Electronic structure, transport, and collective effects in molecular layered systems

• Torsten Hahn,
• Tim Ludwig,
• Carsten Timm and
• Jens Kortus

Beilstein J. Nanotechnol. 2017, 8, 2094–2105, doi:10.3762/bjnano.8.209

• interaction can be treated essentially exactly using Monte Carlo simulations [15]. The main idea is to use the sequential-tunneling rates, which are analogous to Equation 5 and uniform throughout the monolayer, to determine the probabilities of local Monte Carlo updates. Importantly, these rates depend on the

• independent of the occupation of the neighboring sites. Thus the layer decouples into independent sites. Moreover, forward and backward rates are always equal, Rn→m = Rm→n, so that the system is equivalent to a model at infinite temperature. For the other regions, we have performed Monte Carlo simulations as

Investigation of growth dynamics of carbon nanotubes

• Marianna V. Kharlamova

Beilstein J. Nanotechnol. 2017, 8, 826–856, doi:10.3762/bjnano.8.85

• dependent on the synthesis time. At short times (40 s and 2 min), the perpendicular growth was observed, whereas at long times (10 and 30 min) the tangential mode was dominant. Using tight binding Monte Carlo simulations, it was shown that the tangential growth occurs at reaction conditions that are close

Plasticity-mediated collapse and recrystallization in hollow copper nanowires: a molecular dynamics simulation

• Amlan Dutta,
• Arup Kumar Raychaudhuri and
• Tanusri Saha-Dasgupta

Beilstein J. Nanotechnol. 2016, 7, 228–235, doi:10.3762/bjnano.7.21

• the dominating mechanism. Accordingly, analytical theories and Monte Carlo simulations based on the process of thermally activated diffusion process have been developed and carried out [12]. However, the proposed mechanism of collapse via migration of vacancies from the inner core to the outer surface

How decision analysis can further nanoinformatics

• Matthew E. Bates,
• Sabrina Larkin,
• Jeffrey M. Keisler and
• Igor Linkov

Beilstein J. Nanotechnol. 2015, 6, 1594–1600, doi:10.3762/bjnano.6.162

• literature. Monte Carlo simulations were used to normalize and aggregate individual criteria distributions into distributions of overall performance using criteria weights associated with preferences of different key stakeholders [20]. After developing result distributions that reflect current uncertainties

• , the study evaluated research that might best improve decision confidence. Monte Carlo simulations of possible research outcomes (to reduce uncertainty in the input data) and decision outcomes (resulting reduced uncertainty in the distributions of overall scores) were produced for each nanomaterial

• means of MCDA. Uncertainties derived from expert judgment were considered in Monte Carlo simulations [24]. As with MCDA, once the WOE hazard score is determined, each contributor to the hazard score can be further reviewed to see which had the largest effect on the score and which might benefit from

Surface excitations in the modelling of electron transport for electron-beam-induced deposition experiments

• Francesc Salvat-Pujol,
• Roser Valentí and
• Wolfgang S. Werner

Beilstein J. Nanotechnol. 2015, 6, 1260–1267, doi:10.3762/bjnano.6.129

• of partial-wave calculations [48][49]. Inelastic scattering is accounted for by the DIIMFPs described above. Monte-Carlo simulations of electron transport (bulk losses only) for typical geometries in FEBID experiments have been previously considered [2][7]. The inclusion of surface excitations

• Figure 5. The Monte Carlo simulations further allow one to discern the processes that give rise to the different regions of the coincidence spectrum [55]. Thus, it was found that any realistic model of SE emission and low-energy electron transport near solid surfaces must account for surface excitations

Scanning reflection ion microscopy in a helium ion microscope

• Yuri V. Petrov and
• Oleg F. Vyvenko

Beilstein J. Nanotechnol. 2015, 6, 1125–1137, doi:10.3762/bjnano.6.114

• reflection coefficient of the ions, which are incident and reflected at low grazing angles, is not sensitive to the atomic number of the sample material, and the contrast in RI images is determined mostly by the surface morphology. This experimental fact is in agreement with the results of the Monte Carlo

• simulations of the angular dependence of the ion reflection coefficient. Accordingly, RIM can be used for the imaging of surface morphology but not for the imaging of surface composition. The obtained experimental results show that there are some quantitative differences in the surface morphology imaging

Fabrication of high-resolution nanostructures of complex geometry by the single-spot nanolithography method

• Alexander Samardak,
• Margarita Anisimova,
• Aleksei Samardak and
• Alexey Ognev

Beilstein J. Nanotechnol. 2015, 6, 976–986, doi:10.3762/bjnano.6.101

• silicon substrates, gold-coated substrates can also successfully be used for the single-spot nanopattering technique. An explanation of the results related to the resist overexposure was demonstrated using Monte Carlo simulations. Our nanofabrication method significantly accelerates (up to 10 times) the

• (Figure 3). Even at a dose of 2.5 pC, the ring on the Au substrate is still smaller than that patterned onto the Si substrate at a dose 0.35 pC. Our experimental findings are supported by Monte Carlo simulations performed with NanoPECS software [17]. In the case of the Si substrate, most of the electrons

• trajectory distribution of electrons produced by Monte Carlo simulations shows that the upper third part of the pillar is very narrow and can be easily removed by developer (Figure 4). Figure 6 shows the experimental dependence of the outer diameter dout and the core diameter din on the radiation dose for

Electron-stimulated purification of platinum nanostructures grown via focused electron beam induced deposition

• Brett B. Lewis,
• Michael G. Stanford,
• Jason D. Fowlkes,
• Kevin Lester,
• Harald Plank and
• Philip D. Rack

Beilstein J. Nanotechnol. 2015, 6, 907–918, doi:10.3762/bjnano.6.94

• atomic oxygen at nanoparticle surfaces. ΦO2 is the impingement rate of mobile O2 on the nanoparticle surface (this parameter is derived from Monte Carlo simulations of a diffusing test particle impinging on a spherical nanoparticle and will be discussed in detail in the future publication) and depends on

Capillary and van der Waals interactions on CaF₂ crystals from amplitude modulation AFM force reconstruction profiles under ambient conditions

• Annalisa Calò,
• Oriol Vidal Robles,
• Sergio Santos and
• Albert Verdaguer

Beilstein J. Nanotechnol. 2015, 6, 809–819, doi:10.3762/bjnano.6.84

• worth to point out that force vs distance evolutions changing from almost linear decays to abrupt jumps followed by a constant plateau have been shown in function of the increasing relative vapor pressure in Monte Carlo simulations of the interaction forces between nanoparticles [13] and between a rigid

Fundamental edge broadening effects during focused electron beam induced nanosynthesis

• Roland Schmied,
• Jason D. Fowlkes,
• Robert Winkler,
• Phillip D. Rack and
• Harald Plank

Beilstein J. Nanotechnol. 2015, 6, 462–471, doi:10.3762/bjnano.6.47

• measurements. Monte Carlo simulations for radial BSE distributions have been performed by using the software package CASINO v2.42 [48] assuming the AFM-measured deposit values and a typical PtC5 chemistry for such FEBID deposition conditions. All emission profiles were subsequently re-normalized to areal

Nanoporous Ge thin film production combining Ge sputtering and dopant implantation

• Jacques Perrin Toinin,
• Alain Portavoce,
• Khalid Hoummada,
• Michaël Texier,
• Maxime Bertoglio,
• Sandrine Bernardini,
• Marco Abbarchi and
• Lee Chow

Beilstein J. Nanotechnol. 2015, 6, 336–342, doi:10.3762/bjnano.6.32

• classical theories of the stopping of ions in matter and Monte Carlo simulations: the energy loss of ions in matter are calculated and used to provide stopping powers, range and straggling distributions of implanted ions. In addition, the kinetic effects associated with the physics of implantation-mediated

Si/Ge intermixing during Ge Stranski–Krastanov growth

• Alain Portavoce,
• Khalid Hoummada,
• Antoine Ronda,
• Dominique Mangelinck and
• Isabelle Berbezier

Beilstein J. Nanotechnol. 2014, 5, 2374–2382, doi:10.3762/bjnano.5.246

• [41]. Ordered domains were shown to be located in a limited region of the islands, and LeGoues et al. [42] showed that Si/Ge ordering is likely linked to surface reconstruction. Recently, atom-scale Monte Carlo simulations showed that ordering domains in dome islands could indeed correspond to a

Synthesis, characterization, and growth simulations of Cu–Pt bimetallic nanoclusters

• Subarna Khanal,
• Ana Spitale,
• Nabraj Bhattarai,
• Daniel Bahena,
• J. Jesus Velazquez-Salazar,
• Sergio Mejía-Rosales,
• Marcelo M. Mariscal and
• Miguel José-Yacaman

Beilstein J. Nanotechnol. 2014, 5, 1371–1379, doi:10.3762/bjnano.5.150

• are good catalysts for the ORR. Yun and co-workers [34] developed a unified embedded atom model to investigate the most energetically favorable atomic arrangements of Pd–Pt, Cu–Pt, Au–Pt and Ag–Pt nanoalloys using Monte Carlo simulations, obtaining intermetallic compounds for the Pd–Pt system, onion

Electron-beam induced deposition and autocatalytic decomposition of Co(CO)₃NO

• Florian Vollnhals,
• Martin Drost,
• Fan Tu,
• Esther Carrasco,
• Andreas Späth,
• Rainer H. Fink,
• Hans-Peter Steinrück and
• Hubertus Marbach

Beilstein J. Nanotechnol. 2014, 5, 1175–1185, doi:10.3762/bjnano.5.129

• enhanced yield of backscattered electrons (BSE) and thereby induced secondary electrons. Indeed, Monte-Carlo simulations using the software CASINO (v. 2.42) [27] show an increase in the BSE emission coefficient by more than 20% for a 5 nm layer of Co0.51O0.24N0.14C0.11 (composition reported by Gazzadi et

Simulation of electron transport during electron-beam-induced deposition of nanostructures

• Francesc Salvat-Pujol,
• Harald O. Jeschke and
• Roser Valentí

Beilstein J. Nanotechnol. 2013, 4, 781–792, doi:10.3762/bjnano.4.89

• ] mainly consist of equations for the deposition rate, which can either be solved analytically under simplifying assumptions or in a more general form by using Monte Carlo simulations. However, there is no theory that addresses the multi-scale nature of the EBID process, including microscopic and

• ]. Recently, practical Monte Carlo simulations of EBID nanostructure growth have been reported [10][11][12][13] on the basis of simplified transport models based, e.g., on the Rutherford cross section or on a plural-scattering scheme. The latter averages the inelastic scattering of electrons in solids by

• presented the results of Monte Carlo simulations of the electron transport that provide valuable insight into the charge and energy deposition processes induced by the primary electron beam in the EBID process of W(CO)6 nanostructures on SiO2 substrates. The simulations highlight the differences in the

Ni nanocrystals on HOPG(0001): A scanning tunnelling microscope study

• Michael Marz,
• Keisuke Sagisaka and
• Daisuke Fujita

Beilstein J. Nanotechnol. 2013, 4, 406–417, doi:10.3762/bjnano.4.48

• comment on the possibility of carbon interdiffusion into the clusters. Sinharoy and Levenson showed the formation and decomposition of Ni3C in Ni-films deposited on HOPG [24]. Additionally, it is also known from Monte Carlo simulations by Diarra et al. that the solubility of carbon in Ni is significantly

Characterization and properties of micro- and nanowires of controlled size, composition, and geometry fabricated by electrodeposition and ion-track technology

• Maria Eugenia Toimil-Molares

Beilstein J. Nanotechnol. 2012, 3, 860–883, doi:10.3762/bjnano.3.97

Focused electron beam induced deposition: A perspective

• Michael Huth,
• Fabrizio Porrati,
• Christian Schwalb,
• Marcel Winhold,
• Roland Sachser,
• Maja Dukic,
• Jonathan Adams and
• Georg Fantner

Beilstein J. Nanotechnol. 2012, 3, 597–619, doi:10.3762/bjnano.3.70

• of the surface-leaving electrons is very important for FEBID, in particular since the dissociation cross sections tend to be larger at low energies, Monte Carlo simulations, describing in detail the electron transport in the substrate and deposit, provide important insights [8][9]. For the purpose of

• modeling approach presented in the next section effectively incorporates the contribution of secondary electrons. The influence of forward-scattered electrons is important for high-aspect-ratio FEBID structures and can be properly accounted for in Monte Carlo simulations [8][9]. Deposit microstructure: The

• density assuming an energy-integrated dissociation cross section σ. The electron flux profile f(r) at the sample surface is taken to be radially symmetric and can be obtained from Monte Carlo simulations of the electron–solid interaction. Under these conditions the radially symmetric rate equation reads

Nanolesions induced by heavy ions in human tissues: Experimental and theoretical studies

• Marcus Bleicher,
• Lucas Burigo,
• Marco Durante,
• Maren Herrlitz,
• Michael Krämer,
• Igor Mishustin,
• Iris Müller,
• Francesco Natale,
• Igor Pshenichnov,
• Stefan Schramm,
• Gisela Taucher-Scholz and
• Cathrin Wälzlein

Beilstein J. Nanotechnol. 2012, 3, 556–563, doi:10.3762/bjnano.3.64

• . Keywords: DNA repair; heavy ions; microdosimetry; Monte Carlo simulations; nanolesions; radiation-induced nanostructures; Introduction In a low-dose field of γ-rays, such as that normally experienced on Earth due to background radiation, each human cell is traversed by very few electrons, which hence

• . We have also started a full-genome deep-sequencing approach to correlate the microscopy data with the cellular response. In principle, the nanolesion structure can be predicted by accurate Monte Carlo simulations of the energy deposition by the projectile and of the target structure. We used the

Spontaneous dissociation of Co₂(CO)₈ and autocatalytic growth of Co on SiO₂: A combined experimental and theoretical investigation

• Kaliappan Muthukumar,
• Harald O. Jeschke,
• Roser Valentí,
• Evgeniya Begun,
• Johannes Schwenk,
• Fabrizio Porrati and
• Michael Huth

Beilstein J. Nanotechnol. 2012, 3, 546–555, doi:10.3762/bjnano.3.63

• electrodes was formed, whose outline represents a slightly blurry replica of the previously activated region. According to our Monte Carlo simulations using CASINO V2.42 [51] the extent of the blurred region corresponds roughly to the range of the backscattered electrons. Additional islands of the

Size-dependent phase diagrams of metallic alloys: A Monte Carlo simulation study on order–disorder transitions in Pt–Rh nanoparticles

• Johan Pohl,
• Christian Stahl and
• Karsten Albe

Beilstein J. Nanotechnol. 2012, 3, 1–11, doi:10.3762/bjnano.3.1

• Johan Pohl Christian Stahl Karsten Albe Institut für Materialwissenschaft, Technische Universität Darmstadt, Petersenstr. 32, D-64287 Darmstadt, Germany 10.3762/bjnano.3.1 Abstract Nanoparticles of Pt–Rh were studied by means of lattice-based Monte Carlo simulations with respect to the stability

• ]. More general thermodynamic treatments of phase separation in nanoparticles were given by Wautelet et al. [22] and Norskov et al. [21]. The latter authors focused especially on phase equilibria of immiscible Ag–Cu nanoparticles by means of Monte Carlo simulations and found that for all studied alloys

• were studied by means of lattice Monte Carlo simulations [25]. However, as far as we know, a complete size-dependent phase diagram of an ordering nanoalloy has not yet been studied. It is our intention to examine such a size-dependent phase diagram by using the model system of Pt–Rh particles and

Kinetic lattice Monte-Carlo simulations on the ordering kinetics of free and supported FePt L1₀-nanoparticles

• Michael Müller and
• Karsten Albe

Beilstein J. Nanotechnol. 2011, 2, 40–46, doi:10.3762/bjnano.2.5

• species to the interface. In cases where wetting of the substrate or surface facetting occurs, we find that diffusional atomic motion on the surface goes along with an enhanced long-range order. Keywords: FePt; Monte-Carlo simulations; nanoparticles; ordering kinetics; Introduction Nanoparticles in

• correct stacking sequence. In this paper, we present lattice-based kinetic Monte-Carlo simulations of FePt nanoparticles that reveal the influence of free surfaces, bulk vacancies and interaction with a substrate on the disorder–order transition. After describing the methodology, the case of a free

• phase which is due to the lack of vacancies. The kinetic Monte-Carlo simulations of the free FePt nanoparticles were terminated after approximately 30 s of real annealing time which corresponds to one month of computing time. This low efficiency of the algorithm originates from the sampling of the