Mechanism-Enabled Population Balance Modeling of Particle Formation en Route to Particle Average Size and Size Distribution Understanding and Control

Study on Thermally Induced Lignin Aggregation Kinetics for the Preparation of Uniformly Sized Lignin Nanoparticles in Water

Lignin nanoparticles (LNPs) present a potential avenue for the high-value utilization of lignin. However, the simple and ecofriendly method of thermally induced self-assembly for the preparation of LNPs has been overlooked due to a lack of sufficient understanding of the lignin aggregation mechanism. Therefore, this study focuses on the kinetics of thermally induced lignin aggregation. It was found that lignin aggregates formed at lower temperatures exhibit poor stability and are more prone to continuous growth through coalescence. This apparent contradiction with the conventional understanding of thermoresponsive polymers could be attributed to changes in the viscoelasticity of the lignin aggregates during phase separation. Based on this finding, we worked out strategies to optimize the preparation of LNPs in water through thermally induced self-assembly. Pure LNPs with well-defined interfaces and a minimum polydispersity index (PDI) of 0.12 were obtained by increasing the temperature to 125-150 °C. Furthermore, combined with noncovalent modification, LNPs with a PDI of 0.08 would even be formed at 80 °C. Notably, the resulting pure LNPs show potential for application in photonic crystal products that require excellent monodispersity. This study provides a new approach for the environmentally friendly preparation of LNPs with a controllable morphology.

Lights on the Synthesis of Surfactant-Free Colloidal Gold Nanoparticles in Alkaline Mixtures of Alcohols and Water

Surfactant-free colloidal syntheses in aqueous media are attractive to develop nanomaterials relevant for various applications, e. g. catalysis or medicine. However, controlled green syntheses without surfactants of metal nanoparticles in aqueous media remain scarce. Here, room temperature syntheses of gold (Au) nanoparticles (NPs) that require only HAuCl4, alkaline water and an alcohol, i. e. relatively benign chemicals and mild reaction conditions, are developed. The findings of a comprehensive multi-parameters screening performed in small volumes (<3 mL) over 1000+ experiments pave the way to greener high throughput screenings of large parametric spaces and lead to scalable (100 mL) synthetic strategies. A rational selection of the alcohol is proposed. The influence of lights with defined wavelengths (222-690 nm) is investigated. It is found that lights with lower wavelengths favor the formation of smaller 5 nm NPs. Different kinetics and formation pathways are observed for different alcohols and for lights with different wavelengths. The sensitivity to various experimental parameters increases with the alcohol used in the order glycerol Collapse

Key Words

• Gold
• Light
• Nanoparticles
• Room temperature synthesis
• Surfactant-free

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MESH Headings Collapse

Grants

• AUFF-E-2022-9-40 Aarhus Universitets Forskningsfond

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Affiliation(s)

Ditte Røjkjær Rasmussen Biological and Chemical Engineering Department, Aarhus University, 40 Åbogade, Aarhus, 8200, Denmark
Nina Lock Biological and Chemical Engineering Department, Aarhus University, 40 Åbogade, Aarhus, 8200, Denmark
Jonathan Quinson Biological and Chemical Engineering Department, Aarhus University, 40 Åbogade, Aarhus, 8200, Denmark

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Final nanoparticle size distribution under unusual parameter regimes

We explore the large-scale behavior of a stochastic model for nanoparticle growth in an unusual parameter regime. This model encompasses two types of reactions: nucleation, where n monomers aggregate to form a nanoparticle, and growth, where a nanoparticle increases its size by consuming a monomer. Reverse reactions are disregarded. We delve into a previously unexplored parameter regime. Specifically, we consider a scenario where the growth rate of the first newly formed particle is of the same order of magnitude as the nucleation rate, in contrast to the classical scenario where, in the initial stage, nucleation dominates over growth. In this regime, we investigate the final size distribution as the initial number of monomers tends to infinity through extensive simulation studies utilizing state-of-the-art stochastic simulation methods with an efficient implementation and supported by high-performance computing infrastructure. We observe the emergence of a deterministic limit for the particle's final size density. To scale up the initial number of monomers to approximate the magnitudes encountered in real experiments, we introduce a novel approximation process aimed at faster simulation. Remarkably, this approximating process yields a final size distribution that becomes very close to that of the original process when the available monomers approach infinity. Simulations of the approximating process further support the conjecture of the emergence of a deterministic limit.

The Current Understanding of Mechanistic Pathways in Zeolite Crystallization

Zeolite catalysts and adsorbents have been an integral part of many commercial processes and are projected to play a significant role in emerging technologies to address the changing energy and environmental landscapes. The ability to rationally design zeolites with tailored properties relies on a fundamental understanding of crystallization pathways to strategically manipulate processes of nucleation and growth. The complexity of zeolite growth media engenders a diversity of crystallization mechanisms that can manifest at different synthesis stages. In this review, we discuss the current understanding of classical and nonclassical pathways associated with the formation of (alumino)silicate zeolites. We begin with a brief overview of zeolite history and seminal advancements, followed by a comprehensive discussion of different classes of zeolite precursors with respect to their methods of assembly and physicochemical properties. The following two sections provide detailed discussions of nucleation and growth pathways wherein we emphasize general trends and highlight specific observations for select zeolite framework types. We then close with conclusions and future outlook to summarize key hypotheses, current knowledge gaps, and potential opportunities to guide zeolite synthesis toward a more exact science.

Synthesis of graded CdS1-xSex nanoplatelet alloys and heterostructures from pairs of chalcogenoureas with tailored conversion reactivity

A mixture of N,N,N'-trisubstituted thiourea and cyclic N,N,N',N'-tetrasubstituted selenourea precursors were used to synthesize three monolayer thick CdS1-xSex nanoplatelets in a single synthetic step. The microstructure of the nanoplatelets could be tuned from homogeneous alloys, to graded alloys to core/crown heterostructures depending on the relative conversion reactivity of the sulfur and selenium precursors. UV-visible absorption and photoluminescence spectroscopy and scanning transmission electron microscopy electron energy loss spectroscopy (STEM-EELS) images demonstrate that the elemental distribution is governed by the relative precursor conversion kinetics. Slow conversion kinetics produced nanoplatelets with larger lateral dimensions, behavior that is characteristic of precursor conversion limited growth kinetics. Across a 10-fold range of reactivity, CdS nanoplatelets have 4× smaller lateral dimensions than CdSe nanoplatelets grown under identical conversion kinetics. The difference in size is consistent with a rate of CdSe growth that is 4× greater than the rate of CdS. The influence of the relative sulfide and selenide growth rates, the duration of the nucleation phase, and the solute composition on the nanoplatelet microstructure are discussed.

Scientific Machine Learning of 2D Perovskite Nanosheet Formation

We apply a scientific machine learning (ML) framework to aid the prediction and understanding of nanomaterial formation processes via a joint spectral-kinetic model. We apply this framework to study the nucleation and growth of two-dimensional (2D) perovskite nanosheets. Colloidal nanomaterials have size-dependent optical properties and can be observed in situ, all of which make them a good model for understanding the complex processes of nucleation, growth, and phase transformation of 2D perovskites. Our results demonstrate that this model nanomaterial can form through two processes at the nanoscale: either via a layer-by-layer chemical exfoliation process from lead bromide nanocrystals or via direct nucleation from precursors. We utilize a phenomenological kinetic analysis to study the exfoliation process and scientific machine learning to study the direct nucleation and growth and discuss the circumstances under which it is more appropriate to use phenomenological or more complex machine learning models. Data for both analysis techniques are collected through in situ spectroscopy in a stopped flow chamber, incorporating over 500,000 spectra taken under more than 100 different conditions. More broadly, our research shows that the ability to utilize and integrate traditional kinetics and machine learning methods will greatly assist in the understanding of complex chemical systems.

Growth Synchronization and Size Control in Magic-Sized Semiconductor Nanocrystals

"Magic-sized" nanocrystals (MSNCs) grow in discrete jumps between a series of specific sizes. Consequently, MSNCs have been explored as an alternative route to uniform semiconductor particles, potentially with atomic precision. However, because the growth mechanism has been poorly understood, the best strategies to control MSNC syntheses and obtain desired sizes are unknown. Experiments have found that common parameters, such as growth time and temperature, have limited utility. Here, we theoretically and experimentally investigate reactant supersaturation as a tool to control MSNC growth. We compare direct synthesis of CdSe MSNCs with ripening of isolated MSNCs or their mixtures. Surprisingly, we find that MSNCs readily synchronize to the same growth trajectory, even starting from distinct initial conditions, explaining the robustness of MSNC growth. Further, by understanding the synchronization mechanism, we demonstrate methods to control the final MSNC size. These results deepen our knowledge of MSNCs and indicate strategies to tailor their growth.

Design Rules for Obtaining Narrow Luminescence from Semiconductors Made in Solution

Solution-processed semiconductors are in demand for present and next-generation optoelectronic technologies ranging from displays to quantum light sources because of their scalability and ease of integration into devices with diverse form factors. One of the central requirements for semiconductors used in these applications is a narrow photoluminescence (PL) line width. Narrow emission line widths are needed to ensure both color and single-photon purity, raising the question of what design rules are needed to obtain narrow emission from semiconductors made in solution. In this review, we first examine the requirements for colloidal emitters for a variety of applications including light-emitting diodes, photodetectors, lasers, and quantum information science. Next, we will delve into the sources of spectral broadening, including "homogeneous" broadening from dynamical broadening mechanisms in single-particle spectra, heterogeneous broadening from static structural differences in ensemble spectra, and spectral diffusion. Then, we compare the current state of the art in terms of emission line width for a variety of colloidal materials including II-VI quantum dots (QDs) and nanoplatelets, III-V QDs, alloyed QDs, metal-halide perovskites including nanocrystals and 2D structures, doped nanocrystals, and, finally, as a point of comparison, organic molecules. We end with some conclusions and connections, including an outline of promising paths forward.

Chemical Insights into the Formation of Colloidal Iridium Nanoparticles from In Situ X-ray Total Scattering: Influence of Precursors and Cations on the Reaction Pathway

Iridium nanoparticles are important catalysts for several chemical and energy conversion reactions. Studies of iridium nanoparticles have also been a key for the development of kinetic models of nanomaterial formation. However, compared to other metals such as gold or platinum, knowledge on the nature of prenucleation species and structural insights into the resultant nanoparticles are missing, especially for nanoparticles obtained from Ir_xCl_y precursors investigated here. We use in situ X-ray total scattering (TS) experiments with pair distribution function (PDF) analysis to study a simple, surfactant-free synthesis of colloidal iridium nanoparticles. The reaction is performed in methanol at 50 °C with only a base and an iridium salt as precursor. From different precursor salts─IrCl₃, IrCl₄, H₂IrCl₆, or Na₂IrCl₆─colloidal nanoparticles as small as Ir_∼55 are obtained as the final product. The nanoparticles do not show the bulk iridium face-centered cubic (fcc) structure but show decahedral and icosahedral structures. The formation route is highly dependent on the precursor salt used. Using IrCl₃ or IrCl₄, metallic iridium nanoparticles form rapidly from Ir_xCl_y^n- complexes, whereas using H₂IrCl₆ or Na₂IrCl₆, the iridium nanoparticle formation follows a sudden growth after an induction period and the brief appearance of a crystalline phase. With H₂IrCl₆, the formation of different Ir_n (n = 55, 55, 85, and 116) nanoparticles depends on the nature of the cation in the base (LiOH, NaOH, KOH, or CsOH, respectively) and larger particles are obtained with larger cations. As the particles grow, the nanoparticle structure changes from partly icosahedral to decahedral. The results show that the synthesis of iridium nanoparticles from Ir_xCl_y is a valuable iridium nanoparticle model system, which can provide new compositional and structural insights into iridium nanoparticle formation and growth.

Persistent nucleation and size dependent attachment kinetics produce monodisperse PbS nanocrystals

Modern syntheses of colloidal nanocrystals yield extraordinarily narrow size distributions that are believed to result from a rapid "burst of nucleation" (La Mer, JACS, 1950, 72(11), 4847-4854) followed by diffusion limited growth and size distribution focusing (Reiss, J. Chem. Phys., 1951, 19, 482). Using a combination of in situ X-ray scattering, optical absorption, and 13C nuclear magnetic resonance (NMR) spectroscopy, we monitor the kinetics of PbS solute generation, nucleation, and crystal growth from three thiourea precursors whose conversion reactivity spans a 2-fold range. In all three cases, nucleation is found to be slow and continues during >50% of the precipitation. A population balance model based on a size dependent growth law (1/r) fits the data with a single growth rate constant (k G) across all three precursors. However, the magnitude of the k G and the lack of solvent viscosity dependence indicates that the rate limiting step is not diffusion from solution to the nanoparticle surface. Several surface reaction limited mechanisms and a ligand penetration model that fits data our experiments using a single fit parameter are proposed to explain the results.

Iridium and IrOx nanoparticles: an overview and review of syntheses and applications

Precious metals are key in various fields of research and precious metal nanomaterials are directly relevant for optics, catalysis, pollution management, sensing, medicine, and many other applications. Iridium based nanomaterials are less studied than metals like gold, silver or platinum. A specific feature of iridium nanomaterials is the relatively small size nanoparticles and clusters easily obtained, e.g. by colloidal syntheses. Progress over the years overcomes the related challenging characterization and it is expected that the knowledge on iridium chemistry and nanomaterials will be growing. Although Ir nanoparticles have been preferred systems for the development of kinetic-based models of nanomaterial formation, there is surprisingly little knowledge on the actual formation mechanism(s) of iridium nanoparticles. Following the impulse from the high expectations on Ir nanoparticles as catalysts for the oxygen evolution reaction in electrolyzers, new areas of applications of iridium materials have been reported while more established applications are being revisited. This review covers different synthetic strategies of iridium nanoparticles and provides an in breadth overview of applications reported. Comprehensive Tables and more detailed topic-oriented overviews are proposed in Supplementary Material, covering synthesis protocols, the historical role or iridium nanoparticles in the development of nanoscience and applications in catalysis.

Growth kinetics determine the polydispersity and size of PbS and PbSe nanocrystals

A library of thio- and selenourea derivatives is used to adjust the kinetics of PbE (E = S, Se) nanocrystal formation across a 1000-fold range (k r = 10-1 to 10-4 s-1), at several temperatures (80-120 °C), under a standard set of conditions (Pb : E = 1.2 : 1, [Pb(oleate)2] = 10.8 mM, [chalcogenourea] = 9.0 mM). An induction delay (t ind) is observed prior to the onset of nanocrystal absorption during which PbE solute is observed using in situ X-ray total scattering. Density functional theory models fit to the X-ray pair distribution function (PDF) support a Pb2(μ2-S)2(Pb(O2CR)2)2 structure. Absorption spectra of aliquots reveal a continuous increase in the number of nanocrystals over more than half of the total reaction time at low temperatures. A strong correlation between the width of the nucleation phase and reaction temperature is observed that does not correlate with the polydispersity. These findings are antithetical to the critical concentration dependence of nucleation that underpins the La Mer hypothesis and demonstrates that the duration of the nucleation period has a minor influence on the size distribution. The results can be explained by growth kinetics that are size dependent, more rapid at high temperature, and self limiting at low temperatures.

Simple Setup Miniaturization with Multiple Benefits for Green Chemistry in Nanoparticle Synthesis

The development of nanomaterials often relies on wet-chemical synthesis performed in reflux setups using round-bottom flasks. Here, an alternative approach to synthesize nanomaterials is presented that uses glass tubes designed for NMR analysis as reactors. This approach uses less solvent and energy, generates less waste, provides safer conditions, is less prone to contamination, and is compatible with high-throughput screening. The benefits of this approach are illustrated by an in breadth study with the synthesis of gold, iridium, osmium, and copper sulfide nanoparticles.

Estimating reaction parameters in mechanism-enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

In order to quantitatively predict nano- as well as other particle-size distributions, one needs to have both a mathematical model and estimates of the parameters that appear in these models. Here, we show how one can use Bayesian inversion to obtain statistical estimates for the parameters that appear in recently derived mechanism-enabled population balance models (ME-PBM) of nanoparticle growth. The Bayesian approach addresses the question of "how well do we know our parameters, along with their uncertainties?." The results reveal that Bayesian inversion statistical analysis on an example, prototype Ir 0 n nanoparticle formation system allows one to estimate not just the most likely rate constants and other parameter values, but also their SDs, confidence intervals, and other statistical information. Moreover, knowing the reliability of the mechanistic model's parameters in turn helps inform one about the reliability of the proposed mechanism, as well as the reliability of its predictions. The paper can also be seen as a tutorial with the additional goal of achieving a "Gold Standard" Bayesian inversion ME-PBM benchmark that others can use as a control to check their own use of this methodology for other systems of interest throughout nature. Overall, the results provide strong support for the hypothesis that there is substantial value in using a Bayesian inversion methodology for parameter estimation in particle formation systems.

MIL-96-Al for Li-S Batteries: Shape or Size?

Metal-organic frameworks (MOFs) with controllable shapes and sizes show a great potential in Li-S batteries. However, neither the relationship between shape and specific capacity nor the influence of MOF particle size on cyclic stability have been fully established yet. Herein, MIL-96-Al with various shapes, forming hexagonal platelet crystals (HPC), hexagonal bipyramidal crystals (HBC), and hexagonal prismatic bipyramidal crystals (HPBC) are successfully prepared via cosolvent methods. Density functional theory (DFT) calculations demonstrate that the HBC shape with highly exposed (101) planes can effectively adsorb lithium polysulfides (LPS) during the charge/discharge process. By changing the relative proportion of the cosolvents, HBC samples with different particle sizes are prepared. When these MIL-96-Al crystals are used as sulfur host materials, it is found that those with a smaller size of the HBC shape deliver higher initial capacity. These investigations establish that different crystal planes have different adsorption abilities for LPS, and that the MOF particle size should be considered for a suitable sulfur host. More broadly, this work provides a strategy for designing sulfur hosts in Li-S batteries.

Pseudoelementary Steps: A Key Concept and Tool for Studying the Kinetics and Mechanisms of Complex Chemical Systems

The concept of a pseudoelementary step (PEStep) is reviewed, a key concept for approaching the analysis of kinetics data and associated, underlying mechanisms of complex chemical systems. Following a brief Introduction, a definition of a PEStep is given: a PEStep is an initial building block for more complex reactions, that is a starting point for the initial analysis of the observed kinetics and then constructing initial, deliberately minimalistic mechanistic models for complex reactions. PESteps are, therefore and typically, composites of underlying elementary step reactions and can be very useful if not required for the inverse problem of discovering mechanisms from experimental observables for complex reactions. It is the use of PESteps in the inverse problem of mechanism determination that is a primary focus of this review. After a section detailing the results of a literature search of "pseudoelementary step" and related terms such as "pseudoelementary process", pedagogically illustrative examples are given of the use of the PEStep concept in approaching and elucidating the mechanisms of complex reactions. This review shows how the underlying elementary steps of a catalytic cycle were successfully uncovered via a PEStep approach, addresses the classic case of the use of PESteps in determining the mechanisms of oscillating reactions, and examines a well-studied case of an Ir(0)_n nanoparticle formation reaction. This latter example is illustrative in that the Ir(0)_n nanoparticle formation reaction consisting of thousands of underlying elementary steps that, however, can be treated initially kinetically as just two PESteps, a reduction in complexity of 3 orders of magnitude. Known weaknesses and caveats of the PEStep approach are also summarized and discussed. A short summary of Horituti's "Stoichiometric Number" concept is provided, a concept that would appear to merit further investigation and use in the study of complex reactions. Finally, a section is provided that lists a few, selected areas where the PEStep concept and methodology are expected to prove especially important in the future, and a Conclusions section is provided that lists 11 bullet points. The latter serves as a summary of this first review of the PEStep concept and its importance in dealing with the kinetics and in elucidating the mechanisms of more complex, multistep reactions.

Precursor chemistry of metal nitride nanocrystals

Metal nitride nanocrystals are a versatile class of nanomaterials. Depending on their chemical composition, the optical properties vary from those of traditional semiconductor nanocrystals (called quantum dots) to more metallic character (featuring a plasmon resonance). However, the synthesis of colloidal metal nitride nanocrystals is challenging since the underlying precursor chemistry is much less developed compared to the chemistry of metal, metal chalcogenide or metal phosphide nanocrystals. Here, we review chemical approaches that lead (or could lead) to the formation of colloidally stable metal nitride nanocrystals. By systematically comparing different synthetic approaches, we uncover trends and gain insight into the chemistry of these challenging materials. We also discuss and critically evaluate the plausibility of certain suggested mechanisms. This review is meant as a guide for the further development of colloidal nitride nanocrystals.

Extended Nucleation and Superfocusing in Colloidal Semiconductor Nanocrystal Synthesis

Hot-injection synthesis is renowned for producing semiconductor nanocolloids with superb size dispersions. Burst nucleation and diffusion-controlled size focusing during growth have been invoked to rationalize this characteristic yet experimental evidence supporting the pertinence of these concepts is scant. By monitoring a CdSe synthesis in-situ with X-ray scattering, we find that nucleation is an extended event that coincides with growth during 15-20% of the reaction time. Moreover, we show that size focusing outpaces predictions of diffusion-limited growth. This observation indicates that nanocrystal growth is dictated by the surface reactivity, which drops sharply for larger nanocrystals. Kinetic reaction simulations confirm that this so-called superfocusing can lengthen the nucleation period and promote size focusing. The finding that narrow size dispersions can emerge from the counteracting effects of extended nucleation and reaction-limited size focusing ushers in an evidence-based perspective that turns hot injection into a rational scheme to produce monodisperse semiconductor nanocolloids.

AutoDetect-mNP: An Unsupervised Machine Learning Algorithm for Automated Analysis of Transmission Electron Microscope Images of Metal Nanoparticles

The synthesis quality of artificial inorganic nanocrystals is most often assessed by transmission electron microscopy (TEM) for which high-throughput advances have dramatically increased both the quantity and information richness of metal nanoparticle (mNP) characterization. Existing automated data analysis algorithms of TEM mNP images generally adopt a supervised approach, requiring a significant effort in human preparation of labeled data that reduces objectivity, efficiency, and generalizability. We have developed an unsupervised algorithm AutoDetect-mNP for automated analysis of TEM images that objectively extracts morphological information on convex mNPs from TEM images based on their shape attributes, requiring little to no human input in the process. The performance of AutoDetect-mNP is tested on two data sets of bright field TEM images of Au nanoparticles with different shapes and further extended to palladium nanocubes and cadmium selenide quantum dots, demonstrating that the algorithm is quantitatively reliable and can thus serve as a generalizable measure of the morphology distributions of any mNP synthesis. The AutoDetect-mNP algorithm will aid in future developments of high-throughput characterization of mNPs and the future advent of time-resolved TEM studies that can investigate reaction mechanisms of mNP synthesis and reactivity.

Probing Kinetics and Mechanism of Formation of Mixed Metallic Nanoparticles in a Polymer Membrane by Galvanic Replacement between Two Immiscible Metals: Case Study of Nickel/Silver Nanoparticle Synthesis

Galvanic replacement between metals has received notable research interest for the synthesis of heterometallic nanostructures. The growth pattern of the nanostructures depends on several factors such as extent of lattice mismatch, adhesive interaction between the metals, cohesive forces of the individual metals, etc. Due to the difficulties in probing ultrafast kinetics of the galvanic replacement reaction and particle growth in solution, real-time mechanistic investigations are often limited. As a result, the growth mechanism of one metal on the surface of another metal at the nanoscale is poorly understood so far. In the present work, we could successfully probe the galvanic replacement of silver ions with nickel nanoparticles, stabilized in a polymer membrane, using two complementary methods, namely, small-angle X-ray scattering (SAXS) and radiolabeling, and the results are supported by density functional theory (DFT) computations. The silver-nickel system has been chosen for the present investigation because of the high degree of bulk immiscibility caused by the large lattice mismatch (15.9%) and the weak adhesive interaction, which makes it a perfect model system for immiscible metal pairs. Membrane, as a host medium, plays a crucial role in retarding the kinetics of atomic and particle rearrangements (nucleation and growth) due to slower mobility of the atoms (monomers) and particles within the polymer network. This allowed us to examine the real-time concentration of silver monomers during galvanic replacement of silver ions with nickel nanoparticles and evolution of Ni/Ag nanoparticles. From combined experiment and DFT computations, it has been demonstrated, for the first time to the best of our knowledge, that the majority of silver atoms, which are produced on the nickel nanoparticle surface by galvanic reactions, do not form traditional core-shell nanostructures with nickel and undergo a self-governing sequential nucleation and growth of silver nanoparticles via formation of intermediate prenucleation silver clusters, leading to the formation of mixed metallic nanoparticles in the membrane. The surface of NiNPs has a heterogeneous effect on the silver nucleation pathway, which is evident from the reduced critical free energy barrier of nucleation (ΔG_crit). The present work establishes an original mechanistic pathway based on a sequential nucleation model for formation of mixed metallic nanoparticles by the galvanic replacement route, which opens up future possibilities for size-controlled synthesis in mixed systems.

Using Reduction Kinetics to Control and Predict the Outcome of a Colloidal Synthesis of Noble-Metal Nanocrystals

Improving the performance of noble-metal nanocrystals in various applications critically depends on our ability to manipulate their synthesis in a rational, robust, and controllable fashion. Different from a conventional trial-and-error approach, the reduction kinetics of a colloidal synthesis has recently been demonstrated as a reliable knob for controlling the synthesis of noble-metal nanocrystals in a deterministic and predictable manner. Here we present a brief Viewpoint on the recent progress in leveraging reduction kinetics for controlling and predicting the outcome of a synthesis of noble-metal nanocrystals. With a focus on Pd nanocrystals, we first offer a discussion on the correlation between the initial reduction rate and the internal structure of the resultant seeds. The kinetic approaches for controlling both nucleation and growth in a one-pot setting are then introduced with an emphasis on manipulation of the reduction pathways taken by the precursor. We then illustrate how to extend the strategy into a bimetallic system for the preparation of nanocrystals with different shapes and elemental distributions. Finally, the influence of speciation of the precursor on reduction kinetics is highlighted, followed by our perspectives on the challenges and future endeavors in achieving a controllable and predictable synthesis of noble-metal nanocrystals.

From platinum atoms in molecules to colloidal nanoparticles: A review on reduction, nucleation and growth mechanisms

Platinum (Pt) is one of the most studied materials in catalysis today and considered for a wide range of applications: chemical synthesis, energy conversion, air treatment, water purification, sensing, medicine etc. As a limited and non-renewable resource, optimized used of Pt is key. Nanomaterial design offers multiple opportunities to make the most of Pt resources down to the atomic scale. In particular, colloidal syntheses of Pt nanoparticles are well documented and simple to implement, which accounts for the large interest in research and development. For further breakthroughs in the design of Pt nanomaterials, a deeper understanding of the intricate synthesis-structures-properties relations of Pt nanoparticles must be obtained. Understanding how Pt nanoparticles form from molecular precursors is both a challenging and rewarding area of investigation. It is directly relevant to develop improved Pt nanomaterials but is also a source of inspiration to design other precious metal nanostructures. Here, we review the current understanding of Pt nanoparticle formation. This review is aimed at readers with interest in Pt nanoparticles in general and their colloidal syntheses in particular. Readers with a strongest interest on the study of nanomaterial formation will find here the case study of Pt. The preferred model systems and characterization techniques used to perform the study of Pt nanoparticle syntheses are discussed. In light of recent achievements, further direction and areas of research are proposed.

Dust Effects on Ir(0)n Nanoparticle Formation Nucleation and Growth Kinetics and Particle Size-Distributions: Analysis by and Insights from Mechanism-Enabled Population Balance Modeling

The effects of microfiltration removal of filterable dust on nanoparticle formation kinetics and particle-size distribution, in a polyoxometalate polyanion (P₂W₁₅Nb₃O₆₂^9-)-stabilized Ir(0)_n nanoparticle formation system, are analyzed by the newly developed method of Mechanism-Enabled Population Balance Modeling (ME-PBM). The [(Bu₄N)₅Na₃(1,5-COD)Ir·P₂W₁₅Nb₃O₆₂] precatalyst system produces on average Ir(0)_∼200 nanoparticles of 1.74 ± 0.33 nm and hence a particle-size distribution (PSD) of ±19% dispersion when the precatalyst is reduced under H₂ in unfiltered propylene carbonate solvent. But if the precatalyst is reduced in microfiltered solvent and microfiltered reagent solutions (where the filtered solvent is then also used to rinse dust from the glassware), then larger Ir(0)_∼300 1.96 ± 0.16 nm nanoparticles are produced with a remarkable, 2.4-fold lowered ±8% dispersion. The results and effects of the microfiltration reduction of dust are analyzed by the newly developed method of ME-PBM. More specifically, the studies reported herein address eight outstanding questions that are listed in the Introduction. Those questions include: how easy or difficult it is to fit PSD data? What is the ability of the recently discovered alternative termolecular nucleation and two size-dependent growth steps mechanism to account for the effects of dust on the PSD? What types and amount of PSD kinetics data are needed to deconvolute the PSD into the parameters of the ME-PBM? What is the reliability of the resulting rate constants? Additional questions addressed include: if the ME-PBM results offer insights into the remarkable 2.4-fold narrowing of the PSD post simple microfiltration lowering of the dust, and if the results are likely to be more general? The Summary and Conclusions section lists nine specific insights that include comments on needed future studies.