Self-templating assembly of soft microparticles into complex tessellations.

Encoding Archimedean and non-regular tessellations in self-assembled colloidal crystals promises unprecedented structure-dependent properties for applications ranging from low-friction coatings to optoelectronic metamaterials1-7. Yet, despite numerous computational studies predicting exotic structures even from simple interparticle interactions8-12, the realization of complex non-hexagonal crystals remains experimentally challenging13-18. Here we show that two hexagonally packed monolayers of identical spherical soft microparticles adsorbed at a liquid-liquid interface can assemble into a vast array of two-dimensional micropatterns, provided that they are immobilized onto a solid substrate one after the other. The first monolayer retains its lowest-energy hexagonal structure and acts as a template onto which the particles of the second monolayer are forced to rearrange. The frustration between the two lattices elicits symmetries that would not otherwise emerge if all the particles were assembled in a single step. Simply by varying the packing fraction of the two monolayers, we obtain not only low-coordinated structures such as rectangular and honeycomb lattices, but also rhomboidal, hexagonal and herringbone superlattices encoding non-regular tessellations. This is achieved without directional bonding, and the structures formed are equilibrium structures: molecular dynamics simulations show that these structures are thermodynamically stable and develop from short-range repulsive interactions, making them easy to predict, and thus suggesting avenues towards the rational design of complex micropatterns.

Tracking Janus microswimmers in 3D with machine learning.

Advancements in artificial active matter systems heavily rely on our ability to characterise their motion. Yet, the most widely used tool to analyse the latter is standard wide-field microscopy, which is largely limited to the study of two-dimensional motion. In contrast, real-world applications often require the navigation of complex three-dimensional environments. Here, we present a Machine Learning (ML) approach to track Janus microswimmers in three dimensions, using Z-stacks as labelled training data. We demonstrate several examples of ML algorithms using freely available and well-documented software, and find that an ensemble Decision Tree-based model (Extremely Randomised Decision Trees) performs the best at tracking the particles over a volume spanning more than 40 µm. With this model, we are able to localise Janus particles with a significant optical asymmetry from standard wide-field microscopy images, bypassing the need for specialised equipment and expertise such as that required for digital holographic microscopy. We expect that ML algorithms will become increasingly prevalent by necessity in the study of active matter systems, and encourage experimentalists to take advantage of this powerful tool to address the various challenges within the field.

From Single Atoms to Nanoparticles: Autocatalysis and Metal Aggregation in Atomic Layer Deposition of Pt on TiO2 Nanopowder.

A fundamental understanding of the interplay between ligand-removal kinetics and metal aggregation during the formation of platinum nanoparticles (NPs) in atomic layer deposition of Pt on TiO2 nanopowder using trimethyl(methylcyclo-pentadienyl)platinum(IV) as the precursor and O2 as the coreactant is presented. The growth follows a pathway from single atoms to NPs as a function of the oxygen exposure (PO2 × time). The growth kinetics is modeled by accounting for the autocatalytic combustion of the precursor ligands via a variant of the Finke-Watzky two-step model. Even at relatively high oxygen exposures (<120 mbar s) little to no Pt is deposited after the first cycle and most of the Pt is atomically dispersed. Increasing the oxygen exposure above 120 mbar s results in a rapid increase in the Pt loading, which saturates at exposures >> 120 mbar s. The deposition of more Pt leads to the formation of NPs that can be as large as 6 nm. Crucially, high PO2 (≥5 mbar) hinders metal aggregation, thus leading to narrow particle size distributions. The results show that ALD of Pt NPs is reproducible across small and large surface areas if the precursor ligands are removed at high PO2 .

Modular Attachment of Nanoparticles on Microparticle Supports via Multifunctional Polymers.

Nanoparticles are key to a range of applications, due to the properties that emerge as a result of their small size. However, their size also presents challenges to their processing and use, especially in relation to their immobilization on solid supports without losing their favorable functionalities. Here, we present a multifunctional polymer-bridge-based approach to attach a range of presynthesized nanoparticles onto microparticle supports. We demonstrate the attachment of mixtures of different types of metal-oxide nanoparticles, as well as metal-oxide nanoparticles modified with standard wet chemistry approaches. We then show that our method can also create composite films of metal and metal-oxide nanoparticles by exploiting different chemistries simultaneously. We finally apply our approach to the synthesis of designer microswimmers with decoupled mechanisms of steering (magnetic) and propulsion (light) via asymmetric nanoparticle binding, aka Toposelective Nanoparticle Attachment. We envision that this ability to freely mix available nanoparticles to produce composite films will help bridge the fields of catalysis, nanochemistry, and active matter toward new materials and applications.

Fitting an active Brownian particle's mean-squared displacement with improved parameter estimation.

The active Brownian particle (ABP) model is widely used to describe the dynamics of active matter systems, such as Janus microswimmers. In particular, the analytical expression for an ABP's mean-squared displacement (MSD) is useful as it provides a means to describe the essential physics of a self-propelled, spherical Brownian particle. However, the truncated or "short-time" form of the MSD equation is typically fitted, which can lead to significant problems in parameter estimation. Furthermore, heteroscedasticity and the often statistically dependent observations of an ABP's MSD lead to a situation where standard ordinary least-squares regression leads to biased estimates and unreliable confidence intervals. Instead, we propose here to revert to always fitting the full expression of an ABP's MSD at short timescales, using bootstrapping to construct confidence intervals of the fitted parameters. Additionally, after comparison between different fitting strategies, we propose to extract the physical parameters of an ABP using its mean logarithmic squared displacement. These steps improve the estimation of an ABP's physical properties and provide more reliable confidence intervals, which are critical in the context of a growing interest in the interactions of microswimmers with confining boundaries and the influence on their motion.

Effect of Internal Architecture on the Assembly of Soft Particles at Fluid Interfaces.

Monolayers of soft colloidal particles confined at fluid interfaces are at the core of a broad range of technological processes, from the stabilization of responsive foams and emulsions to advanced lithographic techniques. However, establishing a fundamental relation between their internal architecture, which is controlled during synthesis, and their structural and mechanical properties upon interfacial confinement remains an elusive task. To address this open issue, which defines the monolayer's properties, we synthesize core-shell microgels, whose soft core can be chemically degraded in a controlled fashion. This strategy allows us to obtain a series of particles ranging from analogues of standard batch-synthesized microgels to completely hollow ones after total core removal. Combined experimental and numerical results show that our hollow particles have a thin and deformable shell, leading to a temperature-responsive collapse of the internal cavity and a complete flattening after adsorption at a fluid interface. Mechanical characterization shows that a critical degree of core removal is required to obtain soft disk-like particles at an oil-water interface, which present a distinct response to compression. At low packing fractions, the mechanical response of the monolayer is dominated by the outer polymer chains forming a corona surrounding the particles within the interfacial plane, regardless of the presence of a core. By contrast, at high compression, the absence of a core enables the particles to deform in the direction orthogonal to the interface and to be continuously compressed without altering the monolayer structure. These findings show how fine, single-particle architectural control during synthesis can be engineered to determine the interfacial behavior of microgels, enabling one to link particle conformation with the resulting material properties.

Sequential capillarity-assisted particle assembly in a microfluidic channel.

Colloidal patterning enables the placement of a wide range of materials into prescribed spatial arrangements, as required in a variety of applications, including micro- and nano-electronics, sensing, and plasmonics. Directed colloidal assembly methods, which exploit external forces to place particles with high yield and great accuracy, are particularly powerful. However, currently available techniques require specialized equipment, which limits their applicability. Here, we present a microfluidic platform to produce versatile colloidal patterns within a microchannel, based on sequential capillarity-assisted particle assembly (sCAPA). This new microfluidic technology exploits the capillary forces resulting from the controlled motion of an evaporating droplet inside a microfluidic channel to deposit individual particles in an array of traps microfabricated onto a substrate. Sequential depositions allow the generation of a desired spatial layout of colloidal particles of single or multiple types, dictated solely by the geometry of the traps and the filling sequence. We show that the platform can be used to create a variety of patterns and that the microfluidic channel easily allows surface functionalization of trapped particles. By enabling colloidal patterning to be carried out in a controlled environment, exploiting equipment routinely used in microfluidics, we demonstrate an easy-to-build platform that can be implemented in microfluidics labs.

Feedback-controlled active brownian colloids with space-dependent rotational dynamics.

The non-thermal nature of self-propelling colloids offers new insights into non-equilibrium physics. The central mathematical model to describe their trajectories is active Brownian motion, where a particle moves with a constant speed, while randomly changing direction due to rotational diffusion. While several feedback strategies exist to achieve position-dependent velocity, the possibility of spatial and temporal control over rotational diffusion, which is inherently dictated by thermal fluctuations, remains untapped. Here, we decouple rotational diffusion from thermal fluctuations. Using external magnetic fields and discrete-time feedback loops, we tune the rotational diffusivity of active colloids above and below its thermal value at will and explore a rich range of phenomena including anomalous diffusion, directed transport, and localization. These findings add a new dimension to the control of active matter, with implications for a broad range of disciplines, from optimal transport to smart materials.

Thermal atomic layer deposition of gold nanoparticles: controlled growth and size selection for photocatalysis.

Gold nanoparticles have been extensively studied for their applications in catalysis. For Au nanoparticles to be catalytically active, controlling the particle size is crucial. Here we present a low temperature (105 °C) thermal atomic layer deposition approach for depositing gold nanoparticles on TiO2 with controlled size and loading using trimethylphosphino-trimethylgold(iii) and two co-reactants (ozone and water) in a fluidized bed reactor. We show that the exposure time of the precursors is a variable that can be used to decouple the Au particle size from the loading. Longer exposures of ozone narrow the particle size distribution, while longer exposures of water broaden it. By studying the photocatalytic activity of Au/TiO2 nanocomposites, we show how the ability to control particle size and loading independently can be used not only to enhance performance but also to investigate structure-property relationships. This study provides insights into the mechanism underlying the formation and evolution of Au nanoparticles prepared for the first time via vapor phase atomic layer deposition. Employing a vapor deposition technique for the synthesis of Au/TiO2 nanocomposites eliminates the shortcomings of conventional liquid-based processes opening up the possibility of highly controlled synthesis of materials at large scale.

Oriented Attachment and Nanorod Formation in Atomic Layer Deposition of TiO2 on Graphene Nanoplatelets.

Understanding the spontaneous organization of atoms on well-defined surfaces promises to enable control over the shape and size of supported nanostructures. Atomic layer deposition (ALD) boasts atomic-scale control in the synthesis of thin films and nanoparticles. Yet, the possibility to control the shape of ALD-grown nanostructures remains mostly unexplored. Here, we report on the bottom-up formation of both linear and V-shaped anatase TiO2 nanorods (NRs) on graphene nanoplatelets during TiCl4/H2O ALD carried out at 300 °C. NRs as large as 200 nm form after only five ALD cycles, indicating that diffusional processes rather than layer-by-layer growth are behind the NR formation. In particular, high-resolution transmission electron microscopy reveals that the TiO2 NRs and graphene nanoplatelets are in rotational alignment as a result of lattice matching. Crucially, we also show that individual nanocrystals can undergo in-plane oriented attachment.

Tunable 2D binary colloidal alloys for soft nanotemplating.

The realization of non-close-packed nanoscale patterns with multiple feature sizes and length scales via colloidal self-assembly is a highly challenging task. We demonstrate here the creation of a variety of tunable particle arrays by harnessing the sequential self-assembly and deposition of two differently sized microgel particles at the fluid-fluid interface. The two-step process is essential to achieve a library of 2D binary colloidal alloys, which are kinetically inaccessible by direct co-assembly. These versatile binary patterns can be exploited for a range of end-uses. Here we show that they can for instance be transferred to silicon substrates, where they act as masks for the metal-assisted chemical etching of binary arrays of vertically aligned silicon nanowires (VA-SiNWs) with fine geometrical control. In particular, continuous binary gradients in both NW spacing and height can be achieved. Notably, these binary VA-SiNW platforms exhibit interesting anti-reflective properties in the visible range, in agreement with simulations. The proposed strategy can also be used for the precise placement of metallic nanoparticles in non-close-packed arrays. Sequential depositions of soft particles enable therefore the exploration of complex binary patterns, e.g. for the future development of substrates for biointerfaces, catalysis and controlled wetting.

Understanding and Controlling the Aggregative Growth of Platinum Nanoparticles in Atomic Layer Deposition: An Avenue to Size Selection.

We present an atomistic understanding of the evolution of the size distribution with temperature and number of cycles in atomic layer deposition (ALD) of Pt nanoparticles (NPs). Atomistic modeling of our experiments teaches us that the NPs grow mostly via NP diffusion and coalescence rather than through single-atom processes such as precursor chemisorption, atom attachment, and Ostwald ripening. In particular, our analysis shows that the NP aggregation takes place during the oxygen half-reaction and that the NP mobility exhibits a size- and temperature-dependent scaling. Finally, we show that contrary to what has been widely reported, in general, one cannot simply control the NP size by the number of cycles alone. Instead, while the amount of Pt deposited can be precisely controlled over a wide range of temperatures, ALD-like precision over the NP size requires low deposition temperatures (e.g., T < 100 °C) when growth is dominated by atom attachment.

Low-temperature atomic layer deposition delivers more active and stable Pt-based catalysts.

We tailored the size distribution of Pt nanoparticles (NPs) on graphene nanoplatelets at a given metal loading by using low-temperature atomic layer deposition carried out in a fluidized bed reactor operated at atmospheric pressure. The Pt NPs deposited at low temperature (100 °C) after 10 cycles were more active and stable towards the propene oxidation reaction than their high-temperature counterparts. Crucially, the gap in the catalytic performance was retained even after prolonged periods of time (>24 hours) at reaction temperatures as high as 450 °C. After exposure to such harsh conditions the Pt NPs deposited at 100 °C still retained a size distribution that is narrower than the one of the as-synthesized NPs obtained at 250 °C. The difference in performance correlated with the difference in the number of facet sites as estimated after the catalytic test. Our approach provides not only a viable route for the scalable synthesis of stable supported Pt NPs with tailored size distributions but also a tool for studying the structure-function relationship.