of redox active-sites at a density that is ideal to improve the reaction kinetics. The obtained new electrocatalyst, PCN-226, thereby shows high ORR activity. We further demonstrate PCN-226 as a promising electrode material for practical applications in rechargeable Zn-air batteries, with a high peak power density of 133 mW cm-2. Being one of the very few electrocatalytic MOFs for ORR, this work provides a new concept by designing chain-based structures to enrich the diversity of efficient electrocatalysts and MOFs.

3.
ACS Appl Mater Interfaces ; 12(34): 38256-38265, 2020 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-32799519

RESUMO

Discovering acid-stable, cost-effective, and active catalysts for oxygen evolution reaction (OER) is critical since this reaction is a bottleneck in many electrochemical energy conversion systems. The current systems use extremely expensive iridium oxide catalysts. Identifying Ir-free or less-Ir containing catalysts has been suggested as the goal, but no systematic strategy to discover such catalysts has been reported. In this work, we perform first-principles-based high-throughput catalyst screening to discover OER-active and acid-stable catalysts focusing on equimolar bimetallic oxides with space groups derived from those of IrOx. We develop an approach to evaluate acid-stability under the reaction condition by utilizing the Materials Project database and density functional theory (DFT) calculations. For acid-stable materials, we further investigate their OER catalytic activities and identify promising OER catalysts that satisfy all the desired properties: Co-Ir, Fe-Ir, and Mo-Ir bimetallic oxides. Based on the calculated results, we provide insights to efficiently perform future high-throughput screening to discover catalysts with desirable properties and discuss the remaining challenges.

4.
J Phys Chem Lett ; 11(9): 3185-3191, 2020 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-32191473

RESUMO

The binding site and energy is an invaluable descriptor in high-throughput screening of catalysts, as it is accessible and correlates with the activity and selectivity. Recently, comprehensive binding energy prediction machine-learning models have been demonstrated and promise to accelerate the catalyst screening. Here, we present a simple and versatile representation, applicable to any deep-learning models, to further accelerate such process. Our approach involves labeling the binding site atoms of the unrelaxed bare surface geometry; hence, for the model application, density functional theory calculations can be completely removed if the optimized bulk structure is available as is the case when using the Materials Project database. In addition, we present ensemble learning, where a set of predictions is used together to form a predictive distribution that reduces the model bias. We apply the labeled site approach and ensemble to crystal graph convolutional neural network and the ∼40 000 data set of alloy catalysts for CO2 reduction. The proposed model applied to the data set of unrelaxed structures shows 0.116 and 0.085 eV mean absolute error, respectively, for CO and H binding energy, better than the best method (0.13 and 0.13 eV) in the literature that requires costly geometry relaxations. The analysis of the model parameters demonstrates that the model can effectively learn the chemical information related to the binding site.

5.
J Chem Inf Model ; 59(11): 4742-4749, 2019 11 25.
Artigo em Inglês | MEDLINE | ID: mdl-31644279

RESUMO

The surface energy of inorganic crystals is important in understanding experimentally relevant surface properties and designing materials for many applications. Predictive methods and data sets exist for surface energies of monometallic crystals. However, predicting these properties for bimetallic or more complicated surfaces is an open challenge. Computing cleavage energy is the first step in calculating surface energy across a large space. Here, we present a workflow to predict cleavage energies ab initio using high-throughput DFT and a machine learning framework. We calculated the cleavage energy of 3033 intermetallic alloys with combinations of 36 elements and 47 space groups. This high-throughput workflow was used to seed a database of cleavage energies. The database was used to train a crystal graph convolutional neural network (CGCNN). The CGCNN model provides an accurate prediction of cleavage energy with a mean absolute test error of 0.0071 eV/Å2. It can also qualitatively reproduce nanoparticle surface distributions (Wulff constructions). Our workflow provides quantitative insights into unexplored chemical space by predicting which surfaces are relatively stable and therefore more realistic. The insights allow us to down-select interesting candidates that we can study with robust theoretical and experimental methods for applications such as catalyst screening and nanomaterials synthesis.


Assuntos
Ligas/química , Teoria da Densidade Funcional , Redes Neurais de Computação , Simulação por Computador , Cristalização , Ouro/química , Modelos Químicos , Modelos Moleculares , Propriedades de Superfície , Termodinâmica , Titânio/química
6.
Nat Commun ; 10(1): 3997, 2019 Sep 05.
Artigo em Inglês | MEDLINE | ID: mdl-31488826

RESUMO

Shifting electrochemical oxygen reduction towards 2e- pathway to hydrogen peroxide (H2O2), instead of the traditional 4e- to water, becomes increasingly important as a green method for H2O2 generation. Here, through a flexible control of oxygen reduction pathways on different transition metal single atom coordination in carbon nanotube, we discovered Fe-C-O as an efficient H2O2 catalyst, with an unprecedented onset of 0.822 V versus reversible hydrogen electrode in 0.1 M KOH to deliver 0.1 mA cm-2 H2O2 current, and a high H2O2 selectivity of above 95% in both alkaline and neutral pH. A wide range tuning of 2e-/4e- ORR pathways was achieved via different metal centers or neighboring metalloid coordination. Density functional theory calculations indicate that the Fe-C-O motifs, in a sharp contrast to the well-known Fe-C-N for 4e-, are responsible for the H2O2 pathway. This iron single atom catalyst demonstrated an effective water disinfection as a representative application.

7.
ACS Appl Mater Interfaces ; 11(30): 26863-26871, 2019 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-31310093

RESUMO

With promising activity and stability for the oxygen reduction reaction (ORR), transition metal nitrides are an interesting class of non-platinum group catalysts for polymer electrolyte membrane fuel cells. Here, we report an active thin-film nickel nitride catalyst synthesized through a reactive sputtering method. In rotating disk electrode testing in a 0.1 M HClO4 electrolyte, the crystalline nickel nitride film achieved high activity and selectivity to four-electron ORR. It also exhibited good stability during 10 and 40 h chronoamperometry measurements in acid and alkaline electrolyte, respectively. A combined experiment-theory approach, with detailed ex situ materials characterization and density functional theory calculations, provides insight into the structure of the catalyst and its surface during catalysis. Design strategies for activity and stability improvement through alloying and nanostructuring are discussed.

8.
J Phys Chem Lett ; 10(15): 4401-4408, 2019 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31310543

RESUMO

High-throughput screening of catalysts can be performed using density functional theory calculations to predict catalytic properties, often correlated with adsorbate binding energies. However, more complete investigations would require an order of 2 more calculations compared to the current approach, making the computational cost a bottleneck. Recently developed machine-learning methods have been demonstrated to predict these properties from hand-crafted features but have struggled to scale to large composition spaces or complex active sites. Here, we present an application of a deep-learning convolutional neural network of atomic surface structures using atomic and Voronoi polyhedra-based neighbor information. The model effectively learns the most important surface features to predict binding energies. Our method predicts CO and H binding energies after training with 12 000 data for each adsorbate with a mean absolute error of 0.15 eV for a diverse chemical space. Our method is also capable of creating saliency maps that determine atomic contributions to binding energies.

9.
ACS Appl Mater Interfaces ; 11(2): 2006-2013, 2019 Jan 16.
Artigo em Inglês | MEDLINE | ID: mdl-30582334

RESUMO

Developing cost-effective oxygen electrocatalysts with high activity and stability is key to their commercialization. However, economical earth-abundant catalysts based on first-row transition-metal oxides suffer from low electrochemical stability, which is difficult to improve without compromising their activity. Here, using density functional theory calculations, we demonstrate that noble-metal supports lead to bifunctional enhancement of both the stability and the oxygen reduction reaction (ORR) activity of metal (oxy-hydro) oxide nanoislands. We observe a significant stabilization of supported nanoislands beyond the intrinsic stability limits of bulk phases, which originates from a favorable lattice mismatch and reductive charge transfer from oxophilic supports. We discover that interfacial active sites (located between the nanoisland and the support) reinforce the binding strength of reaction intermediates, hence boosting ORR activity. Considering that both stability and activity lead to discovery of CoOOH|Pt, NiOOH|Ag, and FeO2|Ag as viable systems for alkaline ORR, we then use a multivariant linear regression method to identify elementary descriptors for efficient screening of promising cost-effective nanoisland|support catalysts.

10.
J Chem Inf Model ; 58(12): 2392-2400, 2018 12 24.
Artigo em Inglês | MEDLINE | ID: mdl-30453739

RESUMO

The rising application of informatics and data science tools for studying inorganic crystals and small molecules has revolutionized approaches to materials discovery and driven the development of accurate machine learning structure/property relationships. We discuss how informatics tools can accelerate research, and we present various combinations of workflows, databases, and surrogate models in the literature. This paradigm has been slower to infiltrate the catalysis community due to larger configuration spaces, difficulty in describing necessary calculations, and thermodynamic/kinetic quantities that require many interdependent calculations. We present our own informatics tool that uses dynamic dependency graphs to share, organize, and schedule calculations to enable new, flexible research workflows in surface science. This approach is illustrated for the large-scale screening of intermetallic surfaces for electrochemical catalyst activity. Similar approaches will be important to bring the benefits of informatics and data science to surface science research. Lastly, we provide our perspective on when to use these tools and considerations when creating them.


Assuntos
Simulação por Computador , Bases de Dados de Compostos Químicos , Software , Propriedades de Superfície , Termodinâmica
11.
Phys Chem Chem Phys ; 20(32): 21095-21104, 2018 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-30074598

RESUMO

Novel monolayer-boron (borophene) is a recent addition to the family of 2D materials. In particular, full surface hydrogenation of triangular borophene (borophane (BH)) to passivate empty p orbitals in boron is identified as producing a new stable 2D material that possesses direction-dependent Dirac cones similar to graphene. By a series of density functional theory (DFT) computations, we investigated the potential of single transition metal atoms supported on borophane with vacancies (the TM-BH system) as an efficient ORR/OER electrocatalyst for applications in renewable energy technologies. In TM-BH systems, the coupling of d-orbitals of the TM dopant with the p-orbitals of surrounding boron atoms results in an increase in the density of states near the Fermi-level generating active sites to facilitate the ORR/OER via an efficient four-electron transfer mechanism. Among the considered TM-BH systems, Fe-BH and Rh-BH were found to be promising ORR electrocatalysts with overpotentials (ηORR) of 0.43 V and 0.47 V, respectively, whereas, for the OER, Rh-BH with 0.24 V has the smallest ηOER value followed by Co-BH (0.37 V), under the equilibrium electrode potential. These ηORR and ηOER values indicate higher activities than the current most active ORR (Pt(111) (0.63 V)) and OER (rutile-type RuO2 (0.37 V)) electrocatalysts.

12.
Chem Sci ; 9(23): 5152-5159, 2018 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-29997867

RESUMO

In a conventional chemisorption model, the d-band center theory (augmented sometimes with the upper edge of the d-band for improved accuracy) plays a central role in predicting adsorption energies and catalytic activity as a function of the d-band center of solid surfaces, but it requires density functional calculations that can be quite costly for the purposes of large scale screening of materials. In this work, we propose to use the d-band width of the muffin-tin orbital theory (to account for the local coordination environment) plus electronegativity (to account for adsorbate renormalization) as a simple set of alternative descriptors for chemisorption which do not require ab initio calculations for large-scale first-hand screening. This pair of descriptors is then combined with machine learning methods, namely, neural network (NN) and kernel ridge regression (KRR). We show, for a toy set of 263 alloy systems, that the CO adsorption energy on the (100) facet can be predicted with a mean absolute deviation error of 0.05 eV. We achieved this high accuracy by utilizing an active learning algorithm, without which the accuracy was 0.18 eV. In addition, the results of testing the method with other facets such as (111) terrace and (211) step sites suggest that the present model is also capable of handling different coordination environments effectively. As an example of the practical application of this machine, we identified Cu3Y@Cu* as an active and cost-effective electrochemical CO2 reduction catalyst to produce CO with an overpotential ∼1 V lower than a Au catalyst.

13.
Nat Commun ; 9(1): 2235, 2018 06 08.
Artigo em Inglês | MEDLINE | ID: mdl-29884825

RESUMO

Despite numerous studies, the origin of the enhanced catalytic performance of bimetallic nanoparticles (NPs) remains elusive because of the ever-changing surface structures, compositions, and oxidation states of NPs under reaction conditions. An effective strategy for obtaining critical clues for the phenomenon is real-time quantitative detection of hot electrons induced by a chemical reaction on the catalysts. Here, we investigate hot electrons excited on PtCo bimetallic NPs during H2 oxidation by measuring the chemicurrent on a catalytic nanodiode while changing the Pt composition of the NPs. We reveal that the presence of a CoO/Pt interface enables efficient transport of electrons and higher catalytic activity for PtCo NPs. These results are consistent with theoretical calculations suggesting that lower activation energy and higher exothermicity are required for the reaction at the CoO/Pt interface.

14.
Chem Sci ; 9(2): 483-487, 2018 Jan 14.
Artigo em Inglês | MEDLINE | ID: mdl-29629117

RESUMO

Designing highly selective and energy-efficient electrocatalysts to minimize the competitive hydrogen evolution reaction in the electrochemical reduction of aqueous CO2 remains a challenge. In this study, we report that doping Pd with a small amount of Te could selectively convert CO2 to CO with a low overpotential. The PdTe/few-layer graphene (FLG) catalyst with a Pd/Te molar ratio of 1 : 0.05 displayed a maximum CO faradaic efficiency of about 90% at -0.8 V (vs. a reversible hydrogen electrode, RHE), CO partial current density of 4.4 mA cm-2, and CO formation turnover frequency of 0.14 s-1 at -1.0 V (vs. a RHE), which were 3.7-, 4.3-, and 10-fold higher than those of a Pd/FLG catalyst, respectively. Density functional calculations showed that Te adatoms preferentially bind at the terrace sites of Pd, thereby suppressing undesired hydrogen evolution, whereas CO2 adsorption and activation occurred on the high index sites of Pd to produce CO.

15.
Nat Commun ; 8(1): 1449, 2017 11 13.
Artigo em Inglês | MEDLINE | ID: mdl-29129907

RESUMO

The selection of oxide materials for catalyzing the oxygen evolution reaction in acid-based electrolyzers must be guided by the proper balance between activity, stability and conductivity-a challenging mission of great importance for delivering affordable and environmentally friendly hydrogen. Here we report that the highly conductive nanoporous architecture of an iridium oxide shell on a metallic iridium core, formed through the fast dealloying of osmium from an Ir25Os75 alloy, exhibits an exceptional balance between oxygen evolution activity and stability as quantified by the activity-stability factor. On the basis of this metric, the nanoporous Ir/IrO2 morphology of dealloyed Ir25Os75 shows a factor of ~30 improvement in activity-stability factor relative to conventional iridium-based oxide materials, and an ~8 times improvement over dealloyed Ir25Os75 nanoparticles due to optimized stability and conductivity, respectively. We propose that the activity-stability factor is a key "metric" for determining the technological relevance of oxide-based anodic water electrolyzer catalysts.

16.
Chem Sci ; 8(2): 1090-1096, 2017 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-28451248

RESUMO

A single-atom catalyst (SAC) has an electronic structure that is very different from its bulk counterparts, and has shown an unexpectedly high specific activity with a significant reduction in noble metal usage for CO oxidation, fuel cell and hydrogen evolution applications, although physical origins of such performance enhancements are still poorly understood. Herein, by means of density functional theory (DFT) calculations, we for the first time investigate the great potential of single atom catalysts for CO2 electroreduction applications. In particular, we study a single transition metal atom anchored on defective graphene with single or double vacancies, denoted M@sv-Gr or M@dv-Gr, where M = Ag, Au, Co, Cu, Fe, Ir, Ni, Os, Pd, Pt, Rh or Ru, as a CO2 reduction catalyst. Many SACs are indeed shown to be highly selective for the CO2 reduction reaction over a competitive H2 evolution reaction due to favorable adsorption of carboxyl (*COOH) or formate (*OCHO) over hydrogen (*H) on the catalysts. On the basis of free energy profiles, we identified several promising candidate materials for different products; Ni@dv-Gr (limiting potential UL = -0.41 V) and Pt@dv-Gr (-0.27 V) for CH3OH production, and Os@dv-Gr (-0.52 V) and Ru@dv-Gr (-0.52 V) for CH4 production. In particular, the Pt@dv-Gr catalyst shows remarkable reduction in the limiting potential for CH3OH production compared to any existing catalysts, synthesized or predicted. To understand the origin of the activity enhancement of SACs, we find that the lack of an atomic ensemble for adsorbate binding and the unique electronic structure of the single atom catalysts as well as orbital interaction play an important role, contributing to binding energies of SACs that deviate considerably from the conventional scaling relation of bulk transition metals.

17.
ACS Appl Mater Interfaces ; 8(35): 23022-7, 2016 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-27526778

RESUMO

Gold is known currently as the most active single-element electrocatalyst for CO2 electroreduction reaction to CO. In this work, we combine Au with a second metal element, Cu, to reduce the amount of precious metal content by increasing the surface-to-mass ratio and to achieve comparable activity to Au-based catalysts. In particular, we demonstrate that the introduction of a Au-Cu bifunctional "interface" is more beneficial than a simple and conventional homogeneous alloying of Au and Cu in stabilizing the key intermediate species, *COOH. The main advantages of the proposed metal-metal bifunctional interfacial catalyst over the bimetallic alloys include that (1) utilization of active materials is improved, and (2) intrinsic properties of metals are less affected in bifunctional catalysts than in alloys, which can then facilitate a rational bifunctional design. These results demonstrate for the first time the importance of metal-metal interfaces and morphology, rather than the simple mixing of the two metals homogeneously, for enhanced catalytic synergies.

18.
Phys Chem Chem Phys ; 18(13): 9161-6, 2016 Apr 07.
Artigo em Inglês | MEDLINE | ID: mdl-26974401

RESUMO

We theoretically investigate the electrochemical N2 reduction reaction (NRR) mechanism to produce NH3 on the Ru catalyst. All possible N-N dissociation steps during the reduction processes were evaluated along with the conventional associative and dissociative pathways. Based on the calculated free energy diagrams, it is revealed that the kinetically facile intermediate dissociative pathways during the NRR require a thermodynamic limiting potential (-0.71 V) similar to the associative pathway (-0.68 V), although the initial dissociative pathway as in the Haber-Bosch process has a substantial kinetic barrier for the N-N bond dissociation. The competitive hydrogen evolution is found to be a major hurdle for achieving a high efficiency for the electrochemical nitrogen reduction. In the low overpotential region, the hydrogen adsorption is thermodynamically more favorable than the protonation of N2, thereby reducing the number of active sites for the N2 activation. A comparison of free energies in the presence of different H-coverages on the Ru further demonstrates that the H-coverage can significantly increase the energy barrier for the first protonation of N2, resulting in a change of the potential determining step and an increase in the overpotentials.

19.
Phys Chem Chem Phys ; 18(14): 9652-7, 2016 Apr 14.
Artigo em Inglês | MEDLINE | ID: mdl-26996154

RESUMO

While achieving high product selectivity is one of the major challenges of the CO2 electroreduction technology in general, Pb is one of the few examples with high selectivity that produces formic acid almost exclusively (versus H2, CO, or other byproducts). In this work, we study the mechanism of CO2 electroreduction reactions using Pb to understand the origin of high formic acid selectivity. In particular, we first assess the proton-assisted mechanism proposed in the literature using density functional calculations and find that it cannot fully explain the previous selectivity experiments for the Pb electrode. We then suggest an alternative proton-coupled-electron-transfer mechanism consistent with existing observations, and further validate a new mechanism by experimentally measuring and comparing the onset potentials for CO2 reduction vs. H2 production. We find that the origin of a high selectivity of the Pb catalyst for HCOOH production over CO and H2 lies in the strong O-affinitive and weak C-, H-affinitive characteristics of Pb, leading to the involvement of the *OCHO species as a key intermediate to produce HCOOH exclusively and preventing unwanted H2 production at the same time.

20.
Sci Rep ; 4: 4225, 2014 Feb 27.
Artigo em Inglês | MEDLINE | ID: mdl-24573326

RESUMO

Most Li-O2 batteries suffer from sluggish kinetics during oxygen evolution reactions (OERs). To overcome this drawback, we take the lesson from other catalysis researches that showed improved catalytic activities by employing metal alloy catalysts. Such research effort has led us to find Pt3Co nanoparticles as an effective OER catalyst in Li-O2 batteries. The superior catalytic activity was reflected in the substantially decreased overpotentials and improved cycling/rate performance compared to those of other catalysts. Density functional theory calculations suggested that the low OER overpotentials are associated with the reduced adsorption strength of LiO2 on the outermost Pt catalytic sites. Also, the alloy catalyst generates amorphous Li2O2 conformally coated around the catalyst and thus facilitates easier decomposition and higher reversibility. This investigation conveys an important message that understanding elementary reactions and surface charge engineering of air-catalysts are one of the most effective approaches in resolving the chronic sluggish charging kinetics in Li-O2 batteries.

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