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Results for “diffusivity”
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Crystallize It before It Diffuses: Kinetic Stabilization of Thin-Film Phosphorus-Rich Semiconductor CuP 2
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Metal Halide Perovskite Heterostructures: Blocking Anion Diffusion with Single-Layer Graphene
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Finite Element Modeling of Diffusion in Fractured Porous Media by Using Hierarchical Material Properties
Abstract Fractured porous media challenge modeling approaches due to high computational costs and excessive mesh refinement imposed by the extreme scale variability of fractures and the heterogeneity of the surrounding porous rock. To overcome such difficulties, we utilize the hierarchical finite element method ( Hi ‐FEM) that has been developed previously to simulate the electrical potential distribution in complex geologic environments. The method employs the hierarchical basis functions in classical finite element analysis to enable representation of material properties on each dimensional component of a given 3D unstructured finite element, thereby inherently allowing for interactions at the boundary between fracture and a host rock. In this study, we extend its application to transient fluid flow and heat conduction in the Laplace domain. Time‐domain flow solutions are obtained by numerical inverse Laplace transform. We evaluate the accuracy of the method using different flow models and demonstrate its robustness for large‐scale, rock mass models featuring complex fracture networks. Moreover, for the computation of nodal Darcian velocity fields in fractured porous media where the fractures are represented as 2D features, a new approach that employs the Yeh's Galerkin model for both volume and facet elements is proposed. Results show that Hi ‐FEM can produce accurate flow solutions for fractured porous media without any need of coupling or transfer mechanism while still being computationally economical and numerically robust, even for large‐scale simulations.
WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs With Physics‐Informed Neural Networks
Accurate representation of pumping wells is essential for reliable reservoir characterization and simulation of operational scenarios in subsurface flow models. Physics-informed neural networks (PINNs) are emerging as a promising alternative to numerical models for reservoir modeling, offering seamless integration of monitoring data and governing physical equations. However, existing PINN-based studies face major challenges in capturing fluid pressure near wells when using a source/sink term, particularly during the early stages after pumping begins. We address this problem by introducing WellPINN, a workflow in which an initially trained PINN infers fluid pressure across the entire reservoir domain using a large equivalent well radius. This initial PINN solution is then locally refined around the well by a set of subdomain PINNs that are trained for smaller equivalent well radii. Continuity across these subdomain interfaces as well as at the initial condition is ensured by hard-constraining each PINN on its subdomain boundary. Our results demonstrate WellPINN as the first workflow of its kind to focus on accurate inference of fluid pressure from pumping rates throughout the entire injection period, significantly advancing the potential of PINNs for inverse modeling and operational scenario simulations. All data and code for this paper are openly available at https://doi.org/10.20350/DIGITALCSIC/17260.
Twist-angle-dependent interlayer exciton diffusion in WS2–WSe2 heterobilayers
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Ab initio structure solutions from nanocrystalline powder diffraction data via diffusion models
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Superionic fluoride gate dielectrics with low diffusion barrier for two-dimensional electronics
Exploration of new dielectrics with a large capacitive coupling is an essential topic in modern electronics when conventional dielectrics suffer from the leakage issue near the breakdown limit. Here, to address this looming challenge, we demonstrate that rare-earth metal fluorides with extremely low ion migration barriers can generally exhibit an excellent capacitive coupling over 20 μF cm -2 (with an equivalent oxide thickness of ~0.15 nm and a large effective dielectric constant near 30) and great compatibility with scalable device manufacturing processes. Such a static dielectric capability of superionic fluorides is exemplified by MoS 2 transistors exhibiting high on/off current ratios over 10 8 , ultralow subthreshold swing of 65 mV dec -1 and ultralow leakage current density of ~10 -6 A cm -2 . Therefore, the fluoride-gated logic inverters can achieve notably higher static voltage gain values (surpassing ~167) compared with a conventional dielectric. Furthermore, the application of fluoride gating enables the demonstration of NAND, NOR, AND and OR logic circuits with low static energy consumption. In particular, the superconductor–insulator transition at the clean-limit Bi 2 Sr 2 CaCu 2 O 8+δ can also be realized through fluoride gating. In conclusion, our findings highlight fluoride dielectrics as a pioneering platform for advanced electronic applications and for tailoring emergent electronic states in condensed matter.
On the Planckian bound for heat diffusion in insulators
In an insulator, thermal transport at high temperature is expected to be dominated by entirely classical phonon dynamics. In apparent tension with this expectation, recent experimental observations have led to the conjecture that the transport lifetime, τ, is subject to a Planckian bound from below, namely, τ ≳ τ Pl ≡ ℏ / (k B T). Here, we argue that this Planckian bound is due to a quantum-mechanical bound on the sound velocity: v s < v M . The ‘melting velocity’ v M is defined in terms of the melting temperature of the crystal, the interatomic spacing and Planck’s constant. We show that for several classes of insulating crystals, both simple and complex, τ / τ Pl ≈ v M / v s at high temperatures. The velocity bound therefore implies the Planckian bound.
Flavour Hund’s coupling, Chern gaps and charge diffusivity in moiré graphene
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Diffusing protein binders to intrinsically disordered proteins
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Multistate and functional protein design using RoseTTAFold sequence space diffusion
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cDVAE: VAE-guided diffusion for particle accelerator beam 6D phase space projection diagnostics
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Controllable solute-diffusion gel-growth of BCHT: an effective approach towards large functional material single crystal synthesis
An underutilized, but highly advantageous, method of growing functional-single-crystals, the gel-growth technique, is highlighted. Large nonlinear optical crystals, BCHT, were grown and their dehydration phase-transformation to β-BTC were studied.
Doping molecular organic semiconductors by diffusion from the vapor phase
Spiro-OMeTAD can be doped by infiltration of F 4 TCNQ from the vapor phase without causing crystallization. Optical spectroscopy and thermopower measurements examined the question of the formation of dication states by charge transfer doping.
Revealing the correlation between structural evolution and Li[superscript +] diffusion kinetics of n
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The exchange of the fast substrate water in the S 2 state of photosystem II is limited by diffusion of bulk water through channels – implications for the water oxidation mechanism
Access to the oxygen-evolving complex in photosynthesis is restricted by specific barriers in the channels connecting the Mn 4 CaO 5 catalyst with bulk water. Together with other recent data, this finding allows assigning the two substrate waters.