Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Thanks to their remarkable mechanical, electrical, thermal, and barrier properties, graphene-based nanocomposites have been a hot area of research in the past decade. Because of their simple top-down synthesis, graphene oxide (GO) and reduced graphene oxide (rGO) have opened new possibilities for gas barrier, membrane separation, and stimuli-response characteristics in nanocomposites. Herein, we review the synthesis techniques most commonly used to produce these graphene derivatives, discuss how synthesis affects their key material properties, and highlight some examples of nanocomposites with unique and impressive properties. We specifically highlight their performances in separation applications, stimuli-responsive materials, anti-corrosion coatings, and energy storage. Finally, we discuss the outlook and remaining challenges in the field of practical industrial-scale production and use of graphene-derivative-based polymer nanocomposites.

Synthesis, properties, and applications of graphene oxide/reduced graphene oxide and their nanocomposites

A strain sensor has been fabricated from a polymer nanocomposite with multiwalled carbon nanotube (MWNT) fillers. The piezoresistivity
of this nanocomposite strain sensor has been investigated based on an improved three-dimensional (3D) statistical resistor network
model incorporating the tunneling effect between the neighboring carbon nanotubes (CNTs), and a fiber reorientation model. The
numerical results agree very well with the experimental measurements. As compared with traditional strain gauges, much higher sensitivity
can be obtained in the nanocomposite sensors when the volume fraction of CNT is close to the percolation threshold. For a small
CNT volume fraction, weak nonlinear piezoresistivity is observed both experimentally and from numerical simulation. The tunneling
effect is considered to be the principal mechanism of the sensor under small strains.

Tunneling effect in a polymer/carbon nanotube nanocompositestrain sensor

The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. S. 211-215

Spatially-degraded adhesive anchors under material uncertainty

We report the supercapacitive performance of manganese oxide (MnO2)/single-walled carbon nanotube (SWCNT) buckypaper electrodes enabled via electrochemical deposition of MnO2 onto SWCNT buckypaper for the first time. The entangled SWCNT network provides electro-conductive pathways for the charge transfer. We demonstrate that the MnO2/SWCNT buckypaper supercapacitor exhibits a specific capacitance of 605 Fg−1 and gravimetric energy density of ∼120 Whkg−1. Furthermore, our MnO2/SWCNT buckypaper electrode shows excellent rate capability (85% capacity retention at 20 Ag−1) and long cycle life (1% capacity loss after 10,000 charge/discharge cycles). The excellent performance of MnO2/SWCNT buckypaper supercapacitor is attributed to the flower-like unique hierarchical porous architecture of MnO2 around SWCNTs arranged in “pearl necklace” formation, enabling large electrode/electrolyte interface and charge storage surface, better electrolyte penetration, and rapid charge transfer. The results suggest that the MnO2/SWCNT buckypaper electrode can provide excellent supercapacitive performance suitable for future generation electric vehicles.

MnO2/SWCNT buckypaper for high performance supercapacitors

In this study, atomistic based continuum (ABC) multiscale modeling approach is presented for strength and failure prediction of carbon nanotube (CNT) reinforced epoxy composite adhesives in bonded systems. Assuming that the CNTs are uniformly dispersed in the epoxy matrix , the mechanical properties of the nanocomposite adhesive are determined utilizing a two-step sequential homogenization procedure. In the first step, effective mechanical properties of a nanoscale representative volume element (RVE) are determined. The RVE comprises a CNT embedded in the epoxy matrix separated by an interphase . The structure-property relationship at the nanoscale is captured through ABC modeling approach wherein a CNT is modeled as a space-frame structure with beam elements and the epoxy is modeled using solid elements. The interphase between the CNT and the epoxy is modeled using non-linear spring elements to account for non-bonded van-der Waals interactions. In the second step, CNT inclusions with random orientations in the matrix are considered to create a microscale RVE of the nanocomposite. In both the steps, different boundary conditions were applied on the RVEs, and finite element (FE) analyses were conducted to estimate the effective mechanical properties through numerical homogenization. Furthermore, the strength of CNT/epoxy composite is estimated using modified Kelly-Tyson theory. Finally, modeling scheme proposed here is utilized to assess the load carrying capacity and failure behavior of a single lap-joint (SLJ) comprising composite adherends and CNT/epoxy nanocomposite adhesive by conducting continuum scale FE analyses. Results show over 30% improvement in strength for the SLJ with CNT/epoxy bondlayer comprising 2 vol% CNT. The findings of the study indicate that both strength and damage tolerance of the bonded joints can be significantly optimized utilizing nanoreinforced bondlayer.

Multiscale modeling of strength and failure behavior of carbon nanostructure reinforced epoxy composite adhesives in bonded systems

Lightweight cellular materials are engineered to enhance performance attributes such as energy absorption, specific stiffness, negative Poisson's ratio, negative thermal expansion coefficient, etc. However, self‐sensing functionality of such architected materials is seldom explored. Herein, a combined experimental and numerical study on additive manufacturing (AM)‐enabled self‐sensing cellular composites processed via fused filament fabrication, utilizing in‐house engineered multiwall carbon nanotube (MWCNT)/polypropylene random copolymer (PPR) filament feedstocks, is reported. The tunable self‐sensing and enhanced mechanical performance of PPR/MWCNT lattices are experimentally demonstrated by varying their architectural parameters in addition to the MWCNT content. The lattices reveal strain and damage sensitivity gauge factors of 12 and 1.2, respectively, comparable to bulk materials’ commercial gauge factors. Furthermore, self‐sensing lattices exhibit 200%, 155%, 153%, and 137% increase in stiffness, energy absorption capacity (as high as 4.7 MJ m−3), specific energy absorption (20.5 J g−1), and energy absorption efficiency (90%), respectively, compared with their non‐reinforced counterparts. The tunable multifunctional performance of AM‐enabled cellular composites demonstrated here provides guidelines for the design and development of composite lattices with advantaged structural and functional properties for an array of applications such as patient‐specific biomedical devices capable of measuring comfort in prosthetics.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/adem.202200194

Multifunctionality of Nanoengineered Self‐Sensing Lattices Enabled by Additive Manufacturing

The present paper reports the d.c. conductivity measurements at high electric fields in vacuum evaporated thin films of amorphous Se75In25−xPb
 x
 (0 < x < 10). Current-voltage (I-V) Characteristics have been measured at various fixed temperatures. In all the samples, at low electric fields, ohmic behavior is observed. However, at high electric fields (E∼ 104 V/cm), non-ohmic behavior is observed. In case of sample having 4 at.% of Pb, the experimental data fits well with the theory of space charge limited conduction (SCLC). From the fitting of the data, the density of defect states near Fermi level is calculated. Such type of behavior is not observed at higher concentration of Pb in the present glassy system.

Shanmugam Kumar

Papers

Spatially-degraded adhesive anchors under material uncertainty

MnO2/SWCNT buckypaper for high performance supercapacitors

Multiscale modeling of strength and failure behavior of carbon nanostructure reinforced epoxy composite adhesives in bonded systems

Multifunctionality of Nanoengineered Self‐Sensing Lattices Enabled by Additive Manufacturing

Space charge limited conduction in a-Se75In25?xPbx thin films