Colloidal-ALD-Grown Hybrid Shells Nucleate via a Ligand-Precursor Complex

Hybrid oxide coatings generate stable Cu catalysts for CO2 electroreduction

Hybrid organic/inorganic materials have contributed to solve important challenges in different areas of science. One of the biggest challenges for a more sustainable society is to have active and stable catalysts that enable the transition from fossil fuel to renewable feedstocks, reduce energy consumption and minimize the environmental footprint. Here we synthesize novel hybrid materials where an amorphous oxide coating with embedded organic ligands surrounds metallic nanocrystals. We demonstrate that the hybrid coating is a powerful means to create electrocatalysts stable against structural reconstruction during the CO2 electroreduction. These electrocatalysts consist of copper nanocrystals encapsulated in a hybrid organic/inorganic alumina shell. This shell locks a fraction of the copper surface into a reduction-resistant Cu2+ state, which inhibits those redox processes responsible for the structural reconstruction of copper. The electrocatalyst activity is preserved, which would not be possible with a conventional dense alumina coating. Varying the shell thickness and the coating morphology yields fundamental insights into the stabilization mechanism and emphasizes the importance of the Lewis acidity of the shell in relation to the retention of catalyst structure. The synthetic tunability of the chemistry developed herein opens new avenues for the design of stable electrocatalysts and beyond.

Colloidal Atomic Layer Deposition on Nanocrystals Using Ligand-Modified Precursors

Atomic layer deposition (ALD) is a method to grow thin metal oxide layers on a variety of materials for applications spanning from electronics to catalysis. Extending ALD to colloidally stable nanocrystals promises to combine the benefits of thin metal oxide coatings with the solution processability of the nanocrystals. However, challenges persist in applying this method, which relate to finding precursors that promote the growth of the metal oxide while preserving colloidal stability throughout the process. Herein, we introduce a colloidal ALD method to coat nanocrystals with amorphous metal oxide shells using metal and oxygen precursors that act as colloidal stabilizing ligands. Our scheme involves metal-amide precursors modified with solubilizing groups and oleic acid as the oxygen source. The growth of the oxide is self-limiting and proceeds in a layer-by-layer fashion. Our protocol is generalizable and intrinsically scalable. Potential applications in display, light detection, and catalysis are envisioned.

Rational Design of Dinitroxide Polarizing Agents for Dynamic Nuclear Polarization to Enhance Overall NMR Sensitivity

We evaluate the overall sensitivity gains provided by a series of eighteen nitroxide biradicals for dynamic nuclear polarization (DNP) solid-state NMR at 9.4 T and 100 K, including eight new biradicals. We find that in the best performing group the factors contributing to the overall sensitivity gains, namely the DNP enhancement, the build-up time, and the contribution factor, often compete with each other leading to very similar overall sensitivity across a range of biradicals. NaphPol and HydroPol are found to provide the best overall sensitivity factors, in organic and aqueous solvents respectively. One of the new biradicals, AMUPolCbm, provides high sensitivity for all three solvent formulations measured here, and can be considered to be a "universal" polarizing agent.

Exploiting Organometallic Chemistry to Functionalize Small Cuprous Oxide Colloidal Nanocrystals

The ligand chemistry of colloidal semiconductor nanocrystals mediates their solubility, band gap, and surface facets. Here, selective organometallic chemistry is used to prepare small, colloidal cuprous oxide nanocrystals and to control their surface chemistry by decorating them with metal complexes. The strategy is demonstrated using small (3-6 nm) cuprous oxide (Cu2O) colloidal nanocrystals (NC), soluble in organic solvents. Organometallic complexes are coordinated by reacting the surface Cu-OH bonds with organometallic reagents, M(C6F5)2, M = Zn(II) and Co(II), at room temperature. These reactions do not disrupt the Cu2O crystallinity or nanoparticle size; rather, they allow for the selective coordination of a specific metal complex at the surface. Subsequently, the surface-coordinated organometallic complex is reacted with three different carboxylic acids to deliver Cu-O-Zn(O2CR') complexes. Selective nanocrystal surface functionalization is established using spectroscopy (IR, 19F NMR), thermal gravimetric analyses (TGA), transmission electron microscopy (TEM, EELS), and X-ray photoelectron spectroscopy (XPS). Photoluminescence efficiency increases dramatically upon organometallic surface functionalization relative to that of the parent Cu2O NC, with the effect being most pronounced for Zn(II) decoration. The nanocrystal surfaces are selectively functionalized by both organic ligands and well-defined organometallic complexes; this synthetic strategy may be applicable to many other metal oxides, hydroxides, and semiconductors. In the future, it should allow NC properties to be designed for applications including catalysis, sensing, electronics, and quantum technologies.

Surface Chemistry Dictates the Enhancement of Luminescence and Stability of InP QDs upon c-ALD ZnO Hybrid Shell Growth

Indium phosphide quantum dots (InP QDs) are a promising example of Restriction of Hazardous Substances directive (RoHS)-compliant light-emitting materials. However, they suffer from low quantum yield and instability upon processing under ambient conditions. Colloidal atomic layer deposition (c-ALD) has been recently proposed as a methodology to grow hybrid materials including QDs and organic/inorganic oxide shells, which possess new functions compared to those of the as-synthesized QDs. Here, we demonstrate that ZnO shells can be grown on InP QDs obtained via two synthetic routes, which are the classical sylilphosphine-based route and the more recently developed aminophosphine-based one. We find that the ZnO shell increases the photoluminescence emission only in the case of aminophosphine-based InP QDs. We rationalize this result with the different chemistry involved in the nucleation step of the shell and the resulting surface defect passivation. Furthermore, we demonstrate that the ZnO shell prevents degradation of the InP QD suspension under ambient conditions by avoiding moisture-induced displacement of the ligands from their surface. Overall, this study proposes c-ALD as a methodology for the synthesis of alternative InP-based core@shell QDs and provides insight into the surface chemistry that results in both enhanced photoluminescence and stability required for application in optoelectronic devices and bioimaging.

AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning

Closed-loop, autonomous experimentation enables accelerated and material-efficient exploration of large reaction spaces without the need for user intervention. However, autonomous exploration of advanced materials with complex, multi-step processes and data sparse environments remains a challenge. In this work, we present AlphaFlow, a self-driven fluidic lab capable of autonomous discovery of complex multi-step chemistries. AlphaFlow uses reinforcement learning integrated with a modular microdroplet reactor capable of performing reaction steps with variable sequence, phase separation, washing, and continuous in-situ spectral monitoring. To demonstrate the power of reinforcement learning toward high dimensionality multi-step chemistries, we use AlphaFlow to discover and optimize synthetic routes for shell-growth of core-shell semiconductor nanoparticles, inspired by colloidal atomic layer deposition (cALD). Without prior knowledge of conventional cALD parameters, AlphaFlow successfully identified and optimized a novel multi-step reaction route, with up to 40 parameters, that outperformed conventional sequences. Through this work, we demonstrate the capabilities of closed-loop, reinforcement learning-guided systems in exploring and solving challenges in multi-step nanoparticle syntheses, while relying solely on in-house generated data from a miniaturized microfluidic platform. Further application of AlphaFlow in multi-step chemistries beyond cALD can lead to accelerated fundamental knowledge generation as well as synthetic route discoveries and optimization.

Dynamic Nuclear Polarization Enables NMR of Surface Passivating Agents on Hybrid Perovskite Thin Films

Surface and bulk molecular modulators are the key to improving the efficiency and stability of hybrid perovskite solar cells. However, due to their low concentration, heterogeneous environments, and low sample mass, it remains challenging to characterize their structure and dynamics at the atomic level, as required to establish structure–activity relationships. Nuclear magnetic resonance (NMR) spectroscopy has revealed a wealth of information on the atomic-level structure of hybrid perovskites, but the inherent insensitivity of NMR severely limits its utility to characterize thin-film samples. Dynamic nuclear polarization (DNP) can enhance NMR sensitivity by orders of magnitude, but DNP methods for perovskite materials have so far been limited. Here, we determined the factors that limit the efficiency of DNP NMR for perovskite samples by systematically studying layered hybrid perovskite analogues. We find that the fast-relaxing dynamic cation is the major impediment to higher DNP efficiency, while microwave absorption and particle morphology play a secondary role. We then show that the former can be mitigated by deuteration, enabling ¹H DNP enhancement factors of up to 100, which can be harnessed to enhance signals from dopants or additives present in very low concentrations. Specifically, using this new DNP methodology at a high magnetic field and with small sample volumes, we have recorded the NMR spectrum of the 20 nm (6 μg) passivating layer on a single perovskite thin film, revealing a two-dimensional (2D) layered perovskite structure at the surface that resembles the n = 1 homologue but which has greater disorder than in bulk layered perovskites.