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.

Reversible Intercalation of Li Ions in an Earth-Abundant Phyllosilicate Clay.

The phyllosilicate family of clays is an intriguing collection of materials that make ideal models for studying the intercalation of alkali ions due to their layered topology and broadly tunable composition space. In this spirit, we present a hydrothermal method to prepare a layered iron phyllosilicate clay, Fe2Si4O10(OH)2, and an evaluation of its electrochemical performance for the (de)insertion of Li ions. Through careful structural refinement, we determined that this iron clay contains a 2:1 stacking sequence, which is directly analogous to the widely studied mineral montmorillonite, with the crystallites adopting a platelike morphology. Cyclic voltammetry and galvanostatic cycling reveal reversible insertion of lithium into the interstitial layers via a solid solution mechanism. Comparison of ion (de)intercalation with reports on other clay systems like muscovite, KFe2.75Si3.25O10(OH)2, which features a rigidly bound interlayer cation, demonstrates that controlling the net charge on the layers with phyllosilicate minerals is a route to enabling reversible cationic intercalation within the structure.

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.

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.

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.

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.

Synthesis and Electrocatalytic HER Studies of Carbene-Ligated Cu3-xP Nanocrystals.

N-heterocyclic carbenes (NHCs) are an important class of ligands capable of making strong carbon-metal bonds. Recently, there has been a growing interest in the study of carbene-ligated nanocrystals, primarily coinage metal nanocrystals, which have found application as catalysts for numerous reactions. The general ability of NHC ligands to positively affect the catalytic properties of other types of nanocrystal catalysts remains unknown. Herein, we present the first carbene-stabilized Cu3-xP nanocrystals. Inquiries into the mechanism of formation of NHC-ligated Cu3-xP nanocrystals suggest that crystalline Cu3-xP forms directly as a result of a high-temperature metathesis reaction between a tris(trimethylsilyl)phosphine precursor and an NHC-CuBr precursor, the latter of which behaves as a source of both the carbene ligand and Cu+. To study the effect of the NHC surface ligands on the catalytic performance, we tested the electrocatalytic hydrogen evolving ability of the NHC-ligated Cu3-xP nanocrystals and found that they possess superior activity to analogous oleylamine-ligated Cu3-xP nanocrystals. Density functional theory calculations suggest that the NHC ligands minimize unfavorable electrostatic interactions between the copper phosphide surface and H+ during the first step of the hydrogen evolution reaction, which contributes to the superior performance of NHC-ligated Cu3-xP catalysts as compared to oleylamine-ligated Cu3-xP catalysts.