Ali Ramazani

Since the direct dispersion of hydrophobic graphene nanosheets (GNS) in water without the assistance of dispersing agents such as polymeric or surfactant stabilizers are generally considered as an insurmountable challenge, current research aims to develop GNS using a green and solvent-free method. This method is an environmental eco-friendly approach and lets GNS get produced directly from graphite in simple conditions without using any toxic acids and reagents. This method is implemented at the shortest possible time without high temperatures and long synthesis times by using green and non-toxic citric acid as a cheap and eco-friendly intercalation agent at 100 °C without any need for any additional purification. This procedure is a promising route for the generation of stable GNS in water. In the second step, we utilized in-situ synthesis through a green method to develop graphene-MnO 2 nanocomposite by anchoring MnO 2 nanoflowers on graphene sheets. In this approach, there is no need for any additional purification or adding any materials or catalysis. The specific capacitance of 213 F g −1 was obtained for the graphene-MnO 2 nanocomposite at a scan rate of 10 mV s −1 .which makes it a great candidate for supercapacilator applications. In addition, the synthesized nanocomposite retained 90.25% of the initial capacitance after 500 cycles of charge–discharge at a current density of 40 A g −1. The work provides a new approach for synthesized GNS with the functional group without needing reduction agent and in situ anchored GNS with MnO 2 nanoflowers nanocomposite at a green and eco-friendly condition, suggesting GNS and its nanocomposite have potential uses in many different areas of research.

Dual-phase (DP) steel sheets have high potential for utilization as automotive structures due to their good combination of strength and ductility. As sheet metal forming processes induce complicated stress-strain states, determination of forming limit is vital, particularly using numerical approaches. This current study aims to examine the fracture behavior of DP600 steel sheets through several ductile fracture criteria in a wide range of stress states. For a better and more accurate understanding of the experimental tests, parallel numerical simulations were performed. First, the models were calibrated using the results of Nakazima tests, and then the fracture loci in principal strains, and equivalent strain-stress triaxiality spaces were predicted by each model. The capability of the criteria was verified through cross-die and bulge tests. Also, errors were quantified for the calculated results using correlation coefficient and relative error methods. The results reveal that Maximum Shear Stress, Modified Mohr Coulomb, and Lou fracture models were able to predict the onset of fracture with acceptable accuracy. However, Maximum Shear Stress required only one experimental test to be calibrated.

An orientation distribution function based model is used for micromechanical modeling of the titanium-aluminum alloys, Ti-0 wt % Al and Ti-7 wt % Al, which are in demand for many aerospace applications. This probability descriptor based modeling approach is different than crystal plasticity finite element techniques since it computes the averaged material properties using upper bound averaging. A rate-independent single-crystal plasticity model is implemented to compute the effect of macroscopic strain on the polycrystal. An optimization problem is defined for calibrating the basal, prismatic, pyramidal slip system and twin parameters using the available tension and compression experimental data. The crystal plasticity parameters of Ti-7 wt % Al are not studied extensively in literature, and therefore the optimization results for the crystal plasticity model realization produce unique data, which will be beneficial to future studies in the field. The sensitivities of the slip and twin parameters to the design objectives are also investigated to identify the most critical slip system parameters. Using the optimum design parameters, the microstructural textures, during the tension test, are predicted by the crystal plasticity finite element simulations, and compared to the available experimental texture and scanning electron microscope—digital image correlation data.

A peridynamic (PD) implementation of crystal plasticity with an adaptive dynamic relaxation method is presented. Non-ordinary state-based peridynamics and the Newmark's dynamic method with artificial damping are employed to capture strain localizations in polycrystalline microstructures based on a rate-independent crystal plasticity model. Numerical simulations for planar poly-crystals are conducted under plane strain pure shear and compression, respectively. The computational eciency of the explicit PD model is demonstrated to be superior to an implicit PD model for modeling crystal plasticity. The stress field distribution, texture formation, and homogenized stress-strain response predicted by the finite element method and the new dynamic PD model are compared. Finer localization bands are observed in the latter model. The origin and evolution of these shear bands are studied by PD simulations during deformation of three polycrystals with di↵erent orientation distributions. Emphasis is placed on the accuracy and eciency of the adaptive dynamic relaxation method working with crystal plasticity PD models.

We determine the thermal conductivities of a, b, and g graphyne nanotubes (GNTs) as well as of carbon nanotubes (CNTs) using molecular dynamics simulations and the Green-Kubo relationship over the temperature range 50e400 K. We find that GNTs demonstrate considerably lower thermal conductivity than CNTs with the same diameter and length. Among a, b, and g-GNTs, g-GNT has the highest thermal conductivity at all temperatures. By comparing the phonon transport properties of GNTs with CNTs, we find that as the fraction of acetylene bonds in the atomic network increases, the population of high-energy optical phonons increases. This enhances phonon-phonon scattering, and reduces the mean free path, adversely affecting the thermal conductivity of GNTs relative to CNTs. Also reducing the thermal conductivity of GNTs relative to CNTs is the considerably lower acoustic phonon group velocities for the former as well as the lower volumetric heat capacity of GNTs. Optical phonons in a-GNT are high in energy (0.26 eV) with a high population number, making them more energetic than the electronic direct band gap and significantly more energetic than the thermal energy at room temperature. Therefore, we suggest a-GNT as a potential candidate for phonovoltaic energy conversion applications.

Microstructural effects become important at regions of stress concentrators such as notches, cracks and contact surfaces. A multiscale model is presented that efficiently captures microstructural details at such critical regions. The approach is based on a multiresolution mesh that includes an explicit microstructure representation at critical regions where stresses are localized. At regions farther away from the stress concentration, a reduced order model that statistically captures the effect of the microstructure is employed. The statistical model is based on a finite element representation of the orientation distribution function (ODF). As an illustrative example, we have applied the multiscaling method to compute the stress intensity factor K I around the crack tip in a wedge-opening load specimen. The approach is verified with an analytical solution within linear elasticity approximation and is then extended to allow modeling of microstructural effects on crack tip plasticity.

This study aims to simulate the stabilised stress-strain hysteresis loop of dual phase (DP) steel using micromechanical modelling. For this purpose, the investigation was conducted both experimentally and numerically. In the experimental part, the microstructure characterisation, monotonic tensile tests and low cycle fatigue tests were performed. In the numerical part, the representative volume element (RVE) was employed to study the effect of the DP steel microstructure of the low cycle fatigue behavior of DP steel. A dislocation-density based model was utilised to identify the tensile behavior of ferrite and martensite. Then, by establishing a correlation between the monotonic and cyclic behavior of ferrite and martensite phases, the cyclic deformation properties of single phases were estimated. Accordingly, Chaboche kinematic hardening parameters were identified from the predicted cyclic curve of individual phases in DP steel. Finally, the predicted hysteresis loop from low cycle fatigue modelling was in very good agreement with the experimental one. The stabilised hysteresis loop of DP steel can be successfully predicted using the developed approach.

The effect of martensitic phase fraction on the cyclic stress-strain behavior of two DP steels is investigated via a micromechanical model based on a representative volume element (RVE). A dislocation density based model and a Chaboche hardening model are used to identify the isotropic and kinematic hardening behavior of constituent phases, respectively. The Chaboche parameters obtained by fitting flow curves computed from a dislocation density based model for both ferrite and martensite phases of each steel are incorporated into a Finite Element code ABAQUS to simulate the low cycle fatigue with a non-linear kinematic hardening behavior. Based on experimental observations reported in the literature, fatigue crack initiates in ferrite phase. A ductile damage model, therefore, is used to simulate damage initiation in ferrite. The results show that the martensite fraction has a significant influence on cyclic plastic strain accumulation during the cyclic deformation. It is also concluded that with an increase in the martensite volume fraction in DP steel, the elastic component of the total strain amplitude increases and higher fatigue strength is, subsequently, observed.

We present a method of modeling nanoparticle (NP) hydrophobicity using coarse-grained molecular dynamics (CG MD) simulations, and apply this to the interaction of lipids with nanoparticles. To model at a coarse-grained level the wettability or hydrophobicity of a given material, we choose the MARTINI coarse-grained force field, and determine through simulation the contact angles of MARTINI water droplets residing on flat regular surfaces composed of various MARTINI bead types (C1, C2, etc.). Each surface is composed of a single bead type in each of three crystallographic symmetries (FCC, BCC, and HCP). While this method lumps together several atoms (for example, one cerium and two oxygens of CeO 2) into a single CG bead, we can still capture the overall hydrophobicity of the actual material by choosing the MARTINI bead type that gives the best fit of the contact angle to that of the actual material, as determined by either experimental or all-atom simulations. For different MARTINI bead types, the macroscopic contact angle is obtained by extrapolating the microscopic contact angles of droplets of eight different sizes (containing N w = 3224−22978 water molecules) to infinite droplet size. For each droplet, the contact angle was computed from a best fit of a circular curve to the droplet interface extrapolated to the first layer of the surface. We then examine how small nanoparticles of differing wettability interact with MARTINI dipalmitoylphosphotidylcholine (DPPC) lipids and SP-C peptides (a component of lung surfactant). The DPPC shows a transition from tails coating the nanoparticle to a hemimicelle coating the water-wet NP, as the contact angle of a water droplet on the surface is lowered below ∼60°. The results are relevant to developing a taxonomy describing the potential nanotoxicity of nanoparticle interactions with components in the lung.

The ferrite-martensite interfacial energy and equilibrium interfacial length as a function of martensite carbon content are assessed using first-principles atomistic simulations. The weight percent of carbon in the martensite phase was implicitly varied from 0.6 to 1.8 wt percent by modifying the lattice constant of body-centered tetragonal (BCT) martensite according to Kurdjumov and Kaminsky's empirical expressions. With increasing carbon content, a decrease is found in both the interfacial energy and in the equilibrium distance between ferrite and martensite interfaces. Moreover, the Morse inter-atomic potentials between the atoms in the ferrite-martensite interface for four different martensite carbon contents are calculated, and the parameters of the Morse potential are correlated linearly with the martensite carbon content. In addition , the dissociation local strains during uniaxial loading in a direction normal to the interfacial plane are calculated from the interatomic potentials. The local strain at the interface needed for ferrite-martensite interface separation increases with increase in martensite carbon content. The fitted expressions can be used to predict the ferrite-martensite interfacial energy , equilibrium interfacial distance, dissociation local strain at the interface, and the Morse parameters as functions of martensite carbon content within the range of 0.6–1.8 wt percent. Furthermore, the introduced implicit method can potentially be used to study the mechanical properties of other materials with dopant impurities such as n-type and p-type semiconductors.

Transformation Induced Plasticity (TRIP) steels possess high strength and great formability. In the current research work, the effect of banded martensite microstructure onto the mechanical properties and formability behaviour of low-alloyed TRIP steels was investigated. The results showed that the TRIP steel accumulated a larger strain prior to fracture when martensite appeared in form of bands.

In the current research, the effect of age treatment on microstructural evolution, mechanical properties and corrosion resistance of Ti-6Al-4V was studied. The microstructural evaluation of the alloy during solution treatment, intermediate annealing and aging, was investigated by combining results from optical and scanning electron microscopies and uniaxial tensile as well as hardness tests were applied to study the mechanical properties evolutions. It was found that, intermediate annealing after solution treatment improved both, hardness and ductility. The hardness increment was determined to be due to decomposition of some soft alpha prime martensite to alpha + beta, and ductility improvement was assigned to beta phase growth during intermediate annealing, as it interrupts the continuity of brittle alpha phase. The results also showed that aging treatment at 550 C for 4 hours increased clearly the hardness of the studied alloy. It was conclude the decomposition of the soft martensite and precipitation of fine alpha in retained beta phase are the major reasons for hardness increment. The results also showed that aging treatment improved the ductility, although it decreased the work hardening and the corrosion resistance of the studied alloy.

Effective treatment of ovarian cancer depends upon the early detection of the malignancy. Here, we report on the development of a new nanostructured immunosensor for early detection of cancer antigen 125 (CA-125). A gold electrode was modified with mercaptopropionic acid (MPA), and then consecutively conjugated with silica coated gold nanoparticles (AuNP@SiO2), CdSe quantum dots (QDs) and anti-
CA-125 monoclonal antibody (mAb). The engineered MPA|AuNP@SiO2|QD|mAb immunosensor was characterised using transmission electron microscopy (TEM), atomic force microscopy (AFM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Successive conjugation of
AuNP@SiO2, CdSe QD and anti-CA-125 mAb onto the gold electrode resulted in sensitive detection of CA-125 with a limit of detection (LOD) of 0.0016 UmL−1 and a linear detection range (LDR) of 0–0.1 UmL−1. Based on the high sensitivity and specificity of the immunosensor, we propose this highly stable
and reproducible biosensor for the early detection of CA-125.

DP steels are often used to form variety of automobile parts due to their impressive mechanical properties such as high strength and good ductility. Since most of these structural members are prone to failure under different loading conditions, failure initiation and damage mechanisms are considered as important areas to investigate and have been the subject of extensive research work.
The current research work aims to study the effect of microstructural features such as martensite phase fraction and morphology, ferrite grain size and additional phases such as bainite on the mechanical and failure behaviour of DP steels. For this purpose, a microstructure based approach by means of representative volume elements (RVE) is utilized to incorporate the microstructure deformation distribution and the failure mechanisms on this scale.  Micro sections of DP microstructures with various amounts of martensite are converted to 2D RVEs, while 3D RVEs are constructed statistically with randomly distributed phases. A dislocation-based model is used to describe the flow curve of each ferrite and martensite phase separately as a function of carbon partitioning and microstructural features. Numerical tensile tests of RVE are carried out using the ABAQUS/Standard code to predict the flow behaviour of DP steels. For validation, a comparison between predicted and experimental flow curves is carried out. The current research work is conducted in the following steps:
Firstly, the inhomogeneities are quantified in DP steels considering two parameters: average height and aspect ratio of martensite islands. Then the effect of martensite banding is also studied on the hardening behaviour of DP steels. Equiaxed microstructures show higher yield stress and work hardening compared to that of the banded microstructures.
Secondly, a correlation factor between 2D and 3D RVE calculations is developed. Since 2D plane strain modelling gives an underpredicted flow curve for DP steels, while the 3D modelling gives a quantitatively reasonable description of flow curve in comparison to the experimental data, a von Mises stress correlation factor σ3D/σ2D is identified to compare the predicted flow curves of these two dimensionalities showing a third order polynomial relation with respect to martensite fraction and a second order polynomial relation with respect to equivalent plastic strain, respectively. The quantification of this polynomial correlation factor is performed based on laboratory-annealed DP600 steel with varying martensite contents and it is validated for industrially produced DP steels with various chemistries, strength levels and martensite fractions.
Thirdly, the effect of ferrite grain size on the hardening behaviour of DP steels taking in to account geometrically necessary dislocations (GNDs) is studied. For achieving this goal, the volume change during the austenite-to-martensite transformation is modelled, and the resulting prestrained areas in ferrite are considered to be the storage place of GNDs. The thickness of the GND layer around martensite islands is quantified experimentally and numerically. Subsequently, three criteria are developed to describe the strength, thickness, and amount of prestrain in the GND zone as a function of microstructural features in DP steel. The flow curves of simulations that take into account the GND are in better agreement with those of experimental flow curves compared to those of predictions without consideration of the GND. The experimental results obey the Hall-Petch relationship between yield stress and ferrite grain size. Additionally, the simulations are able to predict the Hall-Petch relationship, too.
Fourthly, the effect of bainite phase as an additional phase in DP steel is investigated on the hardening behaviour. For achieving this goal, combined electron backscatter diffraction (EBSD) and electron probe microanalysis (EPMA) measurements are first utilized to quantify the constituents (ferrite, martensite and bainite) in the microstructure. Then, the flow behaviour of the material is modelled using 2D RVE calculations. 2D RVE IS generated from kernel average misorientation (KAM) map. A dislocation-based work-hardening approach is utilized to calculate the flow curve of bainite. The predicted flow curves from 2D RVE calculations are correlated to 3D using the developed correlation factor and excellent agreement is achieved by 3D corrected flow curve from 2D RVE calculations and experimental flow curves.
Finally, failure initiation in DP steels is investigated. For this purpose, xtended finite element method (XFEM) with cohesive zone (traction-separation) law is utilized. In order to determine cohesive parameters for martensite cracking, mini tensile tests with digital image correlation (DIC) technique are carried out to identify the right position for failure initiation and the responsible local strain for this position. In-situ bending test in SEM with EBSD measurements before and after the test are made to identify which phase or interphase fails first. Comparing the image quality (IQ), Inverse pole figure (IPF) and KAM maps before and after the in-situ test shows that the crack initiation occurs in martensite islands. The local strain obtained from mini tensile test with DIC technique is considered as boundary conditions in the RVE calculations. After simulation, the failure strain in martensite is identified using first order homogenization strategy. The identified parameters are validated by comparing the predictions with the experimental results. The developed approach is applied to industrially processed DP steel grades with varying strength levels. The comparison of RVE calculated damage initiation in industrially produced qualities show good agreement to experimental results. Therefore failure initiation in components can be predicted for different DP steel qualities using a two-scale approach based on RVE calculation of the plastic hardening and failure of martensite.