High Moisture-Barrier Performance of Double-Layer Graphene Enabled by Conformal and Clean Transfer.

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.

CsPbI3-Based Phase-Stable 2D Ruddlesden-Popper Perovskites for Efficient Solar Cells.

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.

Multiple-Noncovalent-Interaction-Stabilized Layered Dion-Jacobson Perovskite for Efficient Solar Cells.

Two-dimensional Dion-Jacobson (DJ) perovskites have shown improved structure stability in comparison with Ruddlesden-Popper (RP) perovskites. However, the mechanism behind the improved stability is still largely unexplored. Here a multifluorinated aromatic spacer, namely, 4F-PhDMA, has been successfully developed for 2D DJ perovskites. It is found that the 2D DJ perovskite with a 4F-PhDMA spacer exhibits a high dissociation energy due to the multiple noncovalent interactions. The optimized 2D DJ device based on the 4F-PhDMA spacer (n = 4) exhibits a champion efficiency of 16.62% with much improved light and thermal stability. This efficiency is much higher than that of the control device using an unfluorinated spacer (n = 4, PCE = 10.11%) and is among the highest efficiencies in aromatic-spacer-based 2D DJ perovskite solar cells (PSCs). Our work highlights the importance of incorporating multiple noncovalent interactions in the 2D DJ perovskite by employing a multifluorinated aromatic spacer to achieve DJ PSCs with both high efficiency and high stability.

Thermodynamic Stability Trend of Cubic Perovskites.

Stability is of central importance in current perovskite solar cell research and applications. Goldschmidt tolerance factor (t) recently provided qualitative guidance for experimentalists to engineer stable ABX3 perovskite by tuning effective ionic size with mixing cations or anions and for theorists to search emerging perovskites. Through first-principles calculations, we have calculated decomposition energies of 138 perovskite compounds of potential solar cell applications. Instead of t, we have found that (µ + t)η, where µ and η are the octahedral factor and the atomic packing fraction, respectively, demonstrates a remarkably linear correlation with thermodynamic stability. As a stability descriptor, (µ + t)η is able to predict the relative stability among any two perovskites with an accuracy of ∼90%. This trend is then used to predict decomposition energies of another 69 perovskites, and the results are in excellent agreement with first-principles calculations, indicating the generalization of the trend. This thermodynamic stability trend may help the efficient high-throughput search for emerging stable perovskites and precise control of chemical compositions for stabilizing current perovskites.

Two-Dimensional SiS Layers with Promising Electronic and Optoelectronic Properties: Theoretical Prediction.

Two-dimensional (2D) semiconductors can be very useful for novel electronic and optoelectronic applications because of their good material properties. However, all current 2D materials have shortcomings that limit their performance. As a result, new 2D materials are highly desirable. Using atomic transmutation and differential evolution global optimization methods, we identified two group IV-VI 2D materials, Pma2-SiS and silicene sulfide. Pma2-SiS is found to be both chemically, energetically, and thermally stable. Most importantly, Pma2-SiS has shown good electronic and optoelectronic properties, including direct bandgaps suitable for solar cells, good mobility for nanoelectronics, good flexibility of property tuning by layer control and applied strain, and good air stability as well. Therefore, Pma2-SiS is expected to be a promising 2D material in the field of 2D electronics and optoelectronics. The designing principles demonstrated in identifying these two tantalizing examples have great potential to accelerate the finding of new functional 2D materials.

An approach for full space inverse materials design by combining universal machine learning potential, universal property model, and optimization algorithm.

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.

Understanding Defects in Perovskite Solar Cells through Computation: Current Knowledge and Future Challenge.

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.

Control of one-dimensional magnetism in graphene via spontaneous hydrogenation of the grain boundary.

We propose that control of one-dimensional (1D) magnetism in graphene could be made easier by spontaneous hydrogenation of chemically reactive grain boundaries (GBs) in polycrystalline graphenes. Unlike pristine graphene, where hydrogen adsorption favors the formation of zero-dimensional (0D) clusters, the defect cores (pentagon, heptagon and octagon) at the GBs in polycrystalline graphene promote hydrogenation along the GBs. The hydrogenation in polycrystalline graphene starts at the GBs, proceeds gradually towards the grain interior (GI) and results in smooth 1D graphane-graphene interfaces. Our calculations show that the type (ferro- or antiferro-magnetism) and strength of the magnetism can be controlled by controlling the orientation of GBs. Since GBs in single-layer graphenes can be fabricated in a controllable way in experiments, the hydrogenation of GBs could be a unique method to realize large-area magnetic graphenes for future spintronic applications.

Interphase Boundaries and Their Impact on Carrier Dynamics in Lead Halide Perovskites.

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.

Distilling universal activity descriptors for perovskite catalysts from multiple data sources via multi-task symbolic regression.

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.

Revisiting the Iodine Vacancy Surface Defects to Rationalize Passivation Strategies in Perovskite Solar Cells.

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.

Crystal structure prediction by combining graph network and optimization algorithm.

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.

Unique Photoelectric Properties and Defect Tolerance of Lead-Free Perovskite Cs3Cu2I5 with Highly Efficient Blue Emission.

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.

Double-hole-mediated coupling of dopants and its impact on band gap engineering in TiO2.

A double-hole-mediated coupling of dopants is unraveled and confirmed in TiO2 by density-functional theory calculations. We find that when a dopant complex on neighboring oxygen sites in TiO2 has net two holes, the holes will strongly couple to each other through significant lattice relaxation. The coupling results in the formation of fully filled impurity bands lying above the valence band of TiO2, leading to a much more effective band gap reduction than that induced by monodoping or conventional donor-acceptor codoping. Our results suggest a new path for semiconductor band gap engineering.

Photoinduced Dynamic Defects Responsible for the Giant, Reversible, and Bidirectional Light-Soaking Effect in Perovskite Solar Cells.

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.

High-Performance Blue Perovskite Light-Emitting Diodes Enabled by Efficient Energy Transfer between Coupled Quasi-2D Perovskite Layers.

While there has been extensive investigation into modulating quasi-2D perovskite compositions in light-emitting diodes (LEDs) for promoting their electroluminescence, very few reports have studied approaches involving enhancement of the energy transfer between quasi-2D perovskite layers of the film, which plays very important role for achieving high-performance perovskite LEDs (PeLEDs). In this work, a bifunctional ligand of 4-(2-aminoethyl)benzoic acid (ABA) cation is strategically introduced into the perovskite to diminish the weak van der Waals gap between individual perovskite layers for promoting coupled quasi-2D perovskite layers. In particular, the strengthened interaction between coupled quasi-2D perovskite layers favors an efficient energy transfer in the perovskite films. The introduced ABA can also simultaneously passivate the perovskite defects by reducing metallic Pb for less nonradiative recombination loss. Benefiting from the advanced properties of ABA incorporated perovskites, highly efficient blue PeLEDs with external quantum efficiency of 10.11% and a very long operational stability of 81.3 min, among the best performing blue quasi-2D PeLEDs, are achieved. Consequently, this work contributes an effective approach for high-performance and stable blue PeLEDs toward practical applications.

Passivating Detrimental DX Centers in CH3 NH3 PbI3 for Reducing Nonradiative Recombination and Elongating Carrier Lifetime.

After a period of rapid, unprecedented development, the growth in the efficiency of perovskite solar cells has recently slowed. Further improvement of cell efficiency will rely on the in-depth understanding and delicate control of defect passivation. Here, the formation mechanism of iodine vacancies (VI ), a typical deep defect in CH3 NH3 PbI3 (MAPbI3 ), is elucidated. The structural and electronic behaviors of VI are like those of a DX center, a kind of detrimental defect formed by large atomic displacement. Aided by the passivation mechanism of DX centers in tetrahedral semiconductors, it is found that the introduction of Br strengthens chemical bonds and prevents large atomic displacements during defect charging. It therefore reduces the defect states and diminishes electron-phonon coupling. Using time-domain density functional theory (DFT) combined with nonadiabatic molecular dynamics, it is found that the carrier lifetime can be enhanced from 3.2 ns in defective MAPbI3 to 19 ns in CH3 NH3 Pb(I0.96 Br0.04 )3 . This work advances our understanding of how a small amount of Br doping improves the carrier dynamics and cell performance of MAPbI3 . It may also provide a route to enhance the carrier lifetimes and efficiencies of perovskite solar cells by defect passivation.

High Phase Stability in CsPbI3 Enabled by Pb-I Octahedra Anchors for Efficient Inorganic Perovskite Photovoltaics.

CsPbI3 inorganic perovskite has exhibited some special properties particularly crystal structure distortion and quantum confinement effect, yet the poor phase stability of CsPbI3 severely hinders its applications. Herein, the nature of the photoactive CsPbI3 phase transition from the perspective of PbI6 octahedra is revealed. A facile method is also developed to stabilize the photoactive phase and to reduce the defect density of CsPbI3 . CsPbI3 is decorated with multifunctional 4-aminobenzoic acid (ABA), and steric neostigmine bromide (NGBr) is subsequently used to further mediate the thin films' surface (NGBr-CsPbI3 (ABA)). The ABA or NG cation adsorbed onto the grain boundaries/surface of CsPbI3 anchors the PbI6 octahedra via increasing the energy barriers of octahedral rotation, which maintains the continuous array of corner-sharing PbI6 octahedra and kinetically stabilizes the photoactive phase CsPbI3 . Moreover, the added ABA and NGBr not only interact with shallow- or deep-level defects in CsPbI3 to significantly reduce defect density, but also lead to improved energy-level alignment at the interfaces between the CsPbI3 and the charge transport layers. Finally, the champion NGBr-CsPbI3 (ABA)-based inorganic perovskite solar cell delivers 18.27% efficiency with excellent stability. Overall, this work demonstrates a promising concept to achieve highly phase-stabilized inorganic perovskite with suppressed defect density for promoting its optoelectronic applications.

Simple descriptor derived from symbolic regression accelerating the discovery of new perovskite catalysts.

Symbolic regression (SR) is an approach of interpretable machine learning for building mathematical formulas that best fit certain datasets. In this work, SR is used to guide the design of new oxide perovskite catalysts with improved oxygen evolution reaction (OER) activities. A simple descriptor, µ/t, where µ and t are the octahedral and tolerance factors, respectively, is identified, which accelerates the discovery of a series of new oxide perovskite catalysts with improved OER activity. We successfully synthesise five new oxide perovskites and characterise their OER activities. Remarkably, four of them, Cs0.4La0.6Mn0.25Co0.75O3, Cs0.3La0.7NiO3, SrNi0.75Co0.25O3, and Sr0.25Ba0.75NiO3, are among the oxide perovskite catalysts with the highest intrinsic activities. Our results demonstrate the potential of SR for accelerating the data-driven design and discovery of new materials with improved properties.

Defect mitigation using d-penicillamine for efficient methylammonium-free perovskite solar cells with high operational stability.

Trap-dominated non-radiative charge recombination is one of the key factors that limit the performance of perovskite solar cells (PSCs), which was widely studied in methylammonium (MA) containing PSCs. However, there is a need to elucidate the defect chemistry of thermally stable, MA-free, cesium/formamidinium (Cs/FA)-based perovskites. Herein, we show that d-penicillamine (PA), an edible antidote for treating heavy metal ions, not only effectively passivates the iodine vacancies (Pb2+ defects) through coordination with the -SH and -COOH groups in PA, but also finely tunes the crystallinity of Cs/FA-based perovskite film. Benefiting from these merits, a reduction of non-radiative recombination and an increase in photoluminescence lifetime have been achieved. As a result, the champion MA-free device exhibits an impressive power conversion efficiency (PCE) of 22.4%, an open-circuit voltage of 1.163 V, a notable fill factor of 82%, and excellent long-term operational stability. Moreover, the defect passivation strategy can be further extended to a mini module (substrate: 4 × 4 cm2, active area: 7.2 cm2) as well as a wide-bandgap (∼1.73 eV) Cs/FA perovskite system by delivering PCEs of 16.3% and 20.2%, respectively, demonstrating its universality in defect passivation for efficient PSCs.