Abstract Tuning hydrogen evolution cocatalysts to suppress unwanted side and back reactions is critical for obtaining high catalytic efficiency and stability in photocatalysts comprising noble metal particles. The reactivity of such particles on reducible oxidic support materials, such as titania, can be tuned by exploiting the so-called strong metal–support interaction (SMSI). Yet a fundamental understanding of the effect of the SMSI on the catalytic activity remains lacking, in particular in photocatalytic systems. Such insights, however, are crucial for rationally designing catalysts and exploiting the full potential of this phenomenon. Herein, we utilize the photocatalytic gas-phase oxidation of alcohols on Pt-loaded TiO2, in combination with DFT simulations on TiOx/Pt(111), to gain an atomistic understanding of the effects of the SMSI on the hydrogen evolution reaction. We perform heat treatments at different temperatures in vacuum and investigate the resulting photoreactivity of methanol. The measurements show that annealing to 700 K alters the photoactivity depending on cocatalyst loading and the initial degree of titania reduction. Furthermore, scanning tunneling microscopy reveals the effect of temperature on cluster dispersion. Finally, we conduct theoretical simulations on a model system, which suggest that defects in very thin titania films can act as hydrogen evolution centers, outlining a yet unconsidered pathway for hydrogen formation on encapsulated Pt particles.

Catalytic conversion of oxygenated hydrocarbons via aqueous-phase reforming (APR) is a promising catalytic platform for hydrogen production and water remediation. Herein, we apply periodic density functional theory (DFT) calculations to extensively investigate the energetics of methanol (CH3OH) APR on Pt and Pt-Mn catalysts modeled as single-crystal facets, fcc(111), of extended surfaces and understand their catalytic behavior. First, on pure Pt, we find that the preferable path goes through successive hydrogen abstractions from adsorbed CHxOH species to generate hydrogen (H) atoms, which are strongly bound to the Pt(111) surface, resulting in moderate hydrogen poisoning of the surface. The reaction mechanism of CH3OH-APR under high coverage of hydrogen is then investigated under the proper resting-state conditions (at variance with previous theoretical studies that typically investigated low coverage). We determine that H2O dissociation to OH + H is the rate-determining step for CH3OH-APR on high-hydrogen-coverage Pt(111), with an energy barrier of 0.86 eV (and an overall energy barrier of 0.96 eV). We then find that Mn in Pt-Mn alloys at Pt2Mn composition promotes H2O dissociation by reducing the activation barrier to 0.64 eV. Additionally, Mn atoms alleviate hydrogen poisoning issues by decreasing the interaction between hydrogen and Pt surface atoms and promoting hydrogen evolution, in agreement with experimental observations. Finally, to understand the experimental results after Mn leaching out from the catalysts under APR reaction conditions showing that, surprisingly, the reused catalysts still exhibit good catalytic performance, we model systems with very low subsurface Mn content. We find that mitigation of hydrogen poisoning occurs even when the content of Mn doping is low, thus offering a possible rationalization of the experimental puzzle.

Platinum (Pt) nanocatalysts are essential for facilitating the cathodic oxygen reduction reaction in proton exchange membrane fuel cells but suffer from a trade-off between activity and durability. Here we present the design of an ultrafine nanocatalyst comprising Pt nanoparticles with sparsely embedded cobalt oxide clusters (CoO x @Pt). This design exploits strong Pt/oxide interaction, which grants the catalyst its high structural and chemical durability without sacrificing activity. The CoO x @Pt nanocatalyst delivers a high initial mass activity of 1.10 A mg Pt −1 , a rated power density of 1.04 W cm −2 and a Pt utilization of 10.4 W mg Pt −1 in a membrane electrode assembly. It exhibits notably high durability with an unprecedented rated power loss of 7.5% at a demanding ultralow Pt loading after accelerated stress testing . This remarkable activity and durability could offer a long projected lifetime of 15,000 hours and greatly reduce the lifetime-adjusted cost.

Amino acids are key contributors to nitrogenous emissions during biomass pyrolysis, yet the underlying reaction mechanisms governing their thermal degradation remain only partially understood. In this study, we combine systematic reaction path search algorithms with chemical insight and density functional theory (DFT) simulations to investigate the thermal decomposition of glycine (Gly), the simplest amino acid, with a focus on the formation of ammonia (NH3), a major precursor of environmentally harmful NOx species. We derive a comprehensive reaction network for the thermal decomposition of Gly. Notably, we show that, at variance with water (H2O) that can be generated via simple dimerization in the gas phase, NH3 evolution is kinetically unfavorable at moderate temperatures and low-pressure conditions, while it can proceed with much smaller barriers in the condensed phase via many-body mechanisms involving ionic-pair proton-exchange-driven polymerization pathways. Under such conditions, we predict that NH3 evolution competes with H2O formation, reconciling theoretical predictions with experimental observations.

We present an approach to accelerate the construction of reaction energy diagrams and mechanistic pathways of novel bimetallic catalytic systems by exploiting information on a known case, and we test it on the CuPd system for the catalytic decomposition of methanol. Based on machine-learning and conformal techniques for building training databases, our proposal realizes the multicomponent extension of the conformal sampling of catalytic process (CSCP) approach and maintains its same characteristic features of accuracy, efficiency, and throughput, thus in principle enabling a high-throughput screening of catalytic processes across general alloy compositions. Moreover, the so-derived CSCP reactive MLIP describes equally well the pure (Cu, Pd) and bimetallic (CuPd) catalysts, thus enabling a high-throughput screening for the given catalytic process.

The Haber-Bosch (HB) process, critical for global ammonia production, is hindered by its high energy consumption and operational demands, requiring extreme pressures and temperatures. Developing catalysts that reduce these demands while maintaining practical efficiency is essential for achieving sustainable ammonia synthesis. Here, we investigate the FeCoNi(AlSi)0.76 high-entropy alloy (HEA) as a catalyst for the HB process using quantum mechanics (QM) and kinetic Monte Carlo (kMC) simulations. Mechanistic analysis revealed significantly lower reaction barriers compared to pure Fe, and kMC simulations predict an NH3 turnover frequency (TOF) that is 65 times higher than pure Fe under industrial conditions. Under reduced pressure (21 atm) and moderate temperature condition (673 K), the HEA retained half the NH3 production rate of pure Fe at extreme industrial conditions, revealing its potential to reduce energy and pressure requirements. This study demonstrates the promise of HEAs in enabling more energy-efficient and sustainable ammonia production technologies.

Indium is a well-known stability promoter for high-temperature dry reforming reactions but has not yet been applied to other reforming reactions for hydrogen production, such as those of oxygenated compounds which suffer from rapid deactivation. In addition, little is known about the stabilization mechanism and the limited insights mostly come from ex-situ characterizations. Here, we developed an In-modified Ni-based catalyst by synthesizing a Mg-Al-In mixed oxide support and by depositing Ni via a urea-assisted deposition procedure. The catalyst was evaluated in the steam reforming reaction of acetic acid showing stable activity for more than 24 h at 700 degrees C and S/C = 3 corresponding to double the hydrogen productivity than the unpromoted catalyst which, on the contrary, was not stable. Superior stability was achieved also with glycerol. We then investigated the catalysts under operando conditions performing a quasi-simultaneous XAS and XRD experiment using synchrotron light, assisted by computational modeling. After reduction, the surface of the Ni nanoparticles is enriched with In, as confirmed by TEM-EDS, in the form of a shell consisting of a Ni3In-like phase. The presence of In in the surface layers competes with C insertion thus protecting the Ni particles from coke deposition. As the reaction proceeds, the intermetallic phase is consumed resulting in Ni nanoparticles that are more stable, although less active, than those of the unpromoted catalyst. This may be due to a different faceting caused by the dealloying of the Ni-In phase, which once again disfavors the coke formation.

Platinum (Pt) nanocatalysts are essential for facilitating the cathodic oxygen reduction reaction in proton exchange membrane fuel cells but suffer from a trade-off between activity and durability. Here we present the design of a fine nanocatalyst comprising Pt nanoparticles with sparsely embedded cobalt oxide clusters (CoOx@Pt). This design exploits the strong Pt/oxide interaction, which grants the catalyst its high structural and chemical durability without sacrificing activity. The CoOx@Pt nanocatalyst delivers a high initial mass activity of 1.10 A mgPt-1, a rated power density of 1.04 W cm-2 and a Pt utilization of 10.4 W mgPt-1 in a membrane electrode assembly. It exhibits a notably high durability that features a mass activity retention of 88.2%, a voltage loss of 13.3 mV at 0.8 A cm-2 and a small rated power loss of 7.5% after accelerated stress testing. This durability could offer a long projected lifetime of 15,000 hours and may greatly reduce the lifetime-adjusted cost. Pt-based catalysts are state-of-the-art cathodes in fuel cells, but they experience a trade-off between activity and durability. Now a Pt nanocatalyst with embedded cobalt oxide clusters is shown to promote stability during proton exchange membrane fuel cell operation without sacrificing activity, achieving 88.2% mass activity retention after 30,000 accelerated stress test cycles.

Time-dependent density functional theory (TDDFT) simulations are conducted on a series of chiral gold/silver alloy nanowires to explore whether silver doping can produce an enhancement of circular dichroism at the plasmon resonance in these systems, and to identify the quantum-mechanical origin of the observed effects. We find a strong plasmonic dichroism when one or two helixes of gold atoms are substituted by silver in a linear chiral nanotube, whose pure gold counterpart does not display any plasmonic dichroism, and we rationalize this finding in terms of "decoupling" the destructive interference of excitations in the pure gold nanotube via alloying. However, further attempts to increase the plasmonic dichroism by considering multi-shell gold nanowires in which one entire shell is doped with silver did not produce the desired effect, but rather a decrease in circular dichroism. We show that this latter result is due to a more severe destructive interference in the dipole excitation contributions, and suggest that further amplification should be possible in principle by properly tuning simultaneously the nanowire structure and chemical ordering. Time-dependent density functional theory simulations are conducted on a series of chiral gold/silver alloy nanowires to explore whether silver doping can produce an enhancement of circular dichroism at the plasmon resonance. The quantum-mechanical origin of the observed effects is identified. We find a strong plasmonic dichroism when one or two helixes of gold atoms are substituted by silver in a linear chiral nanotube, whose pure gold counterpart does not display any plasmonic dichroism, and we rationalize this finding in terms of "decoupling" the destructive interference of excitations in the pure gold nanotube via alloying. image

Novel graphene-like nanomaterials with a non-zero bandgap are important for the design of gas sensors. The selectivity toward specific targets can be tuned by introducing appropriate functional groups on their surfaces. In this study, we use first-principles simulations, in the form of density functional theory (DFT), to investigate the covalent functionalization of a single-layer graphitized BC6N with azides to yield aziridine-functionalized adducts and explore their possible use to realize ammonia sensors. First, we determine the most favorable sites for physical adsorption and chemical reaction of methylnitrene, arising from the decomposition of methylazide, onto a BC6N monolayer. Then, we examine the thermodynamics of the [1 + 2]-cycloaddition reaction of various phenylnitrenes and perfluorinated phenylnitrenes para-substituted with (R = CO2H, SO3H) groups, demonstrating favorable energetics. We also monitor the effect of the functionalization on the electronic properties of the nanosheets via density of states and band structure analyses. Finally, we test four dBC6N to gBC6N substrates in the sensing of ammonia. We show that, thanks to their hydrogen bonding capabilities, the functionalized BC6N can selectively detect ammonia, with interaction energies varying from -0.54 eV to -1.37 eV, even in presence of competing gas such as CO2and H2O, as also confirmed by analyzing the change in the electronic properties and the values of recovery times near ambient temperature. Importantly, we model the conductance of a selected substrate alone and in presence of NH3to determine its effect on the integrated current, showing that humidity and coverage conditions should be properly tuned to use HO2C-functionalized BC6N-based nanomaterials to develop selective gas sensors for ammonia.

Assessing the accuracy of first-principles computational approaches is instrumental to predict electronic excitations in metal nanoclusters with quantitative confidence. Here we describe a validation study on the optical response of a set of monolayer-protected clusters (MPC). The photoabsorption spectra of Ag25(DMBT)18-, Ag24Pt(DMBT)182- and Au24Pt(SC4H9)18, where DMBT is 2,4-dimethylbenzenethiolate and SC4H9 is n-butylthiolate, have been obtained at low temperature and compared with accurate TDDFT calculations. An excellent match between theory and experiment, with typical deviations of less than 0.1 eV, was obtained, thereby validating the accuracy and reliability of the proposed computational framework. Moreover, an analysis of the TDDFT simulations allowed us to ascribe all relevant spectral features to specific transitions between occupied/virtual orbital pairs. The doping effect of Pt on the optical response of these ultrasmall MPC systems was identified and discussed.

Computational modeling of catalytic processes at gas/solid interfaces plays an increasingly important role in chemistry, enabling accelerated materials and process optimization and rational design. However, efficiency, accuracy, thoroughness, and throughput must be enhanced to maximize its practical impact. By combining interpolation of DFT energetics via highly accurate Machine-Learning Potentials with conformal techniques for building the training database, we present here an original approach (that we name Conformal Sampling of Catalytic Processes, CSCP), to accelerate and achieve an accurate and thorough sampling of novel systems by exporting existing information on a worked-out case. We use methanol decomposition (of interest in the field of hydrogen production and storage) as a test catalytic reaction. Starting from worked-out Pt-based systems, we show that after only two iterations of active-learning CSCP is able to provide reaction energy diagrams for a set of 7 diverse systems (Pd, Ni, Au, Ag, Cu, Co, Fe) leading to DFT-accuracy-level predictions. Cases exhibiting a change in adsorption sites and mechanisms are also successfully reproduced as tests of catalytic path modification. The CSCP approach thus offers itself as an operative tool to fully take advantage of accumulated information to achieve high-throughput sampling of catalytic processes.

The surface configurations of the low-index facets of a set of spinel oxides are investigated using DFT+U calculations to derive surface energies and predict equilibrium nanoparticle shapes via the Wulff construction. Two very different conditions are investigated, corresponding to application either in heterogeneous catalysis or in electrocatalysis. First, the bare stoichiometric surfaces of NiFe2O4, CoFe2O4, NiCo2O4, and ZnCo2O4 spinels are studied to model their use as high-temperature oxidation catalysts. Second, focusing attention on the electrochemical oxygen evolution reaction (OER) and on the CoFe2O4 inverse spinel as the most promising OER catalyst, we generate surface configurations by adsorbing OER intermediates and, in an innovative study, we recalculate surface energies taking into account adsorption and environmental conditions, i.e., applied electrode potential and O2 pressure. We predict that under OER operating conditions, (111) facets are dominant in CoFe2O4 nanoparticle shapes, in fair agreement with microscopy measurements. Importantly, in the OER case, we predict a strong dependence of nanoparticle shape upon O2 pressure. Increasing O2 pressure increases the size of the higher-index (111) and (110) facets at the expense of the (001) more catalytically active facet, whereas the opposite occurs at low O2 pressure. These predictions should be experimentally verifiable and help define the optimal OER operative conditions.

We present a computational study of the energetics and mechanisms of oxidation of Pt-Mn systems. We use slab models and simulate the oxidation process over the most stable (111) facet at a given Pt2Mn composition to make the problem computationally affordable, and combine Density-Functional Theory (DFT) with neural network potentials and metadynamics simulations to accelerate the mechanistic search. We find, first, that Mn has a strong tendency to alloy with Pt. This tendency is optimally realized when Pt and Mn are mixed in the bulk, but, at a composition in which the Mn content is high enough such as for Pt2Mn, Mn atoms will also be found in the surface outmost layer. These surface Mn atoms can dissociate O2 and generate MnOx species, transforming the surface-alloyed Mn atoms into MnOx surface oxide structures supported on a metallic framework in which one or more vacancy sites are simultaneously created. The thus-formed vacancies promote the successive steps of the oxidation process: the vacancy sites can be filled by surface oxygen atoms, which can then interact with Mn atoms in deeper layers, or subsurface Mn atoms can intercalate into interstitial sites. Both these steps facilitate the extraction of further bulk Mn atoms into MnOx oxide surface structures, and thus the progress of the oxidation process, with typical rate-determining energy barriers in the range 0.9-1.0 eV.

We present a first-principles computational study of the NbS2/WSe2 junction between two transition metal dichalcogenide monolayers as a prototypical metal/semiconductor two-dimensional (2D) lateral heterostructure (LH) to investigate the effects of electrostatic perturbations on electron transport in 2D LH systems. In order to simulate electrostatic (charged or dipolar) defects in the substrate, we introduce ionic systems (LiF lines) properly positioned in two different configurations and study cases, corresponding to modeling two different phenomena: (i) an electrostatic defect in the middle of the semiconducting part of the heterostructure (qualitatively analogous to a gate voltage opposing transmission), and (ii) an electrostatic perturbation realigning and flattening the electrostatic potential along the asymmetric LH junction. In the former case, we determine a substantial decrease of transmission even for small values of the perturbation (providing information that can be used to achieve a quantitative correlation between substrate-induced defectivity and device performance degradation in experiment), whereas in the latter we predict that electron transport can be significantly enhanced by properly tuning external electrostatic perturbations at the interface.

We present a first-principles computational study of the NbS2/WSe2 junction between two transition metal dichalcogenide monolayers as a prototypical metal/semiconductor 2-dimensional (2D) lateral hetero-structure (LH) to investigate the effects of electrostatic perturbations on electron transport in 2D LH systems. In order to simulate electrostatic (charged or dipolar) defects in the substrate, we introduce ionic systems (LiF lines) properly positioned in two different configurations and study cases, corresponding to modeling two different phenomena: (i) an electrostatic defect in the middle of the semiconducting part of the hetero-structure (qualitatively analogous to a gate voltage opposing transmission), and (ii) an electrostatic perturbation re-aligning and flattening the electrostatic potential along the asymmetric LH junction. In the former case, we determine a substantial decrease of transmission even for small values of the perturbation (providing information that can be used to achieve a quantitative correlation between substrate-induced defectivity and device performance degradation in experiment), whereas in the latter we predict that electron transport can be significantly enhanced by properly tuning external electrostatic perturbations at the interface.

We present a first-principles computational study of the NbS2/WSe2 junction between two transition metal dichalcogenide monolayers as a prototypical metal/semiconductor 2-dimensional (2D) lateral hetero-structure (LH) to investigate the effects of electrostatic perturbations on electron transport in 2D LH systems. In order to simulate electrostatic (charged or dipolar) defects in the substrate, we introduce ionic systems (LiF lines) properly positioned in two different configurations and study cases, corresponding to modeling two different phenomena: (i) an electrostatic defect in the middle of the semiconducting part of the hetero-structure (qualitatively analogous to a gate voltage opposing transmission), and (ii) an electrostatic perturbation re-aligning and flattening the electrostatic potential along the asymmetric LH junction. In the former case, we determine a substantial decrease of transmission even for small values of the perturbation (providing information that can be used to achieve a quantitative correlation between substrate-induced defectivity and device performance degradation in experiment), whereas in the latter we predict that electron transport can be significantly enhanced by properly tuning external electrostatic perturbations at the interface.

Monolayer MoS 2 has attracted significant attention owing to its excellent performance as an n‐type semiconductor from the transition metal dichalcogenide (TMDC) family. It is however strongly desired to develop controllable synthesis methods for 2D p‐type MoS 2 , which is crucial for complementary logic applications but remains difficult. In this work, high‐quality NbS 2 –MoS 2 lateral heterostructures are synthesized by one‐step metal–organic chemical vapor deposition (MOCVD) together with monolayer MoS 2 substitutionally doped by Nb, resulting in a p‐type doped behavior. The heterojunction shows a p‐type transfer characteristic with a high on/off current ratio of ≈10 4 , exceeding previously reported values. The band structure through the NbS 2 –MoS 2 heterojunction is investigated by density functional theory (DFT) and quantum transport simulations. This work provides a scalable approach to synthesize substitutionally doped TMDC materials and provides an insight into the interface between 2D metals and semiconductors in lateral heterostructures, which is imperative for the development of next‐generation nanoelectronics and highly integrated devices.

Graphene bearing organic functional groups chemicallytetheredto its surface via covalent bonds can find severalapplications in the sensing of gas, heavy metal ions, and other targetspecies of interest. Herein, we used DFT simulations to study thethermodynamics of graphene functionalization with substituted carbenes,and the use of the resulting adducts to detect gaseous nitrogenatedcompounds focusing on ammonia (NH3), methylamine(MMA), dimethylamine (DMA), and trimethylamine (TMA). We find thatthe modified materials can interact with the amines, selectively alsoin the presence of other gases such as CO2, SO2, H2S, and CH4. Changes in the electronic propertiesof the system upon adsorption such as charge density, Lo''wdinpartial charges, and projected density of states (PDOS) were usedto analyze the interaction. Expected recovery times suggest that thesenanomaterials can be used to detect the nitrogenated compounds hereinvestigated at relatively low temperatures (298 and 373 K). Furthermore,by modeling the conductance of the functionalized graphene bare andin the presence of ammonia, we show that quantum conductance and theintegrated currents are sensitive to functionalization and, importantly,to the presence of ammonia under determined conditions, which in principleallows tuning the sensitivity of the resulting device. Our work thusclarifies the principles governing this phenomenon. Carbene-functionalizedgraphene is concluded to be a potentially good candidate to replacenoble-metal-modified graphene for the detection of ammonia/aminesin chemoresistance or field-effect transistor-based sensors.

Low-dimensional metal-semiconductor vertical heterostructures (VH) are promising candidates in the search of electronic devices at the extreme limits of miniaturization. Within this line of research, here a theoretical/computational study of the NbS2/WSe2 metal-semiconductor vertical hetero-junction using density functional theory (DFT) and conductance simulations is presented. First atomistic models of the NbS2/WSe2 VH considering all the five possible stacking orientations at the interface are constructed, and DFT and quantum-mechanical (QM) scattering simulations are conducted to obtain information on band structure and transmission coefficients. Then an analysis of the QM results in terms of electrostatic potential, fragment decomposition, and band alignment is carried out. The behavior of transmission expected from this analysis is in excellent agreement with, and thus fully rationalizes, the DFT results, and the peculiar double-peak profile of transmission. Finally, maximally localized Wannier functions, projected density of states, and a simple analytic formula to predict and explain quantitatively the differences in transport in the case of epitaxial misorientation are used. Within the class of Transition-Metal Dichalcogenide systems, the NbS2/WSe2 VH exhibits a wide interval of finite transmission and a double-peak profile, features that can be exploited in applications.