Suppressed phase segregation for triple-junction perovskite solar cells.

The tunable bandgaps and facile fabrication of perovskites make them attractive for multi-junction photovoltaics1,2. However, light-induced phase segregation limits their efficiency and stability3-5: this occurs in wide-bandgap (>1.65 electron volts) iodide/bromide mixed perovskite absorbers, and becomes even more acute in the top cells of triple-junction solar photovoltaics that require a fully 2.0-electron-volt bandgap absorber2,6. Here we report that lattice distortion in iodide/bromide mixed perovskites is correlated with the suppression of phase segregation, generating an increased ion-migration energy barrier arising from the decreased average interatomic distance between the A-site cation and iodide. Using an approximately 2.0-electron-volt rubidium/caesium mixed-cation inorganic perovskite with large lattice distortion in the top subcell, we fabricated all-perovskite triple-junction solar cells and achieved an efficiency of 24.3 per cent (23.3 per cent certified quasi-steady-state efficiency) with an open-circuit voltage of 3.21 volts. This is, to our knowledge, the first reported certified efficiency for perovskite-based triple-junction solar cells. The triple-junction devices retain 80 per cent of their initial efficiency following 420 hours of operation at the maximum power point.

Constrained C2 adsorbate orientation enables CO-to-acetate electroreduction.

The carbon dioxide and carbon monoxide electroreduction reactions, when powered using low-carbon electricity, offer pathways to the decarbonization of chemical manufacture1,2. Copper (Cu) is relied on today for carbon-carbon coupling, in which it produces mixtures of more than ten C2+ chemicals3-6: a long-standing challenge lies in achieving selectivity to a single principal C2+ product7-9. Acetate is one such C2 compound on the path to the large but fossil-derived acetic acid market. Here we pursued dispersing a low concentration of Cu atoms in a host metal to favour the stabilization of ketenes10-chemical intermediates that are bound in monodentate fashion to the electrocatalyst. We synthesize Cu-in-Ag dilute (about 1 atomic per cent of Cu) alloy materials that we find to be highly selective for acetate electrosynthesis from CO at high *CO coverage, implemented at 10 atm pressure. Operando X-ray absorption spectroscopy indicates in situ-generated Cu clusters consisting of <4 atoms as active sites. We report a 12:1 ratio, an order of magnitude increase compared to the best previous reports, in the selectivity for acetate relative to all other products observed from the carbon monoxide electroreduction reaction. Combining catalyst design and reactor engineering, we achieve a CO-to-acetate Faradaic efficiency of 91% and report a Faradaic efficiency of 85% with an 820-h operating time. High selectivity benefits energy efficiency and downstream separation across all carbon-based electrochemical transformations, highlighting the importance of maximizing the Faradaic efficiency towards a single C2+ product11.

Open-channel metal particle superlattices.

Although tremendous advances have been made in preparing porous crystals from molecular precursors1,2, there are no general ways of designing and making topologically diversified porous colloidal crystals over the 10-1,000 nm length scale. Control over porosity in this size range would enable the tailoring of molecular absorption and storage, separation, chemical sensing, catalytic and optical properties of such materials. Here, a universal approach for synthesizing metallic open-channel superlattices with pores of 10 to 1,000 nm from DNA-modified hollow colloidal nanoparticles (NPs) is reported. By tuning hollow NP geometry and DNA design, one can adjust crystal pore geometry (pore size and shape) and channel topology (the way in which pores are interconnected). The assembly of hollow NPs is driven by edge-to-edge rather than face-to-face DNA-DNA interactions. Two new design rules describing this assembly regime emerge from these studies and are then used to synthesize 12 open-channel superlattices with control over crystal symmetry, channel geometry and topology. The open channels can be selectively occupied by guests of the appropriate size and that are modified with complementary DNA (for example, Au NPs).

Automated crystal system identification from electron diffraction patterns using multiview opinion fusion machine learning.

A bottleneck in high-throughput nanomaterials discovery is the pace at which new materials can be structurally characterized. Although current machine learning (ML) methods show promise for the automated processing of electron diffraction patterns (DPs), they fail in high-throughput experiments where DPs are collected from crystals with random orientations. Inspired by the human decision-making process, a framework for automated crystal system classification from DPs with arbitrary orientations was developed. A convolutional neural network was trained using evidential deep learning, and the predictive uncertainties were quantified and leveraged to fuse multiview predictions. Using vector map representations of DPs, the framework achieves a testing accuracy of 0.94 in the examples considered, is robust to noise, and retains remarkable accuracy using experimental data. This work highlights the ability of ML to be used to accelerate experimental high-throughput materials data analytics.

Recent Development of Halide Perovskite Materials and Devices for Ionizing Radiation Detection.

Ionizing radiation such as X-rays and γ-rays has been extensively studied and used in various fields such as medical imaging, radiographic nondestructive testing, nuclear defense, homeland security, and scientific research. Therefore, the detection of such high-energy radiation with high-sensitivity and low-cost-based materials and devices is highly important and desirable. Halide perovskites have emerged as promising candidates for radiation detection due to the large light absorption coefficient, large resistivity, low leakage current, high mobility, and simplicity in synthesis and processing as compared with commercial silicon (Si) and amorphous selenium (a-Se). In this review, we provide an extensive overview of current progress in terms of materials development and corresponding device architectures for radiation detection. We discuss the properties of a plethora of reported compounds involving organic-inorganic hybrid, all-inorganic, all-organic perovskite and antiperovskite structures, as well as the continuous breakthroughs in device architectures, performance, and environmental stability. We focus on the critical advancements of the field in the past few years and we provide valuable insight for the development of next-generation materials and devices for radiation detection and imaging applications.

Uncovering the crystal defects within aragonite CaCO3.

Knowledge of deformation mechanisms in aragonite, one of the three crystalline polymorphs of CaCO3, is essential to understand the overall excellent mechanical performance of nacres. Dislocation slip and deformation twinning were claimed previously as plasticity carriers in aragonite, but crystallographic features of dislocations and twins have been poorly understood. Here, utilizing various transmission electron microscopy techniques, we reveal the atomic structures of twins, partial dislocations, and associated stacking faults. Combining a topological model and density functional theory calculations, we identify complete twin elements, characters of twinning disconnection, and the corresponding twin shear angle (∼8.8°) and rationalize unique partial dislocations as well. Additionally, we reveal an unreported potential energy dissipation mode within aragonite, namely, the formation of nanograins via the pile-up of partial dislocations. Based on the microstructural comparisons of biogenic and abiotic aragonite, we find that the crystallographic features of twins are the same. However, the twin density is much lower in abiotic aragonite due to the vastly different crystallization conditions, which in turn are likely due to the absence of organics, high temperature and pressure differences, the variation in inorganic impurities, or a combination thereof. Our findings enrich the knowledge of intrinsic crystal defects that accommodate plastic deformation in aragonite and provide insights into designing bioengineering materials with better strength and toughness.

High Thermoelectric Performance in Rhombohedral GeSe-LiBiTe2.

GeSe, an analogue of SnSe, shows promise in exhibiting exceptional thermoelectric performance in the Pnma phase. The constraints on its dopability, however, pose challenges in attaining optimal carrier concentrations and improving ZT values. This study demonstrates a crystal structure evolution strategy for achieving highly doped samples and promising ZTs in GeSe via LiBiTe2 alloying. A rhombohedral phase (R3m) can be stabilized in the GeSe-LiBiTe2 system, further evolving into a cubic (Fm3̅m) phase with a rising temperature. The band structures of GeSe-LiBiTe2 in the rhombohedral and cubic phases feature a similar multiple-valley energy-converged valence band of L and Σ bands. The observed high carrier concentration (∼1020 cm-3) reflects the effective convergence of these bands, enabling a high density-of-states effective mass and an enhanced power factor. Moreover, a very low lattice thermal conductivity of 0.6-0.5 W m-1 K-1 from 300 to 723 K is achieved in 0.9GeSe-0.1LiBiTe2, approaching the amorphous limit value. This remarkably low lattice thermal conductivity is related to phonon scattering from point defects, planar vacancies, and ferroelectric instability-induced low-energy Einstein oscillators. Finally, a maximum ZT value of 1.1 to 1.3 at 723 K is obtained, with a high average ZT value of over 0.8 (400-723 K) in 0.9GeSe-0.1LiBiTe2 samples. This study establishes a viable route for tailoring crystal structures to significantly improve the performance of GeSe-related compounds.

Implications and Optimization of Domain Structures in IV-VI High-Entropy Thermoelectric Materials.

High-entropy semiconductors are now an important class of materials widely investigated for thermoelectric applications. Understanding the impact of chemical and structural heterogeneity on transport properties in these compositionally complex systems is essential for thermoelectric design. In this work, we uncover the polar domain structures in the high-entropy PbGeSnSe1.5Te1.5 system and assess their impact on thermoelectric properties. We found that polar domains induced by crystal symmetry breaking give rise to well-structured alternating strain fields. These fields effectively disrupt phonon propagation and suppress the thermal conductivity. We demonstrate that the polar domain structures can be modulated by tuning crystal symmetry through entropy engineering in PbGeSnAgxSbxSe1.5+xTe1.5+x. Incremental increases in the entropy enhance the crystal symmetry of the system, which suppresses domain formation and loses its efficacy in suppressing phonon propagation. As a result, the room-temperature lattice thermal conductivity increases from κL = 0.63 Wm-1 K-1 (x = 0) to 0.79 Wm-1 K-1 (x = 0.10). In the meantime, the increase in crystal symmetry, however, leads to enhanced valley degeneracy and improves the weighted mobility from µw = 29.6 cm2 V-1 s-1 (x = 0) to 35.8 cm2 V-1 s-1 (x = 0.10). As such, optimal thermoelectric performance can be achieved through entropy engineering by balancing weighted mobility and lattice thermal conductivity. This work, for the first time, studies the impact of polar domain structures on thermoelectric properties, and the developed understanding of the intricate interplay between crystal symmetry, polar domains, and transport properties, along with the impact of entropy control, provides valuable insights into designing GeTe-based high-entropy thermoelectrics.

Probing Structural Transformations and Degradation Mechanisms by Direct Observation in SIFSIX-3-Ni for Direct Air Capture.

Despite global efforts to reduce carbon dioxide (CO2) emissions, continued industrialization threatens to exacerbate climate change. This work investigates methods to capture CO2, with a focus on the SIFSIX-3-Ni metal-organic framework (MOF) as a direct air capture (DAC) sorbent. SIFSIX-3-Ni exhibits promising CO2 adsorption properties but suffers from degradation processes under accelerated aging, which are akin to column regeneration conditions. Herein, we have grown the largest SIFSIX-3-Ni single crystals to date, facilitating single crystal X-ray diffraction analyses that enabled direct observation of the H2O and CO2 dynamics through adsorption and desorption. In addition, a novel space group (I4/mcm) for the SIFSIX-3-Ni is identified, which provided insights into structural transitions within the framework and elucidated water's role in degrading CO2 uptake performance as the material ages. In situ X-ray scattering methods revealed long-range and local structural transformations associated with CO2 adsorption in the framework pores as well as a temperature-dependent desorption mechanism. Pair distribution function analysis revealed a partial decomposition to form nonporous single-layer nanosheets of edge-sharing nickel oxide octahedra upon aging. The formation of these nanosheets is irreversible and reduces the amount of active material for the CO2 sorption. These findings provide crucial insights for the development of efficient and stable DAC sorbents, effectively reducing greenhouse gases, and suggest avenues for enhancing MOF stability under practical DAC conditions.

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.

Phosphate Elimination and Recovery Lightweight (PEARL) membrane: A sustainable environmental remediation approach.

Aqueous phosphate pollution can dramatically impact ecosystems, introducing a variety of environmental, economic, and public health problems. While novel remediation tactics based on nanoparticle binding have shown considerable promise in nutrient recovery from water, they are challenging to deploy at scale. To bridge the gap between the laboratory-scale nature of these nanostructure solutions and the practical benchmarks for deploying an environmental remediation tool, we have developed a nanocomposite material. Here, an economical, readily available, porous substrate is dip coated using scalable, water-based processes with a slurry of nanostructures. These nanomaterials have tailored affinity for specific adsorption of pollutants. Our Phosphate Elimination and Recovery Lightweight (PEARL) membrane can selectively sequester up to 99% of phosphate ions from polluted waters at environmentally relevant concentrations. Moreover, mild tuning of pH promotes at will adsorption and desorption of nutrients. This timed release allows for phosphate recovery and reuse of the PEARL membrane repeatedly for numerous cycles. We combine correlative microscopy and spectroscopy techniques to characterize the complex microstructure of the PEARL membrane and to unravel the mechanism of phosphate sorption. More broadly, through the example of phosphate pollution, this work describes a platform membrane approach based on nanostructures with specific affinity coated on a porous structure. Such a strategy can be tuned to address other environmental remediation challenges through the incorporation of other nanomaterials.

Crystal structure engineering in multimetallic high-index facet nanocatalysts.

In the context of metal particle catalysts, composition, shape, exposed facets, crystal structure, and atom distribution dictate activity. While techniques have been developed to control each of these parameters, there is no general method that allows one to optimize all parameters in the context of polyelemental systems. Herein, by combining a solid-state, Bi-influenced, high-index facet shape regulation strategy with thermal annealing, we achieve control over crystal structure and atom distribution on the exposed high-index facets, resulting in an unprecedentedly diverse library of chemically disordered and ordered multimetallic (Pt, Co, Ni, Cu, Fe, and Mn) tetrahexahedral (THH) nanoparticles. Density functional theory calculations show that surface Bi modification stabilizes the {210} high-index facets of the nanoparticles, regardless of their internal atomic ordering. Moreover, we find that the ordering transition temperatures for the nanoparticles are dependent on their composition, and, in the case of Pt3Fe1 THH nanoparticles, increasing Ni substitution leads to an order-to-disorder transition at 900 °C. Finally, we have discovered that ordered intermetallic THH Pt1Co1 nanocatalysts exhibit a catalytic performance superior to disordered THH Pt1Co1 nanoparticles and commercial Pt/C catalysts toward methanol electrooxidation, highlighting the importance of crystal structure and atom distribution control on high-index facets in nanoscale catalysts.

"Soft" oxidative coupling of methane to ethylene: Mechanistic insights from combined experiment and theory.

The oxidative coupling of methane to ethylene using gaseous disulfur (2CH4 + S2 → C2H4 + 2H2S) as an oxidant (SOCM) proceeds with promising selectivity. Here, we report detailed experimental and theoretical studies that examine the mechanism for the conversion of CH4 to C2H4 over an Fe3O4-derived FeS2 catalyst achieving a promising ethylene selectivity of 33%. We compare and contrast these results with those for the highly exothermic oxidative coupling of methane (OCM) using O2 (2CH4 + O2 → C2H4 + 2H2O). SOCM kinetic/mechanistic analysis, along with density functional theory results, indicate that ethylene is produced as a primary product of methane activation, proceeding predominantly via CH2 coupling over dimeric S-S moieties that bridge Fe surface sites, and to a lesser degree, on heavily sulfided mononuclear sites. In contrast to and unlike OCM, the overoxidized CS2 by-product forms predominantly via CH4 oxidation, rather than from C2 products, through a series of C-H activation and S-addition steps at adsorbed sulfur sites on the FeS2 surface. The experimental rates for methane conversion are first order in both CH4 and S2, consistent with the involvement of two S sites in the rate-determining methane C-H activation step, with a CD4/CH4 kinetic isotope effect of 1.78. The experimental apparent activation energy for methane conversion is 66 ± 8 kJ/mol, significantly lower than for CH4 oxidative coupling with O2 The computed methane activation barrier, rate orders, and kinetic isotope values are consistent with experiment. All evidence indicates that SOCM proceeds via a very different pathway than that of OCM.

Machine Learning-Enabled Image Classification for Automated Electron Microscopy.

Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of "big data" and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.

Silver Atom Off-Centering in Diamondoid Solid Solutions Causes Crystallographic Distortion and Suppresses Lattice Thermal Conductivity.

The class I-III-VI2 diamondoid compounds with tetrahedral bonding are important semiconductors widely applied in optoelectronics. Understanding their heat transport properties and developing an effective method to predict the diamondoid solid solutions' thermal conductivity will help assess their impact as thermoelectrics. In this work, we investigated in detail the heat transport properties of CuGa1-xInxTe2 and Cu1-xAgxGaTe2 and found that in the Ag-alloyed solid solutions, the Ag atom off-centering effect results in crystallographic distortion and extra strong acoustic-optical phonon scattering and an extremely low lattice thermal conductivity. Moreover, we integrate the alloy scattering and the off-centering effect with the crystallographic distortion parameter to develop a modified Klemens model that predicts the thermal conductivity of diamondoid solid solutions. Finally, we demonstrate that Cu1-xAgxGaTe2 solid solutions are promising p-type thermoelectric materials, with a maximum ZT of 1.23 at 850 K for Cu0.58Ag0.4GaTe2.

Chemical Behavior and Local Structure of the Ruddlesden-Popper and Dion-Jacobson Alloyed Pb/Sn Bromide 2D Perovskites.

The alloyed lead/tin (Pb/Sn) halide perovskites have gained significant attention in the development of tandem solar cells and other optoelectronic devices due to their widely tunable absorption edge. To gain a better understanding of the intriguing properties of Pb/Sn perovskites, such as their anomalous bandgap's dependence on stoichiometry, it is important to deepen the understanding of their chemical behavior and local structure. Herein, we investigate a series of two-dimensional Ruddlesden-Popper (RP) and Dion-Jacobson (DJ) phase alloyed Pb/Sn bromide perovskites using butylammonium (BA) and 3-(aminomethyl)pyridinium (3AMPY) as the spacer cations: (BA)2(MA)n-1PbxSnn-xBr3n+1 (n = 1-3) and (3AMPY)(MA)n-1PbxSnn-xBr3n+1 (n = 1-3) through a solution-based approach. Our results show that the ratio and site preference of Pb/Sn atoms are influenced by the layer thickness (n) and spacer cations (A'), as determined by single-crystal X-ray diffraction. Solid-state 1H, 119Sn, and 207Pb NMR spectroscopy analysis shows that the Pb atoms prefer the outer layers in n = 3 members: (BA)2(MA)PbxSnn-xBr10 and (3AMPY)(MA)PbxSnn-xBr10. Layered 2D DJ alloyed Pb/Sn bromide perovskites (3AMPY)(MA)n-1PbxSnn-xBr3n+1 (n = 1-3) demonstrate much narrower optical band gaps, lower energy PL emission peaks, and longer carrier lifetimes compared to those of RP analogs. Density functional theory calculations suggest that Pb-rich alloys (Pb:Sn ∼4:1) for n = 1 compounds are thermodynamically favored over 50:50 (Pb:Sn ∼1:1) compositions. From grazing-incidence wide-angle X-ray scattering (GIWAXS), we see that films in the RP phase orient parallel to the substrate, whereas for DJ cases, random orientations are observed relative to the substrate.

Unraveling the Role of Entropy in Thermoelectrics: Entropy-Stabilized Quintuple Rock Salt PbGeSnCdxTe3+x.

Entropy-engineered materials are garnering considerable attention owing to their excellent mechanical and transport properties, such as their high thermoelectric performance. However, understanding the effect of entropy on thermoelectrics remains a challenge. In this study, we used the PbGeSnCdxTe3+x family as a model system to systematically investigate the impact of entropy engineering on its crystal structure, microstructure evolution, and transport behavior. We observed that PbGeSnTe3 crystallizes in a rhombohedral structure at room temperature with complex domain structures and transforms into a high-temperature cubic structure at ∼373 K. By alloying CdTe with PbGeSnTe3, the increased configurational entropy lowers the phase-transition temperature and stabilizes PbGeSnCdxTe3+x in the cubic structure at room temperature, and the domain structures vanish accordingly. The high-entropy effect results in increased atomic disorder and consequently a low lattice thermal conductivity of 0.76 W m-1 K-1 in the material owing to enhanced phonon scattering. Notably, the increased crystal symmetry is conducive to band convergence, which results in a high-power factor of 22.4 µW cm-1 K-1. As a collective consequence of these factors, a maximum ZT of 1.63 at 875 K and an average ZT of 1.02 in the temperature range of 300-875 K were obtained for PbGeSnCd0.08Te3.08. This study highlights that the high-entropy effect can induce a complex microstructure and band structure evolution in materials, which offers a new route for the search for high-performance thermoelectrics in entropy-engineered materials.

The emergence of valency in colloidal crystals through electron equivalents.

Colloidal crystal engineering of complex, low-symmetry architectures is challenging when isotropic building blocks are assembled. Here we describe an approach to generating such structures based upon programmable atom equivalents (nanoparticles functionalized with many DNA strands) and mobile electron equivalents (small particles functionalized with a low number of DNA strands complementary to the programmable atom equivalents). Under appropriate conditions, the spatial distribution of the electron equivalents breaks the symmetry of isotropic programmable atom equivalents, akin to the anisotropic distribution of valence electrons or coordination sites around a metal atom, leading to a set of well-defined coordination geometries and access to three new low-symmetry crystalline phases. All three phases represent the first examples of colloidal crystals, with two of them having elemental analogues (body-centred tetragonal and high-pressure gallium), while the third (triple double-gyroid structure) has no known natural equivalent. This approach enables the creation of complex, low-symmetry colloidal crystals that might find use in various technologies.

Combustion Synthesis and Polymer Doping of Metal Oxides for High-Performance Electronic Circuitry.

ConspectusTransparent conducting oxides (TCOs) are inorganic electrical conductors with optical band gaps greater than 3.3 eV. TCOs have been extensively explored in functional windows, touch screen applications, transparent displays, solar cells, and even electronic circuits. Amorphous metal oxide (a-MO) semiconductors are a TCO class that has made impressive progress since the first 2004 demonstration of their utility as the semiconducting layer in thin-film transistors (TFTs). Their excellent counterintuitive electron mobilities in the amorphous state fill the performance gap between amorphous silicon and polysilicon, widening TFT applicability to high-value products such as high-resolution flat panel displays and emerging flexible/wearable electronics. The possibility of solution processing MO "inks" from air-stable precursors, via roll-to-roll and high-throughput printing, further expands their appeal. However, most MO TFTs fabricated using solution-processing require postdeposition film annealing at elevated temperatures (>400 °C) to ensure high-quality films and stable charge transport. Thus, MO fabrication on and TFT integration with inexpensive and typically temperature-sensitive flexible polymer substrates remains challenging, as does reducing MO processing times to those acceptable for high-throughput semiconductor circuit manufacture. Consequently, new MO film processing methodologies are being developed to meet these requirements. Among them, science-based combustion synthesis (CS) and polymer doping are promising complementary approaches to optimize materials quality and manufacturing efficiency; they are the topic of this Account.This Account summarizes the progress in CS and MO polymer doping research, made largely at Northwestern University over the past decade, to create high-performance MO TFTs. Regarding CS, we begin with an overview of combustion precursor chemistry that strongly affects the resulting film quality and device performance. Then, single fuel and dual fuel combustion syntheses for diverse MO systems are discussed. Representative examples highlight recent advances, with a focus on the relationship between (co)fuel-oxidizer types/amounts, thermal behavior, film microstructure, and TFT performance. Next, the discussion focuses on polymer doping of several MO matrices as a new approach to achieve semiconducting MO compositions with excellent performance and mechanical flexibility. Thus, the effect of the polymer architecture and content in the MO precursor formulations on the MO film composition, microstructure, electronic structure, and charge transport are discussed. The concluding remarks highlight challenges and emerging opportunities.

Defect Contrast with 4D-STEM: Understanding Crystalline Order with Virtual Detectors and Beam Modification.

Material properties strongly depend on the nature and concentration of defects. Characterizing these features may require nano- to atomic-scale resolution to establish structure-property relationships. 4D-STEM, a technique where diffraction patterns are acquired at a grid of points on the sample, provides a versatile method for highlighting defects. Computational analysis of the diffraction patterns with virtual detectors produces images that can map material properties. Here, using multislice simulations, we explore different virtual detectors that can be applied to the diffraction patterns that go beyond the binary response functions that are possible using ordinary STEM detectors. Using graphene and lead titanate as model systems, we investigate the application of virtual detectors to study local order and in particular defects. We find that using a small convergence angle with a rotationally varying detector most efficiently highlights defect signals. With experimental graphene data, we demonstrate the effectiveness of these detectors in characterizing atomic features, including vacancies, as suggested in simulations. Phase and amplitude modification of the electron beam provides another process handle to change image contrast in a 4D-STEM experiment. We demonstrate how tailored electron beams can enhance signals from short-range order and how a vortex beam can be used to characterize local symmetry.