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.

Magnetic Order, Electrical Doping, and Charge-State Coupling at Amphoteric Defect Sites in Mn-Doped 2D Semiconductors.

Two-dimensional (2D) dilute magnetic semiconductors (DMSs) are attractive material platforms for applications in multifunctional nanospintronics due to the prospect of embedding controllable magnetic order within nanoscale semiconductors. Identifying candidate host material and dopant systems requires consideration of doping formation energies, magnetic ordering, and the tendency for dopants to form clustered domains. In this work, we consider the defect thermodynamics and the dilute magnetic properties across charge states of 2D-MoS2 and 2D-WS2 with Mn magnetic dopants as candidate systems for 2D-DMSs. Using hybrid density functional calculations, we study the magnetic and electronic properties of these systems across configurations with thermodynamically favorable defects: 2D-MoS2 doped with Mn atoms at sulfur site (MnS), at two Mo sites (2MnMo), on top of a Mo atom (Mn-top), and at a Mo site (MnMo). While the majority of the Mn-defect complexes provide trap states, MnMo and MnW are amphoteric, although previously predicted to be donor defects. The impact of cluster formation of these amphoteric defects on magnetic ordering is also considered; both MnMo-MnMo (2Mn2Mo) and MnW-MnW (2Mn2W) clusters are found to be stable in ferromagnetic (FM) ordering. Interestingly, we observed the defect charge state dependent magnetic behavior of 2Mn2Mo and 2Mn2W clusters in 2D-TMDs. We investigate that the FM coupling of 2Mn2Mo and 2Mn2W clusters is stable in only a neutral charge state; however, the antiferromagnetic (AFM) coupling is stable in the +1 charge state. 2Mn2Mo clusters provide shallow donor levels in AFM coupling and deep donor levels in FM coupling. 2Mn2W clusters lead to trap states in the FM and AFM coupling. We demonstrate the AFM to FM phase transition at a critical electron density nce = 3.5 × 1013 cm-2 in 2D-MoS2 and 2D-WS2. At a 1.85% concentration of Mn, we calculate the Curie temperature of 580 K in the mean-field approximation.

Dynamic self-reinforcement of gene expression determines acquisition of cellular mechanical memory.

Mechanotransduction describes activation of gene expression by changes in the cell's physical microenvironment. Recent experiments show that mechanotransduction can lead to long-term "mechanical memory," in which cells cultured on stiff substrates for sufficient time (priming phase) maintain altered phenotype after switching to soft substrates (dissipation phase) as compared to unprimed controls. The timescale of memory acquisition and retention is orders of magnitude larger than the timescale of mechanosensitive cellular signaling, and memory retention time changes continuously with priming time. We develop a model that captures these features by accounting for positive reinforcement in mechanical signaling. The sensitivity of reinforcement represents the dynamic transcriptional state of the cell composed of protein lifetimes and three-dimensional chromatin organization. Our model provides a single framework connecting microenvironment mechanical history to cellular outcomes ranging from no memory to terminal differentiation. Predicting cellular memory of environmental changes can help engineer cellular dynamics through changes in culture environments.

Recursive feedback between matrix dissipation and chemo-mechanical signaling drives oscillatory growth of cancer cell invadopodia.

Most extracellular matrices (ECMs) are known to be dissipative, exhibiting viscoelastic and often plastic behaviors. However, the influence of dissipation, in particular mechanical plasticity in 3D confining microenvironments, on cell motility is not clear. In this study, we develop a chemo-mechanical model for dynamics of invadopodia, the protrusive structures that cancer cells use to facilitate invasion, by considering myosin recruitment, actin polymerization, matrix deformation, and mechano-sensitive signaling pathways. We demonstrate that matrix dissipation facilitates invadopodia growth by softening ECMs over repeated cycles, during which plastic deformation accumulates via cyclic ratcheting. Our model reveals that distinct protrusion patterns, oscillatory or monotonic, emerge from the interplay of timescales for polymerization-associated extension and myosin recruitment dynamics. Our model predicts the changes in invadopodia dynamics upon inhibition of myosin, adhesions, and the Rho-Rho-associated kinase (ROCK) pathway. Altogether, our work highlights the role of matrix plasticity in invadopodia dynamics and can help design dissipative biomaterials to modulate cancer cell motility.

Interfacial Electromechanics Predicts Phase Behavior of 2D Hybrid Halide Perovskites.

Quasi-two-dimensional (2D) mixed-cation hybrid halide perovskites (A'2AN-1MNX3N+1; A' = large organic molecule with cationic group, A = [Cs+, CH3NH3+, HC(NH2)2+], M = [Pb, Sn, Ge], X = [I-, Br-, Cl-]) have rapidly emerged as candidates to improve the structural stability and device lifetime of 3D perovskite semiconductor devices under operating conditions. The addition of the large A' cation to the traditional AMX3 structure introduces several synthetic degrees of freedom and breaks M-X bonds, giving rise to peculiar critical phase behavior in the phase space of these complex materials. In this work, we propose a thermodynamic model parametrized by first-principles calculations to generate the phase diagram of 2D and quasi-2D perovskites (q-2DPKs) based on the mechanics and electrostatics of the interface between the A' cations and the metal halide octahedral network. Focusing on the most commonly studied methylammonium lead iodide system where A' is n-butylammonium (BA; CH3(CH2)3NH3+), we find that the apparent difficulty in synthesizing phase-pure samples with a stoichiometric index N > 5 can be attributed to the energetic competition between repulsion of opposing interfacial dipole layers and mechanical relaxation induced by interfacial stress. Our model shows quantitative agreement with experimental observations of the maximum phase-pure stoichiometric index (Ncrit) and explains the nonmonotonic evolution of the lattice parameters with increasing stoichiometric index (N). This model is generalizable to the entire family of q-2DPKs and can guide the design of photovoltaic and optical materials that combine the structural stability of the q-2DPKs while retaining the charge carrier properties of their 3D counterparts.

Controlled Growth of Large-Area Bilayer Tungsten Diselenides with Lateral P-N Junctions.

Bilayer two-dimensional (2D) van der Waals (vdW) materials are attracting increasing attention due to their predicted high quality electronic and optical properties. Here, we demonstrate dense, selective growth of WSe2 bilayer flakes by chemical vapor deposition with the use of a 1:10 molar mixture of sodium cholate and sodium chloride as the growth promoter to control the local diffusion of W-containing species. A large fraction of the bilayer WSe2 flakes showed a 0 (AB) and 60° (AA') twist between the two layers, whereas Moiré 15 and 30° twist angles were also observed. Well-defined monolayer-bilayer junctions were formed in the as-grown bilayer WSe2 flakes, and these interfaces exhibited p-n diode rectification and an ambipolar transport characteristic. This work provides an efficient method for the layer-controlled growth of 2D materials, in particular, 2D transition metal dichalcogenides, and promotes their applications in next-generation electronic and optoelectronic devices.

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.

Toward a Mechanistic Understanding of Vertical Growth of van der Waals Stacked 2D Materials: A Multiscale Model and Experiments.

Vertical stacking of monolayers via van der Waals (vdW) interaction opens promising routes toward engineering physical properties of two-dimensional (2D) materials and designing atomically thin devices. However, due to the lack of mechanistic understanding, challenges remain in the controlled fabrication of these structures via scalable methods such as chemical vapor deposition (CVD) onto substrates. In this paper, we develop a general multiscale model to describe the size evolution of 2D layers and predict the necessary growth conditions for vertical (initial + subsequent layers) versus in-plane lateral (monolayer) growth. An analytic thermodynamic criterion is established for subsequent layer growth that depends on the sizes of both layers, the vdW interaction energies, and the edge energy of 2D layers. Considering the time-dependent growth process, we find that temperature and adatom flux from vapor are the primary criteria affecting the self-assembled growth. The proposed model clearly demonstrates the distinct roles of thermodynamic and kinetic mechanisms governing the final structure. Our model agrees with experimental observations of various monolayer and bilayer transition metal dichalcogenides grown by CVD and provides a predictive framework to guide the fabrication of vertically stacked 2D materials.