RESUMEN
Graphene growth on widely used dielectrics/insulators via chemical vapor deposition (CVD) is a strategy toward transfer-free applications of CVD graphene for the realization of advanced composite materials. Here, we develop graphene-skinned alumina fibers/fabrics (GAFs/GAFFs) through graphene CVD growth on commercial alumina fibers/fabrics (AFs/AFFs). We reveal a vapor-surface-solid growth model on a non-metallic substrate, which is distinct from the well-established vapor-solid model on conventional non-catalytic non-metallic substrates, but bears a closer resemblance to that observed on catalytic metallic substrates. The metalloid-catalytic growth of graphene on AFs/AFFs resulted in reduced growth temperature (~200 °C lower) and accelerated growth rate (~3.4 times faster) compared to that obtained on a representative non-metallic counterpart, quartz fiber. The fabricated GAFF features a wide-range tunable electrical conductivity (1-15000 Ω sq-1), high tensile strength (>1.5 GPa), lightweight, flexibility, and a hierarchical macrostructure. These attributes are inherited from both graphene and AFF, making GAFF promising for various applications including electrical heating and electromagnetic interference shielding. Beyond laboratory level preparation, the stable mass production of large-scale GAFF has been achieved through a home-made roll-to-roll system with capacity of 468-93600 m2/year depending on product specifications, providing foundations for the subsequent industrialization of this material, enabling its widespread adoption in various industries.
RESUMEN
We present a full space inverse materials design (FSIMD) approach that fully automates the materials design for target physical properties without the need to provide the atomic composition, chemical stoichiometry, and crystal structure in advance. Here, we used density functional theory reference data to train a universal machine learning potential (UPot) and transfer learning to train a universal bulk modulus model (UBmod). Both UPot and UBmod were able to cover materials systems composed of any element among 42 elements. Interfaced with optimization algorithm and enhanced sampling, the FSIMD approach is applied to find the materials with the largest cohesive energy and the largest bulk modulus, respectively. NaCl-type ZrC was found to be the material with the largest cohesive energy. For bulk modulus, diamond was identified to have the largest value. The FSIMD approach is also applied to design materials with other multi-objective properties with accuracy limited principally by the amount, reliability, and diversity of the training data. The FSIMD approach provides a new way for inverse materials design with other functional properties for practical applications.
RESUMEN
Materials demonstrating positive thermal expansion (PTE) or negative thermal expansion (NTE) are quite common, whereas those exhibiting zero thermal expansion (ZTE) are notably scarce. In this work, we identify the mechanical descriptors, namely in-plane tensile stiffness and out-of-plane bending stiffness, that can effectively classify PTE and NTE 2D crystals. By utilizing high throughput calculations and the state-of-the-art symbolic regression method, these descriptors aid in the discovery of ZTE or 2D Invar monolayers with the linear thermal expansion coefficient (LTEC) within ±2 × 10-6 K-1 in the middle range of temperatures. Additionally, the descriptors assist the discovery of large PTE and NTE 2D monolayers with the LTEC larger than ±15 × 10-6 K-1, which are so-called 2D anti-Invar monolayers. Advancing our understanding of materials with exceptionally low or high thermal expansion is of substantial scientific and technological interest, particularly in the development of next-generation electronics at the nanometer or even Ångstrom scale.
RESUMEN
Direct chemical vapor deposition (CVD) growth of graphene on dielectric/insulating materials is a promising strategy for subsequent transfer-free applications of graphene. However, graphene growth on noncatalytic substrates is faced with thorny issues, especially the limited growth rate, which severely hinders mass production and practical applications. Herein, graphene glass fiber fabric (GGFF) is developed by graphene CVD growth on glass fiber fabric. Dichloromethane is applied as a carbon precursor to accelerate graphene growth, which has a low decomposition energy barrier, and more importantly, the produced high-electronegativity Cl radical can enhance adsorption of active carbon species by Cl-CH2 coadsorption and facilitate H detachment from graphene edges. Consequently, the growth rate is increased by ~3 orders of magnitude and carbon utilization by ~960-fold, compared with conventional methane precursor. The advantageous hierarchical conductive configuration of lightweight, flexible GGFF makes it an ultrasensitive pressure sensor for human motion and physiological monitoring, such as pulse and vocal signals.
RESUMEN
Conventional conductive materials such as metals are crucial functional components of conductive systems in diverse electronic instruments. However, their severe intrinsic impedance mismatch with air dielectric causes strong reflection of incident electromagnetic waves, and the resulting low electromagnetic transmissivity typically interferes with surrounding electromagnetic signal communications in modern multifunction-integrated instruments. Herein, graphene glass fiber fabric (GGFF) that merges intrinsic electrical and electromagnetic properties of graphene with dielectric attributes and highly porous macrostructure of glass fiber fabric (GFF) is innovatively developed. Using a novel decoupling chemical vapor deposition growth strategy, high-quality and layer-limited graphene is prepared on noncatalytic nonmetallic GFF in a controlled manner; this is pivotal to realizing GGFF with the desired compatibility among high conductivity, low electromagnetic reflectivity, and high electromagnetic transmissivity. At the same sheet resistance over a wide range of values (250-3000 Ω·sq-1), the GGFF exhibits significantly lower electromagnetic reflectivity (by 0.42-0.51) and higher transmissivity (by 0.27-0.62) than those of its metal-based conductive counterpart (CuGFF). The material design strategy reported herein provides a constructive solution to eliminate the incompatibility between electrical conductivity and electromagnetic transmissivity faced by conventional conductive materials, spotlighting the applicability of GGFF in electric heating scenarios in radar, antenna, and stealth systems.
RESUMEN
Lead halide perovskites with superior optoelectrical properties are emerging as a class of excellent materials for applications in solar cells and light-emitting devices. However, perovskite films often exhibit abundant intrinsic defects, which can limit the efficiency of perovskite-based optoelectronic devices by acting as carrier recombination centers. Thus, an understanding of defect chemistry in lead halide perovskites assumes a prominent role in further advancing the exploitation of perovskites, which, to a large extent, is performed by relying on first-principles calculations. However, the complex defect structure, strong anharmonicity, and soft lattice of lead halide perovskites pose challenges to defect studies. In this perspective, on the basis of briefly reviewing the current knowledge concerning computational studies on defects, this work concentrates on addressing the unsolved problems and proposing possible research directions in future. This perspective particularly emphasizes the indispensability of developing advanced approaches for deeply understanding the nature of defects and conducting data-driven defect research for designing reasonable strategies to further improve the performance of perovskite applications. Finally, this work highlights that theoretical studies should pay more attention to establishing close and clear links with experimental investigations to provide useful insights to the scientific and industrial communities.
RESUMEN
Storage phosphors displaying defect emissions are indispensable in technologically advanced radiation dosimeters. The current dosimeter is limited to the passive detection mode, where ionizing radiation-induced deep-trap defects must be activated by external stimulation such as light or heat. Herein, we designed a new type of shallow-trap storage phosphor by controlling the dopant amounts of Ag+ and Bi3+ in the host lattice of Cs2NaInCl6. A distinct phenomenon of X-ray-induced emission (XIE) is observed for the first time in an intrinsically nonemissive perovskite. The intensity of XIE exhibits a quantitative relationship with the accumulated dose, enabling a real-time radiation dosimeter. Thermoluminescence and in situ X-ray photoelectron spectroscopy verify that the emission originates from the radiative recombination of electrons and holes associated with X-ray-induced traps. Theoretical calculations reveal the evolution process of Cl-Cl dimers serving as hole trap states. Analysis of temperature-dependent radioluminescence spectra provides evidence that the intrinsic electron-phonon interaction in 0.005 Ag+@ Cs2NaInCl6 is significantly reduced under X-ray irradiation. Moreover, 0.025 Bi3+@ Cs2NaInCl6 shows an elevated sensitivity to the accumulated dose with a broad response range from 0.08 to 45.05 Gy. This work discloses defect manipulation in halide double perovskites, giving rise to distinct shallow-trap storage phosphors that bridge traditional deep-trap storage phosphors and scintillators and enabling a brand-new type of material for real-time radiation dosimetry.
RESUMEN
Graphene films that can theoretically block almost all molecules have emerged as promising candidate materials for moisture barrier films in the applications of organic photonic devices and gas storage. However, the current barrier performance of graphene films does not reach the ideal value. Here, we reveal that the interlayer distance of the large-area stacked multilayer graphene is the key factor that suppresses water permeation. We show that by minimizing the gap between the two monolayers, the water vapor transmission rate of double-layer graphene can be as low as 5 × 10-3 g/(m2 d) over an A4-sized region. The high barrier performance was achieved by the absence of interfacial contamination and conformal contact between graphene layers during layer-by-layer transfer. Our work reveals the moisture permeation mechanism through graphene layers, and with this approach, we can tailor the interlayer coupling of manually stacked two-dimensional materials for new physics and applications.
RESUMEN
Interphase boundaries (IBs) are widely present in lead halide perovskites (LHPs) owing to their relatively low phase transition barriers. However, their atomic structures and electronic properties have rarely been investigated. In this study, various IB structures were constructed computationally, and their influences on the charge carrier transport properties of LHPs were studied by calculating the effective interphase boundary energy and analyzing the electronic structure. The results show that the presence of IBs plays a significant role in carrier transport and that they may be tuned to prolong carrier lifetimes. This study provides insights for improving the performance of LHPs by engineering IBs, primarily by their compositional phases and ratios.
RESUMEN
Bilayer graphene (BLG) is intriguing for its unique properties and potential applications in electronics, photonics, and mechanics. However, the chemical vapor deposition synthesis of large-area high-quality bilayer graphene on Cu is suffering from a low growth rate and limited bilayer coverage. Herein, we demonstrate the fast synthesis of meter-sized bilayer graphene film on commercial polycrystalline Cu foils by introducing trace CO2 during high-temperature growth. Continuous bilayer graphene with a high ratio of AB-stacking structure can be obtained within 20 min, which exhibits enhanced mechanical strength, uniform transmittance, and low sheet resistance in large area. Moreover, 96 and 100% AB-stacking structures were achieved in bilayer graphene grown on single-crystal Cu(111) foil and ultraflat single-crystal Cu(111)/sapphire substrates, respectively. The AB-stacking bilayer graphene exhibits tunable bandgap and performs well in photodetection. This work provides important insights into the growth mechanism and the mass production of large-area high-quality BLG on Cu.
RESUMEN
Developing activity descriptors via data-driven machine learning (ML) methods can speed up the design of highly active and low-cost electrocatalysts. Despite the fact that a large amount of activity data for electrocatalysts is stored in the literature, data from different publications are not comparable due to different experimental or computational conditions. In this work, an interpretable ML method, multi-task symbolic regression, was adopted to learn from data in multiple experiments. A universal activity descriptor to evaluate the oxygen evolution reaction (OER) performance of oxide perovskites free of calculations or experiments was constructed and reached high accuracy and generalization ability. Utilizing this descriptor with Bayesian-optimized parameters, a series of compelling double perovskites with excellent OER activity were predicted and further evaluated using first-principles calculations. Finally, the two ML-predicted nickel-based perovskites with the best OER activity were successfully synthesized and characterized experimentally. This work opens a new way to extend machine-learning material design by utilizing multiple data sources.
RESUMEN
The direct growth of graphene affording wafer-scale uniformity on insulators is paramount to electronic and optoelectronic applications; however, it remains a challenge to date, because it entails an entirely different growth mode than that over metals. Herein, the metal-catalyst-free growth of quasi-suspended graphene on a Si wafer is demonstrated using an interface-decoupling chemical vapor deposition strategy. The employment of lower-than-conventional H2 dosage and concurrent introduction of methanol during growth can effectively weaken the interaction between the synthesized graphene and the underlying substrate. The growth mode can be thus fine-tuned, producing a predominantly monolayer graphene film with wafer-level homogeneity. Graphene thus grown on a 4 inch Si wafer enables the transfer-free fabrication of high-performance graphene-based field-effect transistor arrays that exhibit almost no shift in the charge neutral point, indicating a quasi-suspended feature of the graphene. Moreover, a carrier mobility up to 15 000 cm2 V-1 s-1 can be attained. This study is anticipated to offer meaningful insights into the synthesis of wafer-scale high-quality graphene on dielectrics for practical graphene devices.
RESUMEN
Current knowledge on the nature of surface iodine vacancies (VI), which are important for the photovoltaic performance and stability of perovskite solar cells, is debatable. We investigated VI on a stable MAI-terminated CH3NH3PbI3 (MAPbI3) surface. First-principles calculations indicated the sensitivity of the atomic structure of surface VI to the charge states and locations on the surface layer. VI in the outermost layer are benign; however, those near the surface can be detrimental. Illumination can promote the diffusion of VI from the outermost layer into the bulk, making them detrimental. There are two mechanisms for the surface passivation of VI: (i) passivation in the second layer to eliminate deep-state VI and (ii) passivation in the outermost layer to inhibit VI diffusion upon illumination (working condition of solar cells). This work rationalizes contradictory reports on the surface properties of halide perovskites and proposes insights into their surface passivation to fabricate high-performing solar cells.
RESUMEN
The lead-free copper-based halide perovskite Cs3Cu2I5 is a promising material that can overcome the toxicity and instability of lead-based halide perovskites, thereby affording remarkable performance in the field of optoelectronics. Cs3Cu2I5 perovskite exhibits blue emission with a very high photoluminescence quantum yield (PLQY). First-principles calculations were used herein to theoretically expound the origins of the high PLQY of Cs3Cu2I5: (i) the low symmetry of Cs3Cu2I5 breaks the forbidden transition and enables the transition process; (ii) the large transition matrix and high transition rate increase the probability for radiative recombination of Cs3Cu2I5; (iii) the good defect tolerance broadens the path for thermal relaxation and radiative recombination. The high transition rate and good defect tolerance account for the high-efficiency PLQY of the lead-free copper-based perovskite, Cs3Cu2I5.
RESUMEN
Crystal structure prediction is a long-standing challenge in condensed matter and chemical science. Here we report a machine-learning approach for crystal structure prediction, in which a graph network (GN) is employed to establish a correlation model between the crystal structure and formation enthalpies at the given database, and an optimization algorithm (OA) is used to accelerate the search for crystal structure with lowest formation enthalpy. The framework of the utilized approach (a database + a GN model + an optimization algorithm) is flexible. We implemented two benchmark databases, i.e., the open quantum materials database (OQMD) and Matbench (MatB), and three OAs, i.e., random searching (RAS), particle-swarm optimization (PSO) and Bayesian optimization (BO), that can predict crystal structures at a given number of atoms in a periodic cell. The comparative studies show that the GN model trained on MatB combined with BO, i.e., GN(MatB)-BO, exhibit the best performance for predicting crystal structures of 29 typical compounds with a computational cost three orders of magnitude less than that required for conventional approaches screening structures through density functional theory calculation. The flexible framework in combination with a materials database, a graph network, and an optimization algorithm may open new avenues for data-driven crystal structural predictions.
RESUMEN
Inorganic CsPbI3 perovskite has shown great promise in highly stable perovskite solar cells due to the lack of volatile organic components. However, the inferior phase stability in ambient conditions resulted from the very small Cs+, limiting their practical applications. Here, CsPbI3-based 2D Ruddlesden-Popper (RP) perovskites were developed using two thiophene-based aromatic spacers, namely, 2-thiophenemethylamine hydroiodide (ThMA) and 2-thiopheneformamidine hydroiodide (ThFA), which significantly improved the phase stability by releasing the large inner stress of black-phase CsPbI3. The optimized ThFA-based 2D RP perovskite (n = 5, ThFA-Cs) device achieves a record efficiency of 16.00%. Importantly, the ThFA-Cs devices could maintain an average of 98% of their initial efficiencies after being stored in N2 at room temperature for 3000 h and 92% of their initial value at 80 °C for 960 h. This work provides a new perspective for exploration of the phase-stable CsPbI3-based perovskite with reduced dimensions for high-performance solar cells.
RESUMEN
Rubidium cation (Rb+ ) addition is witnessed to play a pivotal role in boosting the comprehensive performance of organic-inorganic hybrid perovskite solar cells. However, the origin of such success derived from irreplaceable superiorities brought by Rb+ remains ambiguous. Herein, grain-boundary-including atomic models are adopted for the accurate theoretical analysis of practical Rb+ distribution in perovskite structures. The spatial distribution, covering both the grain interiors and boundaries, is thoroughly identified by virtue of synchrotron-based grazing-incidence X-ray diffraction. On this basis, the prominent elevation of the halogen vacancy formation energy, improved charge-carrier dynamics, and the electronic passivation mechanism in the grain interior are expounded. As evidenced by the increased energy barrier and suppressed microcurrent, the critical role of Rb+ addition in blocking the diffusion pathway along grain boundaries, inhibiting halide phase segregation, and eventually enhancing intrinsic stability is elucidated. Hence, the linkage avalanche effect of occupied location dominated by subtle changes in Rb+ concentration on electronic defects, ion migration, and phase stability is completely investigated in detail, shedding a new light on the advancement of high-efficiency cascade-incorporating strategies and perovskite compositional engineering.
RESUMEN
Perovskite solar cells (PSCs) exhibit large, reversible, and bidirectional light-soaking effects (LSEs); however, these anomalous LSEs are poorly understood, limiting the stability engineering and commercialization. We present a unified defect theory for the LSEs in lead halide perovskites by reconciling their defect photochemistry, ionic migration, and carrier dynamics. We considered typical detrimental defects (IPb, Ii, VI) and observed that two atomic configurations were favored, where the carrier lifetime of one configuration was nearly 1 order of magnitude longer than that in the other. First-principles calculations showed that light illumination promotes ion-diffusion-assisted transitions from energetically stable configurations to metastable configurations, which are converted back to stable configurations in the dark. Fermi-level-dependent formation energies of stable/metastable configurations were used to rationalize contradictory experimental results of anomalous LSEs in PSCs observed in various studies, thus providing insights for minimizing the LSE to achieve high-performance stable PSCs.
RESUMEN
The interesting physical and chemical properties of carbon nanotubes (CNTs) have prompted the search for diverse inorganic nanotubes with different compositions to expand the number of available nanotechnology applications. Among these materials, crystalline inorganic nanotubes with well-defined structures and uniform sizes are suitable for understanding structure-activity relationships. However, their preparation comes with large synthetic challenges owing to their inherent complexity. Herein, we report the example of a crystalline nanotube array based on a supertetrahedral chalcogenide cluster, K3[K(Cu2Ge3Se9)(H2O)] (1). To the best of our knowledge, this nanotube array possesses the largest diameter of crystalline inorganic nanotubes reported to date and exhibits an excellent structure-dependent electric conductivity and an oriented photoconductive behavior. This work represents a significant breakthrough both in terms of the structure of cluster-based metal chalcogenides and in the conductivity of crystalline nanotube arrays (i.e., an enhancement of ~4 orders of magnitude).