Spatial imaging of carbon reactivity centers in Pd/C catalytic systems

Determining the orderliness of carbon materials with nanoparticle imaging and explainable machine learning

Carbon materials have paramount importance in various fields of materials science, from electronic devices to industrial catalysts. The properties of these materials are strongly related to the distribution of defects-irregularities in electron density on their surfaces. Different materials have various distributions and quantities of these defects, which can be imaged using a procedure that involves depositing palladium nanoparticles. The resulting scanning electron microscopy (SEM) images can be characterized by a key descriptor-the ordering of nanoparticle positions. This work presents a highly interpretable machine learning approach for distinguishing between materials with ordered and disordered arrangements of defects marked by nanoparticle attachment. The influence of the degree of ordering was experimentally evaluated on the example of catalysis via chemical reactions involving carbon-carbon bond formation. This represents an important step toward automated analysis of SEM images in materials science.

Time-Resolved Formation and Operation Maps of Pd Catalysts Suggest a Key Role of Single Atom Centers in Cross-Coupling

An approach to the spatially localized characterization of supported catalysts over a reaction course is proposed. It consists of a combination of scanning, transmission, and high-resolution scanning transmission electron microscopy to determine metal particles from arrays of surface nanoparticles to individual nanoparticles and individual atoms. The study of the evolution of specific metal catalyst particles at different scale levels over time, particularly before and after the cross-coupling catalytic reaction, made it possible to approach the concept of 4D catalysis-tracking the positions of catalytic centers in space (3D) over time (+1D). The dynamic behavior of individual palladium atoms and nanoparticles in cross-coupling reactions was recorded with nanometer accuracy via the precise localization of catalytic centers. Single atoms of palladium leach out into solution from the support under the action of the catalytic system, where they exhibit extremely high catalytic activity compared to surface metal nanoparticles. Monoatomic centers, which make up only approximately 1% of palladium in the Pd/C system, provide more than 99% of the catalytic activity. The remaining palladium nanoparticles changed their shape and could move over the surface of the support, which was recorded by processing images of the array of nanoparticles with a neural network and aligning them using automatically detected keypoints. The study reveals a novel opportunity for single-atom catalysis─easier detachment (capture) from (on) the carbon support surface is the origin of superior catalytic activity, rather than the operation of single atomic catalytic centers on the surface of the support, as is typically assumed.

Automated Recognition of Nanoparticles in Electron Microscopy Images of Nanoscale Palladium Catalysts

Automated computational analysis of nanoparticles is the key approach urgently required to achieve further progress in catalysis, the development of new nanoscale materials, and applications. Analysis of nanoscale objects on the surface relies heavily on scanning electron microscopy (SEM) as the experimental analytic method, allowing direct observation of nanoscale structures and morphology. One of the important examples of such objects is palladium on carbon catalysts, allowing access to various chemical reactions in laboratories and industry. SEM images of Pd/C catalysts show a large number of nanoparticles that are usually analyzed manually. Manual analysis of a statistically significant number of nanoparticles is a tedious and highly time-consuming task that is impossible to perform in a reasonable amount of time for practically needed large amounts of samples. This work provides a comprehensive comparison of various computer vision methods for the detection of metal nanoparticles. In addition, multiple new types of data representations were developed, and their applicability in practice was assessed.

Deep neural network analysis of nanoparticle ordering to identify defects in layered carbon materials

Smoothness/defectiveness of the carbon material surface is a key issue for many applications, spanning from electronics to reinforced materials, adsorbents and catalysis. Several surface defects cannot be observed with conventional analytic techniques, thus requiring the development of a new imaging approach. Here, we evaluate a convenient method for mapping such "hidden" defects on the surface of carbon materials using 1-5 nm metal nanoparticles as markers. A direct relationship between the presence of defects and the ordering of nanoparticles was studied experimentally and modeled using quantum chemistry calculations and Monte Carlo simulations. An automated pipeline for analyzing microscopic images is described: the degree of smoothness of experimental images was determined by a classification neural network, and then the images were searched for specific types of defects using a segmentation neural network. An informative set of features was generated from both networks: high-dimensional embeddings of image patches and statics of defect distribution.

Visualization of catalyst dynamics and development of a practical procedure to study complex "cocktail"-type catalytic systems

The ability to distinguish molecular catalysis from nanoscale catalysis provides a key to success in the field of catalyst development, particularly for the transition to sustainable economies. Complex evolution of catalyst precursors, facilitated by dynamic interconversions and leaching, makes the identification of catalytically active forms an important task, which is sometimes very difficult. We propose a simple method for in situ capturing of nanoparticles with carbon-coated grids directly from reaction mixtures. Application of this method to the Mizoroki-Heck reaction allowed visualization of dynamic changes of the dominant form of palladium particles in the reaction mixtures with homogeneous and heterogeneous catalyst precursors. Changes in the size and shape of the palladium particles reflecting the progress of the catalytic chemical reaction were demonstrated. Detailed computational modeling was carried out to confirm the generality of this approach and its feasibility for different catalytic systems. The computational models revealed strong binding of metal particles to the carbon coating comprising efficient binding sites. The approach was tested for trapping Cr, Co, Ag, Ni, Cu, Pd, Cd, Ir, Ru and Rh nanoparticles from solutions containing micromolar starting concentrations of the metal precursors. The developed approach provides a unique tool for studying intrinsic properties of catalytic systems.

Chemisorbed oxygen or surface oxides steer the selectivity in Pd electrocatalytic propene oxidation observed by operando Pd L-edge X-ray absorption spectroscopy

Operando Pd X-ray absorption spectroscopy elucidates how the surface oxygen species steer the selectivity in the electrochemical oxidation of propene.

Comparative study of aryl halides in Pd-mediated reactions: key factors beyond the oxidative addition step

The comparative experimental study of Ar–X (X = Cl, Br, I) reactivity and analysis reported herein suggest that oxidative addition cannot be considered the sole reason of the observed low reactivity of aryl chlorides.

Electron microscopy dataset for the recognition of nanoscale ordering effects and location of nanoparticles

A unique ordering effect has been observed in functional catalytic nanoscale materials. Instead of randomly arranged binding to the catalyst surface, metal nanoparticles show spatially ordered behavior resulting in formation of geometrical patterns. Understanding of such nanoscale materials and analysis of corresponding microscopy images will never be comprehensive without appropriate reference datasets. Here we describe the first dataset of electron microscopy images comprising individual nanoparticles which undergo ordering on a surface towards the formation of geometrical patterns. The dataset developed in this study spans three levels of nanoscale organization: (i) individual nanoparticles (1-5 nm) and arrays of nanoparticles (5-20 nm), (ii) ordering effects (20-200 nm) and (iii) complex patterns (from nm to μm scales). The described dataset for the first time provides a possibility for the development of machine learning algorithms to study the unique phenomena of nanoparticles ordering and hierarchical organization.

Carbocatalytic Acetylene Cyclotrimerization: A Key Role of Unpaired Electron Delocalization

Development of sustainable catalysts for synthetic transformations is one of the most challenging and demanding goals. The high prices of precious metals and the unavoidable leaching of toxic metal species leading to environmental contamination make the transition metal-free catalytic systems especially important. Here we demonstrate that carbene active centers localized on carbon atoms at the zigzag edge of graphene represent an alternative platform for efficient catalytic carbon-carbon bond formation in the synthesis of benzene. The studied acetylene trimerization reaction is an efficient atom-economic route to build an aromatic ring-a step ubiquitously important in organic synthesis and industrial applications. Computational modeling of the reaction mechanism reveals a principal role of the reversible spin density oscillations that govern the overall catalytic cycle, facilitate the product formation, and regenerate the catalytically active centers. Dynamic π-electron interactions in 2D carbon systems open new opportunities in the field of carbocatalysis, unachievable by means of transition metal-catalyzed transformations. The theoretical findings are confirmed experimentally by generating key moieties of the carbon catalyst and performing the acetylene conversion to benzene.

High-Performance Synthesis of Phosphorus-Doped Graphene Materials and Stabilization of Phosphoric Micro- and Nanodroplets

A thermally induced cascade process leading to the formation of stable micro- and nanometer-size phosphoric droplets was developed starting from a molecular precursor. Microwave-induced pyrolysis of 1,2,3,4,5-pentaphenylphosphole oxide proceeded through a series of subsequent transformations involving formation of phosphorus-doped graphene oxide layers, seeding of carbon surface with phosphorus centers, and assembling of stable droplets. A complex nanostructured organization of the material was established in a remarkably short time of 3 min, and the process was performed in a thermally induced manner using microwave irradiation. High stability of the liquid phosphoric structures on the surface of doped graphene oxide over a few-month period was demonstrated, as well as under challenging conditions in organic solvents (chloroform, methylene chloride, or toluene media) and even under sonication. Detailed examination of this material by electron microscopy and a number of analytical methods showed its unique organization at the nanoscale, whereas computational modeling revealed unusually strong binding of phosphorus oxide P₄O₁₀ to the graphene surface. The study demonstrates a fascinating opportunity to access a complex nanostructured multicomponent material from a single and easily available molecular precursor.

Systematic Study of the Behavior of Different Metal and Metal-Containing Particles under the Microwave Irradiation and Transformation of Nanoscale and Microscale Morphology

In recent years, the application of microwave (MW) irradiation has played an increasingly important role in the synthesis and development of high performance nanoscale catalytic systems. However, the interaction of microwave irradiation with solid catalytic materials and nanosized structures remains a poorly studied topic. In this paper we carried out a systematic study of changes in morphology under the influence of microwave irradiation on nanoscale particles of various metals and composite particles, including oxides, carbides, and neat metal systems. All systems were studied in the native solid form without a solvent added. Intensive absorption of microwave radiation was observed for many samples, which in turn resulted in strong heating of the samples and changes in their chemical structure and morphology. A comparison of two very popular catalytic materials—metal particles (M) and supported metal on carbon (M/C) systems—revealed a principal difference in their behavior under microwave irradiation. The presence of carbon support influences the heating mechanism; the interaction of substances with the support during the heating is largely determined by heat transfer from the carbon. Etching of the carbon surface, involving the formation of trenches and pits on the surface of the carbon support, were observed for various types of the investigated nanoparticles.

Exploring the performance of nanostructured reagents with organic-group-defined morphology in cross-coupling reaction

The great impact of the nanoscale organization of reactive species on their performance in chemical transformations creates the possibility of fine-tuning of reaction parameters by modulating the nano-level properties. This methodology is extensively applied for the catalysts development whereas nanostructured reactants represent the practically unexplored area. Here we report the palladium- and copper-catalyzed cross-coupling reaction involving nano-structured nickel thiolate particles as reagents. On the basis of experimental findings we propose the cooperative effect of nano-level and molecular-level properties on their reactivity. The high degree of ordering, small particles size, and electron donating properties of the substituents favor the product formation. Reactant particles evolution in the reaction is visualized directly by dynamic liquid-phase electron microscopy including recording of video movies. Mechanism of the reaction in liquid phase is established using on-line mass spectrometry measurements. Together the findings provide new opportunities for organic chemical transformations design and for mechanistic studies.

Probing the Evolution of Palladium Species in Pd@MOF Catalysts during the Heck Coupling Reaction: An Operando X-ray Absorption Spectroscopy Study

The mechanism of the Heck C-C coupling reaction catalyzed by Pd@MOFs has been investigated using operando X-ray absorption spectroscopy (XAS) and powder X-ray diffraction (PXRD) combined with transmission electron microscopy (TEM) analysis and nuclear magnetic resonance (¹H NMR) kinetic studies. A custom-made reaction cell was used, allowing operando PXRD and XAS data collection using high-energy synchrotron radiation. By analyzing the XAS data in combination with ex situ studies, the evolution of the palladium species is followed from the as-synthesized to its deactivated form. An adaptive reaction mechanism is proposed. Mononuclear Pd(II) complexes are found to be the dominant active species at the beginning of the reaction, which then gradually transform into Pd nanoclusters with 13-20 Pd atoms on average in later catalytic turnovers. Consumption of available reagent and substrate leads to coordination of Cl^- ions to their surfaces, which causes the poisoning of the active sites. By understanding the deactivation process, it was possible to tune the reaction conditions and prolong the lifetime of the catalyst.

Dynamic Behavior of Metal Nanoparticles in Pd/C and Pt/C Catalytic Systems under Microwave and Conventional Heating

Metal on carbon catalysts (M/C) are ubiquitously used in modern research and industry to carry out a variety of chemical transformations. Stable metal-support frameworks and inertness of the carbon materials are usually taken for granted in these very useful catalytic systems. Initially, the present study was aimed to increase the efficiency of Pd/C and Pt/C catalytic systems under microwave and conventional heating. Interestingly, a dynamic behavior of the metal nanoparticles was revealed, and a series of carbon support transformations occurred during the thermal treatments of the catalysts. Microwave and thermal heating of the M/C catalysts resulted in substantial transformations of the carbon supports via the formation of pits, trenches, nanofibers, and nanowalls. Detailed studies with field-emission scanning electron microscopy were carried out involving statistical averaging over large surface areas. The effects of the dynamic behaviors of the supported metal particles on the catalytic activities of the synthetically useful Mizoroki-Heck and Suzuki-Miyaura reactions were demonstrated. Revealed dynamic behavior and modification of the carbon support due to microwave treatment were observed in a number of M/C systems (M = Pd, Pt, Ni, Co, Cu, Fe, and Au).

Factors Influencing the Performance of Pd/C Catalysts in the Green Production of Hydrogen from Formic Acid

Formic acid derived from biomass is known to be used for hydrogen production over Pd catalysts. The effects of preparation variables, structure of the carbon support, surface functional composition on the state of Pd, and catalytic properties of the samples in the vapor-phase decomposition of formic acid were studied. In all catalysts derived from Pd acetate, metal particles visible by conventional TEM had similar sizes, but the adsorption capacity towards CO responded strongly to N-doping of the carbon surface. Moreover, a decrease in the CO/Pd values was accompanied by a significant increase in the reaction rate. Taking account of X-ray photoelectron spectroscopy (XPS) and atomic resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF/STEM) data, the trends observed were assigned to a larger fraction of single electron-deficient Pd atoms in the N-doped samples, which do not adsorb CO but interact with formic acid to produce hydrogen. This was confirmed by extended DFT studies. The obtained results are valuable for the development of Pd catalysts on carbon supports for different processes.

Shielding the chemical reactivity using graphene layers for controlling the surface properties of carbon materials

Graphene can efficiently shield chemical interactions and gradually decrease the binding to reactive defect areas. In the present study, we have used the observed graphene shielding effect to control the reactivity patterns on the carbon surface. The experimental findings show that a surface coating with a tiny carbon layer of 1-2 nm thickness is sufficient to shield the defect-mediated reactivity and create a surface with uniform binding ability. The shielding effect was directly observed using a combination of microscopy techniques and evaluated with computational modeling. The theoretical calculations indicate that a few graphene layers can drastically reduce the binding energy of the metal centers to the surface defects by 40-50 kcal mol(-1). The construction of large carbon areas with controlled surface reactivity is extremely difficult, which is a key limitation in many practical applications. Indeed, the developed approach provides a flexible and simple tool to change the reactivity patterns on large surface areas within a few minutes.

Catalytic C-H bond functionalisation chemistry: the case for quasi-heterogeneous catalysis

This feature article examines the potential of heterogeneous Pd species to mediate catalytic C-H bond functionalisation processes employing suitable substrates (e.g. aromatic/heteroaromatic compounds). A focus is placed on the reactivity of supported and non-supported Pd nanoparticle (PdNPs) catalysts, in addition to the re-appropriation of well-established heterogeneous Pd catalysts such as Pd/C. Where possible, reasonable comparisons are made between PdNPs and traditional 'homogeneous' Pd precatalyst sources (which form PdNPs). The involvement of higher order Pd species in traditional cross-coupling processes, such as Mizoroki-Heck, Sonogashira and Suzuki-Miyaura reactions, allows the exemplification of potential future topics for study in the area of catalytic C-H bond functionalisation processes.

High electrocatalytic activity of carbon-supported Pd@PdO NPs catalysts prepared by a HaNPV virions template

A novel Pd@PdO nanoparticles (NPs) catalyst was successfully prepared by a HaNPV virions template in the absence of reducing agents.

Analysis of model Pd- and Pt-containing contaminants in aqueous media using ESI-MS and the fragment partitioning approach

A series of monometallic complexes, homo- and heteronuclear clusters of palladium and platinum were detected and characterized by ESI-MS study of simple Pd and Pt salts using newly-developed fragment partitioning approach for signals assignment.