Multiscale Simulation Research Articles

Advanced multi-scale mechanobiological simulations enable the distinction between healthy and pathological bone growth patterns

Advanced multi-scale mechanobiological simulations enable the distinction between healthy and pathological bone growth patterns

Sensitivity analysis of a multi-scale biofuel primary atomization simulation tool

The purpose is to produce a benchmarked commercial Volume of Fluid (VOF)-to-Discrete Phase Modeling (DPM) numerical algorithm using an experimental study of high-viscosity jet fuel blend C-3. Where the mesh resolution was too coarse to resolve sufficient gas-liquid interfacial curvature, the solver automatically converted VOF biofuel phase mass, momentum, and energy into the equivalent DPM biofuel phase at the sub-grid scale level. Particular attention herein was given to the sensitivity of the results to various numerical degrees of freedom related to the local criteria for conversion of a biofuel from VOF to DPM. The proliferation of commercial simulation tools mandates detailed parametric evaluations. It was found that, while instantaneous conversion rates were extremely sensitive to conversion criteria, atomization physics were not sensitive to the conversion rate effects. Also, this flow system exhibited an outstanding dependence on simulated azimuthal angle, rendering lower order models ineffective. Data sampling methods and durations, along with mesh resolution, were explored such that a particular set of parameters provided a validated model.

A multiscale model to understand the interface chemistry, contacts, and dynamics during lithium stripping

A reversible Li-metal electrode, paired with a solid electrolyte, is critical for attaining higher energy density and safer batteries beyond the current lithium-ion cells. A stable stripping process may be even harder to attain as the stripping process will remove Li-atoms from the surface, and naturally reduce surface contact area, if not self-corrected by other mechanisms, such as diffusion and plastic deformation under an applied external stack pressure. Here, we capture these mechanisms occurring at multiple length- and time- scales, i.e., interface interactions, vacancy hopping, and plastic deformation, by integrating density functional theory (DFT) simulations, kinetic Monte Carlo (KMC), and continuum finite element method (FEM). By assuming the self-affine nature of multiscale contacts, we predict the steady-state contact area as a function of stripping current density, interface wettability, and stack pressure. We further estimate the exponential increase of overpotential due to contact area loss to maintain the same stripping current density. We demonstrate that a lithiophilic interface requires less stack pressure to reach the same steady-state contact area fraction than a lithiophobic interface. A “tolerable steady-state” contact area loss for maintaining stable stripping is estimated at 20 %, corresponding to a 10 % increase in overpotential. To constrain contact loss within the tolerance, the required stack pressure is 0.1, 0.5, and 2 times the yield strength of lithium metal for three distinct interfaces, lithiophilic Li/lithium oxide(Li2O), Li/lithium lanthanum zirconium oxide(LLZO), and lithiophoblic Li/lithium fluoride(LiF), respectively. The modeling results agree with experiments on the impact of the stack pressure quantitatively, while the discrepancy in stripping rate sensitivity is attributed to the simplifying interface interaction in our simulations. Overall, this multiscale simulation framework demonstrates the importance of electrochemical-mechanical coupling in understanding the dynamics of the Li/SE interface during stripping.

TOPAS-Tissue: A Framework for the Simulation of the Biological Response to Ionizing Radiation at the Multi-Cellular Level.

This work aims to develop and validate a framework for the multiscale simulation of the biological response to ionizing radiation in a population of cells forming a tissue. We present TOPAS-Tissue, a framework to allow coupling two Monte Carlo (MC) codes: TOPAS with the TOPAS-nBio extension, capable of handling the track-structure simulation and subsequent chemistry, and CompuCell3D, an agent-based model simulator for biological and environmental behavior of a population of cells. We verified the implementation by simulating the experimental conditions for a clonogenic survival assay of a 2-D PC-3 cell culture model (10 cells in 10,000 µm2) irradiated by MV X-rays at several absorbed dose values from 0-8 Gy. The simulation considered cell growth and division, irradiation, DSB induction, DNA repair, and cellular response. The survival was obtained by counting the number of colonies, defined as a surviving primary (or seeded) cell with progeny, at 2.7 simulated days after irradiation. DNA repair was simulated with an MC implementation of the two-lesion kinetic model and the cell response with a p53 protein-pulse model. The simulated survival curve followed the theoretical linear-quadratic response with dose. The fitted coefficients α = 0.280 ± 0.025/Gy and β = 0.042 ± 0.006/Gy2 agreed with published experimental data within two standard deviations. TOPAS-Tissue extends previous works by simulating in an end-to-end way the effects of radiation in a cell population, from irradiation and DNA damage leading to the cell fate. In conclusion, TOPAS-Tissue offers an extensible all-in-one simulation framework that successfully couples Compucell3D and TOPAS for multiscale simulation of the biological response to radiation.

Lys716 in the transmembrane domain of yeast mitofusin Fzo1 modulates anchoring and fusion

Outer mitochondrial membrane fusion, a vital cellular process, is mediated by mitofusins. However, the underlying molecular mechanism remains elusive. We have performed extensive multiscale molecular dynamics simulations to predict a model of the transmembrane (TM) domain of the yeast mitofusin Fzo1. Coarse-grained simulations of the two TM domain helices, TM1 and TM2, reveal a stable interface, which is controlled by the charge status of residue Lys716. Atomistic replica-exchange simulations further tune our model, which is confirmed by a remarkable agreement with an independent AlphaFold2 (AF2) prediction of Fzo1 in complex with its fusion partner Ugo1. Furthermore, the presence of the TM domain destabilizes the membrane, even more if Lys716 is charged, which can be an asset for initiating fusion. The functional role of Lys716 was confirmed with yeast experiments, which show that mutating Lys716 to a hydrophobic residue prevents mitochondrial fusion.

A Small Molecule Impedes the Aβ1-42 Tetramer Neurotoxicity by Preserving Membrane Integrity: Microsecond Multiscale Simulations.

Amyloid-β (Aβ1-42) peptides aggregated into plaques deposited in the brain are the main hallmark of Alzheimer's disease (AD), a social and economic burden worldwide. In this context, insoluble Aβ1-42 fibrils are the main components of plaques. The recent trials that used approved AD drugs show that they can remove the fibrils from AD patients' brains, but they did not halt the course of the disease. Mounting evidence envisages that the soluble Aβ1-42 oligomers' interactions with the neuronal membrane trigger higher cell death than Aβ1-42 fibril interactions. Developing a compound that can alleviate the oligomer's toxicity is one of the most demanding tasks for curing the disease. We performed two molecular dynamics (MD) simulations in an explicit solvent model. In the first case, 55-μs of multiscale all-atom (AA)/coarse-grained (CG) MD simulations were carried out to decipher the impact of a previously described small anti-Aβ molecule, termed M30 (2-octahydroisoquinolin-2(1H)-ylethanamine), on an Aβ1-42 tetramer structure in close contact with a DMPC bilayer. In the second case, 15-μs AA/CG MD simulations were performed to rationalize the dynamics between Aβ1-42 and Aβ1-42-M30 tetramer complexes embedded in DMPC. On the membrane bilayer, we found that the Aβ1-42 tetramer penetrates the bilayer surface due to unrestricted conformational flexibility and many contacts with the membrane phosphate groups. In contrast, no Aβ1-42-M30 tetramer penetration was observed during the entire course of the simulation. In the case of the membrane-embedded Aβ1-42 tetramer, the integrity of the bottom bilayer leaflet was severely affected by the interactions between the negatively charged phosphate groups and the positively charged residues of the Aβ1-42 tetramer, resulting in a deep tetramer penetration into the bilayer hydrophobic region. These contacts were not observed in the case of the membrane-embedded Aβ1-42-M30 tetramer. It was noted that M30 molecules bind to Aβ1-42 tetramer through hydrogen bonds, resulting in a conformational stable Aβ1-42-M30 complex. The associated complex has reduced conformational changes and an enhanced rigidity that prevents the tetramer dissociation by interfering with the tetramer-membrane contacts. Our findings suggest that the M30 molecules could bind to Aβ1-42 tetramer resulting in a rigid structure, and that such complexes do not significantly perturb the membrane bilayer organization. These observations support the in vitro and in vivo experimental evidence that the M30 molecules prevent synaptotocity, improving AD-affected mice memory.

A Lennard-Jones potential based cohesive zone model and its application in multiscale damage simulation of graphene reinforced nanocomposites

A new mixed-mode cohesive zone model based on Lennard-Jones potential (LJCZM) is proposed to simulate the interface failure between graphene and epoxy matrix. The values of model parameters are obtained from a large number of molecular dynamics simulations, and a UMAT subroutine is programmed and validated to introduce this model into the ABAQUS platform. This process spans from the nanoscale to the microscale, which provides a new routine for the multiscale damage modeling of the graphene reinforced epoxy nanocomposite at microscale. In addition, the continuous damage phase-field model is used to simulate the matrix damage, and the values of model parameters are determined from the molecular dynamic simulations of the bulk epoxy at nanoscale. At last, the effects of parameters such as volume fraction, aspect ratio, orientation, and curvature of graphene nanoplatelets are investigated. The results indicate that the nanocomposite reinforced with high content and large aspect ratio graphene nanoplatelets presents the lower ultimate stress and fracture strain. In addition, the orientation and waviness of the graphene also significantly affect the mechanical properties of the nanocomposites. The nanocomposite reinforced with graphene platelets with greater waviness has higher stiffness and strength but lower toughness. The rationality and effectiveness of the model are verified through comparison with other existing results.

Microscopic mechanism investigation of extraction of lignin by benzyltriethylammonium chloride-based deep eutectic solvents

Benzyltriethylammonium chloride (BTEAC)-based deep eutectic solvent (DES) has a high delignification rate in the pretreatment of lignocellulose, and the lignin obtained from the removal has the advantages of high purity and low molecular weight. The interaction mechanism between BTEAC-based DES and lignin at molecular level was investigated by multiscale simulation analytical approach. By analyzing the types of weak interaction, charge distribution, number of hydrogen bonds, energy distribution and density distribution in different systems, the influence of six hydrogen bond donor (HBD) structures on the extraction process was clarified. The interaction between Cl- and lignin is mainly electrostatic interaction, and the interaction between BTEA+ and lignin is mainly van der Waals (vdW) interaction. The original π-π stacking of lignin is replaced by the new π-π stacking between BTEA+ and lignin. The effects of different functional groups and length of carbon chain on the interaction were researched. The acidic HBD with short carbon chain has a larger interaction and can affect the ether bond on the lignin. Among them, due to the smaller volume of formic acid (FA), it provides more space for BTEA+ to contact with lignin, resulting in stronger interaction. The molecular-level theoretical foundation underpinning the efficacy of BTEAC-FA in lignin removal during the pretreatment process is provided.

Simulation-Directed Construction of Bamboo-Forest-Like Heat Conduction Networks to Enhance Silicon Rubber Composites' Heat Conduction Properties.

Highly vertically thermally conductive silicon rubber (SiR) composites are widely used as thermal interface materials (TIMs) for chip cooling. Herein, inspired by water transport and transpiration of Moso bamboo-forests extensively existing in south China, and guided by filler self-assembly simulation, bamboo-forest-like heat conduction networks, with bamboo-stems-like vertically aligned polydopamine-coated carbon fibers (VA-PCFs), and bamboo-leaves-like horizontally layered Al2O3(HL-Al2O3), are rationally designed and constructed. VA-PCF/HL-Al2O3/SiR composites demonstrated enhanced heat conduction properties, and their through-plane thermal conductivity and thermal diffusivity reached 6.47W(mK)-1 and 3.98mm2s-1 at 12vol% PCF and 4vol% Al2O3 loadings, which are 32% and 38% higher than those of VA-PCF (12vol%) /SiR composites, respectively. The heat conduction enhancement mechanisms of VA-PCF/HL-Al2O3 networks on their SiR composites are revealed by multiscale simulation: HL-Al2O3 bridges the separate VA-PCF heat flow channels, and transfers more heat to the matrix, thereby increasing the vertical heat flux in composites. Along with high volume resistivity, low compression modulus, and coefficient of thermal expansion, VA-PCF/HL-Al2O3/SiR composites demonstrate great application potential as TIMs, which is proven using multiphysics simulation. This work not only makes a meaningful attempt at simulation-driven biomimetic material structure design but also provides inspiration for the preparation of TIMs.

Boosted Intracavity Aperture in Macrocyclic Amines Enabling Finely Regulated Microporous Membranes.

Finely tuning the pore structure of traditional nanofiltration (NF) membranes is challenging but highly effective for achieving efficient separations. Herein, we propose a concept of using macrocyclic amines (1,4,7-triazacyclononane, 3A; 1,4,7,10-tetraazacyclododecane, 4A1; and 1,4,8,11-tetraazacyclotetradecane, 4A2) with different intra-annular apertures to finely modulate the pore structure of microporous membranes via interfacial polymerization (IP). The boost in the intracavity size of the building blocks results in heightened steric hindrance of these amine monomers, leading to a controlled increase in membrane pore size, as demonstrated by both film characterizations and multiscale simulations. In conjunction with the increased intracavity size, the water permeability follows an augmented trend of 3A-TMC, 4A1-TMC, and 4A2-TMC (TMC: trimesoyl chloride) while exhibiting increased molecular weight cut-offs due to larger free-volume elements and stronger pore interconnectivity. Our proposed macrocyclic amine design strategy provides a guideline for finely regulated microporous membranes with high potential in NF-related applications.

Extra trees regression assisted 1D monolith reactor simulations based on microkinetic analysis and rate transformation

The incorporation of microkinetic method for surface reaction calculation is a key development direction in monolith reactor simulations, albeit posing significant computational stability and efficiency challenges. A data-driven multi-scale simulation framework is proposed to bridge the gap between macroscopic numerical model and microscopic reaction solvers. After the generating of precomputed microkinetic dataset, we utilize a tailor-designed preprocessing transformation, AD_log10, to effectively manage the common challenges of large variances and reversed directions in microkinetic rate data. A suite of machine learning regression models is developed as reaction rate solver integrated into the 1D two-phase monolith model. We employ NH3 selective catalytic oxidation on Cu(100) and Cu(111) as probe systems to validate our framework’s efficacy. In the context of on-board simulations under operating conditions, the Extra Trees Regression (with best regression performance) based model exhibits commendable accuracy and efficiency, successfully addressing complex processes previously unmanageable with interpolation-based models. This innovative approach paves the way for advanced monolith reactor modeling and sheds light on multi-scale simulation methodologies in chemical reaction engineering.

Multiscale modelling and characterisation of fused filament fabricated neat and graphene nanoplatelet reinforced G-polymers

AbstractIn this study, the fused filament fabrication of novel biodegradable G-polymer is investigated, including also filaments reinforced by graphene nanoplatelets. A combined framework of computational multiscale modelling and experimental studies is applied to characterise and model the mechanical behaviour of composite and nanocomposite materials, fabricated using a 3D-printer by depositing G-polymer filaments in +45$$^\circ$$ ∘ and $$-45^\circ$$ - 45 ∘ angles. The investigation is performed on both hot-extruded single filaments and 3D-printed specimens. Experimental results of hot-extruded single filaments are utilized on the microscale to extract the macroscale constitutive models. At the microscale level, representative volume elements with different percentages of penetration are analyzed to compute the effective orthotropic elastic material properties. A comprehensive comparison study is conducted using different micromechanical models, multiscale simulation outputs, and the mechanical properties resulting from experiments. The accuracy of the results obtained from the homogenization technique is validated against realistic finite element microstructural models and experimental measurements. The results demonstrate that computational homogenization, when coupled with accurate property characterisation, serves as a reliable tool for predicting the elastic response of 3D-printed parts. Furthermore, the proposed framework reduces the need for extensive experimental replication and lowers manufacturing costs.

A polycrystal plasticity-cellular automaton integrated modeling method for continuous dynamic recrystallization and its application to AA2196 alloy

Continuous dynamic recrystallization usually dominates the microstructural evolution in hot working of aluminum alloys, in which the high-angle grain boundaries of new grains mainly originate from the gradual increase in subgrain misorientation angles. In this work, an integrated computational method is proposed to simulate continuous dynamic recrystallization process of aluminum alloys by coupling three-dimensional cellular automaton and visco-plastic self-consistent models. The stress response, dislocation accumulation and recovery, and evolution of crystal orientations are computed in the context of polycrystal plasticity; the formation and rotation of subgrains, followed by stored energy and curvature-driven boundary migration, are captured and visualized by cellular automaton. The non-octahedral slip mode {110}<110> is additionally introduced to capture the 〈001〉 texture during hot compression. A universal cell topology deformation method is adopted to achieve an effective track of grain morphology evolution during plastic deformation. The proposed simulation framework is validated through simulating the isothermal uniaxial compression process of AA2196 alloy under different temperatures and strain rates. The orientation dependence of CDRX during compression is numerically reproduced by correlating the subgrain formation and rotation process with the activation state of slip systems. The simulated macroscopic flow stress, 3D microstructure and inherent microstructural characteristics such as subgrain size, subgrain boundaries and textures are in good agreement with the experimental results. The proposed method provides an effective and efficient tool for multi-scale simulation of hot forming process of aluminum alloys.

Effects of surface micro-texturing laser-etching on adhesive property and failure behaviors of basalt fiber composite single-lap-joint

Laser-etching technology can perform micro-nano processing on the sub-surface of composite, thereby enhancing its mechanical interlocking to improve the adhesive performance. However, it can easily cause surface fiber damage and destroy the integrity of composite. Hence, the influences of surface micro-texturing and laser-etching effect on the adhesive property and failure behaviors of basalt fiber reinforced polymer (BFRP) composite single-lap-joint are investigated. Here, different surface micro-texturing of BFRP with different laser-etching power and line space are processed by laser-etching. The surface morphology and wetting property of experimental samples are characterized, and single lap tests are conducted to evaluate the adhesive properties. Results show that the adhesive property firstly increases and then decreases with the laser power increase, where the samples etched with 10 W and line space of 0.1 mm perform the best. It is found that the epoxy on the surface is removed by laser-etching to improve the contact area, but the fiber damage is formed to affect the adhesive property. When the laser-etching reaches a certain depth in spite of fiber damage, it can achieve the best bonding performance with the balance of performance and structural integrity. Finally, the multi-scale simulations are conducted to effectively demonstrate the laser-etched interface bonding behavior and damage evolution process of BFRP single lap joints.

Recognition and Characterization of Nanoscale Phases: Modulus Mapping of Asphalt Film in Pavement Mixture Cores.

The objective of this study is to recognize and characterize the nanoscale phase modulus mapping of the asphalt film in pavement mixture cores using atomic force microscopy quantitative nanomechanical technology. The pavement core samples from the upper and middle layers of four highways and laboratory samples were taken as the research object. The phase modulus-macro property correlation of recovered asphalt was analyzed using mathematical statistics. The results showed that the pavement core samples had more significant multi-phase and diversified phase characteristics compared to lab samples. This indicated that the asphalt in the pavement core had an obvious phase separation phenomenon due to aging. The phase modulus of each sample was distributed across a relatively wide numerical range, and there were also many numerical points with large fluctuations. Especially for the mixture sample containing SBS (Styrene-Butadiene-Styrene)-modified asphalt, the phase modulus distribution mappings presented a multi-peak phenomenon. Hence, considering the distribution characteristics of the data, the box plot method was introduced. Compared with quantified results from laboratory samples, the phase modulus of SBS-modified asphalt increased by 0.96 times, 1.18 times and 1.15 times, and that of base asphalt increased by 0.59 times, 0.56 times, 0.42 times, 1.24 times and 0.39 times, respectively. This indicates that the aging degree of asphalt in the upper layer was generally greater than that of the asphalt in the middle layer and that there was an aging gradient in the direction of pavement depth. All points were within the 95% confidence band in terms of correlation fitting, indicating a better fitting effect between phase modulus and complex shear modulus, as well as between phase modulus and penetration. This research provides innovative ideas for future multi-scale numerical simulation and cross-scale performance model development of asphalt binders.

Multiscale Parametrization Of a Friction Model For Metal Cutting Using Contact Mechanics, Atomistic Simulations, And Experiments

In this study, we developed and parametrized a friction model for finite element (FE) cutting simulations of AISI4140 steel, combining experimental data and numerical simulations at various scales. Given the severe thermomechanical loads during cutting, parametrization of friction models based on analogous experiments has been proven difficult, such that the cutting process itself is often used for calibration. Instead, our model is based on the real area of contact between rough surfaces and the stress required to shear adhesive micro contacts. We utilized microtextured cutting tools and their negative imprint on chips to orient chip and tool surfaces, enabling the determination of a combined surface roughness. This effective roughness was then applied in contact mechanics calculations using a penetration hardness model informed by indentation hardness measurements. Consistent with Bowden and Tabor theory, we observed that the fractional contact area increased linearly with the applied normal load, and the effective roughness remained insensitive to cutting fluid application. Additionally, we calculated the required shear stress as a function of normal load using DFT-based molecular dynamics simulations for a tribofilm formed at the interface, with its composition inferred from ex-situ XPS depth profiling of the cutting tools. Our friction model demonstrated good agreement with experimental results in two-dimensional FE chip forming simulations of orthogonal cutting processes, evaluated by means of cutting force, passive force, and contact length prediction. This work presents a proof of concept for a physics-based approach to calibrate constitutive models in metal cutting, potentially advancing the use of multiscale and multiphysical simulations in machining.Graphical abstract

Mechanism of activation and autophosphorylation of a histidine kinase

Histidine kinases (HK) are one of the main prokaryotic signaling systems. Two structurally conserved catalytic domains inside the HK enable autokinase, phosphotransfer, and phosphatase activities. Here, we focus on a detailed mechanistic understanding of the functional cycle of the WalK HK by a multi-scale simulation approach, consisting of classical as well as hybrid QM/MM molecular dynamics simulation. Strikingly, a conformational transition induced solely in DHp leads to the correct activated conformation in CA crucial for autophosphorylation. This finding explains how variable sensor domains induce the transition from inactive to active state. The subsequent autophosphorylation inside DHp proceeds via a penta-coordinated transition state to a protonated phosphohistidine intermediate. This intermediate is consequently deprotonated by a suitable nearby base. The reaction energetics are controlled by the final proton acceptor and presence of a magnesium cation. The slow rates of the process result from the high energy barrier of the conformational transition between inactive and active states. The phosphorylation step exhibits a lower barrier and down-the-hill energetics. Thus, our work suggests a detailed mechanistic model for HK autophosphorylation.

Reproducing vortex-induced vibrations of rooftop twin-mast by multi-scale coupled simulation of urban wind fields

The Shenzhen Electronics Group (SEG) Plaza in Shenzhen, China, experienced visible vibrations attributed to significant vortex-induced vibrations of the large spacing twin-mast atop the building. The vibration event occurred under complex urban wind environments. In order to reproduce wind fields around SEG Plaza, a multiscale simulation was carried out by integrating the Weather Research and Forecasting (WRF) and Computational Fluid Dynamics (CFD) models. The aerodynamic characteristics and wake modes of twin-mast are investigated by a downscale CFD simulation in detail. Finally, vortex-induced vibration (VIV) of twin-mast was analyzed considering fluid-structure interaction. This work reveals that wind conditions during the SEG Plaza vibration incident were appropriate for the VIV occurrence of twin-mast, and the results of VIV simulation agree well with the field monitoring results by computer vision identification. This study effectively reproduces the full pictures of VIVs of the rooftop twin-mast during this rare event, offering a critical view for the analysis of this event.

Dual-Vacancy-Engineered ZnIn2S4 Nanosheets for Harnessing Low-Frequency Vibration Induced Piezoelectric Polarization Coupled with Static Dipole Field to Enhance Photocatalytic H2 Evolution.

This study investigates the impact of In- and S-vacancy concentrations on the photocatalytic activity of non-centrosymmetric zinc indium sulfide (ZIS) nanosheets for the hydrogen evolution reaction (HER). A positive correlation between the concentrations of dual In and S vacancies and the photocatalytic HER rate over ZIS nanosheets is observed. The piezoelectric polarization, stimulated by low-frequency vortex vibration to ensure the well-dispersion of ZIS nanosheets in solution, plays a crucial role in enhancing photocatalytic HER over the dual-vacancy engineered ZIS nanosheets. The piezoelectric characteristic of the defective ZIS nanosheets is confirmed through the piezopotential response measured using piezoelectric force microscopy. Piezophotocatalytic H2 evolution over the ZIS nanosheets is boosted under accelerated vortex vibrations. The research explores how vacancies alter ZIS's dipole moment and piezoelectric properties, thereby increasing electric potential gradient and improving charge-separation efficiency, through multi-scale simulations, including Density Functional Theory and Finite Element Analysis, and a machine-learning interatomic potential for defect identification. Increased In and S vacancies lead to higher electric potential gradients in ZIS along [100] and [010] directions, attributing to dipole moment and the piezoelectric effect. This research provides a comprehensive exploration of vacancy engineering in ZIS nanosheets, leveraging the piezopotential and dipole field to enhance photocatalytic performances.

Designed Spin-Texture-Lattice to Control Anisotropic Magnon Transport in Antiferromagnets.

Spin waves in magnetic materials are promising information carriers for future computing technologies due to their ultra-low energy dissipation and long coherence length. Antiferromagnets are strong candidate materials due, in part, to their stability to external fields and larger group velocities. Multiferroic antiferromagnets, such as BiFeO3 (BFO), have an additional degree of freedom stemming from magnetoelectric coupling, allowing for control of the magnetic structure, and thus spin waves, with the electric field. Unfortunately, spin-wave propagation in BFO is not well understood due to the complexity of the magnetic structure. In this work, long-range spin transport is explored within an epitaxially engineered, electrically tunable, 1D magnonic crystal. A striking anisotropy is discovered in the spin transport parallel and perpendicular to the 1D crystal axis. Multiscale theory and simulation suggest that this preferential magnon conduction emerges from a combination of a population imbalance in its dispersion, as well as anisotropic structural scattering. This work provides a pathway to electrically reconfigurable magnonic crystals inantiferromagnets.