Correction: Self-limiting stoichiometry in SnSe thin films
Correction for ‘Self-limiting stoichiometry in SnSe thin films’ by Jonathan R. Chin et al. , Nanoscale , 2023, 15 , 9973–9984, https://doi.org/10.1039/D3NR00645J.
Chin, Jonathan R.↗
Engineering topics
Wang, Ke
Publications and source records attributed to Wang, Ke.
Step engineering for nucleation and domain orientation control in WSe 2 epitaxy on c -plane sapphire
In this study, epitaxial growth of two-dimensional transition metal dichalcogenides on sapphire has emerged as a promising route to wafer-scale single-crystal films. Steps on the sapphire act as sites for transition metal dichalcogenide nucleation and can impart a preferred domain orientation, resulting in a substantial reduction in mirror twins. Here we demonstrate control of both the nucleation site and unidirectional growth direction of WSe 2 on c-plane sapphire by metal–organic chemical vapour deposition. The unidirectional orientation is found to be intimately tied to growth conditions via changes in the sapphire surface chemistry that control the step edge location of WSe 2 nucleation, imparting either a 0° or 60° orientation relative to the underlying sapphire lattice. The results provide insight into the role of surface chemistry on transition metal dichalcogenide nucleation and domain alignment and demonstrate the ability to engineer domain orientation over wafer-scale substrates.
36 MATERIALS SCIENCE↗
Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites
Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.
36 MATERIALS SCIENCE↗
Extended-Surface Thin-Film Platinum Electrocatalysts with Tunable Nanostructured Morphologies
Not Available
36 MATERIALS SCIENCE↗
MgSiP 2 : An Infrared Nonlinear Optical Crystal with a Large Non‐Resonant Phase‐Matchable Second Harmonic Coefficient and High Laser Damage Threshold
Superior infrared nonlinear optical (NLO) crystals are in urgent demand in the development of lasers and optical technologies for communications and computing. The critical challenge is to find a crystal with large non‐resonant phase‐matchable NLO coefficients and high laser damage threshold (LDTs) simultaneously, which however scale inversely. This work reports such a material, MgSiP 2, that exhibits a large second harmonic generation (SHG) coefficient of d 14 ≈ d 36 = 89 ± 5 pm V −1 at 1550 nm fundamental wavelength, surpassing the commercial NLO crystals AgGaS 2 , AgGaSe 2 , and ZnGeP 2 . First principles theory reveals the polarizability and geometric arrangement of the [SiP 4 ] tetrahedral units as the origin of this large nonlinear response. Remarkably, it also exhibits a high LDT value of 684 GW cm −2 , which is six times larger than ZnGeP 2 and three times larger than CdSiP 2 . It has a wide transparency window of 0.53–10.35 µm, allowing broadband tunability. Further, it is Type I and Type II phase‐matchable with large effective SHG coefficients of d eff,I ≈80.2 pm V −1 and d eff,II ≈73.4 pm V −1 . The outstanding properties of MgSiP 2 make it a highly attractive candidate for optical frequency conversion in the infrared.
36 MATERIALS SCIENCE↗
Self-limiting stoichiometry in SnSe thin films
Raman spectroscopy showing the initial formation of SnSe 2 followed by the stabilization of SnSe with increased growth time.
36 MATERIALS SCIENCE↗
Self‐Assembly of 0D/3D Perovskite Bi‐Layer from a Micro‐Emulsion Ink
Abstract 2D/3D bilayer perovskite synthesized using sequential deposition methods has shown effectiveness in enhancing the stability of perovskite solar devices. However, these approaches present several limitations such as uncontrolled chemical processes, disordered interfacial states, and microscale heterogeneities that can chemically, structurally, and electronically compromise the performance of solar modules. Here, this work demonstrates an emulsion‐based self‐assembly approach using natural lipid biomolecules in a nonionic solution system to form a 0D/3D bilayer structure. The new capping layer is composed of 0D‐entity nanoparticles of perovskite encapsulated by a hydrophobic lipid membrane, analogous to a cell structure, formed through a molecular self‐assembly process. This 0D layer provides a strong water repellent characteristics, optimum interface microstructure, and excellent homogeneity that drives significant enhancement in stability. Solar modules with a large active area of 70 cm 2 fabricated using films comprising of 0D/3D bilayer structure are found to show consistent efficiency of >19% for 2800 h of continuous illumination in the air (60% relative humidity). This emulsion‐based self‐assembly approach is expected to have a transformative impact on the design and development of stable perovskite‐based devices.
0D/3D bilayers↗
Adaptively Optimizing Experiments: Past, Present, and Future
This is a presentation for the May 31 - June 3, 2023, SIAM conference with the goal to present advances in mathematical modeling and a case study as part of the Carbon Capture Simulation Initiative.
Dowling, Alexander↗
Electro-thermal actuation in percolative ferroelectric polymer nanocomposites
Not provided.
Chemistry↗
Correlation between cation order/disorder and the electrocaloric effect in the MLCCs of complex perovskite ferroelectrics
The physical properties (dielectric, ferroelectric, piezoelectric, etc.) of complex perovskite ferroelectrics depend on the degree of order/disorder and the scale of the ordered domains. In this study, the electrocaloric (EC) properties of three representative complex perovskite ferroelectrics, Pb(Mg 1/3 Nb 2/3 )O 3 -8PbTiO 3 (PMN-8PT), 1mol% Sm-doped Pb(Mg 1/3 Nb 2/3 )O 3 -8PbTiO 3 (1S-PMN-8PT) and Pb(Sc 1/2 Ta 1/2 )O 3 (PST) are evaluated. Multi-layer ceramic capacitors (MLCCs) with identical structural configurations were fabricated for these three compounds, and their EC properties were characterized by direct measurement using a thermocouple. The EC temperature change of PMN-8PT, 1S-PMN-8PT and PST MLCCs under 20 V μm –1 at room temperature were found to be 1.42 K, 1.54 K, and 3.10 K, respectively. X-ray diffraction and high-resolution transmission electron microscopy data suggests that the high EC performance of PST is related to the ordering of B-site cations (Sc 3+ and Ta 5+ ) with the ordering parameter S = 0.82 and a long coherence length of ~100 nm, such that the sample transitioned from a relaxor ferroelectric to a normal ferroelectric. Furthermore, these results provide pathway towards design of high performance EC materials required for solid state refrigeration and air-conditioning technologies.
36 MATERIALS SCIENCE↗
Stoichiometric Control and Optical Properties of BaTiO 3 Thin Films Grown by Hybrid MBE
BaTiO 3 is a technologically relevant material in the perovskite oxide class with above-room-temperature ferroelectricity and a very large electro-optical coefficient, making it highly suitable for emerging electronic and photonic devices. An easy, robust, straightforward, and scalable growth method is required to synthesize epitaxial BaTiO 3 thin films with sufficient control over the film's stoichiometry to achieve reproducible thin film properties. Here the growth of BaTiO 3 thin films by hybrid molecular beam epitaxy is reported. A self-regulated growth window is identified using complementary information obtained from reflection high energy electron diffraction, the intrinsic film lattice parameter, film surface morphology, and scanning transmission electron microscopy. Subsequent optical characterization of the BaTiO 3 films by spectroscopic ellipsometry revealed refractive index and extinction coefficient values closely resembling those of stoichiometric bulk BaTiO 3 crystals for films grown inside the growth window. Even in the absence of a lattice parameter change of BaTiO 3 thin films, degradation of optical properties is observed, accompanied by the appearance of a wide optical absorption peak in the IR spectrum, attributed to optical transitions involving defect states present. Therefore, the optical properties of BaTiO 3 can be utilized as a much finer and more straightforward probe to determine the stoichiometry level present in BaTiO 3 films.
36 MATERIALS SCIENCE↗
Multiscale Electrothermal Design of a Modular Multilevel Converter for Medium-Voltage Grid-Tied Applications
As a key feature of modular multilevel converters (MMCs), a large number of semiconductor devices are employed in the converter and distributed over a stack of submodules. Each submodule has a strict temperature limit that imposes constraints on the operating range of the converter. Different loading conditions/losses in the submodules lead to unavoidable temperature variations inside the MMC, which consequently affect the system-level performance and reliability. This paper is focused on the electrothermal analysis and design of a medium-voltage silicon carbide (SiC)-based MMC system, from submodule power semiconductors to the overall MMC system integration of multiple submodules, for grid-connected applications. Loss calculations are performed to estimate the cooling requirements and aid thermal design at different levels. The performance of a forced-air cooling approach is analyzed within a numerical modeling framework. Maximum temperature of the SiC power modules is predicted using numerical tools. Thermal design of the MMC cabinet with various arrangements of air inlet(s) and outlet(s) is investigated and compared from a cooling performance perspective. A fully resolved model of the arrangement that yields optimal results is developed to accurately predict the temperature profile of the essential components in the submodules.
computational fluid dynamics↗
When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing
Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing method for high-resolution printing for a wide range of material systems. A key challenge limiting the broader adoption of AJP in the material science community is the lack of methods to precisely control thickness. Herein, we develop a model-based design of experiment (MBDoE) framework that integrates physics-informed models, nonlinear regression, and information criteria to postulate, select and calibrate the best model to describe and optimize the AJP manufacturing process. Starting with already available data from system commissioning (e.g., prior single variable sensitivity analysis), four candidate physics-informed models are postulated and trained. MBDoE identifies a single additional optimal experiment to validate these predictive models with quantified uncertainties, which are then used to determine the best experimental conditions to control printed film thickness. As a comparative benchmark, the analysis is repeated using the same dataset with nonparametric Gaussian process regression (GPR) model that does not incorporate physical information. Using MBDoE principles, we find that only five experiments are necessary to calibrate the nonlinear physics-informed parametric model, and with said limited data, this model outperforms the black-box machine learning GPR model. This key result underscores an emerging trend in the data science community: incorporating physical information into predictive models often drastically reduces the data requirements. Leveraging MBDoE further increased the data efficiency. By design, the proposed data science framework is general in nature and can be easily extended to other experimental and additive manufacturing systems beyond AJP.
Aerosol jet printing↗
A universal all-solid synthesis for high throughput production of halide perovskite
Abstract Halide perovskites show ubiquitous presences in growing fields at both fundamental and applied levels. Discovery, investigation, and application of innovative perovskites are heavily dependent on the synthetic methodology in terms of time-/yield-/effort-/energy- efficiency. Conventional wet chemistry method provides the easiness for growing thin film samples, but represents as an inefficient way for bulk crystal synthesis. To overcome these, here we report a universal solid state-based route for synthesizing high-quality perovskites, by means of simultaneously applying both electric and mechanical stress fields during the synthesis, i.e., the electrical and mechanical field-assisted sintering technique. We employ various perovskite compositions and arbitrary geometric designs for demonstration in this report, and establish such synthetic route with uniqueness of ultrahigh yield, fast processing and solvent-free nature, along with bulk products of exceptional quality approaching to single crystals. We exemplify the applications of the as-synthesized perovskites in photodetection and thermoelectric as well as other potentials to open extra chapters for future technical development.
36 MATERIALS SCIENCE↗
Gate-tunable Veselago interference in a bipolar graphene microcavity
The relativistic charge carriers in monolayer graphene can be manipulated in manners akin to conventional optics. Klein tunneling and Veselago lensing have been previously demonstrated in ballistic graphene pn-junction devices, but collimation and focusing efficiency remains relatively low, preventing realization of advanced quantum devices and controlled quantum interference. Here, we present a graphene microcavity defined by carefully-engineered local strain and electrostatic fields. Electrons are manipulated to form an interference path inside the cavity at zero magnetic field via consecutive Veselago refractions. The observation of unique Veselago interference peaks via transport measurement and their magnetic field dependence agrees with the theoretical expectation. We further utilize Veselago interference to demonstrate localization of uncollimated electrons and thus improvement in collimation efficiency. Our work sheds new light on relativistic single-particle physics and provide a new device concept toward next-generation quantum devices based on manipulation of ballistic electron trajectory.
36 MATERIALS SCIENCE↗
Circular economy as a climate strategy: current knowledge and calls-to-action
Existing pledges and NDC targets, even if fully achieved, are still not sufficient to meet the Paris climate goals. Considerable additional strategies and actions are urgently needed to close the emission gap. Built environment, transport, food system, and clean energy are the most relevant sectors for circular economy strategies to deliver climate change mitigation benefits. Circular economy strategies can complement decarbonization measures to further reduce GHG emissions from material production, help lower emissions from operational energy use in the built environment and transport, and cut emissions from waste management. The largest potential GHG emissions reductions through circularity come from consumption side measures and product design measures. Circular economy strategies can support a sustainable clean energy transition, by helping relieve the mineral supply pressure, increasing supply chain resilience, preventing new waste challenges, accelerating the adoption of clean energy technologies, as well as maximizing their climate benefits. Furthermore, circular economy strategies can help enhance adaptation to climate change. Nine calls-to-action are put forward, for government, business, and civil society leaders to accelerate circular economy strategies with the highest potential for climate benefits, and for the research community to close critical knowledge gaps.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Machine learning-assisted ultrafast flash sintering of high-performance and flexible silver–selenide thermoelectric devices
Flexible thermoelectric generators (TEGs) have shown immense potential for serving as a power source for wearable electronics and the Internet of Things. A key challenge preventing large-scale application of TEGs lies in the lack of a high-throughput processing method, which can sinter thermoelectric (TE) materials rapidly while maintaining their high thermoelectric properties. Herein, we integrate high-throughput experimentation and Bayesian optimization (BO) to accelerate the discovery of the optimum sintering conditions of silver–selenide TE films using an ultrafast intense pulsed light (flash) sintering technique. Due to the nature of the high-dimensional optimization problem of flash sintering processes, a Gaussian process regression (GPR) machine learning model is established to rapidly recommend the optimum flash sintering variables based on Bayesian expected improvement. For the first time, an ultrahigh-power factor flexible TE film (a power factor of 2205 μW m -1 K -2 with a zT of 1.1 at 300 K) is demonstrated with a sintering time less than 1.0 second, which is several orders of magnitude shorter than that of conventional thermal sintering techniques. Further, the films also show excellent flexibility with 92% retention of the power factor (PF) after 10 3 bending cycles with a 5 mm bending radius. In addition, a wearable thermoelectric generator based on the flash-sintered films generates a very competitive power density of 0.5 mW cm -2 at a temperature difference of 10 K. This work not only shows the tremendous potential of high-performance and flexible silver–selenide TEGs but also demonstrates a machine learning-assisted flash sintering strategy that could be used for ultrafast, high-throughput and scalable processing of functional materials for a broad range of energy and electronic applications.
25 ENERGY STORAGE↗