Magnet-in-ferroelectric crystals exhibiting photomultiferroicity.

Growing crystallographically incommensurate and dissimilar organic materials is fundamentally intriguing but challenging for the prominent cross-correlation phenomenon enabling unique magnetic, electronic, and optical functionalities. Here, we report the growth of molecular layered magnet-in-ferroelectric crystals, demonstrating photomanipulation of interfacial ferroic coupling. The heterocrystals exhibit striking photomagnetization and magnetoelectricity, resulting in photomultiferroic coupling and complete change of their color while inheriting ferroelectricity and magnetism from the parent phases. Under a light illumination, ferromagnetic resonance shifts of 910 Oe are observed in heterocrystals while showing a magnetization change of 0.015 emu/g. In addition, a noticeable magnetization change (8% of magnetization at a 1,000 Oe external field) in the vicinity of ferro-to-paraelectric transition is observed. The mechanistic electric-field-dependent studies suggest the photoinduced ferroelectric field effect responsible for the tailoring of photo-piezo-magnetism. The crystallographic analyses further evidence the lattice coupling of a magnet-in-ferroelectric heterocrystal system.

The Case for a Defect Genome Initiative.

The Materials Genome Initiative (MGI) has streamlined the materials discovery effort by leveraging generic traits of materials, with focus largely on perfect solids. Defects such as impurities and perturbations, however, drive many attractive functional properties of materials. The rich tapestry of charge, spin, and bonding states hosted by defects are not accessible to elements and perfect crystals, and defects can thus be viewed as another class of "elements" that lie beyond the periodic table. Accordingly, a Defect Genome Initiative (DGI) to accelerate functional defect discovery for energy, quantum information, and other applications is proposed. First, major advances made under the MGI are highlighted, followed by a delineation of pathways for accelerating the discovery and design of functional defects under the DGI. Near-term goals for the DGI are suggested. The construction of open defect platforms and design of data-driven functional defects, along with approaches for fabrication and characterization of defects, are discussed. The associated challenges and opportunities are considered and recent advances towards controlled introduction of functional defects at the atomic scale are reviewed. It is hoped this perspective will spur a community-wide interest in undertaking a DGI effort in recognition of the importance of defects in enabling unique functionalities in materials.

Bilayer Kagome Borophene with Multiple van Hove Singularities.

The appearance of van Hove singularities near the Fermi level leads to prominent phenomena, including superconductivity, charge density wave, and ferromagnetism. Here a bilayer Kagome lattice with multiple van Hove singularities is designed and a novel borophene with such lattice (BK-borophene) is proposed by the first-principles calculations. BK-borophene, which is formed via three-center two-electron (3c-2e) σ-type bonds, is predicted to be energetically, dynamically, thermodynamically, and mechanically stable. The electronic structure hosts both conventional and high-order van Hove singularities in one band. The conventional van Hove singularity resulting from the horse saddle is 0.065 eV lower than the Fermi level, while the high-order one resulting from the monkey saddle is 0.385 eV below the Fermi level. Both the singularities lead to the divergence of electronic density of states. Besides, the high-order singularity is just intersected to a Dirac-like cone, where the Fermi velocity can reach 1.34 × 106  m s-1 . The interaction between the two Kagome lattices is critical for the appearance of high-order van Hove singularities. The novel bilayer Kagome borophene with rich and intriguing electronic structure offers an unprecedented platform for studying correlation phenomena in quantum material systems and beyond.

Pressure-controlled magnetism in 2D molecular layers.

Long-range magnetic ordering of two-dimensional crystals can be sensitive to interlayer coupling, enabling the effective control of interlayer magnetism towards voltage switching, spin filtering and transistor applications. With the discovery of two-dimensional atomically thin magnets, a good platform provides us to manipulate interlayer magnetism for the control of magnetic orders. However, a less-known family of two-dimensional magnets possesses a bottom-up assembled molecular lattice and metal-to-ligand intermolecular contacts, which lead to a combination of large magnetic anisotropy and spin-delocalization. Here, we report the pressure-controlled interlayer magnetic coupling of molecular layered compounds via chromium-pyrazine coordination. Room-temperature long-range magnetic ordering exhibits pressure tuning with a coercivity coefficient up to 4 kOe/GPa, while pressure-controlled interlayer magnetism also presents a strong dependence on alkali metal stoichiometry and composition. Two-dimensional molecular interlayers provide a pathway towards pressure-controlled peculiar magnetism through charge redistribution and structural transformation.

Valley-Polarized Interlayer Excitons in 2D Chalcogenide-Halide Perovskite-van der Waals Heterostructures.

Interlayer excitons (IXs) in two-dimensional (2D) heterostructures provide an exciting avenue for exploring optoelectronic and valleytronic phenomena. Presently, valleytronic research is limited to transition metal dichalcogenide (TMD) based 2D heterostructure samples, which require strict lattice (mis) match and interlayer twist angle requirements. Here, we explore a 2D heterostructure system with experimental observation of spin-valley layer coupling to realize helicity-resolved IXs, without the requirement of a specific geometric arrangement, i.e., twist angle or specific thermal annealing treatment of the samples in 2D Ruddlesden-Popper (2DRP) halide perovskite/2D TMD heterostructures. Using first-principle calculations, time-resolved and circularly polarized luminescence measurements, we demonstrate that Rashba spin-splitting in 2D perovskites and strongly coupled spin-valley physics in monolayer TMDs render spin-valley-dependent optical selection rules to the IXs. Consequently, a robust valley polarization of ∼14% with a long exciton lifetime of ∼22 ns is obtained in type-II band aligned 2DRP/TMD heterostructure at ∼1.54 eV measured at 80 K. Our work expands the scope for studying spin-valley physics in heterostructures of disparate classes of 2D semiconductors.

Dimensional Transformation of Molecular Magnetic Materials.

Two-dimensional (2D) magnetic layered materials have revolutionized size dependent magnetism to manipulate spin-based devices. However, it has been challenging to artificially create 2D magnetic materials from three-dimensional (3D) crystal structures with a variety of material groups. Here, we present the dimensionality manipulation via cation exchange of a 3D Prussian blue analogue [RbMnFe(CN)6] toward a 2D magnetic sheet [(K,Rb)(V,Mn)(Cr,Fe)(CN)6] with the magnetic ordering temperature rising from 12 to 330 K. Such a 2D magnetic sheet achieves crystalline V-Cr coordination in the Prussian blue lattice with pronounced anisotropy and stimuli responsiveness. The pressure dependent magnetic tunability of such 2D networks is predicted using first-principles calculations and demonstrated using the phase transitions of the hydrogel. This previously unobserved phenomenon of dimensional manipulation of a bulk crystal structure provides a rational strategy to expand the diversity and chemical compositions of 2D molecular magnetic material libraries.

Lithiating magneto-ionics in a rechargeable battery.

Magneto-ionics, real-time ionic control of magnetism in solid-state materials, promise ultralow-power memory, computing, and ultralow-field sensor technologies. The real-time ion intercalation is also the key state-of-charge feature in rechargeable batteries. Here, we report that the reversible lithiation/delithiation in molecular magneto-ionic material, the cathode in a rechargeable lithium-ion battery, accurately monitors its real-time state of charge through a dynamic tunability of magnetic ordering. The electrochemical and magnetic studies confirm that the structural vacancy and hydrogen-bonding networks enable reversible lithiation and delithiation in the magnetic cathode. Coupling with microwave-excited spin wave at a low frequency (0.35 GHz) and a magnetic field of 100 Oe, we reveal a fast and reliable built-in magneto-ionic sensor monitoring state of charge in rechargeable batteries. The findings shown herein promise an integration of molecular magneto-ionic cathode and rechargeable batteries for real-time monitoring of state of charge.

Antisite defect qubits in monolayer transition metal dichalcogenides.

Being atomically thin and amenable to external controls, two-dimensional (2D) materials offer a new paradigm for the realization of patterned qubit fabrication and operation at room temperature for quantum information sciences applications. Here we show that the antisite defect in 2D transition metal dichalcogenides (TMDs) can provide a controllable solid-state spin qubit system. Using high-throughput atomistic simulations, we identify several neutral antisite defects in TMDs that lie deep in the bulk band gap and host a paramagnetic triplet ground state. Our in-depth analysis reveals the presence of optical transitions and triplet-singlet intersystem crossing processes for fingerprinting these defect qubits. As an illustrative example, we discuss the initialization and readout principles of an antisite qubit in WS2, which is expected to be stable against interlayer interactions in a multilayer structure for qubit isolation and protection in future qubit-based devices. Our study opens a new pathway for creating scalable, room-temperature spin qubits in 2D TMDs.

Structure motif-centric learning framework for inorganic crystalline systems.

Incorporation of physical principles in a machine learning (ML) architecture is a fundamental step toward the continued development of artificial intelligence for inorganic materials. As inspired by the Pauling's rule, we propose that structure motifs in inorganic crystals can serve as a central input to a machine learning framework. We demonstrated that the presence of structure motifs and their connections in a large set of crystalline compounds can be converted into unique vector representations using an unsupervised learning algorithm. To demonstrate the use of structure motif information, a motif-centric learning framework is created by combining motif information with the atom-based graph neural networks to form an atom-motif dual graph network (AMDNet), which is more accurate in predicting the electronic structures of metal oxides such as bandgaps. The work illustrates the route toward fundamental design of graph neural network learning architecture for complex materials by incorporating beyond-atom physical principles.

Electrocatalytic CO2 reduction on earth abundant 2D Mo2C and Ti3C2 MXenes.

Mo2C and Ti3C2 MXenes were investigated as earth-abundant electrocatalyts for the CO2 reduction reaction (CO2RR). Mo2C and Ti3C2 exhibited faradaic efficiencies of 90% (250 mV overpotential) and 65% (650 mV overpotential), respectively, for the reduction of CO2 to CO in acetonitrile using an ionic liquid electrolyte. The use of ionic liquid 1-ethyl-2-methylimidazolium tetrafluoroborate as an electrolyte in organic solvent suppressed the competing hydrogen evolution reaction. Density functional theory (DFT) calculations suggested that the catalytic active sites are oxygen vacancy sites on both MXene surfaces. Also, a spontaneous dissociation of adsorbed COOH species to a water molecule and adsorbed CO on Mo2C promote the CO2RR.

Hierarchically 3D Porous Ag Nanostructures Derived from Silver Benzenethiolate Nanoboxes: Enabling CO2 Reduction with a Near-Unity Selectivity and Mass-Specific Current Density over 500 A/g.

Silver nanostructures with hierarchical porosities of multiple length scales have been synthesized through electrochemical reduction of silver benzenethiolate nanoboxes. The porous Ag nanostructures exhibit superior catalytic performance toward electrochemical reduction of CO2. The Faradaic efficiency of reducing CO2 to CO can be close to 100% at high cathodic potentials, benefiting from the readsorbed benzenethiolate ions on the Ag surface that can suppress the hydrogen evolution reaction (HER). Density functional theory calculations using the SCAN functional reveal that the disfavored H binding on the benzenethiolate-modified Ag surface is responsible for inhibiting the HER. The mass-specific activity of CO2 reduction can be over 500 A/g because the multiple-scale porosities maximize the diffusion of reactive species to and away from the Ag surface. The unique multiscale porosities and surface modification of the as-synthesized Ag nanostructures make them a class of promising catalysts for electrochemical reduction of CO2 in protic electrolytes to achieve maximum activity and selectivity.

Magnetically active transition metal cation-substituted alumina.

Alumina (Al2O3) is one of the most widely used ceramic materials for innumerable applications, due to its unique combination of attractive physical and mechanical properties. These intrinsic properties are dictated by the numerous phases that Al2O3 forms and its related phase transformations. Transition metal (TM) cation dopants (iron (Fe), cobalt (Co), nickel (Ni) and manganese (Mn)), even in sparse amounts, have been shown to significantly affect the phase transformation and microstructural evolution of Al2O3. Small concentrations of TM cation dopants have successfully been incorporated to synthesize magnetically active Al2O3, while reducing the θ to α phase transformation temperature by 150 °C, and maintaining the outstanding mechanical properties. In addition, first-principle calculations based on density-functional theory with hybrid functional (HSE06) and the PBE+U methods have provided a mechanistic understanding of the formation energy and magnetism of the TM-doped α and θ phases of Al2O3. The results reveal a potential route for phase transition regulation and external magnetic field-induced texturing of Al2O3 ceramics.

Chemisorption Can Reverse Defect-Defect Interaction on Heterogeneous Catalyst Surfaces.

Atomic-level understanding of roles of defect-defect interaction in the bonding of adsorbates on surfaces is critical for tailoring catalysts atom-by-atom and designing new catalysts. Here, from first-principles calculations, we propose a microscopic mechanism for the role of sulfur vacancy-vacancy interaction in hydrogen bonding on surfaces of MoS2, a nonprecious two-dimensional catalyst for hydrogen evolution reaction. We find that before hydrogen adsorption the interaction of a sulfur vacancy with others is repulsive, originating from the antibonding-like coupling of occupied in-gap vacancy states. When the sulfur vacancy is adsorbed by a hydrogen atom, its interaction with other unadsorbed sulfur vacancies becomes attractive, which can be attributed to the decoupling of repulsive vacancy-vacancy interactions and the occupying of bonding-like coupling states between the in-gap vacancy states that are unoccupied before hydrogen adsorption. This repulsive-to-attractive reverse of vacancy-vacancy interaction reduces the hydrogen adsorption energy and explains why the hydrogen adsorption energy decreases with increasing sulfur vacancy concentration. The emerging picture enables a more general discussion of local defect effects on the adsorption of various adsorbates at different surfaces, providing guidance to improve catalytic performance through defect engineering.

Elastic Properties and Fracture Behaviors of Biaxially Deformed, Polymorphic MoTe2.

Biaxial deformation of suspended membranes widely exists and is used in nanoindentation to probe elastic properties of structurally isotropic two-dimensional (2D) materials. However, the elastic properties and, in particular, the fracture behaviors of anisotropic 2D materials remain largely unclarified in the case of biaxial deformation. MoTe2 is a polymorphic 2D material with both isotropic (2H) and anisotropic (1T' and Td) phases and, therefore, an ideal system of single-stoichiometric materials with which to study these critical issues. Here, we report the elastic properties and fracture behaviors of biaxially deformed, polymorphic MoTe2 by combining temperature-variant nanoindentation and first-principles calculations. It is found that due to similar atomic bonding, the effective moduli of the three phases deviate by less than 15%. However, the breaking strengths of distorted 1T' and Td phases are only half the value of 2H phase due to their uneven distribution of bonding strengths. Fractures of both isotropic 2H and anisotropic 1T' phases obey the theorem of minimum energy, forming triangular and linear fracture patterns, respectively, along the orientations parallel to Mo-Mo zigzag chains. Our findings not only provide a reference database for the elastic behaviors of versatile MoTe2 phases but also illuminate a general strategy for the mechanical investigation of any isotropic and anisotropic 2D materials.

High current carrying and thermal conductive copper-carbon conductors.

The surging demand for miniaturized compact devices has generated the need for new metal conductors with high current carrying ampacity, electric and thermal conductivity. Herein, we report carbon-metal conductors that exhibit a high breakdown current density (39% higher than copper) and electrical conductivity (e.g. 63% higher than that of copper at 363 K) in a broad temperature range. The mechanistic studies of thermal conductivity through first-principle modeling show that the multilayer graphene percolation networks efficiently decrease the electron-phonon coupling in the copper-graphene composites, even if phonon modes are activated at a high temperature. These results imply that the copper-based composites have the potential to be the next generation metal conductor with high electrical and thermal conductivity, as well as excellent current-carrying ampacity. More importantly, the developed composite can be deployed in the ink form, making it possible to be utilized by the microelectronic fabrication process.

Learning atoms for materials discovery.

Exciting advances have been made in artificial intelligence (AI) during recent decades. Among them, applications of machine learning (ML) and deep learning techniques brought human-competitive performances in various tasks of fields, including image recognition, speech recognition, and natural language understanding. Even in Go, the ancient game of profound complexity, the AI player has already beat human world champions convincingly with and without learning from the human. In this work, we show that our unsupervised machines (Atom2Vec) can learn the basic properties of atoms by themselves from the extensive database of known compounds and materials. These learned properties are represented in terms of high-dimensional vectors, and clustering of atoms in vector space classifies them into meaningful groups consistent with human knowledge. We use the atom vectors as basic input units for neural networks and other ML models designed and trained to predict materials properties, which demonstrate significant accuracy.

Alkaline-stable nickel manganese oxides with ideal band gap for solar fuel photoanodes.

Combinatorial (photo)electrochemical studies of the (Ni-Mn)Ox system reveal a range of promising materials for oxygen evolution photoanodes. X-ray diffraction, quantum efficiency, and optical spectroscopy mapping reveal stable photoactivity of NiMnO3 in alkaline conditions with photocurrent onset commensurate with its 1.9 eV direct band gap. The photoactivity increases upon mixture with 10-60% Ni6MnO8 providing an example of enhanced charge separation via heterojunction formation in mixed-phase thin film photoelectrodes. Density functional theory-based hybrid functional calculations of the band edge energies in this oxide reveal that a somewhat smaller than typical fraction of exact exchange is required to explain the favorable valence band alignment for water oxidation.

Cobalt Intercalated Layered NiFe Double Hydroxides for the Oxygen Evolution Reaction.

We present a combined experimental and theoretical study to demonstrate that the electrocatalytic activity of NiFe layered double hydroxides (NiFe LDHs) for the oxygen evolution reaction (OER) can be significantly enhanced by systematic cobalt incorporation using coprecipitation and/or intercalation. Electrochemical measurements show that cobalt modified NiFe LDH possesses an enhanced activity for the OER relative to pristine NiFe LDH. The Co-modified NiFe LDH exhibits overpotentials in the range of 290-322 mV (at 10 mA cm-2), depending on the degree of cobalt content. The best catalyst, cobalt intercalated NiFe LDH achieved a current density of 10 mA cm-2 at an overpotential of ∼265 mV (compared to 310 mV for NiFe LDH), with a near unity (99%) faradaic efficiency and long-term stability. Density functional theory calculations revealed that enhanced activity of Co-modified NiFe LDH could be attributed to the ability of Co to tune the electronic structure of the NiFe LDH so that optimal binding of OER reaction intermediates could be achieved.

Negative Poisson's ratio in 1T-type crystalline two-dimensional transition metal dichalcogenides.

Materials with a negative Poisson's ratio, also known as auxetic materials, exhibit unusual and counterintuitive mechanical behaviour-becoming fatter in cross-section when stretched. Such behaviour is mostly attributed to some special re-entrant or hinged geometric structures regardless of the chemical composition and electronic structure of a material. Here, using first-principles calculations, we report a class of auxetic single-layer two-dimensional materials, namely, the 1T-type monolayer crystals of groups 6-7 transition-metal dichalcogenides, MX2 (M=Mo, W, Tc, Re; X=S, Se, Te). These materials have a crystal structure distinct from all other known auxetic materials. They exhibit an intrinsic in-plane negative Poisson's ratio, which is dominated by electronic effects. We attribute the occurrence of such auxetic behaviour to the strong coupling between the chalcogen p orbitals and the intermetal t2g-bonding orbitals within the basic triangular pyramid structure unit. The unusual auxetic behaviour in combination with other remarkable properties of monolayer two-dimensional materials could lead to novel multi-functionalities.

Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment.

The limited number of known low-band-gap photoelectrocatalytic materials poses a significant challenge for the generation of chemical fuels from sunlight. Using high-throughput ab initio theory with experiments in an integrated workflow, we find eight ternary vanadate oxide photoanodes in the target band-gap range (1.2-2.8 eV). Detailed analysis of these vanadate compounds reveals the key role of VO4 structural motifs and electronic band-edge character in efficient photoanodes, initiating a genome for such materials and paving the way for a broadly applicable high-throughput-discovery and materials-by-design feedback loop. Considerably expanding the number of known photoelectrocatalysts for water oxidation, our study establishes ternary metal vanadates as a prolific class of photoanode materials for generation of chemical fuels from sunlight and demonstrates our high-throughput theory-experiment pipeline as a prolific approach to materials discovery.