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The atomic scale structure of the active sites in heterogeneous catalysts is central to their reactivity and selectivity. Therefore, understanding active site stability and evolution under different reaction conditions is key to the design of efficient and robust catalysts. Herein we describe theoretical calculations which predict that carbon monoxide can be used to stabilize different active site geometries in bimetallic alloys and then demonstrate experimentally that the same PdAu bimetallic catalyst can be transitioned between a single-atom alloy and a Pd cluster phase. Each state of the catalyst exhibits distinct selectivity for the dehydrogenation of ethanol reaction with the single-atom alloy phase exhibiting high selectivity to acetaldehyde and hydrogen versus a range of products from Pd clusters. First-principles based Monte Carlo calculations explain the origin of this active site ensemble size tuning effect, and this work serves as a demonstration of what should be a general phenomenon that enables in situ control over catalyst selectivity. Single-atom alloys are promising catalysts for a number of different reactions. Here, the authors demonstrate that carbon monoxide can be used to transition a PdAu catalyst between a single atom and a cluster phase which exhibit distinct selectivities for ethanol dehydrogenation.

The recent availability of shale gas has led to a renewed interest in C-H bond activation as the first step towards the synthesis of fuels and fine chemicals. Heterogeneous catalysts based on Ni and Pt can perform this chemistry, but deactivate easily due to coke formation. Cu-based catalysts are not practical due to high C-H activation barriers, but their weaker binding to adsorbates offers resilience to coking. Using Pt/Cu single-atom alloys (SAAs), we examine C-H activation in a number of systems including methyl groups, methane and butane using a combination of simulations, surface science and catalysis studies. We find that Pt/Cu SAAs activate C-H bonds more efficiently than Cu, are stable for days under realistic operating conditions, and avoid the problem of coking typically encountered with Pt. Pt/Cu SAAs therefore offer a new approach to coke-resistant C-H activation chemistry, with the added economic benefit that the precious metal is diluted at the atomic limit.

Fine-grained sandstones, siltstones, and shales have become increasingly important to satisfy the ever-growing global energy demands. Of particular current interest are shale rocks, which are mudstones made up of organic and inorganic constituents of varying pore sizes. These materials exhibit high heterogeneity, low porosity, varying chemical composition and low pore connectivity. Due to the complexity and the importance of such materials, many experimental, theoretical and computational efforts have attempted to quantify the impact of rock features on fluids diffusivity and ultimately on permeability. In this study, we introduce a stochastic kinetic Monte Carlo approach developed to simulate fluid transport. The features of this approach allow us to discuss the applicability of 2D vs 3D models for the calculation of transport properties. It is found that a successful model should consider realistic 3D pore networks consisting of pore bodies that communicate via pore throats, which however requires a prohibitive amount of computational resources. To overcome current limitations, we present a rigorous protocol to stochastically generate synthetic 3D pore networks in which pore features can be isolated and varied systematically and individually. These synthetic networks do not correspond to real sample scenarios but are crucial to achieve a systematic evaluation of the pore features on the transport properties. Using this protocol, we quantify the contribution of the pore network’s connectivity, porosity, mineralogy, and pore throat width distribution on the diffusivity of supercritical methane. A sensitivity analysis is conducted to rank the significance of the various network features on methane diffusivity. Connectivity is found to be the most important descriptor, followed by pore throat width distribution and porosity. Based on such insights, recommendations are provided on possible technological approaches to enhance fluid transport through shale rocks and equally complex pore networks. The purpose of this work is to identify the significance of various pore network characteristics using a stochastic KMC algorithm to simulate the transport of fluids. Our findings could be relevant for applications that make use of porous media, ranging from catalysis to radioactive waste management, and from environmental remediation to shale gas production.

Catalytic surface reaction networks exhibit nonlinear dissipative phenomena, such as bistability. Macroscopic rate law descriptions predict that the reaction system resides on one of the two steady-state branches of the bistable region for an indefinite period of time. However, the smaller the catalytic surface, the greater the influence of coverage fluctuations, given that their amplitude normally scales as the square root of the system size. Thus, one can observe fluctuation-induced transitions between the steady-states. In this work, a model for the bistable catalytic CO oxidation on small surfaces is studied. After a brief introduction of the average stochastic modelling framework and its corresponding deterministic limit, we discuss the non-equilibrium conditions necessary for bistability. The entropy production rate, an important thermodynamic quantity measuring dissipation in a system, is compared across the two approaches. We conclude that, in our catalytic model, the most favorable non-equilibrium steady state is not necessary the state with the maximum or minimum entropy production rate.

Single-atom alloys have recently emerged as highly active and selective alloy catalysts. Unlike pure metals, single-atom alloys escape the well-established conceptual framework developed nearly three decades ago for predicting catalytic performance. Although this offers the opportunity to explore so far unattainable chemistries, this leaves us without a simple guide for the design of single-atom alloys able to catalyse targeted reactions. Here, based on thousands of density functional theory calculations, we reveal a 10-electron count rule for the binding of adsorbates on the dopant atoms, usually the active sites, of single-atom alloy surfaces. A simple molecular orbital approach rationalizes this rule and the nature of the adsorbate–dopant interaction. In addition, our intuitive model can accelerate the rational design of single-atom alloy catalysts. Indeed, we illustrate how the unique insights provided by the electron count rule help identify the most promising dopant for an industrially relevant hydrogenation reaction, thereby reducing the number of potential materials by more than one order of magnitude. Single-atom alloys have emerged as highly active and selective catalysts that do not follow the traditional models of heterogeneous catalysis. Now it has been shown that the binding of adsorbates at their surface abides by a simple 10-electron count rule, which can identify promising catalysts for various applications.

Background The lac operon genetic switch is considered as a paradigm of genetic regulation. This system has a positive feedback loop due to the LacY permease boosting its own production by the facilitated transport of inducer into the cell and the subsequent de-repression of the lac operon genes. Previously, we have investigated the effect of stochasticity in an artificial lac operon network at the single cell level by comparing corresponding deterministic and stochastic kinetic models. Results This work focuses on the dynamics of cell populations by incorporating the above kinetic scheme into two Monte Carlo (MC) simulation frameworks. The first MC framework assumes stochastic reaction occurrence, accounts for stochastic DNA duplication, division and partitioning and tracks all daughter cells to obtain the statistics of the entire cell population. In order to better understand how stochastic effects shape cell population distributions, we develop a second framework that assumes deterministic reaction dynamics. By comparing the predictions of the two frameworks, we conclude that stochasticity can create or destroy bimodality, and may enhance phenotypic heterogeneity. Conclusions Our results show how various sources of stochasticity act in synergy with the positive feedback architecture, thereby shaping the behavior at the cell population level. Further, the insights obtained from the present study allow us to construct simpler and less computationally intensive models that can closely approximate the dynamics of heterogeneous cell populations.

Background An adaptive coarse-grained (kinetic) Monte Carlo (ACGMC) simulation framework is applied to reaction and diffusion dynamics in inhomogeneous domains. The presented model is relevant to the diffusion and dimerization dynamics of epidermal growth factor receptor (EGFR) in the presence of plasma membrane heterogeneity and specifically receptor clustering. We perform simulations representing EGFR cluster dissipation in heterogeneous plasma membranes consisting of higher density clusters of receptors surrounded by low population areas using the ACGMC method. We further investigate the effect of key parameters on the cluster lifetime. Results Coarse-graining of dimerization, rather than of diffusion, may lead to computational error. It is shown that the ACGMC method is an effective technique to minimize error in diffusion-reaction processes and is superior to the microscopic kinetic Monte Carlo simulation in terms of computational cost while retaining accuracy. The low computational cost enables sensitivity analysis calculations. Sensitivity analysis indicates that it may be possible to retain clusters of receptors over the time scale of minutes under suitable conditions and the cluster lifetime may depend on both receptor density and cluster size. Conclusions The ACGMC method is an ideal platform to resolve large length and time scales in heterogeneous biological systems well beyond the plasma membrane and the EGFR system studied here. Our results demonstrate that cluster size must be considered in conjunction with receptor density, as they synergistically affect EGFR cluster lifetime. Further, the cluster lifetime being of the order of several seconds suggests that any mechanisms responsible for EGFR aggregation must operate on shorter timescales (at most a fraction of a second), to overcome dissipation and produce stable clusters observed experimentally.

The conversion of oxygen-rich biomass into hydrocarbon fuels requires efficient hydrodeoxygenation catalysts during the upgrading process. However, traditionally prepared CoMoS 2 catalysts, although efficient for hydrodesulfurization, are not appropriate due to their poor activity, sulfur loss and rapid deactivation at elevated temperature. Here, we report the synthesis of MoS 2 monolayer sheets decorated with isolated Co atoms that bond covalently to sulfur vacancies on the basal planes that, when compared with conventionally prepared samples, exhibit superior activity, selectivity and stability for the hydrodeoxygenation of 4-methylphenol to toluene. This higher activity allows the reaction temperature to be reduced from the typically used 300 °C to 180 °C and thus allows the catalysis to proceed without sulfur loss and deactivation. Experimental analysis and density functional theory calculations reveal a large number of sites at the interface between the Co and Mo atoms on the MoS 2 basal surface and we ascribe the higher activity to the presence of sulfur vacancies that are created local to the observed Co–S–Mo interfacial sites. Converting oxygen-rich biomass into fuels requires the removal of oxygen groups through hydrodeoxygenation. MoS 2 monolayer sheets decorated with isolated Co atoms bound to sulfur vacancies in the basal plane have now been synthesized that exhibit superior catalytic activity, selectivity and stability for the hydrodeoxygenation of 4-methylphenol to toluene when compared to conventionally prepared materials.

The catalytic decomposition of ammonia under mild conditions is a promising route for green hydrogen production. However, conventional dissociative ammonia decomposition pathways over metal sites are suffering from the Brønsted−Evans−Polanyi (BEP) constraint which establishes an inverse correlation between atomic N binding energy and the N-H bond dissociation energy. Herein, we report a ruthenium-supported nitrogen-doped cerium oxide (Ru/N-CeO 2 ) catalyst that breaks this limitation and exhibits significantly enhanced catalytic activity compared to its undoped counterpart. Furthermore, we reveal that N dopants can act as independent active sites, enabling an associative mechanism distinct from the conventional Ru-driven pathway. Comprehensive isotopic labelling experiments together with computational techniques elucidate the reaction mechanism over the N site and reveal a distinct correlation between the location of the active site and catalytic activity. The proximal N site exhibits the highest activity, challenging the conventional view that activity is dominated by metal–support interfacial sites. While N doping is a commonly used approach for surface modification, our findings show that it can also alter the reaction mechanism by introducing new active sites. These insights offer valuable guidance for the rational design of catalytic supports in ammonia decomposition and open new directions for catalytic systems limited by scaling relationships in heterogenous catalysis.

Spillover of reactants from one active site to another is important in heterogeneous catalysis but is notoriously hard to detect or control, especially for hydrogen. The hydrogen spillover pathway on a Pd–Cu alloy can now be controlled by reversible adsorption of a spectator molecule. This effect observed during a surface catalysed reaction should prove useful for controlling uptake and release of hydrogen in a model storage system. Spillover of reactants from one active site to another is important in heterogeneous catalysis and has recently been shown to enhance hydrogen storage in a variety of materials 1 , 2 , 3 , 4 , 5 , 6 , 7 . The spillover of hydrogen is notoriously hard to detect or control 1 , 2 , 4 , 5 , 6 . We report herein that the hydrogen spillover pathway on a Pd/Cu alloy can be controlled by reversible adsorption of a spectator molecule. Pd atoms in the Cu surface serve as hydrogen dissociation sites from which H atoms can spillover onto surrounding Cu regions. Selective adsorption of CO at these atomic Pd sites is shown to either prevent the uptake of hydrogen on, or inhibit its desorption from, the surface. In this way, the hydrogen coverage on the whole surface can be controlled by molecular adsorption at a minority site, which we term a ‘molecular cork’ effect. We show that the molecular cork effect is present during a surface catalysed hydrogenation reaction and illustrate how it can be used as a method for controlling uptake and release of hydrogen in a model storage system 1 , 2 , 4 , 5 , 6 , 8 .