Nanoscale Model Research Articles

Numerical Modelling of Carrier Transport in Organic Field Effect Transistors

Background: Organic field effect transistors (OFETs), used in the fabrication of nanosensors, are one of the most promising devices in organic electronics because of their lightweight, flexibility, and low fabrication cost. However, the optimization of such OFETs is still in an early stage due to the minimal analytical and numerical models presented in the literature. Objective: This research presses to demonstrate a numerical carrier transport model based on the finite element method (FEM) to investigate the I-V characteristic of OFETs. Methods: Two various organic semiconductor materials have been included in the study, polyaniline and pentacene, where micro-scale, as well as nano-scale models have been presented. OFETs regarding channel length, dielectric thickness, and doping level impact have been studied. We nominated the threshold voltage, the on/off current ratio, the sub-threshold swing, and the field effect mobilities as the primary output evaluating parameters. Results: The numerical model has shown the criticality of the doping effect on tuning the device flowing drain current to exceed 300 μA saturation current, along with a threshold voltage of -0.1 V under a channel length of 30 nm. Conclusion: The study highlights the effectiveness of polyaniline over pentacene as nano-channel length OFET due to the boosted conductivity of polyaniline concerning pentacene.

Effects of Interfacial Imperfections on Nanoscale Adhesive Contact for Layered Medium

Depending on processing technologies and working conditions, imperfect bonding at the layer-substrate interface may occur, resulting in diverse mechanical responses compared to a perfectly bonded layer-substrate system. This study focuses on an imperfect interface under force-like conditions and incorporates it into a nanoscale adhesive contact model to explore the influences of interfacial imperfection on the adhesive contact behaviors of the layered medium. The adhesive contact model is formulated based on the Lennard-Jones (LJ) potential and the Hammaker summation method. The adhesive contact problem is addressed by solving the nonlinear surface gap equations between the contact bodies. The deformation within the gap equations, accounting for the influence of imperfections, is computed using the fast Fourier transform (FFT) algorithm. This study explores the influence of three stress jumping coefficients t1,t2 and t3, which quantitatively characterize the interfacial imperfection, and their coeffects with material parameters, including imperfection depth (layer thickness), adhesion work, and elastic modulus, on the adhesive contact behaviors of the layered medium. The findings underscore that the normal stress jumping coefficient t3 exerts the most significant impact, wherein a higher t3 value corresponds to a smaller adhesive force and a larger absolute contact approach, while tangential stress jumping coefficients t1 and t2 exhibit negligible influence. Decreasing t3 values correspond to varying interaction force-contact approach responses and contribute to alleviating contact stability in cases with large Tabor parameters. Interfacial imperfections manifest their influence by modifying the pressure-displacement response, with noticeable effects only within a specific imperfection depth range h¯<40. While the introduction of interfacial imperfections does not alter the fundamental impact of material parameters—such as imperfection depth, adhesion work ratios, and elastic modulus ratios—on adhesive force and contact approach, it does modify the magnitude of these effects. Furthermore, imperfections alter stress distribution, increasing maximal von Mises stress and causing stress concentration within the layer and at the interface. In summary, force-like imperfections reduce surface displacement, resulting in a smaller region of positive pressure and ultimately contributing to a larger adhesive force. However, this effect is accompanied by increased stress concentration at the imperfect interface. This heightened stress level poses a potential risk to the system's reliability.

Nano-scale modeling of energy dissipation in a single lamella reveals the significant contribution of collagen-mineral sliding to intrinsic bone toughness

Although collagen-mineral sliding is recognized as one of the intrinsic mechanisms that contribute to the bone toughness, its precise role in energy release at the nano-scale, as well as its relationship to other intrinsic toughness mechanisms, remains unclear. This lack of understanding stems from the challenges associated with quantifying the specific nature of contact at the mineral-collagen interface, and the energy dissipation capacity resulting from plastic deformation at this scale. To address this issue, we developed a three-dimensional model of mineralized collagen fibril using ABAQUS, incorporating hyperelastic isotropic collagen, elastic isotropic mineral, and a cohesive contact formulation to represent the collagen-mineral interface. Knowing the properties of collagen and mineral and using a parametric modeling approach, we estimated the properties of contact based on experimental measurements of the stress-strain behavior in a single bone lamella, considering the angle of the collagen fibril in relation to the loading axis. By comparing the experimental elastic modulus with the model predictions, we determined that the cohesive contact exhibited a maximum strength of 9 MPa and a fracture energy of 50 mJ/m2 within the bone. Further analysis indicated that fracture energy at the collagen-mineral interface is potentially closer to 5 mJ/m2. Using these findings, we concluded that the interfaces were responsible for 52% to 98% of the energy release in mineralized collagen fibrils, depending on collagen angle, both directly and indirectly by influencing stress and strain in adjacent collagen fibril. The results of this study demonstrated that plastic deformation at the collagen-mineral interface is the primary mechanism underlying bone toughness at the nano-scale. Importantly, we found that these conclusions held true regardless of the angle of the collagen fibril relative to the loading axis. The modeling framework presented in this study provides a valuable tool for investigating the elastic and post-yield behavior of bone across different mineral volume fractions at the nano-scale, and at the lamellar level.

A Mechanism of Resistance Switching in CNT Based Memory Devices

Carbon nanotubes (CNTs) show promise for high energy efficiency electronic devices due to their high electrical conductivity. One possible application is in the fabrication of resistance-change computer memory, where the application of an external electrical bias can use a CNT layer as the switching element in a RAM cell. Memory cells of this type have been extensively demonstrated, where the electrical resistance of a switching layer of CNTs can be reversibly controlled by the application of external bias [1].To better understand these devices, we have developed a nanoscale model of their electrical switching. Towards this end, first-principles calculations of the electrical conductivity of CNT-CNT junctions were performed using the Density Functional Tight Binding (DFTB) in combination with the Non-Equilibrium Greens functions (NEGF) approach, enabling an improved understanding of the tunnelling of electrons across a range of CNT junctions [2]. These results demonstrate that the conductivity of CNT contacts depends on the overlap area between nanotubes and exponentially on the distances between the carbon atoms of the interacting CNTs. Secondly, we employed coarse-grained molecular dynamics [3,4] to produce nanoscale dense CNT film models like those used in the devices. We devise a set of metrics for characterising the structural properties of CNT films, and apply them to a set of model films designed to mimic those used in microelectronics devices. In order to understand how the geometrical properties of CNTs affect the film structure, we analyse films with different CNT chirality and length distributions. Unlike previous studies that focused on relatively low-density systems below ∼0.4 g/cm3, we also consider films with density of ∼0.6 g/cm3, as employed in experimentally fabricated CNT-based NRAM devices. By adding amorphous carbon to the film models, in varying amounts, we are then able to assess its effects. Finally, these two elements were combined to produce electrical simulations of the conductivity of the CNT films connected to TiN electrodes. These electrodes are shown to be partially oxidized during the device fabrication. The electrical conductivity in a device is characterized by formation of conduction paths formed by CNTs between the electrodes and connected via the CNT junctions. The conductivity is modulated by charging of CNTs and amorphous carbon present in the film.Using these simulations, we propose a resistance switching mechanism in TiN/CNT/TiN devices based on the physical movement of CNTs. During the initial operation of the device, oxygen is released from the oxidized bottom electrode and this readily reacts with individual CNTs to form charge trapping sites. Once these sites have become charged, they enable controllable movement of CNTs at the bottom electrode under the application of electric field. By reversibly connecting and disconnecting such CNTs from the bottom electrode, the electrical conductivity through the CNT film as a whole can be controlled.

The impact of double‐diffusive convection on electroosmotic peristaltic transport of magnetized Casson nanofluid in a porous asymmetric channel

AbstractThe primary objective of the present article is to investigate the heat and mass transfer in mixed convection peristaltic flow of Casson nanofluid through an asymmetric permeable channel filled with a porous medium in the presence of electroosmosis. Magnetohydrodynamics and radiative heat transfer are also considered. The study is motivated by industrial micro‐pumping systems utilizing multi‐functional nanomaterials. Researchers have investigated the distinct temperature and rheological properties of Casson nanofluids. Solutal molecular diffusion and nanoparticle diffusion are both examined. Mixing nanoparticles with Casson fluid alters its flow characteristics and heat transmission, amalgamating different properties that are useful in a wide range of industrial and scientific applications. Buongiorno's two‐component nanoscale model is deployed for simulating nanofluid transport, and the Rosseland diffusion flux is utilized for optically thick electromagnetic liquids. Heat generation or absorption and cross‐diffusion (Soret and Dufour) effects are also incorporated in the model. An efficient analytical approach known as the long wavelength‐low Reynolds number lubrication approximation (LWL‐LRN) is utilized to solve the non‐dimensional boundary value problem. Validation of the solutions with previous studies is included. Graphs are presented using MATLAB 2022b to visualize the influence of key parameters including permeability, magnetic field, thermal radiation, Grashof number, Brownian motion, thermophoresis, electrical field and Prandtl number on transport characteristics (velocity, temperature, concentration), and trapping phenomena associated with peristaltic propulsion. As thermophoresis and Brownian parameters are intensified, there is a strong response in nanoparticles which induces axial acceleration, as observed at locations y = 0.15, where u = 0.191, and y = 0.33, where u is elevated to 0.14. An increase in radiation parameter () results in a depletion in axial velocity magnitudes along the left half of the wall and also modifies velocity distribution in the right section of the microchannel. An increase in the thermal radiation parameter (Rn) and heat absorption (sink) is found to suppress temperatures. Increasing heat generation, thermal Grashof number (Gr), and solutal Grashof number (Gc) decelerate axial flow in the left half space but accelerate flow in the right half space of the micro‐channel. Increasing radiation parameters and thermal Biot number boost temperatures when heat sink is present but reduce them when heat source (generation) is present. Increasing radiation parameter boosts nanoparticle volume fraction (concentration) whereas an elevation in heat generation and thermal Biot number both induce the opposite effect. Increasing the magnetic field damps the flow and reduces the number of boluses present. However, bolus volume increases with greater thermal Grashof Number , Darcy (permeability) number , and Helmholtz‐Smoluchowski velocity , that is, stronger axial electrical field.

A modular DNA origami nanocompartment for engineering a cell-free, protein unfolding and degradation pathway

Within the cell, chemical reactions are often confined and organized through a modular architecture. This facilitates the targeted localization of molecular species and their efficient translocation to subsequent sites. Here we present a cell-free nanoscale model that exploits compartmentalization strategies to carry out regulated protein unfolding and degradation. Our synthetic model comprises two connected DNA origami nanocompartments (each measuring 25 nm × 41 nm × 53 nm): one containing the protein unfolding machine, p97, and the other housing the protease chymotrypsin. We achieve the unidirectional immobilization of p97 within the first compartment, establishing a gateway mechanism that controls substrate recruitment, translocation and processing within the second compartment. Our data show that, whereas spatial confinement increases the rate of the individual reactions by up to tenfold, the physical connection of the compartmentalized enzymes into a chimera efficiently couples the two reactions and reduces off-target proteolysis by almost sixfold. Hence, our modular approach may serve as a blueprint for engineering artificial nanofactories with reshaped catalytic performance and functionalities beyond those observed in natural systems.

A molecular dynamics investigation of laminar pyrocarbons elasticity up to high-temperatures

The mechanical properties of anisotropic carbons such as the pyrocarbon (pyC) matrices in C/C composites remain poorly documented, especially at elevated temperatures where these materials find most of their applications. We provide here a comprehensive molecular dynamics investigation of the high temperature – up to 4000 K – elastic behavior of six nanoscale pyC models in the context of fast temperature increases, not allowing for major structural modifications such as graphitization. We show that the structure of the most anisotropic and less disordered carbons, like the rough laminar (RL) pyC, is mostly not affected by annealing at the nanosecond timescale, aside from healing unstable defects like two-coordinated atoms at graphene edges. Conversely, highly disordered and less anisotropic carbons like the smooth laminar (SL) pyC show some significant rearrangements at grain boundaries and the development of some limited microporosity. The elastic constants of all highly anisotropic models moderately decrease with increasing temperature, somehow similarly to what is observed for graphite. Elastic constants of the SL pyC show a stronger decrease at high temperature, due to the decrease in density even though all models retain an important degree of stiffness up to 4000 K.

Electro-mechanical vibration characteristics of imperfect sandwich FG piezoelectric honeycomb nanoplates resting on Kerr foundation

This study presents an innovative analytical approach to examine the electro-mechanical vibration characteristics of sandwich nanoplates featuring a honeycomb core and two surface layers composed of imperfect piezoelectric functionally graded (FG) material, incorporating porosities, atop a Kerr elastic foundation. Utilizing nonlocal elasticity theory and four-variable refined plate theory (HSDT-4), we account for nanoscale effects and model the electric potential variation across the piezoelectric layer thickness as a combination of cosine and linear variations satisfying Maxwell's equation. The proposed method's novelty lies in its comprehensive analysis of the interplay between porosity, elastic foundation parameters, material properties, geometrical dimensions, external voltage, and nonlocal parameters on the free vibration frequency of these nanostructures. Numerical simulations validate the model's reliability and assess the significant impacts of these factors. Our findings contribute to the optimization of nanostructural designs for advanced engineering applications, highlighting the method's added value in predicting the behavior of imperfect piezoelectric FG honeycomb nanoplates.

Nano-cutting mechanism of ion implantation-modified SiC: reducing subsurface damage expansion and abrasive wear

This study utilized ion implantation to modify the material properties of silicon carbide (SiC) to mitigate subsurface damage during SiC machining. The paper analyzed the mechanism of hydrogen ion implantation on the machining performance of SiC at the atomic scale. A molecular dynamics model of nanoscale cutting of an ion-implanted SiC workpiece using a non-rigid regular tetrakaidecahedral diamond abrasive grain was established. The study investigated the effects of ion implantation on crystal structure phase transformation, dislocation nucleation, and defect structure evolution. Results showed ion implantation modification decreased the extension depth of amorphous structures in the subsurface layer, thereby enhancing the surface and subsurface integrity of the SiC workpiece. Additionally, dislocation extension length and volume within the lattice structure were lower in the ion-implanted workpiece compared to non-implanted ones. Phase transformation, compressive pressure, and cutting stress of the lattice in the shear region per unit volume were lower in the ion-implanted workpiece than the non-implanted one. Taking the diamond abrasive grain as the research subject, the mechanism of grain wear under ion implantation was explored. Grain expansion, compression, and atomic volumetric strain wear rate were higher in the non-implanted workpiece versus implanted ones. Under shear extrusion of the SiC workpiece, dangling bonds of atoms in the diamond grain were unstable, resulting in graphitization of the diamond structure at elevated temperatures. This study established a solid theoretical and practical foundation for realizing non-destructive machining at the atomic scale, encompassing both theoretical principles and practical applications.

Novel full-scale model verified by atomic surface and developed composite microfiber and slurry polishing system

Polishing mechanisms between fibers of a polishing pad and slurry are elusive, rising a challenge to develop high-performance composite polishing system. To solve this challenge, a novel full-scale model is proposed from mm to nm, consisting of macro, meso, micro and nanoscale. The model is verified by atomic surface and developed composite microfiber and slurry polishing system. Prior to chemical mechanical polishing, fused silica was polished by ceria slurry. A novel polishing pad was prepared using microfibers with a diameter of 2.5 μm, and a novel green slurry contained silica abrasives, hydrogen peroxide, sodium carbonate, sorbitol and xanthan gum. After CMP, an atomic surface with Ra of 0.108 nm was achieved, and the thickness of damaged layer is 1.95 nm. In terms of the macroscale model suggested, the maximum stress on the microfiber pad decreased 417.7 %, and the direct contact area increased 41.23 % compared with those of a commercial nonwoven pad. The peak stress exceeded 1 MPa on the commercial pad, while it reduced to about one fourth on the developed microfiber pad, according to the mesoscale fiber-slurry model proposed. Reactive force field molecular dynamics simulations, i.e. nanoscale model, reveal that a slurry layer existing at interface effectively impedes direct contact between abrasives and fused silica. With increasing the polishing load, material removal mode transformed from an atom to atomic chains. The constructed full-scale model and developed composite polishing system provide new insights to analyze, design and manufacture high-performance polishing pads, slurry and system.

Molecular Probing of the Microscopic Pressure at Contact Interfaces.

Obtaining insights into friction at the nanoscopic level and being able to translate these into macroscopic friction behavior in real-world systems is of paramount importance in many contexts, ranging from transportation to high-precision technology and seismology. Since friction is controlled by the local pressure at the contact it is important to be able to detect both the real contact area and the nanoscopic local pressure distribution simultaneously. In this paper, we present a method that uses planarizable molecular probes in combination with fluorescence microscopy to achieve this goal. These probes, inherently twisted in their ground states, undergo planarization under the influence of pressure, leading to bathochromic and hyperchromic shifts of their UV-vis absorption band. This allows us to map the local pressure in mechanical contact from fluorescence by exciting the emission in the long-wavelength region of the absorption band. We demonstrate a linear relationship between fluorescence intensity and (simulated) pressure at the submicron scale. This relationship enables us to experimentally depict the pressure distribution in multiasperity contacts. The method presented here offers a new way of bridging friction studies of the nanoscale model systems and practical situations for which surface roughness plays a crucial role.

Vibrational analysis of graphyne-based nanoplates using a hybrid nonlocal strain gradient-atomistic simulation model

By employing a hybrid atomistic-continuum model, we can combine the advantages of atomic and continuum models. In this approach, resonance frequencies are matched to those obtained from the continuum model using the size effect and Young’s modulus as fit parameters. Our proposed method examines how radius affects the elastic modulus, size effect parameters, and resonance frequency values of the graphyne family, taking into account both macro and nano-scale models. The non-local strain gradient model has been calibrated to achieve optimal error. In contrast, the error is highest when the non-local strain gradient effect is not considered in the continuum mechanics model.

From sedimentation to consolidation of kaolinite: A molecular dynamic study

The consolidation of clay is the main measure for reclamation project, which is related to the compressibility, permeability, and coupling effect of clay-water. However, the mechanism of consolidation of clay remains unclear. This study focuses on the microscopic consolidation property of kaolinite using Molecular Dynamics (MD) simulation method. The nano-scale consolidation model was established to reproduce the sedimentation to consolidation. According to the different distribution of water film in pores, the consolidation process could be divided into different stages: (1) in the process of sedimentation and primary consolidation, the drainage occurred continuously except the strongly bound water; (2) just a part of the strongly bound water could be drained during the secondary consolidation. The minimum consolidation stress which can cause significant consolidation was found to be 0.1 GPa in a narrow throat of about 1 nm at nano-scale. The evolution of interparticle spacing between kaolinite particles during the consolidation process was analyzed to reflect the role of interparticle water on the pore water pressure and effective stress. Besides, models with different wettability show that the drainage of water on hydrophilic basal surface was difficult, while water molecules on hydrophobic basal surface are more easily expelled and have directional flow paths.

Elasticity of dense anisotropic carbons: A machine learning model of the structure–property relationship informed by large scale molecular dynamics data

Dense anisotropic carbons are praised materials for thermostructural applications, yet, so far, a detailed structure–property relationship for these materials is still lacking, especially for the pyrocarbon (pyC) matrices in carbon/carbon composites. Here we compute the full elastic tensors of 210 recently introduced nanoscale models of anisotropic carbons (Polewczyk et al., 2023), covering domain sizes (Lc and La) and orientation angles (OA, as a measure of nanotexture) relevant to most as-prepared and moderately heat-treated pyC matrices: Lc∈ [1.5:8 nm]; La∈ [2:5.5 nm]; and OA ∈ [25:110°]. Isothermal and adiabatic elastic tensors, corresponding to the slow quasi-static and ultra-fast loading regimes, respectively, are considered. Analyzing the database of computed elastic constants with a random forest regressor supervised learning algorithm we show that all elastic constants can be predicted accurately using Lc, La and OA as descriptors. Among the latter, OA is the one showing, by far, the strongest correlation with the elastic tensors. For such dense, non porous carbons, 3 of the 6 isothermal and 5 of the 6 adiabatic constants can even be accurately predicted using OA as the unique material descriptor. Calculation of the universal anisotropy index shows that isothermal tensors show more anisotropy than adiabatic ones, indicating that stress relaxation favors elastic anisotropy. Eventually, the Young’s moduli and Poisson coefficients of six models of actual pyCs are presented and their longitudinal moduli compared to tensile measurements, showing relatively poor agreement. These results suggest that accounting for texture at a larger scale is required to capture pyC matrices elasticity. The developed supervised learning model is available for online use at https://web.ism.u-bordeaux.fr/rfr.

Molecular dynamics investigation of the effect of nanostructured surfaces on flow boiling

As a prominent limiting factor in the performance of microelectronic devices, the improvement of heat dissipation is of utmost importance. The enhancement of heat and mass transfer during boiling by nanostructured surfaces has been demonstrated in many studies. In this study, a nanoscale flow-boiling model is developed by molecular dynamics method in order to deeply investigate the microscopic mechanism of nanostructure-enhanced heat transfer. Simple liquid argon is heated by grooved substrate to explore the effect of the depth of the cavities on the boiling heat transfer. The results indicate that the grooved surface improves heat transfer performance through two key mechanisms. Firstly, it induces bubble nucleation, and secondly, it delays the onset of film boiling. The presence of cavities allows the argon atoms within to absorb additional energy from the surrounding walls and be in closer proximity to the heating layer. This reduction in solid thermal resistance results in increased heat transfer efficiency, leading to earlier bubble nucleation and a greater propensity for nucleation within the cavities. The low horizontal velocity of argon atoms within the cavities suggests their ability to retain a significant number of atoms, thereby effectively mitigating the deterioration of heat transfer caused by the formation of a vapor film on the solid wall. The comprehensive performance is observed to improve with increasing depth of the cavities within the range investigated in this study.

Analysis of Lanthanum Oxide Based Double-Gate SOI MOSFET using Monte-Carlo Process.

This work proposes a Double-Gate (DG) MOSFET with a Single Material made of Silicon On-Insulator (SOI). The Lanthanum Oxide material with a high k-dielectric constant has been used as an interface between two gates and the channel. The Monte Carlo analysis has been used to determine the Conduction Band Energy (Ec) profiles and electron sheet carrier densities (ns) for a Silicon channel thickness (tsi) of 10 nm at 0.5 V gate drain-source voltages. The transverse electric fields are weak at the midchannel of DG SOI MOSFETs, where quantum effects are encountered. The Monte Carlo simulation has been confirmed to be effective for high-energy transport. A particle description reproduces the granularity property of the transport for nanoscale modeling. This work utilizes a Monte Carlo (MC) Simulation for the proposed Double Gate Single Material Silicon On Insulator MOSFET with (La2O3=2 nm) as dielectric oxide on upper and lower gate material. The electrical properties of the DG SOI MOSFETs with Lanthanum Oxide were analyzed using Monte Carlo simulation, including the conduction band energy, electric field, potential distribution, particle movement, and average velocity. The peak electric field (E) simulation results and an average drift velocity (υavg) of 6Í105 V/cm and 1.6Í107 cm/s were obtained, respectively. The conduction band energy for the operating region of the source has been observed to be 4 % to the drain side, which obtained a value of -0.04 eV at the terminal end. This proposed patent design, such as double-gate SOI-based devices, is the best suggestion for significant scalability challenges. Emerging technologies reach the typical DG SOI MOSFET's threshold performance when their geometrical dimensions are in the nanometer region. This device based on nanomaterial compounds has been more submissive than conventional devices. The nanomaterials usage in the design is more suitable for downscaling and reducing packaging density.

Nanoscale modeling of an efficient Carbon Nanotube-based RF switch using XG-Boost machine learning algorithm

Nanoscale modeling of an efficient Carbon Nanotube-based RF switch using XG-Boost machine learning algorithm

Nanoscale insight into fluidity improvement of supplementary cementitious materials on concrete: The nano-lubrication process

The workability of concrete is a fundamental property that is frequently influenced by chemical admixtures. In this paper, we provide an interesting perspective to understand the effect of silica fume on the fluidity of cement slurries. By employing molecular dynamics techniques, a nanoscale boundary friction model is proposed to evaluate the flow of cement slurries resulting from cement hydration. According to conventional experimental data, interfacial friction decreases as the water content rises. And additional lubrication of the silica surface is possible. The investigation into the microscopic mechanisms behind interfacial lubrication reveals that water lubricates SiO2 and CSH sheets in various ways at low and high water levels. Throughout the system, non-covalent water-water and water-calcium bonds break down during the lubricating process. It appears that some calcium atoms are split out of the CSH matrix, a sign of a covalent break. In the high water content system, this separation did not happen despite the lubricating action in the low water content system. It is also possible to visually evaluate the impact of additional cementitious materials on the cement paste's fluidity by using the recently discovered mechanism.

Sputtering from rough tungsten surfaces: Data-driven molecular dynamics simulations

The sputtering of tungsten surfaces caused by hot plasma particles is an important process in fusion reactors where divertors are typically made of tungsten sheets. In this study, we present a molecular dynamics simulation strategy to investigate the sputtering yields of tungsten surfaces with geometrical defects. This should serve as a model for non-monocrystalline surfaces in general and could also be a rough model for nanoscale “fuzzy” layers, which are known to be formed by surface bombardment with energetic particles. Using a non-cumulative approach, we simulate the irradiation of tungsten surfaces with cone-shaped, cylindrical, and spherical defects by argon atoms. We analyze the sputtering yields as functions of particle energy and defect sizes. As a result, we find that surfaces with distinctly shaped defects always exhibit reduced sputtering yields, compared to smooth ones. We also investigate the angular distributions of sputtered particles and find them mostly to be in accordance with prior experimental and computational results.

Toward Morphologic Atlasing of the Human Whole Brain at the Nanoscale

Although no dataset at the nanoscale for the entire human brain has yet been acquired and neither a nanoscale human whole brain atlas has been constructed, tremendous progress in neuroimaging and high-performance computing makes them feasible in the non-distant future. To construct the human whole brain nanoscale atlas, there are several challenges, and here, we address two, i.e., the morphology modeling of the brain at the nanoscale and designing of a nanoscale brain atlas. A new nanoscale neuronal format is introduced to describe data necessary and sufficient to model the entire human brain at the nanoscale, enabling calculations of the synaptome and connectome. The design of the nanoscale brain atlas covers design principles, content, architecture, navigation, functionality, and user interface. Three novel design principles are introduced supporting navigation, exploration, and calculations, namely, a gross neuroanatomy-guided navigation of micro/nanoscale neuroanatomy; a movable and zoomable sampling volume of interest for navigation and exploration; and a nanoscale data processing in a parallel-pipeline mode exploiting parallelism resulting from the decomposition of gross neuroanatomy parcellated into structures and regions as well as nano neuroanatomy decomposed into neurons and synapses, enabling the distributed construction and continual enhancement of the nanoscale atlas. Numerous applications of this atlas can be contemplated ranging from proofreading and continual multi-site extension to exploration, morphometric and network-related analyses, and knowledge discovery. To my best knowledge, this is the first proposed neuronal morphology nanoscale model and the first attempt to design a human whole brain atlas at the nanoscale.