Transfer Learning of Full Molecular Weight Distributions via High-Throughput Computer-Controlled Polymerization.

The skew and shape of the molecular weight distribution (MWD) of polymers have a significant impact on polymer physical properties. Standard summary metrics statistically derived from the MWD only provide an incomplete picture of the polymer MWD. Machine learning (ML) methods coupled with high-throughput experimentation (HTE) could potentially allow for the prediction of the entire polymer MWD without information loss. In our work, we demonstrate a computer-controlled HTE platform that is able to run up to 8 unique variable conditions in parallel for the free radical polymerization of styrene. The segmented-flow HTE system was equipped with an inline Raman spectrometer and offline size exclusion chromatography (SEC) to obtain time-dependent conversion and MWD, respectively. Using ML forward models, we first predict monomer conversion, intrinsically learning varying polymerization kinetics that change for each experimental condition. In addition, we predict entire MWDs including the skew and shape as well as SHAP analysis to interpret the dependence on reagent concentrations and reaction time. We then used a transfer learning approach to use the data from our high-throughput flow reactor to predict batch polymerization MWDs with only three additional data points. Overall, we demonstrate that the combination of HTE and ML provides a high level of predictive accuracy in determining polymerization outcomes. Transfer learning can allow exploration outside existing parameter spaces efficiently, providing polymer chemists with the ability to target the synthesis of polymers with desired properties.

The effect of crystallinity on photocatalytic performance of Co3O4 water-splitting cocatalysts.

Cocatalysts, when loaded onto a water splitting photocatalyst, accelerate the gas evolution reaction and improve the efficiency of the photocatalyst. In this paper, we report that the efficiency of the photocatalyst is enhanced using an amorphous cobalt oxide cocatalyst. The WO3 film, when loaded with amorphous or nanocrystalline Co3O4, shows an improvement of up to 40% in photocurrent generation and 34% in hydrogen gas evolution. The effect of cocatalyst crystallinity on performance was systematically studied, and we found that the photocurrent deteriorates with the conversion of the cocatalyst to a highly crystalline phase at an annealing temperature of 500 °C. The mechanism of this effect was studied in detail using electrochemical impedance spectroscopy, and the enhancement effect produced by the amorphous cocatalyst is attributed to the large density of unsaturated catalytically active sites in the amorphous material.

Sol-gel deposited Cu2O and CuO thin films for photocatalytic water splitting.

Cu2O and CuO are attractive photocatalytic materials for water splitting due to their earth abundance and low cost. In this paper, we report the deposition of Cu2O and CuO thin films by a sol-gel spin-coating process. Sol-gel deposition has distinctive advantages such as low-cost solution processing and uniform film formation over large areas with a precise stoichiometry and thickness control. Pure-phase Cu2O and CuO films were obtained by thermal annealing at 500 °C in nitrogen and ambient air, respectively. The films were successfully incorporated as photocathodes in a photoelectrochemical (PEC) cell, achieving photocurrents of -0.28 mA cm(-2) and -0.35 mA cm(-2) (for Cu2O and CuO, respectively) at 0.05 V vs. a reversible hydrogen electrode (RHE). The Cu2O photocurrent was enhanced to -0.47 mA cm(-2) upon incorporation of a thin layer of a NiOx co-catalyst. Preliminary stability studies indicate that CuO may be more stable than Cu2O as a photocathode for PEC water-splitting.

Probing surface states in PbS nanocrystal films using pentacene field effect transistors: controlling carrier concentration and charge transport in pentacene.

We used a bilayer field effect transistor (FET) consisting of a thin PbS nanocrystals (NCs) film interfaced with vacuum-deposited pentacene to probe trap states in NCs. We interpret the observed threshold voltage shift in context of charge carrier trapping by PbS NCs and relate the magnitude of the threshold voltage shift to the number of trapped carriers. We explored a series of NC surface ligands to modify the interface between PbS NCs and pentacene and demonstrate the impact of interface chemistry on charge carrier density and the FET mobility in a pentacene FET.

Experimentally validated inverse design of multi-property Fe-Co-Ni alloys.

This study presents a machine learning (ML) framework aimed at accelerating the discovery of multi-property optimized Fe-Ni-Co alloys, addressing the time-consuming, expensive, and inefficient nature of traditional methods of material discovery, development, and deployment. We compiled a detailed heterogeneous database of the magnetic, electrical, and mechanical properties of Fe-Co-Ni alloys, employing a novel ML-based imputation strategy to address gaps in property data. Leveraging this comprehensive database, we developed predictive ML models using tree-based and neural network approaches for optimizing multiple properties simultaneously. An inverse design strategy, utilizing multi-objective Bayesian optimization (MOBO), enabled the identification of promising alloy compositions. This approach was experimentally validated using high-throughput methodology, highlighting alloys such as Fe66.8Co28Ni5.2 and Fe61.9Co22.8Ni15.3, which demonstrated superior properties. The predicted properties data closely matched experimental data within 14% accuracy. Our approach can be extended to a broad range of materials systems to predict novel materials with an optimized set of properties.

Closed-Loop Multi-Objective Optimization for Cu-Sb-S Photo-Electrocatalytic Materials' Discovery.

Copper antimony sulfides are regarded as promising catalysts for photo-electrochemical water splitting because of their earth abundance and broad light absorption. The unique photoactivity of copper antimony sulfides is dependent on their various crystalline structures and atomic compositions. Here, a closed-loop workflow is built, which explores Cu-Sb-S compositional space to optimize its photo-electrocatalytic hydrogen evolution from water, by integrating a high-throughput robotic platform, characterization techniques, and machine learning (ML) optimization workflow. The multi-objective optimization model discovers optimum experimental conditions after only nine cycles of integrated experiments-machine learning loop. Photocurrent testing at 0 V versus reversible hydrogen electrode (RHE) confirms the expected correlation between the materials' properties and photocurrent. An optimum photocurrent of -186 µA cm-2 is observed on Cu-Sb-S in the ratio of 9:45:46 in the form of single-layer coating on F-doped SnO2 (FTO) glass with a corresponding bandgap of 1.85 eV and 63.2% Cu1+ /Cu species content. The targeted intelligent search reveals a nonobvious CuSbS composition that exhibits 2.3 times greater activity than baseline results from random sampling.

Machine-Learning-Assisted Discovery of Mechanosynthesized Lead-Free Metal Halide Perovskites for the Oxidative Photocatalytic Cleavage of Alkenes.

Lead-free metal halide perovskites can potentially be air- and water-stable photocatalysts for organic synthesis, but there are limited studies on them for this application. Separately, machine learning (ML), a critical subfield of artificial intelligence, has played a pivotal role in identifying correlations and formulating predictions based on extensive datasets. Herein, an iterative workflow by incorporating high-throughput experimental data with ML to discover new lead-free metal halide perovskite photocatalysts for the aerobic oxidation of styrene is described. Through six rounds of ML optimization guided by SHapley Additive exPlanations (SHAP) analysis, BA2CsAg0.95Na0.05BiBr7 as a photocatalyst that afforded an 80% yield of benzoic acid under the standard conditions is identified, which is a 13-fold improvement compared to the 6% with when using Cs2AgBiBr6 as the initial photocatalyst benchmark that is started. BA2CsAg0.95Na0.05BiBr7 can tolerate various functional groups with 22 styrene derivatives, highlighting the generality of the photocatalytic properties demonstrated. Radical scavenging studies and density functional theory calculations revealed that the formation of the reactive oxygen species superoxide and singlet oxygen in the presence of BA2CsAg0.95Na0.05BiBr7 are critical for photocatalysis.

P(VDF-TrFE) ferroelectric nanotube array for high energy density capacitor applications.

Poly(vinylidene-fluoride-co-trifluoroethylene) (P(VDF-TrFE)) ferroelectric nanotube arrays were fabricated using an anodized alumina membrane (AAM) as a template and silver electrodes were deposited on both the outer and inner sides of the nanotubes by an electroless plating method. The nanotubes have the unique structure of being sealed at one end and linked at the open end, thus preventing electrical shorting between the inner and outer electrodes. Compared with a P(VDF-TrFE) film with a similar overall thickness, the idealized nanotube array has a theoretical capacitance that is 763 times larger due to the greatly enlarged contact area between the electrodes and the polymer dielectric. A capacitance that is 95 times larger has been demonstrated experimentally, thus indicating that such nanotube arrays are promising for realizing high density capacitance and high power dielectric energy storage.

Machine learning-assisted optimization of multi-metal hydroxide electrocatalysts for overall water splitting.

Green hydrogen produced via electrochemical water splitting is a suitable candidate to replace emission-intensive fuels. However, the successful widespread adoption of green hydrogen is contingent on the development of low-cost, earth-abundant catalysts. Herein, machine learning models built on experimental data were used to optimize the precursor ratios of hydroxide-based electrocatalysts, with the objective of improving the product's electrocatalytic performance for overall water splitting. The Neural Network-based models were found to be the most effective in predicting and minimizing the overpotentials of the catalysts, reaching a minimum in two iterations. The relatively mild reaction conditions of the synthesis procedure, coupled with its scalability demonstrated herein, renders the optimized catalyst relevant for industrial implementation in the future. The optimized catalyst, characterized to be a molybdate-intercalated CoFe LDH, demonstrated overpotentials of 266 and 272 mV at 10 mA cm-2 for oxygen and hydrogen evolution reactions respectively in alkaline electrolyte, alongside unwavering stability for overall water splitting over 50 h. Overall, our results reflect the efficacy and advantages of machine learning strategies to alleviate the time and labour-intensive nature of experimental optimizations, which can greatly accelerate electrocatalysts research.

Surface charge as activity descriptors for electrochemical CO2 reduction to multi-carbon products on organic-functionalised Cu.

Intensive research in electrochemical CO2 reduction reaction has resulted in the discovery of numerous high-performance catalysts selective to multi-carbon products, with most of these catalysts still being purely transition metal based. Herein, we present high and stable multi-carbon products selectivity of up to 76.6% across a wide potential range of 1 V on histidine-functionalised Cu. In-situ Raman and density functional theory calculations revealed alternative reaction pathways that involve direct interactions between adsorbed histidine and CO2 reduction intermediates at more cathodic potentials. Strikingly, we found that the yield of multi-carbon products is closely correlated to the surface charge on the catalyst surface, quantified by a pulsed voltammetry-based technique which proved reliable even at very cathodic potentials. We ascribe the surface charge to the population density of adsorbed species on the catalyst surface, which may be exploited as a powerful tool to explain CO2 reduction activity and as a proxy for future catalyst discovery, including organic-inorganic hybrids.

Photogenerated exciton dissociation in highly coupled lead salt nanocrystal assemblies.

Internanocrystal coupling induced excitons dissociation in lead salt nanocrystal assemblies is investigated. By combining transient photoluminescence spectroscopy, grazing incidence small-angle X-ray scattering, and time-resolved electric force microscopy, we show that excitons can dissociate, without the aid of an external bias or chemical potential gradient, via tunneling through a potential barrier when the coupling energy is comparable to the exciton binding energy. Our results have important implications for the design of nanocrystal-based optoelectronic devices.

Photoelectrochemical Water-Splitting Using CuO-Based Electrodes for Hydrogen Production: A Review.

The cost-effective, robust, and efficient electrocatalysts for photoelectrochemical (PEC) water-splitting has been extensively studied over the past decade to address a solution for the energy crisis. The interesting physicochemical properties of CuO have introduced this promising photocathodic material among the few photocatalysts with a narrow bandgap. This photocatalyst has a high activity for the PEC hydrogen evolution reaction (HER) under simulated sunlight irradiation. Here, the recent advancements of CuO-based photoelectrodes, including undoped CuO, doped CuO, and CuO composites, in the PEC water-splitting field, are comprehensively studied. Moreover, the synthesis methods, characterization, and fundamental factors of each classification are discussed in detail. Apart from the exclusive characteristics of CuO-based photoelectrodes, the PEC properties of CuO/2D materials, as groups of the growing nanocomposites in photocurrent-generating devices, are discussed in separate sections. Regarding the particular attention paid to the CuO heterostructure photocathodes, the PEC water splitting application is reviewed and the properties of each group such as electronic structures, defects, bandgap, and hierarchical structures are critically assessed.

SnSe nanocrystals: synthesis, structure, optical properties, and surface chemistry.

The colloidal synthesis of SnSe nanoparticles is accomplished through the injection of bis[bis(trimethylsilyl)amino]tin(II) into hot trioctylphosphine:selenium in the presence of oleylamine. Through the manipulation of reaction temperature particles are grown with the average diameter reliably tuned to 4-10 nm. Quantum confinement is examined by establishing a relationship between particle size and band gap while the in depth growth dynamics are illuminated through UV-vis-NIR spectroscopy. Surface chemistry effects are explored, including the demonstration of useful ligand exchanges and the development of routes toward anisotropic particle growth. Finally, transient current-voltage properties of SnSe nanocrystal films in the dark and light are examined.

PbSe nanocrystal excitonic solar cells.

We report the design, fabrication, and characterization of colloidal PbSe nanocrystal (NC)-based photovoltaic test structures that exhibit an excitonic solar cell mechanism. Charge extraction from the NC active layer is driven by a photoinduced chemical potential energy gradient at the nanostructured heterojunction. By minimizing perturbation to PbSe NC energy levels and thereby gaining insight into the "intrinsic" photovoltaic properties and charge transfer mechanism of PbSe NC, we show a direct correlation between interfacial energy level offsets and photovoltaic device performance. Size dependent PbSe NC energy levels were determined by cyclic voltammetry and optical spectroscopy and correlated to photovoltaic measurements. Photovoltaic test structures were fabricated from PbSe NC films sandwiched between layers of ZnO nanoparticles and PEDOT:PSS as electron and hole transporting elements, respectively. The device current-voltage characteristics suggest a charge separation mechanism that is distinct from previously reported Schottky devices and consistent with signatures of excitonic solar cells. Remarkably, despite the limitation of planar junction structure, and without film thickness optimization, the best performing device shows a 1-sun power conversion efficiency of 3.4%, ranking among the highest performing NC-based solar cells reported to date.

Recent Advances in Plasmonic Perovskite Solar Cells.

Perovskite solar cells (PSCs) have emerged recently as promising candidates for next generation photovoltaics and have reached power conversion efficiencies of 25.2%. Among the various methods to advance solar cell technologies, the implementation of nanoparticles with plasmonic effects is an alternative way for photon and charge carrier management. Surface plasmons at the interfaces or surfaces of sophisticated metal nanostructures are able to interact with electromagnetic radiation. The properties of surface plasmons can be tuned specifically by controlling the shape, size, and dielectric environment of the metal nanostructures. Thus, incorporating metallic nanostructures in solar cells is reported as a possible strategy to explore the enhancement of energy conversion efficiency mainly in semi-transparent solar cells. One particularly interesting option is PSCs with plasmonic structures enable thinner photovoltaic absorber layers without compromising their thickness while maintaining a high light harvest. In this Review, the effects of plasmonic nanostructures in electron transport material, perovskite absorbers, the hole transport material, as well as enhancement of effective refractive index of the medium and the resulting solar cell performance are presented. Aside from providing general considerations and a review of plasmonic nanostructures, the current efforts to introduce these plasmonic structures into semi-transparent solar cells are outlined.

Carrier control in 2D transition metal dichalcogenides with Al2O3 dielectric.

We report transport measurements of dual gated MoS2 and WSe2 devices using atomic layer deposition grown Al2O3 as gate dielectrics. We are able to achieve current pinch-off using independent split gates and observe current steps suggesting possible carrier confinement. We also investigated the impact of gate geometry and used electrostatic potential simulations to explain the observed device physics.

Modification of Vapor Phase Concentrations in MoS2 Growth Using a NiO Foam Barrier.

Single-layer molybdenum disulfide (MoS2) has attracted significant attention due to its electronic and physical properties, with much effort invested toward obtaining large-area high-quality monolayer MoS2 films. In this work, we demonstrate a reactive-barrier-based approach to achieve growth of highly homogeneous single-layer MoS2 on sapphire by the use of a nickel oxide foam barrier during chemical vapor deposition. Due to the reactivity of the NiO barrier with MoO3, the concentration of precursors reaching the substrate and thus nucleation density is effectively reduced, allowing grain sizes of up to 170 µm and continuous monolayers on the centimeter length scale being obtained. The quality of the monolayer is further revealed by angle-resolved photoemission spectroscopy measurement by observation of a very well resolved electronic band structure and spin-orbit splitting of the bands at room temperature with only two major domain orientations, indicating the successful growth of a highly crystalline and well-oriented MoS2 monolayer.

Carbon-ensemble-manipulated ZnS heterostructures for enhanced photocatalytic H2 evolution.

In this paper, we demonstrate a facile design of ZnS-based heterostructures tailored by versatile glucose-derived carbon ensembles, including carbon dots (CDs) and thin carbon shells, via hydrothermal synthesis. Tuning the content of glucose allows interesting and simple conversion from CDs to carbon shells on the surfaces of ZnS nanospheres. The as-formed ZnS/carbon nanocomposites exhibit an enhanced hydrogen evolution rate, up to 4.9 times over bare ZnS nanospheres, from sacrificial photocatalytic water splitting under solar light. The upconverted photoluminescence properties of the carbon nanomaterials, coupled with favorable electron transfer ability, are responsible for the improved photocatalytic behavior. Additionally, the difference in the hydrogen rates between CDs and the carbon shell was discussed. The inexpensive and convenient strategy may offer new prospects in the engineering of desirable nanostructures with better performance.