Zeolites are widely applied as molecular sieves and porous host materials for active sites in heterogeneous catalysis. Adsorption and reaction kinetics depend critically on the molecular entropy in the zeolite. In this work, we introduce a method to calculate the entropy of molecules in zeolites using Monte Carlo integration of the semiclassical partition function. The method is demonstrated for N-2 and CH4 in chabazite and MFI silicalites. We find that the molecular entropy is lowered by a factor between 1/3 and 1/2 with respect to the gas-phase value. The results are corroborated by explicit molecular dynamics simulations revealing the active molecular degrees of freedom. The possibility of accurate entropy estimations opens up for an improved description of catalytic reactions and sorption phenomena in zeolites.

Modern society depends heavily on heterogeneous catalysis, which creates strong economical and environmental incentives to improve catalyst efficiency. Heterogeneous catalysts are often realized as metal nanoparticles (NPs) supported on oxide surfaces, and catalysts are traditionally developed by trial and error approaches. However, rational catalyst design can be enabled by understanding reactions on the atomic scale. Presently, computational power has matured sufficiently to obtain atomic scale insights into reaction kinetics, directly from first-principles kinetic simulations. This thesis develops the methodologies of first-principles kinetic simulations over NPs. Multiple factors affect modeling of reactions over NPs, such as reaction energy landscapes and entropy changes during reaction. This makes it important to investigate different methodological choices, within kinetic modeling. Herein, Complete Potential Energy Sampling (CPES) is introduced as a method to calculate adsorbate entropy. CPES directly samples the adsorbate potential energy landscape, which allows for systematic improvements over approximate models within mean-field kinetics. CPES is tested on CO-oxidation over Pt(111), where it improves agreement with experimental references. Furthermore, CPES is applied to enable accurate description of molecular entropy in zeolites. Reaction energy landscapes on NPs are challenging to calculate as NPs contain multiple different sites. Thus, NPs are commonly approximated using extended surfaces as model systems. In this thesis, the challenge of mapping out NP reaction energy landscapes is solved pragmatically using scaling relations. Kinetic Monte Carlo simulations are used to investigate the kinetics for CO-oxidation over Pt and selective acetylene hydrogenation over Pd/Cu single-atom alloys. It is found that kinetic couplings between the NP-sites govern the kinetics. The kinetic couplings influence how turnover frequency and selectivity depend on particle size, shape, and strain. Thus, the energetics of isolated sites and extended surface models are found to have limited value as descriptors for NP catalysis.

Understanding reaction kinetics over metal-nanoparticles is central in technical catalyst design. In this Perspective, we compare computational methods to analyze and model reaction kinetics on metal nanoparticles. We discuss energy-barrier and Sabatier analysis, mean-field microkinetic modeling, and kinetic Monte Carlo simulations. By explicit simulations, we show that reactions on metal-nanoparticles are characterized by long-range kinetic couplings, which requires methods that consider coupled site-assemblies. In light of these observations, extended model surfaces may not capture the complexity of nanoparticle-kinetics, and arguments about catalytic performance relying on single energy barriers may be insufficient.

Adsorption and reaction energies on metal surfaces are known to depend sensitively on strain. How such effects influence catalytic reactions over nanoparticles is, however, largely unexplored. Here we investigate the effect of strain on the catalytic performance of CO oxidation over Pt nanoparticles using scaling relations kinetic Monte Carlo simulations. The catalytic activities are compared with the corresponding results for Pt(111). We find that a moderate expansive strain yields higher catalytic activities for both nanoparticles and extended surfaces. The strong kinetic couplings between different sites on nanoparticles makes the particles respond non-linearly to strain. This is in contrast with Pt(111), which shows a linear response to strain. The present work demonstrates the possibilities with strain-engineering and highlights the limitation in extrapolating results from extended surfaces to nanoparticles.

Single-atom alloys, which are prepared by embedding isolated metal sites in host metals, are promising systems for improved catalyst selectivity. For technical applications, catalysts based on nanoparticles are preferred thanks to a large surface area. Herein, we investigate hydrogenation of acetylene to ethylene using kinetic Monte Carlo simulations based on density functional theory and compare the performance of Pd/Cu nanoparticles with Pd(111) and Pd/Cu(111). We find that embedding Pd in Cu systems strongly enhances the selectivity and that the reaction mechanism is fundamentally different for nano-particles and extended surfaces. The reaction mechanism on nanoparticles is complex and involves elementary steps that proceed preferentially over different sites. Edge and corner sites on nanoparticles are predicted to lower the selectivity, and we infer that a rational design strategy in selective acetylene hydrogenation is to maximize the number of (111) sites in relation to edge sites for Pd/Cu nanoparticles.

Kinetic Monte Carlo (kMC) is an essential tool in heterogeneous catalysis enabling the understanding of dominant reaction mechanisms and kinetic bottlenecks. Here we present MonteCoffee, which is a general-purpose object-oriented and programmable kMC application written in python. We outline the implementation and provide examples on how to perform simulations of reactions on surfaces and nanoparticles and how to simulate sorption isotherms in zeolites. By permitting flexible and fast code development, MonteCoffee is a valuable alternative to previous kMC implementations.

Heterogeneous catalysis is an enabling technology that utilises transition metal nanoparticles (NPs) supported on oxides to promote chemical reactions. Structural mismatch at the NP-support interface generates lattice strain that could affect catalytic properties. However, detailed knowledge about strain in supported NPs remains elusive. We experimentally measure the strain at interfaces, surfaces and defects in Pt NPs supported on alumina and ceria with atomic resolution using high-precision scanning transmission electron microscopy. The largest strains are observed at the interfaces and are predominantly compressive. Atomic models of Pt NPs with experimentally measured strain distributions are used for first-principles kinetic Monte Carlo simulations of the CO oxidation reaction. The presence of only a fraction of strained surface atoms is found to affect the turnover frequency. These results provide a quantitative understanding of the relationship between strain and catalytic function and demonstrate that strain engineering can potentially be used for catalyst design.

AbstractIn this paper we present the design and synthesis of 25 new low band gap polymers. The polymers were characterized by UV-vis spectroscopy which showed optical band gaps of 2.0–0.9 eV. The polymers which were soluble enough were applied in organic photovoltaics, both small area devices with a spin coated active layer and in large area modules where all layers including the active layer were either roll-to-roll coated or printed. These experiments showed that the design of polymers compatible with roll-toroll coating is not straightforward and that there are various issues such as donor/acceptor fitting within the polymer, side chains to ensure solubility and HOMO/LUMO level alignment with the acceptor (e.g. [60]PCBM) to take into consideration.

Heterogeneous catalysts are often designed as metal nanoparticles supported on oxide surfaces. Here, the relation between particle morphology and reaction kinetics is investigated by scaling relation kinetic Monte Carlo simulations using CO oxidation over Pt nanoparticles as a model reaction. We find that different particle morphologies result in vastly different catalytic activities. The activity is strongly affected by kinetic couplings between sites, and a wide site distribution generally enhances the activity. The present study highlights the role of site-assemblies as a concept that, in addition to isolated active sites, can be used to understand catalytic reactions over nanoparticles.

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Heterogeneous catalysis is vitally important to modern society, and one path towards rational catalyst design is through atomistic scale understanding. The atomistic scale can be linked to macroscopic observables by microkinetic models based on first-principles calculations. With the increasing accuracy of first-principles methods and growing com- putational resources, it has become important to investigate and further develop the methodology of microkinetic modeling, which is the theme of this thesis. First, a procedure for mean-field microkinetic modeling of reactions over extended surfaces is developed, where complete methane oxidation over Pd(100) and Pd(111) is studied as an example. The model reveals how the main reaction mechanisms depend on reaction conditions, and shows poisoning as well as promotion phenomena. Second, the effect of entropy in microkinetic modeling is investigated, where CO oxidation over Pt(111) is used as a model reaction. Entropy is found to affect reaction kinetics substantially. Moreover, a method named Complete Potential Energy Sampling (CPES) is developed as a flexible tool for estimating adsorbate-entropy. Third, a kinetic Monte Carlo method is developed to bridge the materials gap in het- erogeneous catalysis. The computational cost to map out the complete reaction-energy- landscape on a nanoparticle is high, which is solved herein using generalized coordination numbers as descriptors for reaction energies. CO oxidation over Pt is studied, and nanoparticles are found to behave differently than the corresponding extended surfaces. Moreover, the active site is found to vary with reaction conditions. Finally, the reaction orders and apparent activation energies are coupled to the microscale via the degree of rate control, which enhances the atomistic understanding of reaction kinetics.

The intrinsic activity of Pd(100) and Pd(111) for methane oxidation is investigated by Density Functional Theory (DFT)-based mean-field microkinetic modeling. The model includes 32 reaction steps, and the calculated turnover frequencies together with reaction orders compare favorably with experimental data. On both surfaces, the reaction proceeds via complete dehydrogenation of methane to elemental carbon followed by different mechanisms for carbon oxidization. Pd(100) is found to be more active than Pd(111) at temperatures from 400 to 1000 K. For both surfaces, the reaction order in methane approaches unity with increasing temperature. The reaction order in water is positive at low temperatures owing to water-promoted carbon oxidation. Methane dissociation is the main rate-controlling step for Pd(111), whereas formation of COH and CO is also controlling the rate over Pd(100). The present work uncovers the detailed reaction mechanisms for complete methane oxidation over palladium, which can be used in catalyst design to target the rate-controlling steps.

Scaling relations combined with kinetic Monte Carlo simulations are used to study catalytic reactions on extended metal surfaces and nanoparticles. The reaction energies are obtained by density functional theory calculations, where the site-specific values are derived using generalized coordination numbers. This approach provides a way to handle the materials gap in heterogeneous catalysis. CO oxidation on platinum is investigated as an archetypical reaction. The kinetic simulations reveal clear differences between extended surfaces and nano particles in the size range of 1-5 nm. The presence of different types of sites on nanoparticles results in a turnover frequency that is orders of magnitude larger than on extended surfaces. For nanoparticles, the reaction conditions determine which sites dominate the overall activity. At low pressures and high temperatures, edge and corner sites determine the catalytic activity, whereas facet sites dominate the activity at high pressures and low temperatures. Furthermore, the reaction conditions are found to determine the particle-size dependence of the turnover frequency.

Macroscopic kinetic measurables are linked to elementary reaction steps by the degree of rate control.

Printed electronics is emerging as a new, large scale and cost effective technology that will be disruptive in fields such as energy harvesting, consumer electronics and medical sensors. The performance of printed electronic devices relies principally on the carrier mobility and molecular packing of the polymer semiconductor material. Unfortunately, the analysis of such materials is generally performed with destructive techniques, which are hard to make compatible with in situ measurements, and pose a great obstacle for the mass production of printed electronics devices. A rapid, in situ, non-destructive and low-cost testing method is needed. In this study, we demonstrate that nonlinear optical microscopy is a promising technique to achieve this goal. Using ultrashort laser pulses we stimulate two-photon absorption in a roll coated polymer semiconductor and map the resulting two-photon induced photoluminescence and second harmonic response. We show that, in our experimental conditions, it is possible to relate the total amount of photoluminescence detected to important material properties such as the charge carrier density and the molecular packing of the printed polymer material, all with a spatial resolution of 400 nm. Importantly, this technique can be extended to the real time mapping of the polymer semiconductor film, even during the printing process, in which the high printing speed poses the need for equally high acquisition rates.

The influence of different approximations on adsorbate entropies is investigated for density functional theory based mean-field kinetic modeling. Using CO oxidation over Pt(111) as a prototypical reaction, we compare four approximations: the harmonic approximation, the hindered translator, the free translator, and complete potential energy sampling (CPES). The CPES method results in particularly good agreement with previously measured experimental data. Given its general applicability and moderate computational cost, the CPES method stands out as a preferable option to describe adsorbate entropies.

The passage of time from laboratory demonstration of a technology-enabling efficiency value and until methodology and preparative means are in place is explored in this work for the polymer solar cell. Long technical strides need to be taken and efforts much beyond the laboratory solar cell need to be dedicated to bringing new solar cell material discoveries to service as an industrial technology. This includes scaled materials preparation, scaled manufacturing platforms, scaled installation platforms, as well as scaled electronics, monitoring, and control systems. We epitomize this as the "scaling lag'' and highlight its importance when wishing to progress new solar cell materials from science to technology. The scaling gap is an observable element that can be extracted directly from experimental data and can be taken as a sign of technological maturity that can aid early-phase investors in their decision of when to invest in product development based on new technology.

This review summarizes the recent progress in the stability and lifetime of organic photovoltaics (OPVs). In particular, recently proposed solutions to failure mechanisms in different layers of the device stack are discussed comprising both structural and chemical modifications. Upscaling is additionally discussed from the perspective of stability presenting the challenges associated with device packaging and edge protection. An important part of device stability studies is the characterization, and this review provides a short overview of the most advanced techniques for stability characterization reported recently. Lifetime testing and determination is another challenge in the field of organic solar cells and the final sections of this review discuss the testing protocols as well as the generic marker for device lifetime and the methodology for comparing all the lifetime landmarks in one common diagram. These tools were used to determine the baselines for OPV lifetime tested under different ageing conditions. Finally, the current status of lifetime for organic solar cells is presented and predictions are made for progress in the near future.