arXiv subjects

Bohayra Mortazavi

Publications and source records attributed to Bohayra Mortazavi.

At least 37 records · Page 2Linked to original sources

arXiv2021

Ultrahigh thermal conductivity and strength in direct-gap semiconducting graphene-like BC6N: A first-principles and classical investigation

In recent years, graphene-like boron carbide and carbon nitride nanosheets have attracted remarkable attentions, owing to their semiconducting electronic nature and outstanding mechanical and heat transport properties. Graphene-like BC6N is an experimentally realized layered material and most recently has been the focus of numerous theoretical studies. Interestingly, the most stable form of BC6N monolayer remains unexplored and limited information are known concerning its intrinsic physical properties. Herein, on the basis of density functional theory (DFT) calculations we confirm that the most stable form of BC6N nanosheet shows a rectangular unitcell, in accordance with an overlooked experimental finding. We found that BC6N monolayer is a semiconductor with 1.19 eV direct gap and yields anisotropic and excellent absorption of visible light. First-principles results highlight that BC6N nanosheet exhibits anisotropic and ultrahigh tensile strength and lattice thermal conductivity, outperforming all other fabricated 2D semiconductors. We moreover develop classical molecular dynamic models for the evaluation of heat transport and mechanical properties of BC6N nanomembranes. The presented results in this work not only shed light on the most stable configuration of BC6N nanosheet, but also confirm its outstandingly appealing electronic, optical, heat conduction and mechanical properties, extremely motivating for further theoretical and experimental endeavors.

cond-mat.mtrl-sci↗

arXiv2021

High tensile strength and thermal conductivity in BeO monolayer: A first-principles study

In a latest experimental advance, graphene-like and insulating BeO monolayer was successfully grown over silver surface by molecular beam epitaxy (ACS Nano 15(2021), 2497). Inspired by this accomplishment, in this work we conduct first-principles based simulations to explore the electronic, mechanical properties and thermal conductivity of graphene-like BeO, MgO and CaO monolayers. The considered nanosheets are found to show desirable thermal and dynamical stability. BeO monolayer is found to show remarkably high elastic modulus and tensile strength of 408 and 53.3 GPa, respectively. The electronic band gap of BeO, MgO and CaO monolayers are predicted to be 6.72, 4.79, and 3.80 eV, respectively, using the HSE06 functional. On the basis of iterative solutions of the Boltzmann transport equation, the room temperature lattice thermal conductivity of BeO, MgO and CaO monolayers are predicted to be 385, 64 and 15 W/mK, respectively. Our results reveal substantial decline in the electronic band gap, mechanical strength and thermal conductivity by increasing the weight of metal atoms. This work highlights outstandingly high thermal conductivity, carrier mobility and mechanical strength of insulating BeO nanosheets and suggest them as promising candidates to design strong and insulating components with high thermal conductivities.

cond-mat.mtrl-sci↗

arXiv2021

Ultrahigh stiffness and anisotropic Dirac cones in BeN4 and MgN4 monolayers: A first-principles study

Beryllium polynitrides, BeN4 is a novel layered material, which has been most recently fabricated under high pressure (Phys. Rev. Lett. 126(2021), 175501). As a new class of 2D materials, in this work we conduct first-principles calculations to examine the stability and explore the electronic nature of MN4 (M= Be, Mg, Ir, Rh, Ni, Cu, Au, Pd, Pt) monolayers. Acquired results confirm the dynamical and thermal stability of BeN4, MgN4, IrN4, PtN4 and RhN4 monolayers. Interestingly, BeN4 and MgN4 monolayers are found to show anisotropic Dirac cones in their electronic structure. While PtN4 monolayer is predicted to be a narrow band-gap semiconductor, IrN4 and RhN4 monolayers are found to be metallic systems. We also elaborately explore the effects of number of atomic layers on the electronic features of BeN4 nanosheets, which reveal highly appealing physics. Our results highlight that BeN4 nanosheet yield ultrahigh elastic modulus and mechanical strength, outperforming all other carbon-free 2D materials. Notably, RhN4 nanosheet is predicted to yield high capacities of 562, 450 and 900 mAh/g, for Li, Na and Ca ions storages, respectively. This study provides a comprehensive understanding on the intrinsic properties of MN4 nanosheets and highlight their outstanding physics.

cond-mat.mtrl-sci↗

arXiv2021

Ultrahigh carrier mobility, Dirac cone and high stretchability in pyrenyl and pyrazinoquinoxaline graphdiyne/graphyne nanosheets confirmed by first-principles

Graphdiyne nanomaterials are low density and highly porous carbon-based two-dimensional (2D) materials, with outstanding application prospects for electronic and energy storage/conversion systems. In two latest scientific advances, large-area pyrenyl graphdiyne (Pyr-GDY) and pyrazinoquinoxaline graphdiyne (PQ-GDY) nanosheets have been successfully fabricated. As the first theoretical study, herein we conduct first-principles simulations to explore the stability and electronic, optical and mechanical properties of Pyr-GDY, N-Pyr-GDY, PQ-GDY and N-Pyr-GYN monolayers. We particularly examine the intrinsic properties of PQ-graphyne (PQ-GYN) and Pyr-graphyne (Pyr-GYN) monolayers. Acquired results confirm desirable dynamical and thermal stability and high mechanical strength of these novel nanosheets, owing to their strong covalent networks. We show that Pyr-based lattices can show high stretchability. Analysis of optical results also confirm the suitability of Pyr- and PQ-GDY/GYN nanosheets to adsorb in the near-IR, visible, and UV range of light. Notably, PQ-GDY is found to exhibit distorted Dirac cone and highly anisotropic fermi velocities. First-principles results reveal ultrahigh carrier mobilities along the considered nanoporous nanomembranes, particularly PQ-GYN monolayer is predicted to outperform phosphorene and MoS2. Acquired results introduce pyrenyl and pyrazinoquinoxaline graphyne/graphyne as promising candidates to design novel nanoelectronics and energy storage/conversion systems.

cond-mat.mtrl-sci↗

arXiv2021

Machine learning assisted multiscale modeling of composite phase change materials for Li-ion batteries thermal management

In this work, we develop a combined convolutional neural networks (CNNs) and finite element method (FEM) to examine the effective thermal properties of composite phase change materials (CPCMs) consisting of paraffin and copper foam. In this approach, first the CPCM microstructures are modeled using FEM and next the image dataset with corresponding thermal properties is created. The image dataset is subsequently used to train and test the CNN performance, which is then compared with the performance of a popular network architecture for image classification tasks. The predicted thermal properties are employed to define the properties of the CPCM material of a battery pack. The heat generation and electrochemical response of a Li-ion cell during the charging/discharging is simulated by applying Newman battery model. Thermal management is achieved by the latent heat of paraffin, with copper foam for enhancing the thermal conductivity. The multiscale model is finally developed using FEM to investigate the effectiveness of the thermal management of the battery pack. In these models the thermal properties estimated by the FEM and the CNN are employed to define the CPCM materials properties of a battery pack. Our results confirm that the model developed on the basis of a CNN can evaluate the effectiveness of the battery packs thermal management system with an excellent accuracy in comparison with the original FEM models.

physics.comp-ph↗

arXiv2020

Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles

Chemical vapor deposition has been most recently employed to fabricate centimeter-scale high-quality single-layer MoSi2N4 (Science; 2020;369; 670). Motivated by this exciting experimental advance, herein we conduct extensive first-principles based simulations to explore the stability, mechanical properties, lattice thermal conductivity, piezoelectric and flexoelectric response, and photocatalytic and electronic features of MA2Z4 (M = Cr, Mo, W; A = Si, Ge; Z = N, P) monolayers. The considered nanosheets are found to exhibit dynamical stability and remarkably high mechanical properties. Moreover, they show diverse electronic properties from antiferromagnetic metal to half metal and to semiconductors with band gaps ranging from 0.31 to 2.57 eV. Among the studied nanosheets, the MoSi2N4 and WSi2N4 monolayers yield appropriate band edge positions, high electron and hole mobilities, and strong visible light absorption, highly promising for applications in optoelectronics and photocatalytic water splitting. The MoSi2N4 and WSi2N4 monolayers are also predicted to show outstandingly high lattice thermal conductivity of 440 and 500 W/mK, respectively. For the first time we show that machine learning interatomic potentials trained over small supercells can be employed to examine the flexoelectric and piezoelectric properties of complex structures. As the most exciting finding, WSi2N4, CrSi2N4 and MoSi2N4 are found to exhibit the highest piezoelectric coefficients, outperforming all other-known 2D materials. Our results highlight that MA2Z4 nanosheets not only undoubtedly outperform the transition metal dichalcogenides family but also can compete with graphene for applications in nanoelectronics, optoelectronic, energy storage/conversion and thermal management systems.

cond-mat.mtrl-sci↗

arXiv2020

Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

Accurate evaluation of the thermal conductivity of a material can be a challenging task from both experimental and theoretical points of view. In particular for the nanostructured materials, the experimental measurement of thermal conductivity is associated with diverse sources of uncertainty. As a viable alternative to experiment, the combination of density functional theory (DFT) simulations and the solution of Boltzmann transport equation is currently considered as the most trusted approach to examine thermal conductivity. The main bottleneck of the aforementioned method is to acquire the anharmonic interatomic force constants using the computationally demanding DFT calculations. In this work we propose a substantially accelerated approach for the evaluation of anharmonic interatomic force constants via employing machine-learning interatomic potentials (MLIPs) trained over short ab-initio molecular dynamics trajectories. The remarkable accuracy of the proposed accelerated method is confirmed by comparing the estimated thermal conductivities of several bulk and two-dimensional materials with those computed by the full-DFT approach. The MLIP-based method proposed in this study can be employed as a standard tool, which would substantially accelerate and facilitate the estimation of lattice thermal conductivity in comparison with the commonly used full-DFT solution.

cond-mat.mtrl-sci↗

arXiv2020

Machine-Learning Interatomic Potentials Enable First-Principles Multiscale Modeling of Lattice Thermal Conductivity in Graphene/Borophene Heterostructures

One of the ultimate goals of computational modeling in condensed matter is to be able to accurately compute materials properties with minimal empirical information. First-principles approaches such as the density functional theory (DFT) provide the best possible accuracy on electronic properties but they are limited to systems up to a few hundreds, or at most thousands of atoms. On the other hand, classical molecular dynamics (CMD) simulations and finite element method (FEM) are extensively employed to study larger and more realistic systems, but conversely depend on empirical information. Here, we show that machine-learning interatomic potentials (MLIPs) trained over short ab-initio molecular dynamics trajectories enable first-principles multiscale modeling, in which DFT simulations can be hierarchically bridged to efficiently simulate macroscopic structures. As a case study, we analyze the lattice thermal conductivity of coplanar graphene/borophene heterostructures, recently synthesized experimentally (Sci. Adv. 2019; 5: eaax6444), for which no viable classical modeling alternative is presently available. Our MLIP-based approach can efficiently predict the lattice thermal conductivity of graphene and borophene pristine phases, the thermal conductance of complex graphene/borophene interfaces and subsequently enable the study of effective thermal transport along the heterostructures at continuum level. This work highlights that MLIPs can be effectively and conveniently employed to enable first-principles multiscale modeling via hierarchical employment of DFT/CMD/FEM simulations, thus expanding the capability for computational design of novel nanostructures.

cond-mat.mtrl-sci↗

arXiv2020

High thermal conductivity in semiconducting Janus and non-Janus diamanes

Most recently, F-diamane monolayer was experimentally realized by the fluorination of bilayer graphene. In this work we elaborately explore the electronic and thermal conductivity responses of diamane lattices with homo or hetero functional groups, including: non-Janus C2H, C2F and C2Cl diamane and Janus counterparts of C4HF, C4HCl and C4FCl. Noticeably, C2H, C2F, C2Cl, C4HF, C4HCl and C4FCl diamanes are found to show electronic diverse band gaps of, 3.86, 5.68, 2.42, 4.17, 0.86, and 2.05 eV, on the basis of HSE06 method estimations. The thermal conductivity of diamane nanosheets was acquired using the full iterative solutions of the Boltzmann transport equation, with substantially accelerated calculations by employing machine-learning interatomic potentials in obtaining the anharmonic force constants. According to our results, the room temperature lattice thermal conductivity of graphene and C2H, C2F, C2Cl, C4HF, C4HCl and C4FCl diamane monolayers are estimated to be 3636, 1145, 377, 146, 454, 244 and 196 W/mK, respectively. The underlying mechanisms resulting in significant effects of functional groups on the thermal conductivity of diamane nanosheets were thoroughly explored. Our results highlight the substantial role of functional groups on the electronic and thermal conduction responses of diamane nanosheets.

cond-mat.mtrl-sci↗

arXiv2020

Nanoporous C3N4, C3N5 and C3N6 nanosheets; Novel strong semiconductors with low thermal conductivities and appealing optical/electronic properties

Carbon nitride two-dimensional (2D) materials are among the most attractive class of nanomaterials, with wide range of application prospects. As a continuous progress, most recently, two novel carbon nitride 2D lattices of C3N5 and C3N4 have been successfully experimentally realized. Motivated by these latest accomplishments and also by taking into account the well-known C3N4 triazine-based graphitic carbon nitride structures, we predicted two novel C3N6 and C3N4 counterparts. We then conducted extensive density functional theory simulations to explore the thermal stability, mechanical, electronic and optical properties of these novel nanoporous carbon-nitride nanosheets. According to our results all studied nanosheets were found to exhibit desirable thermal stability and mechanical properties. Non-equilibrium molecular dynamics simulations on the basis of machine learning interatomic potentials predict ultralow thermal conductivities for these novel nanosheets. Electronic structure analyses confirm direct band gap semiconducting electronic character and optical calculations reveal the ability of these novel 2D systems to adsorb visible range of light. Extensive first-principles based results by this study provide a comprehensive vision on the stability, mechanical, electronic and optical responses of C3N4, C3N5 and C3N6 as novel 2D semiconductors and suggest them as promising candidates for the design of advanced nanoelectronics and energy storage/conversion systems.

physics.comp-ph↗

arXiv2020

Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials

Phononic properties are commonly studied by calculating force constants using the density functional theory (DFT) simulations. Although DFT simulations offer accurate estimations of phonon dispersion relations or thermal properties, but for low-symmetry and nanoporous structures the computational cost quickly becomes very demanding. Moreover, the computational setups may yield nonphysical imaginary frequencies in the phonon dispersion curves, impeding the assessment of phononic properties and the dynamical stability of the considered system. Here, we compute phonon dispersion relations and examine the dynamical stability of a large ensemble of novel materials and compositions. We propose a fast and convenient alternative to DFT simulations which derived from machine-learning interatomic potentials passively trained over computationally efficient ab-initio molecular dynamics trajectories. Our results for diverse two-dimensional (2D) nanomaterials confirm that the proposed computational strategy can reproduce fundamental thermal properties in close agreement with those obtained via the DFT approach. The presented method offers a stable, efficient, and convenient solution for the examination of dynamical stability and exploring the phononic properties of low-symmetry and porous 2D materials.

cond-mat.mtrl-sci↗

arXiv2020

As2S3, As2Se3 and As2Te3 nanosheets: Superstretchable semiconductors with anisotropic carrier mobilities and optical properties

In this work, density functional theory calculations were carried out to explore the mechanical response, dynamical/thermal stability, electronic/optical properties and photocatalytic features of monoclinic As2X3 (X=S, Se and Te) nanosheets. Acquired phonon dispersions and ab-initio molecular dynamics results confirm the stability of studied nanomembranes. Observation of relatively weak interlayer interactions suggests that the exfoliation techniques can be potentially employed to fabricate nanomembranes from their bulk counterparts. The studied nanosheets were found to show highly anisotropic mechanical properties. Notably, new As2Te3 2D lattice predicted by this study is found to exhibit unique superstretchability, which outperforms other 2D materials. In addition, our results on the basis of HSE06 functional reveal the indirect semiconducting electronic nature for the monolayer to few-layer and bulk structures of As2X3, in which a moderate decreasing trend in the band-gap by increasing the thickness can be established. The studied nanomaterials were found to show remarkably high and anisotropic carrier mobilities. Moreover, optical results show that these nanosheets can absorb the visible light. In particular, the valence and conduction band edge positions, high carrier mobilities and optical responses of As2Se3 nanosheets were found to be highly desirable for the solar water splitting. The comprehensive vision provided by this study not only confirm the stability and highly attractive electronic and optical characteristics of As2S3, As2Se3 and As2Te3 nanosheets, but also offer new possibilities to design superstretchable nanodevices.

physics.comp-ph↗

arXiv2019

Aromatic molecular junctions between graphene sheets: a molecular dynamics screening for enhanced thermal conductance

The proper design and synthesis of molecular junctions for the purpose of establishing percolative networks of conductive nanoparticles represent an opportunity to develop more efficient thermally-conductive nanocomposites, with several potential applications in heat management. In this work, theoretical classical molecular dynamics simulations were conducted to design and evaluate thermal conductance of various molecules serving as thermal bridges between graphene nanosheets. A wide range of molecular junctions was studied, with a focus on the chemical structures that are viable to synthesize at laboratory scale. Thermal conductances were correlated with the length and mechanical stiffness of the chemical junctions. The simulated tensile deformation of the molecular junction revealed that the mechanical response is very sensitive to small differences in the chemical structure. The analysis of the vibrational density of states provided insights into the interfacial vibrational properties. A knowledgedriven design of the molecular junction structures is proposed, aiming at controlling interfacial thermal transport in nanomaterials. This approach may allow for the design of more efficient heat management in nanodevices, including flexible heat spreaders, bulk heat exchangers and heat storage devices.

physics.app-ph↗

arXiv2019

Prediction of C7N6 and C9N4: Stable and strong porous carbon-nitride nanosheets with attractive electronic and optical properties

In this work, three novel porous carbon-nitride nanosheets with C7N6, C9N4 and C10N3 stoichiometries are predicted. First-principles simulations were accordingly employed to evaluate stability and explore the mechanical, electronic and optical properties. Phonon dispersions confirm the dynamical stability of all predicted nanosheets. Nonetheless, ab-initio molecular dynamics results indicate that only C7N6 and C9N4 are thermally stable. C7N6, C9N4 and C10N3 nanosheets were predicted to exhibit high elastic modulus of 212, 202 and 208 N/m and maximum tensile strengths of 14.1, 22.4 and 15.8 N/m, respectively. C7N6 monolayer was confirmed to be a direct band-gap semiconductor, with a 2.25 eV gap according to the HSE06 method estimation. Interestingly, C9N4 and C10N3 monolayers show metallic character. The first absorption peaks of optical spectra reveal that C7N6 nanosheet can absorb the visible light, whereas C9N4 and C10N3 monolayers can absorb the Infrared range of light. Moreover, the absorption coefficient and optical conductivity of predicted nanosheets in the visible range of light are larger than those of the graphene. The results provided by this study confirm the stability and highlight very promising properties of C7N6 and C9N4 nanosheets, which may serve as promising candidates for numerous advanced technologies.

physics.comp-ph↗

arXiv2019

Outstanding strength, optical characteristics and thermal conductivity of graphene-like BC$_3$ and BC$_6$N semiconductors

Carbon based two-dimensional (2D) materials with honeycomb lattices, like graphene, polyaniline carbon-nitride (C$_3$N) and boron-carbide (BC$_3$) exhibit exceptional physical properties. On this basis, we propose two novel graphene-like materials with BC$_6$N stoichiometry. We conducted first-principles calculations to explore the stability, mechanical response, electronic, optical and thermal transport characteristics of graphene-like BC$_3$ and BC$_6$N monolayers. The absence of imaginary frequencies in the phonon dispersions confirm dynamical stability of BC$_3$ and BC$_6$N monolayers. Our first principles results reveal that BC$_3$ and BC$_6$N present high elastic moduli of 256 and 305 N/m, and tensile strengths of 29.0 and 33.4 N/m, with room temperature lattice thermal conductivities of 410 and 1710 W/m.K, respectively. Notably, the thermal conductivity of BC$_6$N is one of the highest among all 2D materials. According to electronic structure calculations, monolayers of BC$_3$ and BC$_6$N are indirect and direct bandgap semiconductors, respectively. The optical analysis illustrate that the first absorption peaks along the in-plane polarization for single-layer BC$_3$ and BC$_6$N occur in the visible range of the electromagnetic spectrum. Our results reveal outstandingly high mechanical properties and thermal conductivity along with attractive electronic and optical features of BC$_3$ and BC$_6$N nanosheets and present them as promising candidates to design novel nanodevices.

cond-mat.mtrl-sci↗

arXiv2019

Theoretical realization of two-dimensional M3(C6X6)2(M= Co, Cr, Cu, Fe, Mn, Ni, Pd, Rh and X= O, S, Se) metal-organic frameworks

Most recently, Cu-hexahydroxybenzene MOF was for the time experimentally realized, through a kinetically controlled approach. Cu-HHB belongs to the family of conductive MOFs with a chemical formula of M3(C6X6)2(X=NH, O, S). Motivated by the recent experimental advance in the fabrication of Cu-HHB, we conducted extensive first-principles simulations to explore the thermal stability, mechanical properties and electronic characteristics of M3(C6X6)2(M= Co, Cr, Cu, Fe, Mn, Ni, Pd, Rh and X= O, S, Se) monolayers. First-principles results confirm that all considered 2D porous lattices are thermally stable at high temperatures over 1500 K. It was moreover found that these novel 2D structures can exhibit linear elasticity with considerable tensile strengths, revealing their suitability for practical applications in nanodevices.Depending on the metal and chalcogen atoms in M3(C6X6)2 monolayers, they can yield various electronic and magnetic properties, such as; magnetic semiconducting, perfect half metallic, magnetic and nonmagnetic metallic behaviours. This work highlights the outstanding physics of M3(C6X6)2 2D porous lattices and will hopefully help to expand this conductive MOF family, as promising candidates to design advanced energy storage/conversion, electronics and spintronics systems.

cond-mat.mes-hall↗

arXiv2019

Nanoporous graphene: a 2D semiconductor with anisotropic mechanical, optical and thermal conduction properties

Nanoporous graphene (NPG), consisting of ordered arrays of nanopores separated by graphene nanoribbons was recently realized using a bottom-up synthesis method (Science 360(2018), 199). In this work we accordingly explored the mechanical response, thermal conductivity and electronic/optical properties of single-layer NPG using the density functional theory and molecular dynamics simulations. Along the armchair direction, NPG was found to exhibit higher tensile strength and thermal conductivity by factors of 1.6 and 2.3, respectively, in comparison with the zigzag direction. Despite of showing high rigidity and tensile strength, NPG was predicted to show around two orders of magnitude suppressed thermal conductivity than graphene. Results based on GGA/PBE highlight that NPG monolayer presents semiconducting electronic character with a direct band-gap of 0.68 eV. According to the HSE06 estimation, NPG monolayer shows a band-gap of 0.88 eV, very promising for the application in nanoelectronics. Optical results reveal that NPG nanomembranes can absorb the visible, IR and NIR light. This work highlights the outstanding physics of NPG, as a novel porous carbon based two-dimensional material, which may serve as a promising candidate to design advanced nanoelectronics, nanooptics and energy conversion systems.

cond-mat.mes-hall↗

arXiv2019

Thermal bridging of graphene nanosheets via covalent molecular junctions. a Non-Equilibrium Green Functions Density Functional Tight-Binding study

Despite the uniquely high thermal conductivity of graphene is well known, the exploitation of graphene into thermally conductive nanomaterials and devices is limited by the inefficiency of thermal contacts between the individual nanosheets. A fascinating yet experimentally challenging route to enhance thermal conductance at contacts between graphene nanosheets is through molecular junctions, allowing covalently connecting nanosheets otherwise interacting only via weak Van der Waals forces. Beside the bare existence of covalent connections, the choice of molecular structures to be used as thermal junctions should be guided by their vibrational properties, in terms of phonon transfer through the molecular junction. In this paper, density functional tight-binding combined with Green functions formalism was applied for the calculation of thermal conductance and phonon spectra of several different aliphatic and aromatic molecular junctions between graphene nanosheets. Effect of molecular junction length, conformation, and aromaticity were studied in detail and correlated with phonon tunnelling spectra. The theoretical insight provided by this work can guide future experimental studies to select suitable molecular junctions in order to enhance the thermal transport by suppressing the interfacial thermal resistances, particularly attractive for various systems, including graphene nanopapers and graphene polymer nanocomposites, as well as related devices. In a broader view, the possibility to design molecular junctions to control phonon transport currently appears as an efficient way to produce phononic devices and controlling heat management in nanostructures.

cond-mat.mes-hall↗