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

The GPR (Ground Penetrating Radar) conference in Hong Kong year 2016 marked the 30th anniversary of the initial meeting in Tifton, Georgia, USA on 1986. The conference has been being a bi-annual event and has been hosted by sixteen cities from four continents. Throughout these 30 years, researchers and practitioners witnessed the analog paper printout to digital era that enables very efficient collection, processing and 3D imaging of large amount of data required in GPR imaging in infrastructure. GPR has systematically progressed forward from “Locating and Testing” to “Imaging and Diagnosis” with the Holy Grail of ’Seeing the unseen’ becoming a reality. This paper reviews the latest development of the GPR’s primary infrastructure applications, namely buildings, pavements, bridges, tunnel liners, geotechnical and buried utilities. We review both the ability to assess structure as built character and the ability to indicate the state of deterioration. Finally, we outline the path to a more rigorous development in terms of standardization, accreditation, and procurement policy.

A review of Ground Penetrating Radar application in civil engineering: A 30-year journey from Locating and Testing to Imaging and Diagnosis

We have produced ultrathin epitaxial graphite films which show remarkable 2D electron gas (2DEG) behavior. The films, composed of typically 3 graphene sheets, were grown by thermal decomposition on the (0001) surface of 6H-SiC, and characterized by surface-science techniques. The low-temperature conductance spans a range of localization regimes according to the structural state (square resistance 1.5 kOhm to 225 kOhm at 4 K, with positive magnetoconductance). Low resistance samples show characteristics of weak-localization in two dimensions, from which we estimate elastic and inelastic mean free paths. At low field, the Hall resistance is linear up to 4.5 T, which is well-explained by n-type carriers of density 10^{12} cm^{-2} per graphene sheet. The most highly-ordered sample exhibits Shubnikov - de Haas oscillations which correspond to nonlinearities observed in the Hall resistance, indicating a potential new quantum Hall system. We show that the high-mobility films can be patterned via conventional lithographic techniques, and we demonstrate modulation of the film conductance using a top-gate electrode. These key elements suggest electronic device applications based on nano-patterned epitaxial graphene (NPEG), with the potential for large-scale integration.

Ultrathin epitaxial graphite: 2D electron gas properties and a route toward graphene-based nanoelectronics

Nanotechnology innovations for the construction industry

Depending on their structure and order (individual, films, bundled, buckypapers, etc.), carbon nanotubes (CNTs) demonstrate different values of thermal conductivity, from the level of thermal insulation with the thermal conductivity of 0.1 W/mK to such high values as 6600 W/mK. This review article concentrates on analyzing the articles on thermal conductivity of CNT networks. It describes various measurement methods, such as the 3-ω method, bolometric, steady-state method and their variations, hot-disk method, laser flash analysis, thermoreflectance method and Raman spectroscopy, and summarizes the results obtained using those techniques. The article provides the main factors affecting the value of thermal conductivity, such as CNT density, number of defects in their structure, CNT ordering within arrays, direction of measurement in relation to their length, temperature of measurement and type of CNTs. The practical methods of using CNT networks and the potential directions of future research in that scope were also described.

/pdf/thermal-conductivity-of-carbon-nanotube-networks-a-review-f9w77k4rp8.pdf

Thermal conductivity of carbon nanotube networks: a review

The assessment of pavement conditions and their evolution with time is a crucial component for the establishment of pavement quality management (QM) plans and the implementation of QM practices. An effective pavement management system (PMS) is based on pavement conditions data continuously collected along the lifetime of a road. These data are used to model the pavement response, evaluate its performances, and trigger the necessary maintenance actions when they do not meet previously defined performance indicators. In the last decades, pavement monitoring via embedded sensing technologies has attracted more and more attention. Indeed, the integration of sensors in the road pavement allows the assessment of the complete history of pavement conditions, starting from sensor installation. Once the technologies are stabilized, collecting this information is expected to help road managers to define more effective asset management plans. This paper first proposes an overview of the most used devices for pavement instrumentation, categorized according to the measured parameters. Then a review of some prominent instrumented sections is presented by focusing on the methodology used for data interpretation.

https://www.mdpi.com/2412-3811/5/2/18/pdf

In Situ Pavement Monitoring: A Review

A cMUT-type capacitive electroacoustic transducer including: at least one membrane configured to oscillate under effect of an electric field and/or an acoustic wave, wherein the membrane is formed from one or more layers of juxtaposed nanotubes or nanowires or nanorods, and an acoustic imaging device or UHF sonar including such transducers.

Cmut cell formed from a membrane of nanotubes or nanowires or nanorods and device for ultra high frequency acoustic imaging including multiple cells of this kind

We investigate the interaction of polyfluorene and fluorene/carbazole copolymers bearing various functional groups and side chains with small to large diameter—from 1.7 nm to 9 nm—carbon nanotubes (CNTs) in vacuo. We use variable-charge molecular dynamics simulations based on the reactive force field ReaxFF. We show that non-covalent functionalization of nanotubes, driven by π − π interactions, is effective for all the polymers studied, thanks to their conjugated backbone and regardless of the presence of specific functional groups. The geometry at equilibrium of these polymer/CNT hybrids is analyzed in detail at the scale of each fluorene or carbazole unit. The role of both the functional groups and the alkyl chain length is analyzed in detail. Adsorption of the polymers on the nanotube sidewalls is shown to be either complete—with the whole chain physisorbed—or partial—due to intrachain coiling or interchain repulsion—depending on the initial geometry, number of polymers, and nanotube diameter. Energetic arguments supplement the described geometric features. Both energetic and geometric adsorption features are derived here for the first time for large diameter carbon nanotubes (up to 9 nm) and fluorene/carbazole copolymers having up to 30 monomers and bearing different functional groups. The force field ReaxFF and its available parameterization used for the simulations are validated, thanks to a benchmark and review on higher-level quantum calculations—for simple π − π interacting compounds made up of polycyclic aromatic molecules adsorbed on a graphene sheet or bilayer graphene. Although it is shown that the influence of the nanotube chirality on the adsorption pattern and binding strength cannot be discussed with our method, we highlight that an available force field such as ReaxFF and its parameterization can be transferable to simulate new systems without specific re-parameterization, provided that this model is validated against reference methods or data. This methodology proves to be a valuable tool for optimal polymer design for nanotube functionalization at no re-parameterization cost and could be adapted to simulate and assist the design of other types of molecular systems.

/pdf/insights-into-the-p-p-interaction-driven-non-covalent-2uhrg5mjqy.pdf

Insights into the π – π interaction driven non-covalent functionalization of carbon nanotubes of various diameters by conjugated fluorene and carbazole copolymers

We study by means of Monte-Carlo numerical simulations the resistance of two-dimensional random percolating networks of stick, widthless nanowires. We use the multi-nodal representation (MNR) to model a nanowire network as a graph. We derive numerically from this model the expression of the total resistance as a function of all meaningful parameters, geometrical and physical, over a wide range of variation for each. We justify our choice of non-dimensional variables applying Buckingham $\pi-$theorem. The effective resistance of 2D random percolating networks of nanowires is found to write as $R^{eq}(\rho,R_c,R_{m,w})=A\left(N,\frac{L}{l^{*}}\right) \rho l^* + B\left(N,\frac{L}{l^{*}}\right) R_c+C\left(N,\frac{L}{l^*} \right) R_{m,w}$ where $N$, $\frac{L}{l^{*}}$ are the geometrical parameters (number of wires, aspect ratio of electrode separation over wire length) and $\rho$, $R_c$, $R_{m,w}$ are the physical parameters (nanowire linear resistance per unit length, nanowire/nanowire contact resistance, metallic electrode/nanowire contact resistance). The dependence of the resistance on the geometry of the network, one the one hand, and on the physical parameters (values of the resistances), on the other hand, is thus clearly separated thanks to this expression, much simpler than the previously reported analytical expressions.

Effective resistance of random percolating networks of stick nanowires : functional dependence on elementary physical parameters

We study by means of Monte Carlo numerical simulations the resistance of two-dimensional random percolating networks of stick, widthless nanowires. We use the multinodal representation [C. G. da Rocha et al., Nanoscale 7, 13011 (2015)] to model a nanowire network as a graph. We derive numerically from this model the expression of the total resistance as a function of all meaningful parameters, geometrical and physical, over a wide range of variation for each. We justify our choice of nondimensional variables by applying the Buckingham π-theorem. The effective resistance of 2D random percolating networks of nanowires is written as R e q ( ρ , R c , R m , w ) = A ( N , L l ∗ ) ρ l ∗ + B ( N , L l ∗ ) R c + C ( N , L l ∗ ) R m , w, where N and L l ∗ are the geometrical parameters (number of wires and aspect ratio of electrode separation over wire length) and ρ, R c, and R m , w are the physical parameters (nanowire linear resistance per unit length, nanowire/nanowire contact resistance, and metallic electrode/nanowire contact resistance). The dependence of the resistance on the geometry of the network, on the one hand, and on the physical parameters (values of the resistances), on the other hand, is thus clearly separated, thanks to this expression, much simpler than the previously reported analytical expressions.We study by means of Monte Carlo numerical simulations the resistance of two-dimensional random percolating networks of stick, widthless nanowires. We use the multinodal representation [C. G. da Rocha et al., Nanoscale 7, 13011 (2015)] to model a nanowire network as a graph. We derive numerically from this model the expression of the total resistance as a function of all meaningful parameters, geometrical and physical, over a wide range of variation for each. We justify our choice of nondimensional variables by applying the Buckingham π-theorem. The effective resistance of 2D random percolating networks of nanowires is written as R e q ( ρ , R c , R m , w ) = A ( N , L l ∗ ) ρ l ∗ + B ( N , L l ∗ ) R c + C ( N , L l ∗ ) R m , w, where N and L l ∗ are the geometrical parameters (number of wires and aspect ratio of electrode separation over wire length) and ρ, R c, and R m , w are the physical parameters (nanowire linear resistance per unit length, nanowire/nanowire ...

https://hal.archives-ouvertes.fr/hal-02281362/document

Bérengère Lebental

Papers

In Situ Pavement Monitoring: A Review

Cmut cell formed from a membrane of nanotubes or nanowires or nanorods and device for ultra high frequency acoustic imaging including multiple cells of this kind

Insights into the π – π interaction driven non-covalent functionalization of carbon nanotubes of various diameters by conjugated fluorene and carbazole copolymers

Effective resistance of random percolating networks of stick nanowires : functional dependence on elementary physical parameters

Effective resistance of random percolating networks of stick nanowires: Functional dependence on elementary physical parameters