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  1. AU="Timon Rabczuk"
  2. AU="Bergenfeld, Irina"
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  1. Article ; Online: Special Issue “Computational Methods for Fracture”

    Timon Rabczuk

    Applied Sciences, Vol 9, Iss 17, p

    2019  Volume 3455

    Abstract: The prediction of fracture and material failure is of major importance for the safety and reliability of engineering structures and the efficient design of novel materials [.] ...

    Abstract The prediction of fracture and material failure is of major importance for the safety and reliability of engineering structures and the efficient design of novel materials [.]
    Keywords n/a ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Language English
    Publishing date 2019-08-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Computational Methods for Fracture in Brittle and Quasi-Brittle Solids

    Timon Rabczuk

    ISRN Applied Mathematics, Vol

    State-of-the-Art Review and Future Perspectives

    2013  Volume 2013

    Keywords Mathematics ; QA1-939 ; Science ; Q ; DOAJ:Mathematics ; DOAJ:Mathematics and Statistics
    Language English
    Publishing date 2013-01-01T00:00:00Z
    Publisher Hindawi Publishing Corporation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Theoretical Prediction of P-Triphenylene-Graphdiyne as an Excellent Anode Material for Li, Na, K, Mg, and Ca Batteries

    Mohammad Salavati / Naif Alajlan / Timon Rabczuk

    Applied Sciences, Vol 11, Iss 5, p

    2021  Volume 2308

    Abstract: The efficient performance of metal-ion batteries strongly depends on electrode materials characteristics. Two-dimensional (2D) materials are among promising electrode materials for metal-ion battery cells, owing to their excellent structural and ... ...

    Abstract The efficient performance of metal-ion batteries strongly depends on electrode materials characteristics. Two-dimensional (2D) materials are among promising electrode materials for metal-ion battery cells, owing to their excellent structural and electronic properties. Two-dimensional graphdiyne has been recently fabricated and revealed unique storage capacities and fast charging rates. The current study explores the performance of the novel phosphorated-triphenylene graphdiyne (P-TpG) monolayer as an anode material for Li-, Na-, K-, Mg-, and Ca-ions storage via extensive density functional theory (DFT) simulations. Our results reveal that the stable structure of P-TpG monolayers delivers ultra-high storage capacities of ~2148, ~1696, ~1017, and ~2035 mA·h·g −1 for Li-, Na-, K-, and Ca- ions, respectively. Notably, the metallic electronic behavior is illustrated by adsorbing metal-ions on the P-TpG nanosheets, suggesting a good electronic conductivity. The NEB results demonstrate that P-TpG can serve as an outstanding candidate for the optimal charging/discharging process. This theoretical study suggests P-TpG nanosheets as a highly promising candidate for the design of advanced metal-ion batteries with remarkable charge capacities and optimal charging/discharging rates.
    Keywords phosphorated triphenylene-graphdiyne ; first principles ; metal-ions batteries ; 2D anode materials ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 540
    Language English
    Publishing date 2021-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Frequency Characteristics of Multiscale Hybrid Nanocomposite Annular Plate Based on a Halpin–Tsai Homogenization Model with the Aid of GDQM

    Mehran Safarpour / Alireza Rahimi / Omid Noormohammadi Arani / Timon Rabczuk

    Applied Sciences, Vol 10, Iss 4, p

    2020  Volume 1412

    Abstract: In this article, we study the vibration performance of multiscale hybrid nanocomposite (MHC) annular plates (MHCAP) resting on Winkler−Pasternak substrates exposed to nonlinear temperature gradients. The matrix material is reinforced with carbon ... ...

    Abstract In this article, we study the vibration performance of multiscale hybrid nanocomposite (MHC) annular plates (MHCAP) resting on Winkler−Pasternak substrates exposed to nonlinear temperature gradients. The matrix material is reinforced with carbon nanotubes (CNTs) or carbon fibers (CF) at the nano- or macroscale, respectively. The annular plate is modeled based on higher-order shear deformation theory (HSDT). We present a modified Halpin−Tsai model to predict the effective properties of the MHCAP. Hamilton’s principle was employed to establish the governing equations of motion, which is finally solved by the generalized differential quadrature method (GDQM). In order to validate the approach, numerical results were compared with available results from the literature. Subsequently, a comprehensive parameter study was carried out to quantify the influence of different parameters such as stiffness of the substrate, patterns of temperature increase, outer temperature, volume fraction and orientation angle of the CFs, weight fraction and distribution patterns of CNTs, outer radius to inner radius ratio, and inner radius to thickness ratio on the response of the plate. The results show that applying a sinusoidal temperature rise and locating more CNTs in the vicinity of the bottom surface yielded the highest natural frequency.
    Keywords higher-order shear deformation theory ; nonlinear temperature gradient ; vibration ; annular plate ; multiscale hybrid nanocomposite ; halpin–tsai homogenization model ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 621
    Language English
    Publishing date 2020-02-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: A Multiscale Investigation on the Thermal Transport in Polydimethylsiloxane Nanocomposites

    Alessandro Di Pierro / Bohayra Mortazavi / Hamidreza Noori / Timon Rabczuk / Alberto Fina

    Nanomaterials, Vol 11, Iss 1252, p

    Graphene vs. Borophene

    2021  Volume 1252

    Abstract: Graphene and borophene are highly attractive two-dimensional materials with outstanding physical properties. In this study we employed combined atomistic continuum multi-scale modeling to explore the effective thermal conductivity of polymer ... ...

    Abstract Graphene and borophene are highly attractive two-dimensional materials with outstanding physical properties. In this study we employed combined atomistic continuum multi-scale modeling to explore the effective thermal conductivity of polymer nanocomposites made of polydimethylsiloxane (PDMS) polymer as the matrix and graphene and borophene as nanofillers. PDMS is a versatile polymer due to its chemical inertia, flexibility and a wide range of properties that can be tuned during synthesis. We first conducted classical Molecular Dynamics (MD) simulations to calculate the thermal conductance at the interfaces between graphene and PDMS and between borophene and PDMS. Acquired results confirm that the interfacial thermal conductance between nanosheets and polymer increases from the single-layer to multilayered nanosheets and finally converges, in the case of graphene, to about 30 MWm −2 K −1 and, for borophene, up to 33 MWm −2 K −1 . The data provided by the atomistic simulations were then used in the Finite Element Method (FEM) simulations to evaluate the effective thermal conductivity of polymer nanocomposites at the continuum level. We explored the effects of nanofiller type, volume content, geometry aspect ratio and thickness on the nanocomposite effective thermal conductivity. As a very interesting finding, we found that borophene nanosheets, despite having almost two orders of magnitude lower thermal conductivity than graphene, can yield very close enhancement in the effective thermal conductivity in comparison with graphene, particularly for low volume content and small aspect ratios and thicknesses. We conclude that, for the polymer-based nanocomposites, significant improvement in the thermal conductivity can be reached by improving the bonding between the fillers and polymer, or in other words, by enhancing the thermal conductance at the interface. By taking into account the high electrical conductivity of borophene, our results suggest borophene nanosheets as promising nanofillers to simultaneously enhance ...
    Keywords borophene ; graphene ; polydimethylsiloxane ; interfacial thermal conductance ; thermal conductivity ; nanocomposites ; Chemistry ; QD1-999
    Subject code 600 ; 621
    Language English
    Publishing date 2021-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Modeling neuron growth using isogeometric collocation based phase field method

    Kuanren Qian / Aishwarya Pawar / Ashlee Liao / Cosmin Anitescu / Victoria Webster-Wood / Adam W. Feinberg / Timon Rabczuk / Yongjie Jessica Zhang

    Scientific Reports, Vol 12, Iss 1, Pp 1-

    2022  Volume 10

    Abstract: Abstract We present a new computational framework of neuron growth based on the phase field method and develop an open-source software package called “NeuronGrowth_IGAcollocation”. Neurons consist of a cell body, dendrites, and axons. Axons and dendrites ...

    Abstract Abstract We present a new computational framework of neuron growth based on the phase field method and develop an open-source software package called “NeuronGrowth_IGAcollocation”. Neurons consist of a cell body, dendrites, and axons. Axons and dendrites are long processes extending from the cell body and enabling information transfer to and from other neurons. There is high variation in neuron morphology based on their location and function, thus increasing the complexity in mathematical modeling of neuron growth. In this paper, we propose a novel phase field model with isogeometric collocation to simulate different stages of neuron growth by considering the effect of tubulin. The stages modeled include lamellipodia formation, initial neurite outgrowth, axon differentiation, and dendrite formation considering the effect of intracellular transport of tubulin on neurite outgrowth. Through comparison with experimental observations, we can demonstrate qualitatively and quantitatively similar reproduction of neuron morphologies at different stages of growth and allow extension towards the formation of neurite networks.
    Keywords Medicine ; R ; Science ; Q
    Subject code 612
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Multiscale modelling of heat conduction in all-MoS₂ single-layer heterostructures

    Mortazavi, Bohayra / Timon Rabczuk

    RSC advances. 2017 Feb. 10, v. 7, no. 18

    2017  

    Abstract: Successful isolation of atom thick molybdenum disulfide (MoS₂) films has opened promising routes toward its practical applications in nanoelectronics. Recently, experimental fabrication of single-layer MoS₂ membranes made from semiconducting (2H) and ... ...

    Abstract Successful isolation of atom thick molybdenum disulfide (MoS₂) films has opened promising routes toward its practical applications in nanoelectronics. Recently, experimental fabrication of single-layer MoS₂ membranes made from semiconducting (2H) and metallic (1T) phases was successfully accomplished in order to reach advanced MoS₂ heterostructures with tunable electronic properties. A comprehensive understanding of the heat conduction properties of these heterostructures plays a crucial role not only for the overheating concerns in nanoelectronics but also for the design of specific systems such as thermoelectric nanodevices. In this investigation, we accordingly explore the thermal conductivity along all-MoS₂ heterostructures by developing a combined atomistic-continuum multiscale model. In this approach, molecular dynamics simulations were employed to compute the thermal conductivity of pristine 2H and 1T phases and also the thermal contact conductance between 1T and 2H phases. Properties obtained from the atomistic simulations were finally used to construct macroscopic samples of MoS₂ heterostructures using the finite element method. Our investigation confirms the possibility of finely tuning the heat transport along MoS₂ heterostructures by controlling the domain size and the concentration of different phases. Findings from our multiscale model provide useful insight regarding the thermal conduction response of all-MoS₂ heterostructures.
    Keywords finite element analysis ; heat transfer ; molecular dynamics ; molybdenum disulfide ; simulation models ; thermal conductivity
    Language English
    Dates of publication 2017-0210
    Size p. 11135-11141.
    Publishing place The Royal Society of Chemistry
    Document type Article
    ISSN 2046-2069
    DOI 10.1039/c6ra26958c
    Database NAL-Catalogue (AGRICOLA)

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  8. Article ; Online: Efficient Deep Learning for Gradient-Enhanced Stress Dependent Damage Model

    Xiaoying Zhuang / L. C. Nguyen / Hung Nguyen-Xuan / Naif Alajlan / Timon Rabczuk

    Applied Sciences, Vol 10, Iss 2556, p

    2020  Volume 2556

    Abstract: This manuscript introduces a computational approach to micro-damage problems using deep learning for the prediction of loading deflection curves. The location of applied forces, dimensions of the specimen and material parameters are used as inputs of the ...

    Abstract This manuscript introduces a computational approach to micro-damage problems using deep learning for the prediction of loading deflection curves. The location of applied forces, dimensions of the specimen and material parameters are used as inputs of the process. The micro-damage is modelled with a gradient-enhanced damage model which ensures the well-posedness of the boundary value and yields mesh-independent results in computational methods such as FEM. We employ the Adam optimizer and Rectified linear unit activation function for training processes and research into the deep neural network architecture. The performance of our approach is demonstrated through some numerical examples including the three-point bending specimen, shear bending on L-shaped specimen and different failure mechanisms.
    Keywords deep neural network ; deep learning ; gradient enhanced damage ; stress-level dependent damage model ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 600
    Language English
    Publishing date 2020-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article: Boron–graphdiyne: a superstretchable semiconductor with low thermal conductivity and ultrahigh capacity for Li, Na and Ca ion storage

    Mortazavi, Bohayra / Masoud Shahrokhi / Xiaoying Zhuang / Timon Rabczuk

    Journal of materials chemistry. 2018 June 12, v. 6, no. 23

    2018  

    Abstract: Most recently, boron–graphdiyne, a π-conjugated two-dimensional (2D) structure made from a merely sp carbon skeleton connected with boron atoms was successfully experimentally realized through a bottom-up synthetic strategy. Motivated by this exciting ... ...

    Abstract Most recently, boron–graphdiyne, a π-conjugated two-dimensional (2D) structure made from a merely sp carbon skeleton connected with boron atoms was successfully experimentally realized through a bottom-up synthetic strategy. Motivated by this exciting experimental advance, we conducted density functional theory (DFT) and classical molecular dynamics simulations to study the mechanical, thermal conductivity and stability, electronic and optical properties of single-layer B-graphdiyne. We particularly analyzed the application of this novel 2D material as an anode for Li, Na, Mg and Ca ion storage. Uniaxial tensile simulation results reveal that B-graphdiyne owing to its porous structure and flexibility can yield superstretchability. The single-layer B-graphdiyne was found to exhibit a semiconducting electronic character, with a narrow band-gap of 1.15 eV based on the HSE06 prediction. It was confirmed that mechanical straining can be employed to further tune the optical absorbance and electronic band-gap of B-graphdiyne. Ab initio molecular dynamics results reveal that B-graphdiyne can withstand high temperatures, like 2500 K. The thermal conductivity of suspended single-layer B-graphdiyne was predicted to be very low, ∼2.5 W mK⁻¹ at room temperature. Our first-principles results reveal the outstanding prospect of B-graphdiyne as an anode material with ultrahigh charge capacities of 808 mA h g⁻¹, 5174 mA hg⁻¹ and 3557 mA h g⁻¹ for Na, Ca and Li ion storage, respectively. The comprehensive insight provided by this investigation highlights the outstanding physics of B-graphdiyne nanomembranes, and suggests them as highly promising candidates for the design of novel stretchable nanoelectronics and energy storage devices.
    Keywords absorbance ; ambient temperature ; anodes ; boron ; calcium ; carbon ; density functional theory ; energy ; lithium ; magnesium ; molecular dynamics ; nanosheets ; prediction ; semiconductors ; simulation models ; sodium ; thermal conductivity
    Language English
    Dates of publication 2018-0612
    Size p. 11022-11036.
    Publishing place The Royal Society of Chemistry
    Document type Article
    ZDB-ID 2702232-8
    ISSN 2050-7496 ; 2050-7488
    ISSN (online) 2050-7496
    ISSN 2050-7488
    DOI 10.1039/c8ta02627k
    Database NAL-Catalogue (AGRICOLA)

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  10. Article: Multiscale modeling of heat conduction in graphene laminates

    Mortazavi, Bohayra / Timon Rabczuk

    Carbon. 2015 Apr., v. 85

    2015  

    Abstract: We developed a combined atomistic-continuum hierarchical multiscale approach to explore the effective thermal conductivity of graphene laminates. To this aim, we first performed molecular dynamics simulations in order to study the heat conduction at ... ...

    Abstract We developed a combined atomistic-continuum hierarchical multiscale approach to explore the effective thermal conductivity of graphene laminates. To this aim, we first performed molecular dynamics simulations in order to study the heat conduction at atomistic level. Using the non-equilibrium molecular dynamics method, we evaluated the length dependent thermal conductivity of graphene as well as the thermal contact conductance between two individual graphene sheets. In the next step, based on the results provided by the molecular dynamics simulations, we constructed finite element models of graphene laminates to probe the effective thermal conductivity at macroscopic level. A similar methodology was also developed to study the thermal conductivity of laminates made from hexagonal boron-nitride (h-BN) films. In agreement with recent experimental observations, our multiscale modeling confirms that the flake size is the main factor that affects the thermal conductivity of graphene and h-BN laminates. Provided information by the proposed multiscale approach could be used to guide experimental studies to fabricate laminates with tunable thermal conduction properties.
    Keywords boron nitride ; finite element analysis ; graphene ; heat ; models ; molecular dynamics ; thermal conductivity
    Language English
    Dates of publication 2015-04
    Size p. 1-7.
    Publishing place Elsevier Ltd
    Document type Article
    ISSN 0008-6223
    DOI 10.1016/j.carbon.2014.12.046
    Database NAL-Catalogue (AGRICOLA)

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