A Monte Carlo estimation of the mean residence time in cells surrounded by thin layers

International audienceWe present a new Monte Carlo method to estimate the mean-residence time of a diffusive particle in a domain surrounded by a thin layer of low diffusivity. Through a homogenization technique, the layer is identified with a membrane. The simulations use a stochastic process called the snapping out Brownian motion the density of which matches suitable transmission conditions at the membrane. We provide a benchmark test which is a simplified form of a real-life problem coming from brain imaging techniques. We also provide a new algorithm to adaptively estimate the exponential rate of the tail of the distribution function of the probability to be in the domain using Monte Carlo simulations

Estimation of the mean residence time in cells surrounded by semi-permeable membranes by a Monte Carlo method

This report aims at validating a Monte Carlo algorithm to simulate the behavior of diffusive particles in a mediawith semi-permeables membranes seen as approximationsof a thin layer problems. Following some homogenization approachfor solving a diffusion Magnetic Resonance Imaging problem (dMRI), we estimate themean residence time inside a cell living a in one-dimensional periodicmedia and compare the estimated value with the one computedby solving an eigenvalue problem. The numerical analysis shows a good agreement, unless the strength of the membraneis too strong

Geo-neutrinos

We review a new interdisciplinary field between Geology and Physics: the study of the Earth's geo-neutrino flux. We describe competing models for the composition of the Earth, present geological insights into the make up of the continental and oceanic crust, those parts of the Earth that concentrate Th and U, the heat producing elements, and provide details of the regional settings in the continents and oceans where operating and planned detectors are sited. Details are presented for the only two operating detectors that are capable of measuring the Earth's geo-neutrinos flux: Borexino and KamLAND; results achieved to date are presented, along with their impacts on geophysical and geochemical models of the Earth. Finally, future planned experiments are highlighted

Modelling CdTe thin film growth over realistic time scales

Cadmium Telluride (CdTe) is an excellent material for low-cost, high efficiency thin-film solar cells and holds the record for watts/cost performance. The laboratory record efficiency of CdTe solar cells lags significantly behind the theoretical maximum for the material. This discrepancy is often attributed to defects such as grain boundaries and dislocations. Thus it is important to do research on how these defects are formed during the growth process. Atomistic simulations, such as Molecular Dynamics (MD) and on-the-fly Kinetic Monte Carlo (OTF-KMC), are widely used in partnership with experiments in addressing problems in materials science. In this work we use computer simulation to predict the growth of the sputter deposited CdTe thin film. At the first stage, MD studies of small cluster energetic impacts were carried out by repeatedly depositing CdxTey (x, y = 0, 1) clusters onto different CdTe surfaces with different energies at random positions. The impacts were simulated on Cd- and Te-terminated (100) surfaces and Cd- and Te-terminated (111) surfaces with typical industrial energies varies from 1 to 40 eV at a temperature of 350 K. More than 1,000 simulations have been preformed for each of these cases so as to sample the possible deposition positions and to collect sufficient statistics. The behaviour of deposited clusters under different conditions are studies. To simulate the process of thin film growth is the next stage in this work. We use different techniques to simulate the growth process on different surfaces. OTF-KMC simulations are performed to simulate the thin film growth process on the (111) CdTe surfaces. Starting with several ad-atoms deposited on the surfaces, in each step, the OTF-KMC method searches for all possible atomic movements (transitions) and randomly selects a transition or deposition to execute based on their corresponding rates. The thin film grows with more and more clusters to be deposited onto the surface with numerous ad-atom diffusions. The growth process on the dimerised Te-terminated (100) surface is very interesting. Knowledge of how the Te dimers on the surface split during the growth is gained in the simulations. MD is used to simulate the growth process with an accelerated deposition rate. Several simulations with different deposition energies are performed to see the differences of dissociation of the surface Te dimers. Post-annealing at different temperatures are applied after the growth simulations to find the optimal annealing temperature

Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall-Runoff) model

Acknowledgements. This work was funded by the NERC/JPI SIWA project (NE/M019896/1) and the European Research Council ERC (project GA 335910 VeWa). Numerical simulations were performed using the Maxwell High Performance Computing Cluster of the University of Aberdeen IT Service, provided by Dell Inc. and supported by Alces Software. The isotope work in Krycklan is funded by the KAW Branch-Point project together with SKB and SITES. We would like to thank Marjolein van Hui- jgevoort for her help with the STARR code, and Masaki Hayashi and two anonymous reviewers for their insightful suggestions that significantly improved the paper. The Supplement related to this article is available online at https://doi.org/10.5194/hess-21-5089-2017-supplement.Peer reviewedPublisher PD

Atomistic Simulations of Ge on Amorphous Silica Substrates

High-quality Ge substrates have numerous applications, including high-efficiency III-V multijunction solar cells and photodetectors. But the high cost of single-crystalline Ge makes the use of Ge-on-Si virtual substrates more practical for device fabrication. However, the lattice mismatch between Ge and Si leads to a highly strained Ge layer when grown directly on the Si lattice. The high mismatch strain unavoidably leads to defects, primarily dislocations, that degrade the Ge film quality. Several approaches for mitigating these defects have been proposed, including selective epitaxial growth (SEG), in which one employs an amorphous layer (most often SiO2) as a mask to reduce the epitaxial contact between the Ge and Si lattices to lower the mismatch strain. SEG has been demonstrated to successfully produce high-quality Ge films on Si, although defects are not fully eliminated. Further improvements will require quantitative understanding of the underlying atomic-scale mechanisms. In this work, we present a computational framework to atomistically model the components of the SEG system (Si/SiO2/Ge). The model is validated by comparing predictions to experimental observations and ab initio calculations of various properties related to crystalline Si and Ge and amorphous SiO2, as well as combinations of these materials. The framework is then applied to study in detail the deposition of Ge on amorphous SiO2. It is shown that the simulations are able to access experimentally meaningful deposition conditions and reproduce several quantities related to the island size distribution. We then extend our simulation framework for deposition to include coarse projective integration (CPI). CPI is a multiscale modeling technique well-suited for situations, like atomic deposition, in which a system exhibits fast, stochastic processes, superposed onto slowly-evolving dynamics. In particular, we demonstrate an approach for generating atomistic configurations from limited knowledge of an island size distribution, which represents one of the key challenges in applying CPI to atomistic deposition. The results generated here should be easily adaptable to other deposition systems

Multi-compartmental MR measurements of the prostate

Purpose A large proportion of the diagnosed prostate cancer patients are suffering from low grade or indolent tumours. Transrectal ultrasound guided biopsy which is conventionally used as the means of diagnosis has a weak correlation with cancer grade or aggressiveness because of its random sampling nature, so that many indolent tumours are treated aggressively with serious side effects. Quantitative magnetic resonance imaging has shown relative success in distinguishing aggressive tumours. It is important to assess the feasibility of different MR modalities such as T2 or diffusion weighted imaging and to optimise them. Methods A variety of biophysical analyses were performed to find correlations between diffusion and T2 weighted magnetic resonance parameters and the changes in complex compartmental structure of the prostate (consisting of ducts, epithelial and stromal cells, and vascularity) with increasing cancer grade. For this aim, Monte Carlo simulations of a semi-restricted compartment (ductal lumen) and two compartmental exchange model (stromal-epithelial or cellular compartment) were used. Additionally, optimisations were performed for T2 and diffusion weighted imaging protocols. Results The biexponential model for diffusion explicitly explained the biophysical changes in prostate cancer. The fast and slow ADC values respectively varied from 2.36 and 0.9 μm2ms-1 in healthy prostate to around 1 and 0.5 μm2ms-1 in the most aggressive tumours. Biexponential T2 acquisitions were optimised to distinguish indolent tumours. There was a 10-20% reduction in estimation errors compared to equally distanced acquisitions, if the target values of T2slow and T2fast were respectively 360 and 60 ms. The optimisations were extended to non-Gaussian diffusion weighted imaging protocols. Conclusion In order to substantially improve the diagnostic accuracy of prostate cancer MR acquisitions, it is recommended to consider the biophysical model and the optimised protocols introduced here. Also, diffusion time and other acquisition details should be considered prior to the imaging

Modelling zinc oxide thin-film growth

Photovoltaics have a significant role in the solution of energy supply and energy security. Research on photovoltaic devices and their production processes has been carried out for decades. The transparent conducting oxide layer, in the photovoltaic solar cell, composed of aluminium doped zinc oxide, is produced through deposition techniques. By modelling these depositions using classical molecular dynamics, a better understanding on the short term kinetics occurring on the growing surface has been achieved. Compared to the molecular dynamics, the employment of the adaptive kinetic Monte Carlo method enabled such surface growth dynamics simulation to reach much longer time scale. Parallelised transition searching was carried out in an on-the-fly manner without lattice approximation or predefined events table. The simulation techniques allowed deposition conditions to be easily changed, such as deposition energy, deposition rate, substrate temperature, plasma pressure, etc. Therefore, in this project three main deposition techniques were modelled including evaporation (thermal and assisted electron beam), reactive magnetron sputtering and pulsed laser depositions. ZnO as a covalent compound with many uses in semiconductors was investigated in its most energy favourable wurtzite configuration. The O-terminated surface was used as the substrate for the growth simulation. Evaporation deposition at room temperature (300 K) with a stoichiometric distribution of deposition species produced incomplete new layers. Holes were observed existing for long times in each layer. Also, stacking faults were formed during the low-energy (1 eV) growth through evaporation. The reactive sputtering depositions were more capable of getting rid of these holes structures and diminished these stacking faults through high energy bombardments but could also break these desirable crystalline structure during the growth. However, single deposition results with high energies showed that the ZnO lattice presented good capacity of self-healing after energetic impacts. Additionally, such self-healing effects were seen for substrate surface during thin film growth by the sputtering depositions. These facts shed some light on that the sputtering technique is the method of choice for ZnO thin film depositions during industrial production. Simulation results of pulsed laser deposition with separated Zn and O species showed the thin films were grown in porous structures as the O-terminated surface could be severely damaged by Zn atoms during the very short pulse window (10 microseconds). An important growth mechanism with ZnO dimer deposited on the O-terminated polar surface was the coupling of these single ZnO dimers, forming highly mobile strings along the surface and thus quenching its dipole moments, whilst the isolated single ZnO dimers were hardly of this mobility. Such strings were the building blocks for the fabrication occurring on the surface resulting in new layers. Last but not least, a reactive force field for modelling Al doped ZnO was fitted. DFT calculations showed that the Al atoms on the surface were likely to replace Zn atoms in their lattice sites for more energy favourable structures. Al on the ZnO surfaces, structures with Al in the bulk as well as configurations with Al interstitials were used to train the force field to reproduce favourable surface binding sites, cohesive energies and lattice dimensions. The combination scheme of MD and the AKMC allowed simulation work to reach over experimentally realistic time scale. Therefore, crucial mechanisms occurring during the growth could be precisely understood and investigated on an atomistic level. It has been shown from the simulation results that certain types of deposition play significant roles in the quality of resultant thin films and surface morphology, thus providing insight to the optimal deposition conditions for growing complete crystalline ZnO layers

The Effect of Hyperthermia on Doxorubicin Therapy and Nanoparticle Penetration in Multicellular Ovarian Cancer Spheroids

The efficient treatment of cancer with chemotherapy is challenged by the limited penetration of drugs into the tumor. Nanoparticles (10 – 100 nanometers) have emerged as a logical choice to specifically deliver chemotherapeutics to tumors, however, their transport into the tumor is also impeded owing to their bigger size compared to free drug moieties. Currently, monolayer cell cultures, as models for drug testing, cannot recapitulate the structural and functional complexity of in-vivo tumors. Furthermore, strategies to improve drug distribution in tumor tissues are also required. In this study, we hypothesized that hyperthermia (43°C) will improve the distribution of silica nanoparticles in three-dimensional multicellular tumor spheroids. Tumor spheroids mimic the functional and histomorphological complexity of in-vivo avascular tumors and are therefore valuable tools to study drug distribution. Ovarian cancer (Skov3) and uterine sarcoma (MES-SA/Dx5) spheroids were generated using the liquid overlay method. The growth ratio and cytotoxicity assays showed that the application of adjuvant hyperthermia with Doxorubicin (DOX) did not yield higher cell killing compared to DOX therapy alone. These results illustrated the role of spheroids in resistance to heat and DOX. In order to study the cellular uptake kinetics of nanoparticles under hyperthermia conditions, the experimental measurements of silica nanoparticle uptake by cells were fitted using a novel inverse estimation method based on Bayesian estimation. This was coupled with advection reaction transport to model nanoparticle transport in spheroids. The model predicted an increase in Area Under the Curve (AUC) and penetration distance (W1/2) that were validated with in-vitro experiments in spheroids. Based on these observations, a novel multifunctional theranostic nanoparticle probe was created for generating highly localized hyperthermia by encapsulating a Near Infrared (NIR) dye, IR820 (for imaging and hyperthermia) and DOX in Organically modified silica nanoparticles (Ormosil). Pegylated Ormosil nanoparticles had an average diameter of 58.2±3.1 nm, zeta potential of -6.9 ± 0.1 mV and high colloidal stability in physiological buffers. Exposure of the IR820 within the nanoparticles to NIR laser led to the generation of hyperthermia as well as release of DOX which translated to higher cell killing in Skov3 cells, deeper penetration of DOX into spheroids and complete destruction of the spheroids. In-vivo bio-distribution studies showed higher fluorescence from organs and increased plasma elimination life of IR820 compared to free IR820. However, possible aggregation of particles on laser exposure and accumulation in lungs still remain a concern

Thermodynamics and Kinetics of Defects at Surfaces

Fundamental understanding of the various electronic and structural properties at surfaces is a prerequisite for improved control of nanometer-scale patterning of surfaces for potential technological applications. In this dissertation, we have used multi-scale theoretical approaches to investigate the thermodynamic and kinetic properties of a few elemental types of surface defects. The multi-scale approaches range from first-principles calculations within density functional theory to empirical embedded atom method (EAM) to statistical analysis to kinetic Monte Carlo simulations. In studying the thermodynamic properties of intrinsic line defects on a vicinal TaC(910) surface, our Monte Carlo simulations in comparison with scanning tuning microscope (STM) images have established the existence of long-range attractive interaction between the steps. For extrinsic point defects underneath a GaAs surface, we have established through our theoretical analysis in comparison with STM observations that many-body effects in a system with purely repulsive interactions can give rise to an effective attractive interaction between the dopants at high dopant densities. In the study of the morphological evolution of monatomiclayer- high islands grown on metal surfaces, we have carried out Kinetic Monte Carlo simulations to demonstrate the importance of the island corner barriers. Our study has shown that if the island corner barrier effect is operational in preventing adatoms v located at an island edge to reach a neighboring edge defining the island corner, the islands thus formed must be non-compact, and develop fractal or dendritic shapes. Based on our EAM calculations of the diffusion barriers for various atomic processes and rate equation analysis, we have explained why fractal islands have rarely been observed on metal fcc(100) surfaces. For ideal surfaces, we have investigated the various driving forces for lattice relaxation based on first-principles calculations, and have proposed a new approach that has the promise to predict the direction of relaxation of the atoms in the surface layer strictly based on bulk properties of the given system. Finally, our fist-principles based interpretation of STM images within the framework of the Tersoff-Hamann theory has resulted in good agreement with STM experiments in revealing the anisotropy of electron density corrugations on several open metallic surfaces