From Gel to Crystal: Mechanism of HfO2 and ZrO2 Nanocrystal Synthesis in Benzyl Alcohol.

Nonaqueous sol-gel syntheses have been used to make many types of metal oxide nanocrystals. According to the current paradigm, nonaqueous syntheses have slow kinetics, thus favoring the thermodynamic (crystalline) product. Here we investigate the synthesis of hafnium (and zirconium) oxide nanocrystals from the metal chloride in benzyl alcohol. We follow the transition from precursor to nanocrystal through a combination of rheology, EXAFS, NMR, TEM, and X-ray total scattering (PDF analysis). Upon dissolving the metal chloride precursor, the exchange of chloride ligands for benzylalkoxide liberates HCl. The latter catalyzes the etherification of benzyl alcohol, eliminating water. During the temperature ramp to the reaction temperature (220 °C), sufficient water is produced to turn the reaction mixture into a macroscopic gel. Rheological analysis shows a network consisting of strong interactions with temperature-dependent restructuring. After a few minutes at the reaction temperature, crystalline particles emerge from the gel, and nucleation and growth are complete after 30 min. In contrast, 4 h are required to obtain the highest isolated yield, which we attribute to the slow in situ formation of water (the extraction solvent). We used our mechanistic insights to optimize the synthesis, achieving high isolated yields with a reduced reaction time. Our results oppose the idea that nonaqueous sol-gel syntheses necessarily form crystalline products in one step, without a transient, amorphous gel state.

Influence of Composition and Structure on the Optoelectronic Properties of Photocatalytic Bi4NbO8Cl-Bi2GdO4Cl Intergrowths.

Mixed metal oxyhalides are an exciting class of photocatalysts, capable of the sustainable generation of fuels and remediation of pollutants with solar energy. Bismuth oxyhalides of the types Bi4MO8X (M = Nb and Ta; X = Cl and Br) and Bi2AO4X (A = most lanthanides; X = Cl, Br, and I) have an electronic structure that imparts photostability, as their valence band maxima (VBM) are composed of O 2p orbitals rather than X np orbitals that typify many other bismuth oxyhalides. Here, flux-based synthesis of intergrowth Bi4NbO8Cl-Bi2GdO4Cl is reported, testing the hypothesis that both intergrowth stoichiometry and M identity serve as levers toward tunable optoelectronic properties. X-ray scattering and atomically resolved electron microscopy verify intergrowth formation. Facile manipulation of the Bi4NbO8Cl-to-Bi2GdO4Cl ratio is achieved with the specific ratio influencing both the crystal and electronic structures of the intergrowths. This compositional flexibility and crystal structure engineering can be leveraged for photocatalytic applications, with comparisons to the previously reported Bi4TaO8Cl-Bi2GdO4Cl intergrowth revealing how subtle structural and compositional features can impact photocatalytic materials.

Design and Application of a Gas Diffusion Electrode (GDE) Cell for Operando and In Situ Studies.

Presented here is an electrochemical three-electrode Gas Diffusion Electrode (GDE) cell tailored for operandoand in situ investigations of electrocatalytic processes, with a particular focus on X-ray scattering studies. The optimized cell is engineered to accommodate the minimal sample-detector distances requisite for comprehensive X-ray total scattering investigations. An in-depth understanding of catalytic processes requires their study under 'working' conditions. Configured as a flow-cell, the setup therefore enables the examination of electrocatalysts under high current densities and associated gas evolution phenomena, particularly pertinent for reactions like the oxygen evolution reaction (OER). Notably, its transparency simplifies cell alignment, troubleshooting, and facilitates scans through the catalyst layer, crucial for background corrections. Demonstrating its versatility, we showcase its utility through Small Angle X-ray Scattering (SAXS), X-ray Diffraction (XRD), and X-ray Pair Distribution Function (PDF) analyses of total scattering data.

Chemical Insights into the Formation of Colloidal Iridium Nanoparticles from In Situ X-ray Total Scattering: Influence of Precursors and Cations on the Reaction Pathway.

Iridium nanoparticles are important catalysts for several chemical and energy conversion reactions. Studies of iridium nanoparticles have also been a key for the development of kinetic models of nanomaterial formation. However, compared to other metals such as gold or platinum, knowledge on the nature of prenucleation species and structural insights into the resultant nanoparticles are missing, especially for nanoparticles obtained from IrxCly precursors investigated here. We use in situ X-ray total scattering (TS) experiments with pair distribution function (PDF) analysis to study a simple, surfactant-free synthesis of colloidal iridium nanoparticles. The reaction is performed in methanol at 50 °C with only a base and an iridium salt as precursor. From different precursor salts─IrCl3, IrCl4, H2IrCl6, or Na2IrCl6─colloidal nanoparticles as small as Ir∼55 are obtained as the final product. The nanoparticles do not show the bulk iridium face-centered cubic (fcc) structure but show decahedral and icosahedral structures. The formation route is highly dependent on the precursor salt used. Using IrCl3 or IrCl4, metallic iridium nanoparticles form rapidly from IrxClyn- complexes, whereas using H2IrCl6 or Na2IrCl6, the iridium nanoparticle formation follows a sudden growth after an induction period and the brief appearance of a crystalline phase. With H2IrCl6, the formation of different Irn (n = 55, 55, 85, and 116) nanoparticles depends on the nature of the cation in the base (LiOH, NaOH, KOH, or CsOH, respectively) and larger particles are obtained with larger cations. As the particles grow, the nanoparticle structure changes from partly icosahedral to decahedral. The results show that the synthesis of iridium nanoparticles from IrxCly is a valuable iridium nanoparticle model system, which can provide new compositional and structural insights into iridium nanoparticle formation and growth.

Influence of the Precursor Structure on the Formation of Tungsten Oxide Polymorphs.

Understanding material nucleation processes is crucial for the development of synthesis pathways for tailormade materials. However, we currently have little knowledge of the influence of the precursor solution structure on the formation pathway of materials. We here use in situ total scattering to show how the precursor solution structure influences which crystal structure is formed during the hydrothermal synthesis of tungsten oxides. We investigate the synthesis of tungsten oxide from the two polyoxometalate salts, ammonium metatungstate, and ammonium paratungstate. In both cases, a hexagonal ammonium tungsten bronze (NH4)0.25WO3 is formed as the final product. If the precursor solution contains metatungstate clusters, this phase forms directly in the hydrothermal synthesis. However, if the paratungstate B cluster is present at the time of crystallization, a metastable intermediate phase in the form of a pyrochlore-type tungsten oxide, WO3·0.5H2O, initially forms. The pyrochlore structure then undergoes a phase transformation into the tungsten bronze phase. Our studies thus experimentally show that the precursor cluster structure present at the moment of crystallization directly influences the formed crystalline phase and suggests that the precursor structure just prior to crystallization can be used as a tool for targeting specific crystalline phases of interest.

Control of H-Related Defects in γ-MnO2 in a Hydrothermal Synthesis.

Manganese dioxide is a good candidate for effective energy storage and conversion as it possesses rich electrochemistry. The compound also shows a wide polymorphism. The γ-variety, an intergrowth of ß- and R-MnO2, has been extensively studied in several types of batteries (e.g., Zn/MnO2, Li-ion) and is a common electrode material for commercial batteries. It is well known that the insertion of protons thermodynamically stabilizes γ-MnO2 with respect to ß-MnO2. Protons can enter the structure either by forming groups of 4 hydroxyls around a Mn4+ vacancy, called a Ruetschi defect, or by forming a hydroxyl group near a Mn3+ ion, called a Coleman defect. These defects differently affect the electrochemistry of manganese oxide, and tailoring their amount in the structure can be used to tune the material properties. Previous studies have addressed the proton insertion process, but the role of the synthesis pathway on the amount of defects created is not well understood. We here investigate how the parameters in a hydrothermal synthesis of γ-MnO2 nanoparticles influence the amount and type of H-related defects. Structural investigations are carried out using Pair Distribution Function analysis, X-ray absorption spectroscopy, thermogravimetric analysis, and inelastic neutron scattering. We demonstrate the possibility to control the amount and type of defects introduced during the synthesis. While the amount of Ruetschi defects increases with synthesis temperature, it decreases with extended synthesis time, along with the amount of Coleman defects. Moreover, we discuss the arrangement of the defects in the γ-MnO2 nanoparticles.

Self-supported Pt-CoO networks combining high specific activity with high surface area for oxygen reduction.

Several concepts for platinum-based catalysts for the oxygen reduction reaction (ORR) are presented that exceed the US Department of Energy targets for Pt-related ORR mass activity. Most concepts achieve their high ORR activity by increasing the Pt specific activity at the expense of a lower electrochemically active surface area (ECSA). In the potential region controlled by kinetics, such a lower ECSA is counterbalanced by the high specific activity. At higher overpotentials, however, which are often applied in real systems, a low ECSA leads to limitations in the reaction rate not by kinetics, but by mass transport. Here we report on self-supported platinum-cobalt oxide networks that combine a high specific activity with a high ECSA. The high ECSA is achieved by a platinum-cobalt oxide bone nanostructure that exhibits unprecedentedly high mass activity for self-supported ORR catalysts. This concept promises a stable fuel-cell operation at high temperature, high current density and low humidification.

Characterization of Nanomaterials with Total Scattering and Pair Distribution Function Analysis: Examples from Metal Oxide Nanochemistry.

The development of new functional nanomaterials builds on an understanding of the intricate relation between material structure and properties. Only by knowing the atomic arrangement can the mechanisms responsible for material properties be elucidated and new materials and technologies developed. Nanomaterials challenge the crystallographic techniques often used for structure characterization, and the structure of many nanomaterials are therefore often assumed to be 'cut-outs' of the corresponding bulk material. Here, I will discuss how Pair Distribution Function (PDF) analysis of total scattering data can aid nanochemists in obtaining a structural understanding of nanoscale materials, focusing on examples from metal oxide chemistry.

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small-Angle X-ray Scattering Analysis.

The combination of in situ pair distribution function (PDF) analysis and small-angle X-ray scattering (SAXS) enables analysis of the formation mechanism of metal oxido nanoclusters and cluster-solvent interactions as they take place. Herein, we demonstrate the method for the formation of clusters with a [Bi38 O45 ] core. Upon dissolution of crystalline [Bi6 O5 (OH)3 (NO3 )5 ]⋅3 H2 O in DMSO, an intermediate rapidly forms, which slowly grows to stable [Bi38 O45 ] clusters. To identify the intermediate, we developed an automated modeling method, where smaller [Bix Oy ] structures based on the [Bi38 O45 ] framework are tested against the data. [Bi22 O26 ] was identified as the main intermediate species, illustrating how combined PDF and SAXS analysis is a powerful tool to gain insight into nucleation on an atomic scale. PDF also provides information on the interaction between nanoclusters and solvent, which is shown to depend on the nature of the ligands on the cluster surface.

Solution Structure, Electronic Energy Levels, and Photophysical Properties of [Eu(MeOH)n-2m(NO3)m]3-m+ Complexes.

The structure of lanthanide(III) ions in solutions high in nitrate has been debated since the early days of lanthanide coordination chemistry. The structure and properties of lanthanides in these solutions are essential in industrial rare-earth separation, as well as in the fundamental solution chemistry of these elements. Pending decades of debate, it was established that nitrate is bidentate and coordinates in the inner sphere, and complexes have been observed with as many as four nitrates coordinated to a single lanthanide(III) center in nonaqueous solutions. We revisit the interactions between nitrate and europium(III) in methanol using optical spectroscopy, X-ray total scattering, and the current understanding of europium(III) photophysics. By a combination of direct and indirect methods to probe the structure, it was found that four distinct species from Eu(MeOH)93+ to [Eu(MeOH)3(NO3)3] are present in solutions containing from 0 to 2 M NO3- ions. It was shown that the changes in transition probabilities together with high-resolution spectra can provide information on speciation and how the minute changes in ligand field affect the microstates. By a comparison to total X-ray scattering, it was concluded that the optical spectra alone allow the constitution and symmetry of the europium(III) species to be determined. Most notably, the minute changes in the all oxygen atom coordination imply significant changes in the optical properties of the europium(III) center.

The effect of weighted averages when determining the speciation and structure-property relationships of europium(iii) dipicolinate complexes.

Lanthanide(iii) coordination chemistry in solution is inherently complicated by the lack of directional interactions and rapid ligand exchange. The latter can be eliminated in kinetically inert complexes, but remains a challenge in complexes between lanthanide(iii) ions and smaller ligands. As multiple conformations and partial decomplexation is an issue even with multidentate ligands, it will influence the observed solution properties of complexes of smaller ligands common in the field of f-elements coordination chemistry such as acetylacetonates and dipicolinates. Here, europium(iii) complexes with one, two and three dipicolinates were investigated in a series of 13 samples, where the composition was varied from 0 to 3 equivalents of dipicolinate. While the results did show the formation of three distinct europium(iii) dipicolinate complexes confirming the literature data on the system, clear discrepancies in speciation related properties were evident when comparing the results from absorption and luminescence spectroscopy. It was concluded that the difference is due to the difference in time constant of the two experiments. Furthermore, it is shown that the information obtained from luminescence arises from a weigthed average, and with discepancies between the observed and actual concentration exceeding 25%, it is advised that the weighted averages are taken into consideration when reporting on solution properties of lanthanide(iii) complexes. From the resolved optical spectra of [Eu(H2O)9]3+, [Eu(DPA)(H2O)6]+, [Eu(DPA)2(H2O)3]-, and [Eu(DPA)3]3-, the excited energy levels and transition probabilities are determined, and it was concluded that both transition probabilities and ligand field effects on the microstates are different in all four species.

Structural characterization and magnetic properties of chromium jarosite KCr3(OD)6(SO4)2.

Potassium chromium jarosite, KCr3(OH)6(SO4)2 (Cr-jarosite), is considered a promising candidate to display spin liquid behavior due to the strong magnetic frustration imposed by the crystal structure. However, the ground state magnetic properties have been debated, since Cr-jarosite is notoriously non-stoichiometric. Our study reports the magnetic properties for deuterated KCr3(OD)6(SO4)2 on chemically well-defined samples, which have been characteried by a combination of powder X-ray diffraction, neutron diffraction, solid state NMR spectroscopy, and scanning electron microscopy with energy dispersive spectroscopy. Eight polycrystalline samples, which all contained only 1-3% Cr vacancies were obtained. However, significant substitution (2-27%) of potassium with H2O and/or H3O+ was observed and resulted in pronounced stacking disorder along the c-axis. A clear second-order transition to an antiferromagnetically ordered phase at TN = 3.8(1) K with a small net moment of 0.03 µB per Cr3+-ion was obtained from vibrating sample magnetometry and temperature dependent neutron diffraction. The moment is attributed to spin canting caused by the Dzyaloshinskii-Moriya interaction. Thus, our experimental results imply that even ideal potassium chromium jarosite will exhibit magnetic order below 4 K and therefore it does not qualify as a true spin liquid material.

Same Precursor, Two Different Products: Comparing the Structural Evolution of In-Ga-O "Gel-Derived" Powders and Solution-Cast Films Using Pair Distribution Function Analysis.

Amorphous metal oxides are central to a variety of technological applications. In particular, indium gallium oxide has garnered attention as a thin-film transistor channel layer material. In this work we examine the structural evolution of indium gallium oxide gel-derived powders and thin films using infrared vibrational spectroscopy, X-ray diffraction, and pair distribution function (PDF) analysis of X-ray total scattering from standard and normal incidence thin-film geometries (tfPDF). We find that the gel-derived powders and films from the same aqueous precursor evolve differently with temperature, forming mixtures of Ga-substituted In2O3 and In-substituted ß-Ga2O3 with different degrees of substitution. X-ray total scattering and PDF analysis indicate that the majority phase for both the powders and films is an amorphous/nanocrystalline ß-Ga2O3 phase, with a minor constituent of In2O3 with significantly larger coherence lengths. This amorphous ß-Ga2O3 phase could not be identified using the conventional Bragg diffraction techniques traditionally used to study crystalline metal oxide thin films. The combination of Bragg diffraction and tfPDF provides a much more complete description of film composition and structure, which can be used to detail the effect of processing conditions and structure-property relationships. This study also demonstrates how structural features of amorphous materials, traditionally difficult to characterize by standard diffraction, can be elucidated using tfPDF.

Structural Evolution of Iron Antimonides from Amorphous Precursors to Crystalline Products Studied by Total Scattering Techniques.

Homogeneous reaction precursors may be used to form several solid-state compounds inaccessible by traditional synthetic routes, but there has been little development of techniques that allow for a priori prediction of what may crystallize in a given material system. Here, the local structures of FeSbx designed precursors are determined and compared with the structural motifs of their crystalline products. X-ray total scattering and atomic pair distribution function (PDF) analysis are used to show that precursors that first nucleate a metastable FeSb3 compound share similar local structure to the product. Interestingly, precursors that directly crystallize to thermodynamically stable FeSb2 products also contain local structural motifs of the metastable phase, despite their compositional disagreement. While both crystalline phases consist of distorted FeSb6 octahedra with Sb shared between either two or three octahedra as required for stoichiometry, a corner-sharing arrangement indicative of AX3-type structures is the only motif apparent in the PDF of either precursor. Prior speculation was that local composition controlled which compounds nucleate from amorphous intermediates, with different compositions favoring different local arrangements and hence different products. This data suggests that local environments in these amorphous intermediates may not be very sensitive to overall composition. This can provide insight into potential metastable phases which may form in a material system, even with a precursor that does not crystallize to the kinetically stabilized product. Determination of local structure in homogeneous amorphous reaction intermediates from techniques such as PDF can be a valuable asset in the development of systematic methods to prepare targeted solid-state compounds from designed precursors.

In situ total X-ray scattering study of WO3 nanoparticle formation under hydrothermal conditions.

Pair distribution function analysis of in situ total scattering data recorded during formation of WO3 nanocrystals under hydrothermal conditions reveal that a complex precursor structure exists in solution. The WO6 polyhedra of the precursor cluster undergo reorientation before forming the nanocrystal. This reorientation is the critical element in the formation of different hexagonal polymporphs of WO3.

POMFinder: identifying polyoxometallate cluster structures from pair distribution function data using explainable machine learning.

Characterization of a material structure with pair distribution function (PDF) analysis typically involves refining a structure model against an experimental data set, but finding or constructing a suitable atomic model for PDF modelling can be an extremely labour-intensive task, requiring carefully browsing through large numbers of possible models. Presented here is POMFinder, a machine learning (ML) classifier that rapidly screens a database of structures, here polyoxometallate (POM) clusters, to identify candidate structures for PDF data modelling. The approach is shown to identify suitable POMs from experimental data, including in situ data collected with fast acquisition times. This automated approach has significant potential for identifying suitable models for structure refinement to extract quantitative structural parameters in materials chemistry research. POMFinder is open source and user friendly, making it accessible to those without prior ML knowledge. It is also demonstrated that POMFinder offers a promising modelling framework for combined modelling of multiple scattering techniques.

The Chemistry of Spinel Ferrite Nanoparticle Nucleation, Crystallization, and Growth.

The nucleation, crystallization, and growth mechanisms of MnFe2O4, CoFe2O4, NiFe2O4, and ZnFe2O4 nanocrystallites prepared from coprecipitated transition metal (TM) hydroxide precursors treated at sub-, near-, and supercritical hydrothermal conditions have been studied by in situ X-ray total scattering (TS) with pair distribution function (PDF) analysis, and in situ synchrotron powder X-ray diffraction (PXRD) with Rietveld analysis. The in situ TS experiments were carried out on 0.6 M TM hydroxide precursors prepared from aqueous metal chloride solutions using 24.5% NH4OH as the precipitating base. The PDF analysis reveals equivalent nucleation processes for the four spinel ferrite compounds under the studied hydrothermal conditions, where the TMs form edge-sharing octahedrally coordinated hydroxide units (monomers/dimers and in some cases trimers) in the aqueous precursor, which upon hydrothermal treatment nucleate through linking by tetrahedrally coordinated TMs. The in situ PXRD experiments were carried out on 1.2 M TM hydroxide precursors prepared from aqueous metal nitrate solutions using 16 M NaOH as the precipitating base. The crystallization and growth of the nanocrystallites were found to progress via different processes depending on the specific TMs and synthesis temperatures. The PXRD data show that MnFe2O4 and CoFe2O4 nanocrystallites rapidly grow (typically <1 min) to equilibrium sizes of 20-25 nm and 10-12 nm, respectively, regardless of applied temperature in the 170-420 °C range, indicating limited possibility of targeted size control. However, varying the reaction time (0-30 min) and temperature (150-400 °C) allows different sizes to be obtained for NiFe2O4 (3-30 nm) and ZnFe2O4 (3-12 nm) nanocrystallites. The mechanisms controlling the crystallization and growth (nucleation, growth by diffusion, Ostwald ripening, etc.) were examined by qualitative analysis of the evolution in refined scale factor (proportional to extent of crystallization) and mean crystallite volume (proportional to extent of growth). Interestingly, lower kinetic barriers are observed for the formation of the mixed spinels (MnFe2O4 and CoFe2O4) compared to the inverse (NiFe2O4) and normal (ZnFe2O4) spinel structured compounds, suggesting that the energy barrier for formation may be lowered when the TMs have no site preference.

ClusterFinder: a fast tool to find cluster structures from pair distribution function data.

A novel automated high-throughput screening approach, ClusterFinder, is reported for finding candidate structures for atomic pair distribution function (PDF) structural refinements. Finding starting models for PDF refinements is notoriously difficult when the PDF originates from nanoclusters or small nanoparticles. The reported ClusterFinder algorithm can screen 104 to 105 candidate structures from structural databases such as the Inorganic Crystal Structure Database (ICSD) in minutes, using the crystal structures as templates in which it looks for atomic clusters that result in a PDF similar to the target measured PDF. The algorithm returns a rank-ordered list of clusters for further assessment by the user. The algorithm has performed well for simulated and measured PDFs of metal-oxido clusters such as Keggin clusters. This is therefore a powerful approach to finding structural cluster candidates in a modelling campaign for PDFs of nanoparticles and nanoclusters.

MLstructureMining: a machine learning tool for structure identification from X-ray pair distribution functions.

Synchrotron X-ray techniques are essential for studies of the intrinsic relationship between synthesis, structure, and properties of materials. Modern synchrotrons can produce up to 1 petabyte of data per day. Such amounts of data can speed up materials development, but also comes with a staggering growth in workload, as the data generated must be stored and analyzed. We present an approach for quickly identifying an atomic structure model from pair distribution function (PDF) data from (nano)crystalline materials. Our model, MLstructureMining, uses a tree-based machine learning (ML) classifier. MLstructureMining has been trained to classify chemical structures from a PDF and gives a top-3 accuracy of 99% on simulated PDFs not seen during training, with a total of 6062 possible classes. We also demonstrate that MLstructureMining can identify the chemical structure from experimental PDFs from nanoparticles of CoFe2O4 and CeO2, and we show how it can be used to treat an in situ PDF series collected during Bi2Fe4O9 formation. Additionally, we show how MLstructureMining can be used in combination with the well-known methods, principal component analysis (PCA) and non-negative matrix factorization (NMF) to analyze data from in situ experiments. MLstructureMining thus allows for real-time structure characterization by screening vast quantities of crystallographic information files in seconds.

Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry.

The rapid growth of materials chemistry data, driven by advancements in large-scale radiation facilities as well as laboratory instruments, has outpaced conventional data analysis and modelling methods, which can require enormous manual effort. To address this bottleneck, we investigate the application of supervised and unsupervised machine learning (ML) techniques for scattering and spectroscopy data analysis in materials chemistry research. Our perspective focuses on ML applications in powder diffraction (PD), pair distribution function (PDF), small-angle scattering (SAS), inelastic neutron scattering (INS), and X-ray absorption spectroscopy (XAS) data, but the lessons that we learn are generally applicable across materials chemistry. We review the ability of ML to identify physical and structural models and extract information efficiently and accurately from experimental data. Furthermore, we discuss the challenges associated with supervised ML and highlight how unsupervised ML can mitigate these limitations, thus enhancing experimental materials chemistry data analysis. Our perspective emphasises the transformative potential of ML in materials chemistry characterisation and identifies promising directions for future applications. The perspective aims to guide newcomers to ML-based experimental data analysis.