A Multistep, Multicomponent Extraction and Separation Microfluidic Route to Recycle Water-Miscible Ionic Liquid Solvents.

Recycling ionic liquid (IL) solvents can reduce the lifecycle cost of these expensive solvents. Liquid-liquid extraction is the most straightforward approach to purify IL solvents and is typically performed with an immiscible washing agent (e.g., water). Herein, we describe a recycling route for water-miscible ILs in which direct recycling is usually challenging. We use hydrophobic ILs as accommodating agents to draw the water-miscible IL from the aqueous washing stream. A biphasic slug flow of the mixed ILs and water is then separated by using a membrane. The water-miscible IL can then be drawn out from the mixed IL phase with acidified water and dried under vacuum. Both the water-miscible IL and the accommodating agent are then recycled. Here, we demonstrated a proof-of-concept of this process by recycling 1-butyl-3-methylimidazolium trifluoromethanesulfonate (BMIM-OTf) in the presence of the accommodating agent 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (BMIM-NTf2) and acidified water. We then demonstrated the capacity to recycle 1-butyl-1-methylpyrrolidinium triflate (BMPYRR-OTf) from a realistic synthetic application: Pt nanoparticle synthesis in the water-miscible IL.

Using Data-Driven Learning to Predict and Control the Outcomes of Inorganic Materials Synthesis.

The design of inorganic materials for various applications critically depends on our ability to manipulate their synthesis in a rational, robust, and controllable fashion. Different from the conventional trial-and-error approach, data-driven techniques such as the design of experiments (DoE) and machine learning are an effective and more efficient way to predictably control materials synthesis. Here, we present a Viewpoint on recent progress in leveraging such techniques for predicting and controlling the outcomes of inorganic materials synthesis. We first compare how the design choice (statistical DoE vs machine learning) affects the type of control it can offer over the resulting product attributes, information elucidated, and experimental cost. These attributes are supported by discussing select case studies from the recent literature that highlight the power of these techniques for materials synthesis. The influence of experimental bias is next discussed, followed finally by our perspectives on the major challenges in the widespread implementation of predictable and controllable materials synthesis using data-driven techniques.

Predictive Synthesis of Copper Selenides Using a Multidimensional Phase Map Constructed with a Data-Driven Classifier.

Copper selenides are an important family of materials with applications in catalysis, plasmonics, photovoltaics, and thermoelectrics. Despite being a binary material system, the Cu-Se phase diagram is complex and contains multiple crystal structures in addition to several metastable structures that are not found on the thermodynamic phase diagram. Consequently, the ability to synthetically navigate this complex phase space poses a significant challenge. We demonstrate that data-driven learning can successfully map this phase space in a minimal number of experiments. We combine soft chemistry (chimie douce) synthetic methods with multivariate analyses via classification techniques to enable predictive phase determination. A surrogate model was constructed with experimental data derived from a design matrix of four experimental variables: C-Se bond strength of the selenium precursor, time, temperature, and solvent composition. The reactions in the surrogate model resulted in 11 distinct phase combinations of copper selenide. These data were used to train a classification model that predicts the phase with 95.7% accuracy. The resulting decision tree enabled conclusions to be drawn about how the experimental variables affect the phase and provided prescriptive synthetic conditions for specific phase isolation. This guided the accelerated phase targeting in a minimum number of experiments of klockmannite CuSe, which could not be isolated in any of the reactions used to construct the surrogate model. The reaction conditions that the model predicted to synthesize klockmannite CuSe were experimentally validated, highlighting the utility of this approach.

The surface chemistry of ionic liquid-treated CsPbBr3 quantum dots.

The power conversion efficiencies of lead halide perovskite thin film solar cells have surged in the short time since their inception. Compounds, such as ionic liquids (ILs), have been explored as chemical additives and interface modifiers in perovskite solar cells, contributing to the rapid increase in cell efficiencies. However, due to the small surface area-to-volume ratio of the large grained polycrystalline halide perovskite films, an atomistic understanding of the interaction between ILs and perovskite surfaces is limited. Here, we use quantum dots (QDs) to study the coordinative surface interaction between phosphonium-based ILs and CsPbBr3. When native oleylammonium oleate ligands are exchanged off the QD surface with the phosphonium cation as well as the IL anion, a threefold increase in photoluminescent quantum yield of as-synthesized QDs is observed. The CsPbBr3 QD structure, shape, and size remain unchanged after ligand exchange, indicating only a surface ligand interaction at approximately equimolar additions of the IL. Increased concentrations of the IL lead to a disadvantageous phase change and a concomitant decrease in photoluminescent quantum yields. Valuable information regarding the coordinative interaction between certain ILs and lead halide perovskites has been elucidated and can be used for informed pairing of beneficial combinations of IL cations and anions.

Formation of a P162- Ink from Elemental Red Phosphorus in a Thiol-Amine Mixture.

A P162- polyphosphide dianion ink was produced by the reaction of red phosphorus with a binary thiol-amine mixture of ethanethiol (ET) and ethylenediamine (en). The polyphosphide was identified by solution 31P NMR spectroscopy and electrospray ionization mass spectrometry. This solute was compared to the reaction products of white phosphorus (P4) and other elemental pnictides in the same solvent system. The reaction of P4 with ET and en gives the same P162- polyphosphide; however, the easier handling and lower reactivity of red phosphorus highlights the novelty of that reaction. Elemental arsenic and antimony both give mononuclear pnictogen-sulfide-thiolate complexes upon reaction with ET and en under otherwise identical conditions, with this difference likely resulting from the greater covalency and tendency of phosphorus to form P-P bonds.

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis.

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42 650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. A classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.

Polymorphic Control of Solution-Processed Cu2SnS3 Films with Thiol-Amine Ink Formulation.

There is increasing demand for tailored molecular inks that produce phase-pure solution-processed semiconductor films. Within the Cu-Sn-S phase space, Cu2SnS3 belongs to the I2-IV-VI3 class of semiconductors that crystallizes in several different polymorphs. We report the ability of thiol-amine solvent mixtures to dissolve inexpensive bulk Cu2S and SnO precursors to generate free-flowing molecular inks. Upon mild annealing, polymorphic control over phase-pure tetragonal (I4̅2m) and orthorhombic (Cmc21) Cu2SnS3 films was realized simply by switching the identity of the thiol (i.e., 1,2-ethanedithiol vs 2-mercaptoethanol, respectively). Polymorph control is dictated by differences in the resulting molecular metal-thiolate complexes and their subsequent decomposition profiles, which likely seed distinct Cu2-x S phases that template the ternary sulfide sublattice. The p-type tetragonal and orthorhombic Cu2SnS3 films possess similar experimental direct optical band gaps of 0.94 and 0.88 eV, respectively, and strong photoelectrochemical current responses. Understanding how ink formulation dictates polymorph choice should inform the development of other thiol-amine inks for solution-processed films.

Activating Molybdenum Carbide Nanoparticle Catalysts under Mild Conditions Using Thermally Labile Ligands.

Transition-metal carbides are promising low-cost materials for various catalytic transformations due to their multifunctionality and noble-metal-like behavior. Nanostructuring transition-metal carbides offers advantages resulting from the large surface-area-to-volume ratios inherent in colloidal nanoparticle catalysts; however, a barrier for their utilization is removal of the long-chain aliphatic ligands on their surface to access active sites. Annealing procedures to remove these ligands require temperatures greater than the catalyst synthesis and catalytic reaction temperatures and may further result in coking or particle sintering that can reduce catalytic performance. One way to circumvent this problem is by replacing the long-chain aliphatic ligands with smaller ligands that can be easily removed through low-temperature thermolytic decomposition. Here, we present the exchange of native oleylamine ligands on colloidal α-MoC1-x nanoparticles for thermally labile tert-butylamine ligands. Analyses of the ligand exchange reaction by solution 1H NMR spectroscopy, FT-IR spectroscopy, and thermogravimetric analysis-mass spectrometry (TGA-MS) confirm the displacement of 60% of the native oleylamine ligands for the thermally labile tert-butylamine, which can be removed with a mild activation step at 250 °C. Catalytic site densities were determined by carbon monoxide (CO) chemisorption, demonstrating that the mild thermal treatment at 250 °C activates ca. 25% of the total binding sites, while the native oleylamine-terminated MoC1-x nanoparticles showed no available surface binding sites after this low-temperature treatment. The mild pretreatment at 250 °C also shows distinctly different initial activities and postinduction period selectivities in the CO2 hydrogenation reaction for the ligand exchanged MoC1-x nanoparticle catalysts and the as-prepared material.

Surface Functionalization of Surfactant-Free Particles: A Strategy to Tailor the Properties of Nanocomposites for Enhanced Thermoelectric Performance.

The broad implementation of thermoelectricity requires high-performance and low-cost materials. One possibility is employing surfactant-free solution synthesis to produce nanopowders. We propose the strategy of functionalizing "naked" particles' surface by inorganic molecules to control the nanostructure and, consequently, thermoelectric performance. In particular, we use bismuth thiolates to functionalize surfactant-free SnTe particles' surfaces. Upon thermal processing, bismuth thiolates decomposition renders SnTe-Bi2 S3 nanocomposites with synergistic functions: 1) carrier concentration optimization by Bi doping; 2) Seebeck coefficient enhancement and bipolar effect suppression by energy filtering; and 3) lattice thermal conductivity reduction by small grain domains, grain boundaries and nanostructuration. Overall, the SnTe-Bi2 S3 nanocomposites exhibit peak z T up to 1.3 at 873 K and an average z T of ≈0.6 at 300-873 K, which is among the highest reported for solution-processed SnTe.

Kinetics and mechanistic details of bulk ZnO dissolution using a thiol-imidazole system.

Oxide dissolution is important for metal extraction from ores and has become an attractive route for the preparation of inks for thin film solution deposition; however, oxide dissolution is often kinetically challenging. While binary "alkahest" systems comprised of thiols and N-donor species, such as amines, are known to dissolve a wide range of oxides, the mechanism of dissolution and identity of the resulting solute(s) remain unstudied. Here, we demonstrate facile dissolution of both bulk synthetic and natural mineral ZnO samples using an "alkahest" that operates via reaction with thiophenol and 1-methylimidazole (MeIm) to give a single, pseudotetrahedral Zn(SPh)2(MeIm)2 molecular solute identified by X-ray crystallography. The kinetics of ZnO dissolution were measured using solution 1H NMR, and the reaction was found to be zero-order in the presence of excess ligands, with more electron withdrawing para-substituted thiophenols resulting in faster dissolution. A negative entropy of activation was measured by Eyring analysis, indicating associative ligand binding in, or prior to, the rate determining step. Combined experimental and computational surface binding studies on ZnO reveal stronger, irreversible thiophenol binding compared to MeIm, leading to a proposed dissolution mechanism initiated by thiol binding to the ZnO surface with the liberation of water, followed by alternating MeIm and thiolate ligand additions, and ultimately cleavage of the ligated zinc complex from the ZnO surface. Design rules garnered from the mechanistic insight provided by this study should inform the dissolution of other bulk oxides into inks for solution processed thin films.

Surface Functionalization of Surfactant-Free Particles: A Strategy to Tailor the Properties of Nanocomposites for Enhanced Thermoelectric Performance.

The broad implementation of thermoelectricity requires high-performance and low-cost materials. One possibility is employing surfactant-free solution synthesis to produce nanopowders. We propose the strategy of functionalizing "naked" particles' surface by inorganic molecules to control the nanostructure and, consequently, thermoelectric performance. In particular, we use bismuth thiolates to functionalize surfactant-free SnTe particles' surfaces. Upon thermal processing, bismuth thiolates decomposition renders SnTe-Bi2S3 nanocomposites with synergistic functions: 1) carrier concentration optimization by Bi doping; 2) Seebeck coefficient enhancement and bipolar effect suppression by energy filtering; and 3) lattice thermal conductivity reduction by small grain domains, grain boundaries and nanostructuration. Overall, the SnTe-Bi2S3 nanocomposites exhibit peak z T up to 1.3 at 873 K and an average z T of ≈0.6 at 300-873 K, which is among the highest reported for solution-processed SnTe.

Formation Pathway of Wurtzite-like Cu2ZnSnSe4 Nanocrystals.

Cu2ZnSnSe4 is a direct band gap semiconductor composed of earth-abundant elements, making it an attractive material for thin-film photovoltaic technologies. Cu2ZnSnSe4 crystallizes in the kesterite structure type as a bulk material, but it can also crystallize in a metastable wurtzite-like crystal structure when synthesized on the nanoscale. The wurtzite-like polymorph introduces unique and useful properties to Cu2ZnSnSe4 materials, including widely tunable band gaps and superior compositional flexibility as compared to kesterite Cu2ZnSnSe4. Here, we investigate the formation pathway of colloidally prepared wurtzite-like Cu2ZnSnSe4 nanocrystals. We show that this quaternary material forms through a chain of reactions, starting with binary Cu3Se2 nanocrystals that, due to both kinetic and thermodynamic reasons, preferentially react with tin to yield hexagonal copper tin selenide intermediates. These ternary intermediates then react with zinc to form the resulting wurtzite-like Cu2ZnSnSe4 nanocrystals. Based on this formation pathway, we suggest synthetic methods that may prevent the formation of unwanted impurity phases that are known to hamper the efficiency of Cu2ZnSnSe4-based optoelectronic devices.

Probing the Ligand Exchange of N-Heterocyclic Carbene-Capped Ag2S Nanocrystals with Amines and Carboxylic Acids.

N-Heterocyclic carbenes (NHCs) are versatile L-type ligands that have been shown to stabilize coinage metal chalcogenide nanocrystals, such as Ag2S, remarkably well. However, very little research has been done on the interaction between NHC ligands and coinage metal chalcogenide nanocrystal surfaces and subsequent ligand exchange reactions. Herein, solution 1H nuclear magnetic resonance methods were used to monitor ligand exchange reactions on stoichiometric Ag2S nanocrystal platforms with various primary amine and carboxylic acid ligands. Despite the introduction of new ligands, the native NHC ligands remain tightly bound to the Ag2S nanocrystal surface and are not displaced at room temperature. Primary amine and carboxylic acid ligands demonstrated quantitative ligand exchange only after the samples had been heated with an excess incoming ligand, which implies a strong NHC-Ag binding energy. Density functional theory affirms that a model NHC ligand binds the strongest to a Ag12S6 cluster surface, followed by amine and carboxylic acid binding; computational analysis is therefore in line with the absence of NHC displacement observed in experiments. Both the bulky sterics of the C14-alkyl chains on the NHC and the high energies for the binding of NHC to the Ag2S surface contribute to the superior colloidal stability over conventional long-chain amine or carboxylic acid ligands (many months vs hours to days).

Discovery of a Wurtzite-like Cu2FeSnSe4 Semiconductor Nanocrystal Polymorph and Implications for Related CuFeSe2 Materials.

I2-II-IV-VI4 and I-III-VI2 semiconductor nanocrystals have found applications in photovoltaics and other optoelectronic technologies because of their low toxicity and efficient light absorption into the near-infrared. Herein, we report the discovery of a metastable wurtzite-like polymorph of Cu2FeSnSe4, a member of the I2-II-IV-VI4 family of semiconductors containing only earth-abundant metals. Density functional theory calculations on this metastable polymorph of Cu2FeSnSe4 indicate that it may be a superior semiconductor for solar energy and optoelectronics applications compared to the thermodynamically preferred stannite polymorph, since the former displays a sharper dispersion of energy levels near the conduction band minimum that can enhance electron mobility and suppress hot electron cooling. The experimental optical band gap was measured by the inverse logarithmic derivative method to be direct, in agreement with theory, and in the range of 1.48-1.59 eV. Mechanistic studies reveal that this metastable phase derives from intermediate Cu3Se2 nanocrystals that serve as a structural template for the final hexagonal wurtzite-like product. We compare the chemistry of wurtzite-like Cu2FeSnSe4 to the related CuFeSe2 material system. Our experimental and computational comparisons between Cu2FeSnSe4 and CuFeSe2 help explain both the crystal chemistry of CuFeSe2 that prevents it from forming wurtzite-like polymorphs and the essential role of Sn in stabilizing the metastable structure of Cu2FeSnSe4. This work provides insight into the importance of elemental composition when designing syntheses for metastable materials.

Crystal Structure of Colloidally Prepared Metastable Ag2Se Nanocrystals.

Structural polymorphism is known for many bulk materials; however, on the nanoscale metastable polymorphs tend to form more readily than in the bulk, and with more structural variety. One such metastable polymorph observed for colloidal Ag2Se nanocrystals has traditionally been referred to as the "tetragonal" phase. While there are reports on the chemistry and properties of this metastable polymorph, its crystal structure, and therefore electronic structure, has yet to be determined. We report that an anti-PbCl2-like structure type (space group P21/n) more accurately describes the powder X-ray diffraction and X-ray total scattering patterns of colloidal Ag2Se nanocrystals prepared by several different methods. Density functional theory (DFT) calculations indicate that this anti-PbCl2-like Ag2Se polymorph is a dynamically stable, narrow-band-gap semiconductor. The anti-PbCl2-like structure of Ag2Se is a low-lying metastable polymorph at 5-25 meV/atom above the ground state, depending on the exchange-correlation functional used.

Statistical Multiobjective Optimization of Thiospinel CoNi2S4 Nanocrystal Synthesis via Design of Experiments.

Thiospinels, such as CoNi2S4, are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi2S4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi2S4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 25-2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/d̅) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.

The Surface Chemistry and Structure of Colloidal Lead Halide Perovskite Nanocrystals.

ConspectusSince the initial discovery of colloidal lead halide perovskite nanocrystals, there has been significant interest placed on these semiconductors because of their remarkable optoelectronic properties, including very high photoluminescence quantum yields, narrow size- and composition-tunable emission over a wide color gamut, defect tolerance, and suppressed blinking. These material attributes have made them attractive components for next-generation solar cells, light emitting diodes, low-threshold lasers, single photon emitters, and X-ray scintillators. While a great deal of research has gone into the various applications of colloidal lead halide perovskite nanocrystals, comparatively little work has focused on the fundamental surface chemistry of these materials. While the surface chemistry of colloidal semiconductor nanocrystals is generally affected by their particle morphology, surface stoichiometry, and organic ligands that contribute to the first coordination sphere of their surface atoms, these attributes are markedly different in lead halide perovskite nanocrystals because of their ionicity.In this Account, emerging work on the surface chemistry of lead halide perovskite nanocrystals is highlighted, with a particular focus placed on the most-studied composition of CsPbBr3. We begin with an in-depth exploration of the native surface chemistry of as-prepared, 0-D cuboidal CsPbBr3 nanocrystals, including an atomistic description of their surface termini, vacancies, and ionic bonding with ligands. We then proceed to discuss various post-synthetic surface treatments that have been developed to increase the photoluminescence quantum yields and stability of CsPbBr3 nanocrystals, including the use of tetraalkylammonium bromides, metal bromides, zwitterions, and phosphonic acids, and how these various ligands are known to bind to the nanocrystal surface. To underscore the effect of post-synthetic surface treatments on the application of these materials, we focus on lead halide perovskite nanocrystal-based light emitting diodes, and the positive effect of various surface treatments on external quantum efficiencies. We also discuss the current state-of-the-art in the surface chemistry of 1-D nanowires and 2-D nanoplatelets of CsPbBr3, which are more quantum confined than the corresponding cuboidal nanocrystals but also generally possess a higher defect density because of their increased surface area-to-volume ratios.