Microkinetic Modeling and Reduced Rate Expressions of Ethylene Hydrogenation and Ethane Hydrogenolysis on Platinum

Catalytic Upcycling of Polyolefins

The large production volumes of commodity polyolefins (specifically, polyethylene, polypropylene, polystyrene, and poly(vinyl chloride)), in conjunction with their low unit values and multitude of short-term uses, have resulted in a significant and pressing waste management challenge. Only a small fraction of these polyolefins is currently mechanically recycled, with the rest being incinerated, accumulating in landfills, or leaking into the natural environment. Since polyolefins are energy-rich materials, there is considerable interest in recouping some of their chemical value while simultaneously motivating more responsible end-of-life management. An emerging strategy is catalytic depolymerization, in which a portion of the C-C bonds in the polyolefin backbone is broken with the assistance of a catalyst and, in some cases, additional small molecule reagents. When the products are small molecules or materials with higher value in their own right, or as chemical feedstocks, the process is called upcycling. This review summarizes recent progress for four major catalytic upcycling strategies: hydrogenolysis, (hydro)cracking, tandem processes involving metathesis, and selective oxidation. Key considerations include macromolecular reaction mechanisms relative to small molecule mechanisms, catalyst design for macromolecular transformations, and the effect of process conditions on product selectivity. Metrics for describing polyolefin upcycling are critically evaluated, and an outlook for future advances is described.

Activation by O2 of AgxPd1-x Alloy Catalysts for Ethylene Hydrogenation

A composition spread alloy film (CSAF) spanning all of AgxPd1-x composition space, xPd = 0 → 1, was used to study catalytic ethylene hydrogenation with and without the presence of O2 in the feed gas. High-throughput measurements of the ethylene hydrogenation activity of AgxPd1-x alloys were performed at 100 Pd compositions spanning xPd = 0 → 1. The extent of ethylene hydrogenation was measured versus xPd at reaction temperatures spanning T = 300 → 405 K and inlet hydrogen partial pressures spanning PH2in = 70 → 690 Torr. The inlet ethylene partial pressure was constant at PC2H4in = 25 Torr, and the O2 inlet partial pressure was either PO2in = 0 or 15 Torr. When PO2in = 0 Torr, only those alloys with xPd ≥ 0.90 displayed observable ethylene hydrogenation activity. As expected, the most active catalyst was pure Pd, which yielded a maximum conversion of ∼0.4 at T = 405 K and PH2in = 690 Torr. Adding a constant O2 partial pressure of PO2in = 15 Torr to the feed stream dramatically increased the catalytic activity across the CSAF at all experimental conditions and catalyst compositions without inducing catalytic ethylene combustion and without measurable O2 consumption. The presence of PO2in = 15 Torr more than doubled the maximum achievable conversion on Pd to ∼0.9 and activated alloys with as little as xPd = 0.6 for ethylene hydrogenation. Measurement of the reaction order with respect to hydrogen, nH2, showed that nH2 ≈ 0 when PO2in = 15 Torr on high xPd alloys but that nH2 increases to values between 0.5 and 1 as xPd decreases or when PO2in = 0 Torr. We attribute this PO2in-induced change in nH2 to a change in the reaction mechanism resulting from different functional catalyst surfaces: one that is O2-activated and Pd-rich and one that is Ag-capped with low activity. Both are extremely sensitive to the bulk alloy composition, xPd, and the reaction temperature, T. These results show that the activity of AgPd catalysts for ethylene hydrogenation depends strongly on the operational conditions. Furthermore, we demonstrate that the exposure of AgPd catalysts to 15 Torr of O2 at moderate temperatures leads to enhanced catalyst performance, presumably by stimulating both Pd segregation to the topmost surface and Pd activation for ethylene hydrogenation.

Nonlinear Reactor Design Optimization With Embedded Microkinetic Model Information

Despite the success of multiscale modeling in science and engineering, embedding molecular-level information into nonlinear reactor design and control optimization problems remains challenging. In this work, we propose a computationally tractable scale-bridging approach that incorporates information from multi-product microkinetic (MK) models with thousands of rates and chemical species into nonlinear reactor design optimization problems. We demonstrate reduced-order kinetic (ROK) modeling approaches for catalytic oligomerization in shale gas processing. We assemble a library of six candidate ROK models based on literature and MK model structure. We find that three metrics—quality of fit (e.g., mean squared logarithmic error), thermodynamic consistency (e.g., low conversion of exothermic reactions at high temperatures), and model identifiability—are all necessary to train and select ROK models. The ROK models that closely mimic the structure of the MK model offer the best compromise to emulate the product distribution. Using the four best ROK models, we optimize the temperature profiles in staged reactors to maximize conversions to heavier oligomerization products. The optimal temperature starts at 630–900K and monotonically decreases to approximately 560 K in the final stage, depending on the choice of ROK model. For all models, staging increases heavier olefin production by 2.5% and there is minimal benefit to more than four stages. The choice of ROK model, i.e., model-form uncertainty, results in a 22% difference in the objective function, which is twice the impact of parametric uncertainty; we demonstrate sequential eigendecomposition of the Fisher information matrix to identify and fix sloppy model parameters, which allows for more reliable estimation of the covariance of the identifiable calibrated model parameters. First-order uncertainty propagation determines this parametric uncertainty induces less than a 10% variability in the reactor optimization objective function. This result highlights the importance of quantifying model-form uncertainty, in addition to parametric uncertainty, in multi-scale reactor and process design and optimization. Moreover, the fast dynamic optimization solution times suggest the ROK strategy is suitable for incorporating molecular information in sequential modular or equation-oriented process simulation and optimization frameworks.

Automated exploitation of the big configuration space of large adsorbates on transition metals reveals chemistry feasibility

Mechanistic understanding of large molecule conversion and the discovery of suitable heterogeneous catalysts have been lagging due to the combinatorial inventory of intermediates and the inability of humans to enumerate all structures. Here, we introduce an automated framework to predict stable configurations on transition metal surfaces and demonstrate its validity for adsorbates with up to 6 carbon and oxygen atoms on 11 metals, enabling the exploration of ~10⁸ potential configurations. It combines a graph enumeration platform, force field, multi-fidelity DFT calculations, and first-principles trained machine learning. Clusters in the data reveal groups of catalysts stabilizing different structures and expose selective catalysts for showcase transformations, such as the ethylene epoxidation on Ag and Cu and the lack of C-C scission chemistry on Au. Deviations from the commonly assumed atom valency rule of small adsorbates are also manifested. This library can be leveraged to identify catalysts for converting large molecules computationally.

The discovery of heterogeneous catalysts for large molecule conversion has been lagging due to the combinatorial inventory of intermediates. Here, the author presents an automated framework to explore the chemical space of reaction intermediates.

Polyolefin plastic waste hydroconversion to fuels, lubricants, and waxes: a comparative study

A direct comparison of the recent advancements in the hydrogenolysis and hydrocracking of polyolefins is lacking. This perspective aims to address this gap while providing insights from model alkane studies to guide future research.

Learning Chemistry of Complex Reaction Systems via a Python First-Principles Reaction Rule Stencil (pReSt) Generator

Complex reaction networks can be generated with automated network generators from initial reactants and reaction rules. Reaction rule specification is central to network generation. These reaction rules are, at present, user-defined based on (intuitive) expert knowledge of chemistry and are often transferred from gas-phase to surface processes. The catalyst active site geometry is usually left out but is often responsible for selectivity. We propose a first-principles-based reaction mechanism generation framework using density functional theory (DFT) data of published reaction mechanisms. The framework "learns the chemistry" from published mechanisms. It can generate reaction networks not studied before, "flag" reactions not seen before for further DFT convergence tests, and easily reconcile differences between catalysts and reactants that may introduce new pathways never seen before. As such, it can be a diagnostic tool for data (mechanism) quality assessment and novel pathway discovery to new molecules. A software, the Python Reaction Stencil (pReSt), was developed for this purpose to wrap around automatic mechanism generation software. Multiple catalytic chemistries are considered to show the efficacy of the proposed framework.

Ab Initio Multiscale Process Modeling of Ethane, Propane and Butane Dehydrogenation Reactions: A Review

Olefins are among the most important structural building blocks for a plethora of chemical reaction products, including petrochemicals, biomaterials and pharmaceuticals. An ever-increasing economic demand has urged scientists, engineers and industry to develop novel technical methods for the dehydrogenation of parent alkane molecules. In particular, the catalysis over precious metal or metal oxide catalysts has been put forward as an alternative way route to thermal-, steam- and fluid catalytic cracking (FCC). Multiscale system modeling as a tool to theoretically understand processes has in the past decade period evolved from a rudimentary measurement-complementing approach to a useful engineering environment. Not only can it predict various experimentally obtained parameters, such as conversion, activity, and selectivity, but it can help us to simulate trends, when changing applicative operating conditions, such as surface gas temperature or pressure, or even support us in the search for the type of materials, their geometrical properties and phases for a better functional performance. An overview of the current set state of the art for saturated organic short chain hydrocarbons (ethane, propane and butane) is presented. Studies that combine at least two different dimensional scales, ranging from atomistic-, bridging across mechanistic mesoscale kinetics, towards reactor- or macroscale, are focused on. Insights considering reactivity are compared.

Surface chemistry dictates stability and oxidation state of supported single metal catalyst atoms

Single atom catalysts receive considerable attention due to reducing noble metal utilization and potentially eliminating certain side reactions. Yet, the rational design of highly reactive and stable single atom catalysts is hampered by the current lack of fundamental insights at the single atom limit. Here, density functional theory calculations are performed for a prototype reaction, namely CO oxidation, over different single metal atoms supported on alumina. The governing reaction mechanisms and scaling relations are identified using microkinetic modeling and principal component analysis, respectively. A large change in the oxophilicity of the supported single metal atom leads to changes in the rate-determining step and the catalyst resting state. Multi-response surfaces are introduced and built cheaply using a descriptor-based, closed form kinetic model to describe simultaneously the activity, stability, and oxidation state of single metal atom catalysts. A double peaked volcano in activity is observed due to competing rate-determining steps and catalytic cycles. Reaction orders of reactants provide excellent kinetic signatures of the catalyst state. Importantly, the surface chemistry determines the stability, oxidation, and resting state of the catalyst.

Development and Assessment of a Criterion for the Application of Brønsted-Evans-Polanyi Relations for Dissociation Catalytic Reactions at Surfaces

We propose and assess a criterion for the application of Brønsted–Evans–Polanyi (BEP) relations for dissociation reactions at surfaces. A theory-to-theory comparison with density functional theory calculations is presented on different reactions, metal catalysts, and surface terminations. In particular, the activation energies of CH, CO, and trans-COOH dissociation reactions on (100), (110), (111), and (211) surfaces of Ni, Cu, Rh, Pd, Ag, and Pt are considered. We show that both the activation energy and the reaction energy can be decomposed into two contributions that reflect the influence of reactant and products in determining either the activation energy or the reaction energy. We show that the applicability of the BEP relation implies that the reaction energy and activation energy correlate to these two contributions in the range of conditions to be described by the BEP relation. A lack of correlation between these components for the activation energy is related to a change in the character of the transition state (TS) and this turns out to be incompatible with a BEP relation because it results in a change of the slope of the BEP relation. Our analysis reveals that these two contributions follow the same trends for the activation energy and for the reaction energy when the path is not characterized either by the formation of stable intermediates or by the change of the binding mechanism of the reactant. As such, one can assess whether a BEP relation can be applied or not for a set of conditions only by means of thermochemical calculations and without requiring the identification of the TS along the reaction pathway. We provide evidence that this criterion can be successfully applied for the preliminary discrimination of the applicability of the BEP relations. For instance, on the one hand, our analysis provides evidence that the two contributions are fully anticorrelated for the trans-COOH dissociation reactions on different metals and surfaces, thus revealing that the reaction is characterized by a change in the TS character. In this situation, no BEP relation can be used to describe the activation energy trend among the different metals and surfaces in full agreement with our DFT calculations. On the other hand, our criterion reveals that the TS character is not expected to change for CH dissociation reactions both for the same facet, different metals and for same metal, different facets, in good agreement with the DFT calculations of the activation energy. The formation of multiple stable intermediates along the reaction pathways and the change of the binding mechanism of one of the reactants are demonstrated to affect the validity of the criterion. As a whole, our findings make possible an assessment of the applicability of the BEP relation and paves the way toward its use for the exploration of complex reaction networks for different metals and surfaces.