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Hexagonal boron nitride (h-BN) is brittle, however, its atomic-scale structural engineering can lead to unprecedented physical properties. Here we report the bulk synthesis of high-density crystalline h-BN solids by using high-temperature spark plasma sintering (SPS) of micron size h-BN powders. In addition to the high mechanical strength and ductile response of such materials, we have obtained anomalous values of dielectric constant beyond theoretical limits, high thermal conductivity, and exceptional neutron radiation shielding capability. Through exhaustive characterizations we reveal that SPS induces non-basal plane crystallinity, twisting of layers, and facilitates inter-grain fusion with a high degree of in-plane alignment across macroscale dimensions, resulting in near-theoretical density and anomalous properties. Our findings highlight the importance of material design, via new approaches such as twisting and interconnections between atomically thin layers, to create novel ceramics with properties that could go beyond their intrinsic theoretical predictions., Comment: Authors revised version, 46 pages, 4 figures

One of the most appealing aspects of machine learning for material design is its high throughput exploration of chemical spaces, but to reach the ceiling of ML-aided exploration, more than current model architectures and processing algorithms are required. New architectures such as Graph Neural Networks (GNNs) have seen significant research investments recently. For heterogeneous catalysis, defining substrate intramolecular bonds and adsorbate/substrate intermolecular bonds is a time-consuming and challenging process. Before applying a model, dataset pre-processing, node/bond descriptor design, and specific model constraints have to be considered. In this work, a framework designed to solve these issues is presented in the form of an automatic graph representation algorithm (AGRA) tool to extract the local chemical environment of metallic surface adsorption sites is presented. This tool is able to gather multiple adsorption geometry datasets composed of different systems and combine them into a single model. To show AGRA's excellent transferability and reduced computational cost compared to other graph representation methods, it was applied to 5 different catalytic reaction datasets and benchmarked against the Open Catalyst Projects (OCP) graph representation method. The two ORR datasets with O/OH adsorbates obtained 0.053 eV RMSD when combined together, whereas the three CO2RR datasets with CHO/CO/COOH obtained an average performance of 0.088 eV RMSD. To further display the algorithm's versatility and extrapolation ability, a model was trained on a subset combination of all 5 datasets with an RMSD of 0.105 eV. This universal model was then used to predict a wide range of adsorption energies and an entirely new ORR catalyst system and then verified through Density Functional Theory calculations

Computational modeling of high entropy alloys (HEA) is challenging given the scalability issues of Density functional theory (DFT) and the non-availability of Interatomic potentials (IP) for molecular dynamics simulations (MD). This work presents a computationally efficient IP for modeling complex elemental interactions present in HEAs. The proposed random features-based IP can accurately model melting behaviour along with various process-related defects. The disordering of atoms during the melting process was simulated. Predicted atomic forces are within 0.08 eV/$\unicode{xC5}$ of corresponding DFT forces. MD simulations predictions of mechanical and thermal properties are within 7$\%$ of the DFT values. High-temperature self-diffusion in the alloy system was investigated using the IP. A novel sparse model is also proposed which reduces the computational cost by 94$\%$ without compromising on the force prediction accuracy.

Structural cellular materials in nature, such as wood, trabecular bone, corals, and dentin combine complex biological functions with structural roles, such as skeletal support and impact protection1,2. They feature complex structural hierarchies from nano- to macroscale that enable optimization of both strength and toughness (flaw tolerance) simultaneously3-9. These hierarchies typically exhibit structural disorder in the arrangement of pores. The degree of disorder, however, has not been systematically quantified before, and its role in the mechanical performance of cellular biomaterials is generally unknown. Here we have applied Voronoi tessellations to quantify the cell size variation in 2D cross-sections of biological and engineered cellular materials, using a disorder parameter (d) ranging between 0 (highly disordered) to 1.0 (regular hexagonal honeycomb). We demonstrate that various plant, fungi, and animal cellular materials show characteristic ranges of disorder. Using 3D printed analogues and numerical methods, we demonstrate experimentally a range of pseudo-order (d=0.6 to 0.8) that exhibits a > 30% increase in fracture toughness (and equivalent strength) compared to hexagonal honeycombs (d=1.0) of equal density. Our results show this range of disorder is similar to that identified in the biological examples, which suggests convergent evolution. This optimal degree of structural disorder limits catastrophic failure, providing an evolutionary advantage for organism survival. Distributed structural damage limits cracks below a maximum threshold size and also enables tissue repair mechanisms after trauma. Our work shows that tailored disorder should be considered as a new design paradigm for digitally fabricated, lightweight architected materials to improve damage tolerance.

We propose a method of neural evolution structures (NESs) combining artificial neural networks (ANNs) and evolutionary algorithms (EAs) to generate High Entropy Alloys (HEAs) structures. Our inverse design approach is based on pair distribution functions and atomic properties and allows one to train a model on smaller unit cells and then generate a larger cell. With a speed-up factor of approximately 1000 with respect to the SQSs, the NESs dramatically reduces computational costs and time, making possible the generation of very large structures (over 40,000 atoms) in few hours. Additionally, unlike the SQSs, the same model can be used to generate multiple structures with the same fractional composition.

The order-disorder transition in Ni-Al alloys under irradiation represents an interplay between various re-ordering processes and disordering due to thermal spikes generated by incident high energy particles. Typically, ordering in enabled by diffusion of thermally-generated vacancies, and can only take place at temperatures where they are mobile and in sufficiently high concentration. Here, in-situ transmission electron micrographs reveal that the presence of He, usually considered to be a deleterious immiscible atom in this material, promotes reordering in Ni3Al at temperatures where vacancies are not effective ordering agents. A rate-theory model is presented, that quantitatively explains this behavior, based on parameters extracted from atomistic simulations. These calculations show that the V2He complex is an effective agent through its high stability and mobility. It is surmised that immiscible atoms may stabilize reordering agents in other materials undergoing driven processes, and preserve ordered phases at temperature where the driven processes would otherwise lead to disorder.

The design of low dimensional materials through surface assisted self-assembly requires a better understanding of the factors that limit and control surface diffusion. We reveal how substrate surface defects hinder the mobility of sub-monolayer organic adsorbates on a metal surface with the model CuPc/Cu(111) system. Post-deposition annealing bonds CuPc molecules into dendritelike clusters that are often mobile at room temperature. Surface defects on Cu(111) create energetic barriers that prevent CuPc cluster motion on the metal surface. This phenomenon was unveiled by the motion of small clusters that show rigid-body diffusion solely in the available space in between defects. When clusters are sufficiently surrounded by defects, they become completely pinned in place and become immobilized., Comment: 15 pages, 6 figures, supplemental 13 pages, 6 figures

N-graphdiyne monolayers, a set of carbon-nitride nanosheets, have been synthesized recently through the polymerization of triazine- and pyrazine-based monomers. Since the two-dimensional nano-structures are mainly composed of light-weight nonmetallic elements including carbon and nitrogen, they might be able to provide high storage capacities for rechargeable cells. In this study, we used extensive first principle calculations such as electronic density of states, band structure, adsorption energy, open-circuit voltage, nudged-elastic band and charge analyses to investigate the application of the newly fabricated N-graphdiyne monolayers as the anode material for Li/Na/Mg ion batteries. Our calculations suggest that while Mg foreign atoms poorly interact with monolayers, Li and Na adatoms illustrate outstanding anodic characteristics for rechargeable storage cells. Electronic density of states calculations indicate that the insertion of Li/Na into the novel N-graphdiyne materials enhances the electrical conductivity of nanosheets. Adsorption energy and open-circuit voltage calculations predict that the nanosheets can provide a high storage capacity spectrum of 623-2180 mAh/g which is higher than that for most recently discovered 2D materials (e.g. phosphorene, borophane, and germanene involve Li binding capacities of 433, 504, and 369 mAh/g, respectively) and it is also significantly greater than the capacity of commercial anode materials (e.g. graphite contains a capacity of 372 mAh/g). This study provides valuable insights about the electronic characteristics of newly fabricated N-graphdiyne nanomaterials, rendering them as promising candidates to be used in the growing industry of rechargeable storage devices.

Since hydrogen fuel involves the highest energy density among all fuels, production of this gas through the solar water splitting approach has been suggested as a green remedy for greenhouse environmental issues due to extensive consumption of fossil fuels. Low dimensional materials possessing a large surface-to-volume ratio can be a promising candidate to be used for the photocatalytic approach. Here, we used extensive first principles calculations to investigate the application of newly fabricated members of two dimensional carbon nitrides including tg-C3N4, hg-C3N4, C2N, and C3N for water splitting. Band engineering via n-type, p-type, and isoelectronic doping agents such as B, N, P, Si, and Ge was demonstrated for tuning the electronic structure; optimizing solar absorption and band alignment for photocatalysis. Pristine tg-C3N4, hg-C3N4, and C2N crystals involve bandgaps of 3.190 eV, 2.772 eV, and 2.465 eV, respectively, which are not proper for water splitting. Among the dopants, Si and Ge dopants can narrow the band gap of carbon nitrides about 0.5 - 1.0 eV, and also increase their optical absorption in the visible spectrum. This study presents the potential for doping with isoelectronic elements to greatly improve the photocatalytic characteristics of carbon nitride nanostructures.

Fast-growing electronics industry and future energy storage needs have encouraged the design of rechargeable batteries with higher storage capacities, and longer life times. In this regard, two-dimensional (2D) materials, specifically boron and carbon nanosheets, have garnered enthusiasm due to their fascinating electronic, optical, mechanical and chemical properties. Recently, a hydrogen boride (HB) nanosheet was successfully fabricated showing remarkable stability and superior physical properties. Motivated by this experimental study, we used first principle electronic structure calculations to study the feasibility of this nanosheet to serve as an anode material for Li/Na/Ca/Mg/Al ion batteries. Most active adsorption sites for single adatoms were evaluated and next adatoms were gradually inserted into the anode surface accordingly. The charge transfer, electronic density of sates, storage capacity, structural stability, open-circuit potential and diffusion energy barriers were explored. Our theoretical study predicts that HB shows outstanding electrode properties for Li and Na ion batteries. The intercalation of both Li and Na adatoms into the HB monolayer can lead to a high identical storage capacity of 1133.8 mAh/g which is promising compared to the capacities of the traditional anode materials; such as graphite (372 mAh/g) and TiO2 (200 mAh/g), and other 2D materials; such as germanene (369 mAh/g), stanene (226 mAh/g), and phosphorene (432.8 mAh/g) nanosheets. These results may open a new horizon for the design of rechargeable batteries with higher storage capacitates.

Two-dimensional (2D) structures of boron atoms so called borophene, have recently attracted remarkable attention. In a latest exciting experimental study, a hydrogenated borophene structure was realized. Motivated by this success, we conducted extensive first-principles calculations to explore the mechanical, thermal conduction, electronic and optical responses of borophene hydride. The mechanical response of borophene hydride was found to be anisotropic in which it can yield an elastic modulus of 131 N/m and a high tensile strength of 19.9 N/m along the armchair direction. Notably, it was shown that by applying mechanical loading the metallic electronic character of borophene hydride can be altered to direct band-gap semiconducting, very appealing for the application in nanoelectronics. The absorption edge of the imaginary part of the dielectric function was found to occur in the visible range of light for parallel polarization. Finally, it was estimated that this novel 2D structure at the room temperature can exhibit high thermal conductivities of 335 W/mK and 293 W/mK along zigzag and armchair directions, respectively. Our study confirms that borophene hydride benefits an outstanding combination of interesting mechanical, electronic, optical and thermal conduction properties, promising for the design of novel nanodevices.

Two-dimensional polyaniline with a C3N stoichiometry, is a newly fabricated material that has expected to possess fascinating electronic, thermal, mechanical and chemical properties . The possibility of further tuning the C3N properties upon the adsorption of foreign adatoms is thus among the most attractive researches. We carried out extensive ab-initio density functional theory (DFT) simulations to investigate the adsorption of various elements including nonmetallic, metalloidic and metallic elements on the C3N monolayer. While pristine C3N acts as a semiconductor with an indirect electronic band gap; the functionalization with nonmetallic and semimetallic elements leads to a p-type doping and induces metallic behavior to the monolayer. On the other hand, metallic adsorption depending on the adatom size and the number of valence electrons may result in semiconducting, half-metallic or metallic properties. Whenever metallic foreign atoms conduct metallic characteristics, they mostly lead to the n-type doping by electron donation to the surface. Moreover, adsorption of transition metals could enhance the magnetic behavior of the monolayer due to the contribution of d electronic states. These results suggest that C3N illustrates viable electronic-magnetic properties which could be promising for semiconducting, nanosensores and catalytic applications.

The ideal strength is the maximum stress a material can withstand, and it is an important intrinsic property for structural applications. Griffith strength limit ~E/9 is the best known upper bound of this property for a material loaded in tension. Here we report that stanene, a recently fabricated two-dimensional material, could approach and possibly exceed this limit from a theoretical perspective. Utilizing first-principles density functional theory, we investigated the nonlinear elastic behavior of stanene and found that its strength could reach ~E/7.4 under uniaxial tension in both armchair and zigzag directions without incurring phonon instability or mechanical failure. The unique mechanical properties of stanene are further appreciated by comparisons with two other Group-IV 2D materials, graphene and silicene., Comment: 18 pages, 4 figures, 3 tables