Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy.

Small-molecule adsorption energies correlate with energy barriers of catalyzed intermediate reaction steps, determining the dominant microkinetic mechanism. Straining the catalyst can alter adsorption energies and break scaling relationships that inhibit reaction engineering, but identifying desirable strain patterns using density functional theory is intractable because of the high-dimensional search space. We train a graph neural network to predict the adsorption energy response of a catalyst/adsorbate system under a proposed surface strain pattern. The training data are generated by randomly straining and relaxing Cu-based binary alloy catalyst complexes taken from the Open Catalyst Project. The trained model successfully predicts the adsorption energy response for 85% of strains in unseen test data, outperforming ensemble linear baselines. Using ammonia synthesis as an example, we identify Cu-S alloy catalysts as promising candidates for strain engineering. Our approach can locate strain patterns that break adsorption energy scaling relations to improve catalyst performance.

SELFIES and the future of molecular string representations.

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, Smiles, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, Smiles has several shortcomings-most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100% robustness: SELF-referencing embedded string (Selfies). Selfies has since simplified and enabled numerous new applications in chemistry. In this perspective, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete future projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages, and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science.

N-Heterocyclic Carbene-Assisted Reversible Migratory Coupling of Aminoborane at Magnesium.

A combined synthetic and theoretical investigation of N-heterocyclic carbene (NHC) adducts of magnesium amidoboranes is presented, which involves a rare example of reversible migratory insertion within a normal valent s-block element. The reaction of (NHC)Mg(N(SiMe3 )2 )2 (1) and dimethylamine borane yields the tris(amide) adduct (NHC-BN)Mg(NMe2 BH3 )(N(SiMe3 )2 ) (2; NHC-BN = NHC-BH2 NMe2 ). In addition to Me2 N=BH2 capture at the NHC C-Mg bond, mechanistic investigations suggest the likelihood of aminoborane migratory insertion from an RMg(NMe2 BH2 NMe2 BH3 ) intermediate. To elucidate these processes, the carbene complexes (NHC)Mg(NMe2 BH3 )2 (8) and (NHC)Mg(NMe2 BH2 NMe2 BH3 )2 (9) were synthesized, and a dynamic migration of Me2 N=BH2 between Mg-N and NHC C-Mg bonds was observed in 9. This unusual reversible migratory insertion is presumably induced by dissimilar charge localization in the - {NMe2 BH2 NMe2 BH3 } anion, as well as the capacity of NHCs to reversibly capture Me2 N=BH2 in the presence of Lewis acidic magnesium species.

Benchmarking the Fluxional Processes of Organometallic Piano-Stool Complexes.

The correlation consistent Composite Approach for transition metals (ccCA-TM) and density functional theory (DFT) computations have been applied to investigate the fluxional mechanisms of cyclooctatetraene tricarbonyl chromium ((COT)Cr(CO)3) and 1,3,5,7-tetramethylcyclooctatetraene tricarbonyl chromium, molybdenum, and tungsten ((TMCOT)M(CO)3 (M = Cr, Mo, and W)) complexes. The geometries of (COT)Cr(CO)3 were fully characterized with the PBEPBE, PBE0, B3LYP, and B97-1 functionals with various basis set/ECP combinations, while all investigated (TMCOT)M(CO)3 complexes were fully characterized with the PBEPBE, PBE0, and B3LYP methods. The energetics of the fluxional dynamics of (COT)Cr(CO)3 were examined using the correlation consistent Composite Approach for transition metals (ccCA-TM) to provide reliable energy benchmarks for corresponding DFT results. The PBE0/BS1 results are in semiquantitative agreement with the ccCA-TM results. Various transition states were identified for the fluxional processes of (COT)Cr(CO)3. The PBEPBE/BS1 energetics indicate that the 1,2-shift is the lowest energy fluxional process, while the B3LYP/BS1 energetics (where BS1 = H, C, O: 6-31G(d'); M: mod-LANL2DZ(f)-ECP) indicate the 1,3-shift having a lower electronic energy of activation than the 1,2-shift by 2.9 kcal mol-1. Notably, PBE0/BS1 describes the (CO)3 rotation to be the lowest energy process, followed by the 1,3-shift. Six transition states have been identified in the fluxional processes of each of the (TMCOT)M(CO)3 complexes (except for (TMCOT)W(CO)3), two of which are 1,2-shift transition states. The lowest-energy fluxional process of each (TMCOT)M(CO)3 complex (computed with the PBE0 functional) has a ΔG‡ of 12.6, 12.8, and 13.2 kcal mol-1 for Cr, Mo, and W complexes, respectively. Good agreement was observed between the experimental and computed 1H-NMR and 13C-NMR chemical shifts for (TMCOT)Cr(CO)3 and (TMCOT)Mo(CO)3 at three different temperature regimes, with coalescence of chemically equivalent groups at higher temperatures.

High-throughput search for magnetic and topological order in transition metal oxides.

The discovery of intrinsic magnetic topological order in MnBi2Te4 has invigorated the search for materials with coexisting magnetic and topological phases. These multiorder quantum materials are expected to exhibit new topological phases that can be tuned with magnetic fields, but the search for such materials is stymied by difficulties in predicting magnetic structure and stability. Here, we compute more than 27,000 unique magnetic orderings for more than 3000 transition metal oxides in the Materials Project database to determine their magnetic ground states and estimate their effective exchange parameters and critical temperatures. We perform a high-throughput band topology analysis of centrosymmetric magnetic materials, calculate topological invariants, and identify 18 new candidate ferromagnetic topological semimetals, axion insulators, and antiferromagnetic topological insulators. To accelerate future efforts, machine learning classifiers are trained to predict both magnetic ground states and magnetic topological order without requiring first-principles calculations.

Tailoring Electronic and Optical Properties of MXenes through Forming Solid Solutions.

Alloying is a long-established strategy to tailor properties of metals for specific applications, thus retaining or enhancing the principal elemental characteristics while offering additional functionality from the added elements. We propose a similar approach to the control of properties of two-dimensional transition metal carbides known as MXenes. MXenes (Mn+1Xn) have two sites for compositional variation: elemental substitution on both the metal (M) and carbon/nitrogen (X) sites presents promising routes for tailoring the chemical, optical, electronic, or mechanical properties of MXenes. Herein, we systematically investigated three interrelated binary solid-solution MXene systems based on Ti, Nb, and/or V at the M-site in a M2XTx structure (Ti2-yNbyCTx, Ti2-yVyCTx, and V2-yNbyCTx, where Tx stands for surface terminations) showing the evolution of electronic and optical properties as a function of composition. All three MXene systems show unlimited solubility and random distribution of metal elements in the metal sublattice. Optically, the MXene systems are tailorable in a nonlinear fashion, with absorption peaks from ultraviolet to near-infrared wavelength. The macroscopic electrical conductivity of solid solution MXenes can be controllably varied over 3 orders of magnitude at room temperature and 6 orders of magnitude from 10 to 300 K. This work greatly increases the number of nonstoichiometric MXenes reported to date and opens avenues for controlling physical properties of different MXenes with a limitless number of compositions possible through M-site solid solutions.

Machine Learning-Enabled Design of Point Defects in 2D Materials for Quantum and Neuromorphic Information Processing.

Engineered point defects in two-dimensional (2D) materials offer an attractive platform for solid-state devices that exploit tailored optoelectronic, quantum emission, and resistive properties. Naturally occurring defects are also unavoidably important contributors to material properties and performance. The immense variety and complexity of possible defects make it challenging to experimentally control, probe, or understand atomic-scale defect-property relationships. Here, we develop an approach based on deep transfer learning, machine learning, and first-principles calculations to rapidly predict key properties of point defects in 2D materials. We use physics-informed featurization to generate a minimal description of defect structures and present a general picture of defects across materials systems. We identify over one hundred promising, unexplored dopant defect structures in layered metal chalcogenides, hexagonal nitrides, and metal halides. These defects are prime candidates for quantum emission, resistive switching, and neuromorphic computing.

Planar, Stair-Stepped, and Twisted: Modulating Structure and Photophysics in Pyrene- and Benzene-Fused N-Heterocyclic Boranes.

Because of their rigidity, polycyclic aromatic hydrocarbons (PAHs) have become a significant building block in molecular materials chemistry. Fusion or doping of boron into PAHs is known to improve the optoelectronic properties by reducing the LUMO energy level. Herein, we report a comprehensive study on the syntheses, structures, and photophysical properties of a new class of fused N-heterocyclic boranes (NHBs), pyrene- and benzene-linked in a "Janus-type" fashion (2-4, 6-9, and 11). Remarkably, these examples of fused NHBs display fluorescent properties, and collectively their emission spans the visible spectrum. The pyrene-fused NHBs all display blue fluorescence, as the excitations are dominated by the pyrene core. In notable contrast, the emission properties of the benzene-fused analogues are highly tunable and are dependent on the electronics of the NHB fragments (i.e., the functional group directly bound to the boron atoms). Pyrene-fused 2-4 and 11 represent the only molecules in which the K-region of pyrene is functionalized with NHB units, and while they exhibit distorted (twisted or stair-stepped) pyrene cores, benzene-fused 6-9 are planar. The electronic structure and optical properties of these materials were probed by computational studies, including an evaluation of aromaticity, electronic transitions, and molecular orbitals.

Accurate First-Principles Calculation of the Vibronic Spectrum of Stacked Perylene Tetracarboxylic Acid Diimides.

π-stacked organic electronic materials are tunable light absorbers with many potential applications in optoelectronics. The optical properties of such molecules are highly dependent on the nature and energy of electron-hole pairs or excitons formed upon light absorption, which in turn are determined by intra- and intermolecular electronic and vibrational excitations. Here, we present a first-principles approach for describing the optical spectrum of stacked organic molecules with strong vibronic coupling. For stacked perylene tetracarboxylic acid diimides, we describe optical excitations by using the time-dependent density functional theory with a Franck-Condon Herzberg-Teller approximation of vibronic effects and validate our approach with comparison to experimental ultraviolet-visible (UV-vis) absorption measurements of solvated model systems. We determine that for larger macromolecules, unlike for single molecules, the sampling of the ground-state potential energy surface significantly influences the optical absorption spectrum. We account for this effect by applying our analysis to ∼100 structures extracted from equilibrated molecular dynamics simulations and averaging the optical spectrum over the entire ensemble. Additionally, we demonstrate that intermolecular electronic coupling within the stacks results in multiple low-energy electronically excited states that all contribute to the optical spectrum. This study provides a computationally feasible recipe for describing the spectroscopic properties of stacked organic chromophores via first-principles density functional theory.

Synthesis of Mo4VAlC4 MAX Phase and Two-Dimensional Mo4VC4 MXene with Five Atomic Layers of Transition Metals.

MXenes are a family of two-dimensional (2D) transition metal carbides, nitrides, and carbonitrides with a general formula of Mn+1XnTx, in which two, three, or four atomic layers of a transition metal (M: Ti, Nb, V, Cr, Mo, Ta, etc.) are interleaved with layers of C and/or N (shown as X), and Tx represents surface termination groups such as -OH, ═O, and -F. Here, we report the scalable synthesis and characterization of a MXene with five atomic layers of transition metals (Mo4VC4Tx), by synthesizing its Mo4VAlC4 MAX phase precursor that contains no other MAX phase impurities. These phases display twinning at their central M layers which is not present in any other known MAX phases or MXenes. Transmission electron microscopy and X-ray diffraction were used to examine the structure of both phases. Energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and high-resolution scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy were used to study the composition of these materials. Density functional theory calculations indicate that other five transition metal-layer MAX phases (M'4M″AlC4) may be possible, where M' and M″ are two different transition metals. The predicted existence of additional Al-containing MAX phases suggests that more M5C4Tx MXenes can be synthesized. Additionally, we characterized the optical, electronic, and thermal properties of Mo4VC4Tx. This study demonstrates the existence of an additional subfamily of M5X4Tx MXenes as well as a twinned structure, allowing for a wider range of 2D structures and compositions for more control over properties, which could lead to many different applications.

Extremely twisted and bent pyrene-fused N-heterocyclic germylenes.

The first examples of pyrene-fused Janus-type N-heterocyclic germylenes (NHGe) are reported. Remarkably, the pyrene linker and the germanium containing rings are extremely twisted, with "twist angles" up to 64°. Coordination of a Lewis base modifies the twisting of pyrene to an overall bent core (141° bend angle).

Engineering Magnetic Phases in Two-Dimensional Non-van der Waals Transition-Metal Oxides.

The family of 2D magnetic materials is continuously expanding because of the rapid discovery of exfoliable van der Waals magnetic systems. Recently, the synthesis of non-van der Waals magnetic "hematene" from common iron ore has opened an unconventional route to 2D material discovery. These non-van der Waals 2D systems are chemically stable and easily available and may have different or enhanced properties compared to their van der Waals counterparts. In this work, we have investigated and explained the nature of magnetic ordering in non-van der Waals 2D metal oxides. Two-dimensional hematene is found to be fully oxygen-passivated and stable under ambient conditions. It exhibits a striped ferrimagnetic ground state with a small net magnetic moment. Superexchange interactions are predicted to control the magnetic ground state of hematene, where pressure-induced spin crossover results in an observable net magnetic moment. Modulating the superexchange by alloying hematenes alters the magnetic ordering, tuning the system to a ferromagnetic ground state. Extending this strategy to the design of a new 2D material, we propose 2D chromia (α-Cr2O3) or "chromene", which, because of larger inter-transition metal distances and suppressed AFM superexchange, has a ferromagnetic ground state. We also show that tuning the magnetic ordering in these materials controls the transport properties by modulating the band gap, which may be of use in spintronic or catalytic applications.

Engineering Zero-Dimensional Quantum Confinement in Transition-Metal Dichalcogenide Heterostructures.

Achieving robust, localized quantum states in two-dimensional (2D) materials like graphene is desirable for optoelectronics and quantum information yet challenging due to the difficulties in confining Dirac fermions. Traditional colloidal nanoparticle and epitaxially grown quantum dots are also impractical for solid-state devices, due to either complex surface chemistry, unreliable spatial positioning, or lack of electrical and optical access. In this work, we design and optimize nanoscale monolayer transition-metal dichalcogenide (TMD) heterostructures to natively host massive Dirac fermion bound states. We develop an integrated multiscale approach to translate first-principles electronic structure to higher length scales, where we apply a continuum model to consider arbitrary 2D quantum dot geometries and sizes. Focusing on a model system of an MoS2 quantum dot in a WS2 matrix (MoS2/WS2), we find discrete bound states in triangular dots with side lengths up to 20 nm. We propose figures of merit that, when optimized for, result in heterostructure configurations engineered for maximally isolated bound states at room temperature. These design principles apply to the entire family of semiconducting TMD materials, and we predict 6.5 nm MoS2/WS2 (quantum dot/matrix) triangular dots and 4.5 nm MoSe2/WSe2 triangular dots as ideal systems for confining massive Dirac fermions.

Prediction of Synthesis of 2D Metal Carbides and Nitrides (MXenes) and Their Precursors with Positive and Unlabeled Machine Learning.

Growing interest in the potential applications of two-dimensional (2D) materials has fueled advancement in the identification of 2D systems with exotic properties. Increasingly, the bottleneck in this field is the synthesis of these materials. Although theoretical calculations have predicted a myriad of promising 2D materials, only a few dozen have been experimentally realized since the initial discovery of graphene. Here, we adapt the state-of-the-art positive and unlabeled (PU) machine learning framework to predict which theoretically proposed 2D materials have the highest likelihood of being successfully synthesized. Using elemental information and data from high-throughput density functional theory calculations, we apply the PU learning method to the MXene family of 2D transition metal carbides, carbonitrides, and nitrides, and their layered precursor MAX phases, and identify 18 MXene compounds that are highly promising candidates for synthesis. By considering both the MXenes and their precursors, we further propose 20 synthesizable MAX phases that can be chemically exfoliated to produce MXenes.

Surface-Engineered MXenes: Electric Field Control of Magnetism and Enhanced Magnetic Anisotropy.

Controlling magnetism in two-dimensional (2D) materials via electric fields and doping enables robust long-range order by providing an external mechanism to modulate magnetic exchange interactions and anisotropy. In this report, we predict that transition metal carbide and nitride MXenes are promising candidates for controllable magnetic 2D materials. The surface terminations introduced during synthesis act as chemical dopants that influence the electronic structure, enabling controllable magnetic order. We show ground-state magnetic ordering in Janus M2XO xF2- x (M is an early transition metal, X is carbon or nitrogen, and x = 0.5, 1, or 1.5) with asymmetric surface functionalization, where local structural and chemical disorder induces magnetic ordering in some systems that are nonmagnetic or weakly magnetic in their pristine form. The resulting magnetic states of these noncentrosymmetric structures can be robustly switched and stabilized by tuning the interlayer exchange couplings with small applied electric fields. Furthermore, bond directionality is enhanced by Janus functionalization, resulting in improved magnetic anisotropy, which is essential to stable 2D magnetic ordering. The mixed termination-induced anisotropy leads to robust Ising ferromagnetism with an out-of-plane easy axis over the full range of relevant termination compositions for Janus Mn2N. Janus Cr2C, V2C, and Ti2C were found to be robustly antiferromagnetic. Our results provide a strategy for exploiting asymmetric surface functionalization to achieve room-temperature nanoscale magnetism under ambient conditions in MXenes with currently available synthesis techniques.

Universal fluctuations in growth dynamics of economic systems.

The growth of business firms is an example of a system of complex interacting units that resembles complex interacting systems in nature such as earthquakes. Remarkably, work in econophysics has provided evidence that the statistical properties of the growth of business firms follow the same sorts of power laws that characterize physical systems near their critical points. Given how economies change over time, whether these statistical properties are persistent, robust, and universal like those of physical systems remains an open question. Here, we show that the scaling properties of firm growth previously demonstrated for publicly-traded U.S. manufacturing firms from 1974 to 1993 apply to the same sorts of firms from 1993 to 2015, to firms in other broad sectors (such as materials), and to firms in new sectors (such as Internet services). We measure virtually the same scaling exponent for manufacturing for the 1993 to 2015 period as for the 1974 to 1993 period and virtually the same scaling exponent for other sectors as for manufacturing. Furthermore, we show that fluctuations of the growth rate for new industries self-organize into a power law over relatively short time scales.

Tuning Noncollinear Spin Structure and Anisotropy in Ferromagnetic Nitride MXenes.

Recent experimental success in the realization of two-dimensional magnetism has invigorated the search for low-dimensional material systems with tunable magnetic anisotropy that exhibit intrinsic long-range ferromagnetic order. Here we report that modifying the surface termination and transition metal in monolayer M2NT x nitride MXenes gives rise to a rich diversity of noncollinear spin structures and finely tunable magnetocrystalline anisotropy. Based on first-principles simulations, we predict that manipulating the strength of the spin-orbit interaction and electron localization via the chemical degrees of freedom can induce sufficient anisotropy to counteract thermal fluctuations that suppress long-range magnetic order. We find that Ti2NO2 and Mn2NF2 MXenes have continuous O(3) and O(2) spin symmetries, respectively, that may be broken by an applied field, while Cr2NO2 and Mn2NO2 are intrinsic Ising ferromagnets with out-of-plane easy axes and magnetic anisotropy energies up to 63 µeV/atom. These systems also exhibit both gapped and gapless Dirac points near the Fermi level. Our study suggests that nitride MXenes offer a promising avenue for achieving both practical spintronic devices and investigating fundamental spin processes in two-dimensional materials.

Prediction of Enhanced Catalytic Activity for Hydrogen Evolution Reaction in Janus Transition Metal Dichalcogenides.

Significant efforts have been made in improving the hydrogen evolution reaction (HER) catalytic activity in transition metal dichalcogenides (TMDs), which are promising nonprecious catalysts. However, previous attempts have exploited possible solutions to activate the inert basal plane, with little improvement. Among them, the most successful modification requires a careful manipulation of vacancy concentration and strain simultaneously. To fully realize the promise of TMD catalysts for HER in an easier and more effective way, a new means in tuning the HER catalytic activity is needed. Herein, we propose exploiting the inherent structural asymmetry in the recently synthesized family of Janus TMDs as a new means to stimulate HER activity. We report a density functional theory (DFT) study of various Janus TMD monolayers as HER catalysts, and identify the WSSe system as a promising candidate, where the basal plane can be activated without large applied tensile strains and in the absence of significant density of vacancies. We predict that it is possible to realize a strain-free Janus TMD-based catalyst that can readily provide promising intrinsic HER catalytic performance. The calculated density of states and electronic structures reveal that the introduction of in-gap states and a shift in the Fermi level in hydrogen adsorbed systems due to Janus asymmetry is the origin of enhanced HER activity. Our results should pave the way to design high-performance and easy-accessible TMD-based HER catalysts.

Prediction of optimal structural water concentration for maximized performance in tunnel manganese oxide electrodes.

Crystal water has been shown to stabilize next-generation energy storage electrodes with structural tunnels to accommodate cation intercalation, but the stabilization mechanism is poorly understood. In this study, we present a simple physical model to explain the energetics of interactions between the electrode crystal lattice, structural water, and electrochemically cycled ions. Our model is applied to understand the effects of crystal water on sodium ion intercalation in a tunnel manganese oxide structure, and we predict that precisely controlling the crystal water concentration can optimize the ion intercalation voltage and capacity and promote stable cycling. The analysis yields a critical structural water concentration by accounting for the interplay between elastic and electrostatic contributions to the free energy. Our predictions are validated with first-principles calculations and electrochemical measurements. The theoretical framework used here can be extended to predict critical concentrations of stabilizing molecules to optimize performance in next-generation battery materials.

Tunable Magnetism and Transport Properties in Nitride MXenes.

Two-dimensional materials with intrinsic and robust ferromagnetism and half-metallicity are of great interest to explore the exciting physics and applications of nanoscale spintronic devices, but no such materials have been experimentally realized. In this study, we predict several M2NTx nitride MXene structures that display these characteristics based on a comprehensive study using a crystal field theory model and first-principles simulations. We demonstrate intrinsic ferromagnetism in Mn2NTx with different surface terminations (T = O, OH, and F), as well as in Ti2NO2 and Cr2NO2. High magnetic moments (up to 9 µB per unit cell), high Curie temperatures (1877 to 566 K), robust ferromagnetism, and intrinsic half-metallic transport behavior of these MXenes suggest that they are promising candidates for spintronic applications, which should stimulate interest in their synthesis.