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At least 469 records · Page 26

Cluster dynamics simulation of xenon diffusion during irradiation in UO 2

Diffusion of fission gas in UO 2 nuclear fuel impacts several important performance metrics, such as fission gas release, swelling, and thermal conductivity. Current empirical models of fission gas release have significant uncertainty, some of which derives from the bulk diffusion rate and its dependence on, for example, fuel chemistry and irradiation. In this work, we have applied the previously-developed Free Energy Cluster Dynamics (FECD) methodology in the code Centipede to calculate xenon cluster concentrations in UO 2 under intrinsic (high temperature) and irradiation-enhanced (intermediate temperature) conditions in order to develop a model of the xenon diffusion coefficient based on the atomic scale mechanisms responsible for transport. While the diffusion mechanism for xenon in UO 2 is adequately described by the Xe + U 2 O vacancy cluster for intrinsic conditions, a similar process is not capable of capturing measured in-pile fission gas diffusivity at intermediate temperatures. Therefore, a different diffusion mechanism must dominate under this regime. Using calculated atomistic data, we have shown that irradiation-enhanced diffusion at intermediate temperatures occurs via the larger Xe + U 4 O y vacancy clusters, which have lower migration barriers and increase in concentration by several orders of magnitude compared to intrinsic conditions. This mechanism is enabled by the increased uranium vacancy concentration under irradiation due to Frenkel pair production. In addition, the fast migration of uranium interstitials with two attached oxygen interstitials lowers the total uranium interstitial concentration through reactions with sinks. This allows the extended defects, such as Xe + U 4 O y vacancy clusters, to maintain high concentrations by limiting annihilation with attached vacancies. Furthermore, predictions using the Xe + U 4 O y diffusion mechanism are in good agreement with experiment, albeit with some differences in the Arrhenius slope, which we believe may be related to either experimental or model parameter uncertainty. Lastly, an analytical expression suitable for application in fuel performance simulations was derived to capture the predictions of the Centipede simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Impact of grain boundary and surface diffusion on predicted fission gas bubble behavior and release in UO 2 fuel

In this work, we quantify the impact of grain boundary (GB) and surface diffusion on fission gas bubble evolution and fission gas release in UO 2 nuclear fuel using simulations with a hybrid phase field/cluster dynamics model. Here, we begin with a comprehensive literature review of uranium vacancy and xenon atom diffusivity in UO 2 through the bulk, along GBs, and along surfaces. In our model we represent fast GB and surface diffusion using a heterogeneous diffusivity that is a function of the order parameters that represent bubbles and grains. We find that the GB diffusivity directly impacts the rate of gas release via GB transport, and that the GB diffusivity is likely below 104 times the lower value from Olander and van Uffelen. We also find that the surface diffusivity impacts bubble coalescence and mobility, and that the bubble surface diffusivity is likely below 10 -4 times the value from Zhou and Olander.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experimental observation of nonlinear relation between pressure and water flux is consistent with the solution-diffusion model

In several recent studies, it has been proposed that the fundamental understanding of penetrant transport in dense polymer membranes occurring via the solution-diffusion model, which has been the generally accepted theoretical framework for describing penetrant transport in such materials for the past several decades, is flawed. An alternate mechanistic framework based on the idea of two-phase flow in a porous medium (i.e., pore-flow) has been broadly advanced instead, with proponents of this approach claiming that the pore-flow theoretical framework provides the necessary mechanistic insight to design novel polymeric membrane materials for emerging applications. In this study, we show experimental results for hydraulic permeation of water that are entirely consistent with the solution-diffusion theory, without modification, for three dense polymeric membranes: crosslinked poly(ethylene glycol diacrylate) (XLPEGDA), Nafion 117 ionomer in the sodium counterion form (Nafion 117-Na), and cellulose acetate (CA). By measuring water flux at transmembrane pressures up to 240 bar, we observe a nonlinear relationship between the transmembrane pressure (TMP) and water flux, J w , for XLPEGDA and Nafion 117-Na, while this relationship is linear for CA. We demonstrate that the behavior of these three materials is described via the solution-diffusion model. According to the solution-diffusion model, flux is, to a good approximation, proportional to the transmembrane concentration difference induced by the pressure difference across the membrane, rather than to TMP itself. Water sorption isotherms are reported for all three materials. They further justify the nonlinear relationship between TMP and J w observed in XLPEGDA and Nafion 117-Na, emphasizing that the nonlinearity in the flux/TMP relationship stems from nonlinearities in the sorption isotherm with pressure. Additionally, the relationship between water flux and TMP can be predicted, a priori, with no adjustable parameters when a predictive model for the diffusion coefficient of water is employed in conjunction with the experimental water sorption isotherms in the solution-diffusion model. Furthermore, our results demonstrate the validity of the solution-diffusion model to describe transport of penetrants in dense polymer membranes, while highlighting the sensitivity of the solution-diffusion model to the many physical and mathematical simplifications commonly applied to the theory in literature.

materials↗

Directly resolving surface vs. lattice self-diffusion in iron at the nanoscale using in situ atom probe capabilities

Surface self-diffusion studies on metals under elevated reaction conditions are limited, as it is inherently challenging to unambiguously follow atomic transport across highly-reactive surfaces. Here, quantitative and mechanistic insight into thermally induced atomic transport processes in bcc α-iron at the sub-nanometer level was achieved using isotopic tracer techniques coupled with in situ atom probe tomography (APT) capabilities. Specifically, using a reactor directly connected to the APT, needle-shaped specimens fabricated from epitaxial thin films with an embedded 57 Fe tracer layer were annealed in Ar at 500 °C and 350 °C for 1 hour. Furthermore, the tracer was positioned at various depths in the APT specimen by field evaporation, enabling targeted and simultaneous analysis of lattice and surface diffusion. 57 Fe concentration profiles reveal lattice self-diffusion occurs at 500 °C on the order of ~7 – 9 monolayers, while lattice diffusion is not resolvable at 350 °C. Considerable surface transport was, however, observed at both conditions, where atomic transport over the specimen surface led to the formation of a thin (≤1 nm), isotopically-intermixed layer at the surface. Further, the observed isotopic redistributions at 500 °C were convoluted by additional processes occurring in the subsurface, such as atomic intermixing in correlation with lattice diffusion. However, surface diffusion was determined to be the primary transport process at 350 °C and was thereby quantified. Ultimately, these results demonstrate the significance of surface self-diffusion as a short circuit pathway. More broadly, this approach has the potential to provide detailed insight into (self-)diffusion mechanisms across various materials while targeting site-specific reactions under elevated reaction conditions.

36 MATERIALS SCIENCE↗

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Furthermore, fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Simulations of CH 4 and CO 2 Diffusion in Rigid Nanoporous Amorphous Materials

Molecular diffusion in nanoporous materials is important in determining the rate of equilibration of various adsorption processes and plays a pivotal role in kinetic separations and membrane-based separations. Because generating realistic structures of amorphous nanoporous materials is difficult, far less is known about diffusion in amorphous nanoporous materials than in their crystalline counterparts. Here, we present molecular dynamics simulations assessing the room-temperature self-diffusion of CH 4 and CO 2 in a wide range of rigid amorphous nanoporous materials, including porous carbons, kerogens, polymers of intrinsic microporosity, and hyper-cross-linked polymers. Our results are the largest collection of molecular diffusivities in amorphous nanoporous materials to date. In each material, the diffusivity increases with the adsorbate concentration at low and moderate adsorbate concentrations, reaching a maximum before decreasing due to steric effects at higher concentrations. The observed diffusivities are much slower than that would be expected based on standard descriptions of Knudsen diffusivity. Here we show that the observed diffusivities are not correlated in a simple way with scalar descriptors of the pore structures such as the pore limiting diameter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Random Walks and Sticky Surfaces: Single-Molecule Measurements of Solute Diffusion in Ethanol/Water-Filled Anodic Alumina Nanopores

Nanoporous anodic aluminum oxide (AAO) membranes are now being explored for use in advanced chemical separations, including in the dehydration of biofuels such as ethanol. Optimization of membrane performance requires an in-depth understanding of how solvent mixtures and solutes behave under nanoconfinement. In this work, the diffusion of rhodamine B (RhB) dye through 10 nm and 20 nm AAO nanopores filled with a series of ethanol/water mixtures (0 - 33% water) is explored by fluorescence correlation spectroscopy (FCS). RhB was found to diffuse through the pores by two distinct mechanisms with mean diffusion coefficients, $D_f$ and $D_s$, reflecting fast and slow diffusive motions, respectively, with values that differ by nearly two orders of magnitude. Further, both $D_f$ and $D_s$ increased with pore size and were significantly smaller than $D_b$, the RhB diffusion coefficient in bulk liquid. Mean $D_f$ values follow a composition-dependent trend that closely mimics the viscosity dependence of $D_b$. Additional slowing of fast RhB diffusion is attributed to both hydrodynamic drag and electrostatic interactions with the nanopore surface. The mean $D_s$ values exhibit a different trend with increasing water content, revealing an increase in $D_s$ and a decrease in the contributions of slow diffusion to the observed dynamics. The fluorescence time transient data used in the analysis show that the slow diffusion process is strongly hindered and likely involves frequent adsorption of RhB to the pore surfaces. These results provide new insights into the detailed molecular-level mechanisms of mass transport in nanoporous AAO membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion Behavior of Differently Charged Molecules in Self-Assembled Organic Nanotubes Studied Using Imaging Fluorescence Correlation Spectroscopy

The diffusion behavior of fluorescent molecules within bolaamphiphile-based organic nanotubes (ONTs) was systematically explored using imaging fluorescence correlation spectroscopy (imaging FCS). Anionic sulforhodamine B (SRB), zwitterionic/cationic rhodamine B (RB) or cationic rhodamine 123 (R123) was loaded into ONTs having cylindrical hollow structures (ca. 10 nm in inner diameter) with amine and glucose groups on the inner and outer surfaces, respectively. Wide-field fluorescence video microscopy was used to acquire imaging FCS data for dye-doped ONTs in aqueous solutions of different ionic strengths (1 – 500 mM) at different pH (3.4 – 8.4). The diffusion behavior of these dyes was discussed on the basis of their apparent diffusion coefficients (D) that were determined by autocorrelating the time transient of fluorescence intensity at each pixel on an ONT. Molecular diffusion in the ONTs was significantly slowed by molecule-nanotube interactions, as shown by the very small D (10-1 – 10-2 µm2/s). The pH-dependence of D revealed that dye diffusion was basically controlled by electrostatic interactions associated with the protonation of the amine groups on the ONT inner surface. The pH-dependent change in D was observed over a wide pH range, possibly due to electrostatically induced variations in the pKa of the densely packed ammonium ions on the ONT inner surface. On the other hand, the influence of ionic strength on D was relatively unclear, suggesting the involvement of non-coulombic interactions with the ONTs in molecular diffusion. Notably, individual ONTs of different lengths (1 – 5 µm) afforded similar diffusion coefficients for each type of dye at each solution condition, implying that the properties of ONTs were uniform in terms of solute loading and release. These conclusions highlight the characteristics of molecular diffusion behavior within the ONTs, and will help in the design of organic nanotubes better suited for use as drug vehicles and contaminant adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unraveling Interdiffusion Phenomena and the Role of Nanoscale Diffusion Barriers in the Copper–Gold System

Diffusion is one of the most fundamental concepts in materials science, playing a pivotal role in materials synthesis, forming, and degradation. Of particular importance is solid state interdiffusion of metals which defines the usable parameter space for material combinations in the form of alloys. This parameter space can be explored on the macroscopic scale by using diffusion couples. However, this method reaches its limit when going to low temperatures, small scales, and when testing ultrathin diffusion barriers. Therefore, this work transfers the principle of the diffusion couples to small scales by using core–shell nanowires and in situ heating. This allows us to delve into the interdiffusion dynamics of copper and gold, revealing the interplay between diffusion and the disorder–order phase transition. Our in situ TEM experiments in combination with chemical mapping reveal the interdiffusion coefficients of Cu and Au at low temperatures and highlight the impact of ordering processes on the diffusion behavior. The formation of ordered domains within the solid-solution is examined using high-resolution imaging and nanodiffraction including strain mapping. In addition, we examine the effectiveness of ultrathin Al 2 O 3 barrier layers to control interdiffusion of the diffusion couple. Our findings indicate that a 5 nm thick layer serves as an efficient diffusion barrier. Furthermore, this research provides valuable insights into the interdiffusion behavior of Cu and Au on the nanoscale, offering potential applications in the development of miniaturized integrated circuits and nanodevices.

alloys↗

Predicting Effective Diffusion Coefficients in Mudrocks Using a Fractal Model and Small-Angle Neutron Scattering Measurements

The determination of effective diffusion coefficients of gases or solutes in the water–saturated pore space of mudrocks is time consuming and technically challenging. Yet, reliable values of effective diffusion coefficients are important to predict migration of hydrocarbon gases in unconventional reservoirs, dissipation of (explosive) gases through clay barriers in radioactive waste repositories, mineral alteration of seals to geological CO 2 storage reservoirs and contaminant migration through aquitards. In this study, small angle and very small angle neutron scattering techniques have been utilized to determine a range of transport properties in mudrocks, including porosity, pore size distributions and surface and volume fractal dimensions of pores and grains, from which diffusive transport parameters can be estimated. Using a fractal model derived from Archie's Law, we calculate effective diffusion coefficients from these parameters and compare them to laboratory–derived effective diffusion coefficients for CO 2 , H 2 , CH 4 and HTO on either the same or related mudrock samples. The samples include Opalinus Shale from the underground laboratory in Mont Terri, Switzerland; Boom Clay from a core drilled in Mol, Belgium and a marine claystone cored in Utah, USA. The predicted values were compared to laboratory diffusion measurements. The measured and modeled diffusion coefficients show good agreement, differing generally by less than factor 5. Furthermore, neutron or X–ray scattering analysis is therefore proposed as a novel method for fast, accurate estimation of effective diffusion coefficients in mudrocks, together with simultaneous measurement of multiple transport parameters including porosity, pore size distributions and surface areas, important for (reactive) transport modelling.

58 GEOSCIENCES↗

A Pore‐Scale Investigation of Mineral Precipitation Driven Diffusivity Change at the Column‐Scale

Abstract Mineral precipitation affects the pore structure and thus transport properties of porous media. In this study, we investigated the pore‐scale dynamics of precipitation in diffusion controlled systems and the resulting impacts on the effective diffusivity, using a micro‐continuum reactive transport model. Forty two‐dimensional pore structures representing both idealized and realistic geometries were simulated with consideration of different precipitation scenarios and rates. A homogeneous nucleation scenario reproduced patterns observed in previous experimental study showing mixing‐induced precipitation, and a surface growth scenario captured the pattern for mineral precipitation on a substrate with the same or similar mineral structures. In all cases, local precipitation resulted in the reduction in the average porosity of the domain ( Φ ) until the cessation of diffusive transport and the termination of precipitation. The minimum porosity reached was referred to as the critical porosity ( Φ c ). The effective diffusivity ( D eff ) decreased with Φ and dropped sharply to effectively zero, that is, the critical effective diffusivity ( D eff c ), as Φ c was reached. These pore‐scale dynamics can be captured by a revised relationship that explicitly considers the critical porosity and the corresponding effective diffusivity, and the pre‐exponential coefficient and the exponent of the relationship varied with initial pore structure and the precipitation kinetics. Overall, the homogeneous nucleation scenario results in systematically larger Φ c and coefficients that give rise to a sharper decrease in diffusivity as Φ c is approached, compared to the surface growth scenario. The revised relationship was also implemented at continuum scale and used to examine column scale diffusivity change and reactions.

58 GEOSCIENCES↗

Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

Here, this report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along < c > is found to be slightly higher than that along < a >, with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.

36 MATERIALS SCIENCE↗

Ion diffusion coefficients in poly(3-alkylthiophenes) for energy conversion and biosensing: role of side-chain length and microstructure

Conductive polymers are promising materials as active elements for energy storage and conversion devices due to mixed ion–electron conduction. The ion diffusion coefficient is a relative measure of the efficacy of ion transport, allowing for comparison between materials and electrochemical conditions. In this work, diffusion coefficients of hexafluorophosphate (PF6–) counterions in poly(3-alkylthiophene) (P3AT) materials are measured as a function of both side-chain length and microstructure using electrochemical impedance spectroscopy (EIS). For semi-crystalline films, the diffusion coefficient is found to be anomalous and nearly independent of applied electrochemical potential. Here, the anomalous behavior of diffusion indicates that spin casting yields compact films with an enthalpic barrier to ion transport, attributed to ionic trapping. Diffusion coefficient values ~10 –11 cm 2 s –1 were measured for all films, indicating interchain spacing, in the absence of strong intermolecular interactions with the electrolyte, is not a viable design strategy to control ion transport. For the prototypical system of poly(3-hexylthiophene), we observe almost no potential dependence in ion transport for regioregular and regiorandom films of comparable molecular weight, with both exhibiting anomalous diffusion. Alternatively, changing the microstructure of poly(3-hexylthiophene) to a mostly amorphous, ion-imprinted structure yields ~500× increase in the diffusion coefficient to ~2 × 10 –8 cm 2 s –1 at 0.8 V vs. Ag/Ag + with behavior closer to ordinary diffusion. Collectively, these results indicate new insight into ion transport in conductive polymers, where ionic trapping effects can be mitigated through electrodeposition protocols over post-synthesis processing (i.e. spin coating).

14 SOLAR ENERGY↗

Phosphorus out-diffusion in laser molten silicon

Laser doping via liquid phase diffusion enables the formation of defect free pn junctions and a tailoring of diffusion profiles by varying the laser pulse energy density and the overlap of laser pulses. We irradiate phosphorus diffused 100 oriented p-type float zone silicon wafers with a 5 μm wide line focused 6.5 ns pulsed frequency doubled Nd:YVO{sub 4} laser beam, using a pulse to pulse overlap of 40%. By varying the number of laser scans N{sub s} = 1, 2, 5, 10, 20, 40 at constant pulse energy density H = 1.3 J/cm{sup 2} and H = 0.79 J/cm{sup 2} we examine the out-diffusion of phosphorus atoms performing secondary ion mass spectroscopy concentration measurements. Phosphorus doping profiles are calculated by using a numerical simulation tool. The tool models laser induced melting and re-solidification of silicon as well as the out-diffusion of phosphorus atoms in liquid silicon during laser irradiation. We investigate the observed out-diffusion process by comparing simulations with experimental concentration measurements. The result is a pulse energy density independent phosphorus out-diffusion velocity v{sub out} = 9 ± 1 cm/s in liquid silicon, a partition coefficient of phosphorus 1 < k{sub p} < 1.1 and a diffusion coefficient D = 1.4(±0.2)cm{sup 2}/s × 10{sup −3 }× exp[−183 meV/(k{sub B}T)].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Self-diffusion in the non-Newtonian regime of shearing liquid crystal model systems based on the Gay-Berne potential

The self-diffusion coefficients of nematic phases of various model systems consisting of regular convex calamitic and discotic ellipsoids and non-convex bodies such as bent-core molecules and soft ellipsoid strings have been obtained as functions of the shear rate in a shear flow. Then the self-diffusion coefficient is a second rank tensor with three different diagonal components and two off-diagonal components. These coefficients were found to be determined by a combination of two mechanisms, which previously have been found to govern the self-diffusion of shearing isotropic liquids, namely, (i) shear alignment enhancing the diffusion in the direction parallel to the streamlines and hindering the diffusion in the perpendicular directions and (ii) the distortion of the shell structure in the liquid whereby a molecule more readily can escape from a surrounding shell of nearest neighbors, so that the mobility increases in every direction. Thus, the diffusion parallel to the streamlines always increases with the shear rate since these mechanisms cooperate in this direction. In the perpendicular directions, these mechanisms counteract each other so that the behaviour becomes less regular. In the case of the nematic phases of the calamitic and discotic ellipsoids and of the bent core molecules, mechanism (ii) prevails so that the diffusion coefficients increase. However, the diffusion coefficients of the soft ellipsoid strings decrease in the direction of the velocity gradient because the broadsides of these molecules are oriented perpendicularly to this direction due the shear alignment (i). The cross coupling coefficient relating a gradient of tracer particles in the direction of the velocity gradient and their flow in the direction of the streamlines is negative and rather large, whereas the other coupling coefficient relating a gradient in the direction of the streamlines and a flow in the direction of the velocity gradient is very small.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

First-principles study of migration and diffusion mechanisms of helium in α-Be

The behavior of interstitial helium in α-Be has been studied with first-principles method. It is found that the most favored position for helium is the basal octahedral (BO) site, closely followed by the basal tetrahedral (BT) site, in agreement with previous predictions. The interaction energy between the helium and the neighborhood Be atoms and the deformation energy of α-Be matrix are calculated. The feasible minimum-energy pathways (MEP) of interstitial helium atoms in α-Be matrix and the corresponding atomic structures of the saddle points associated with the each MEP are investigated. The temperature-dependent diffusion coefficients have also been predicted. It is confirmed that the interstitial helium diffuses two-dimensionally at low temperatures; however, it can diffuse three-dimensionally at higher temperatures. Besides, the microscopic parameters in the pre-factor and activation energy of the diffusion coefficients are obtained. Both diffusion coefficients are higher than the available experiment data, which may attribute to the fact that under real condition the diffusion is not free, i.e. the actual α-Be matric has various defects and impurities which heavily affect the diffusion of helium. Therefore, our theoretical prediction is the upper bound for helium diffusion in α-Be matrix.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Study of defect formation from process step anomalies in limited boron source diffusion in crystalline silicon

In limited dopant source diffusion process, the deposition and the drive in conditions of the source play an important role in pn- junction formation. The pre diffusion anomalies can introduce defects in the emitter region during the process of diffusion which can glide into the bulk region. So, the defects formed in the emitter region due to different pre diffusion issues are studied in this work with boron spin on dopant source diffused in n-type crystalline Si. The samples are prepared for different diffusion conditions of times carried out at diffusion temperature of 900°C. Different characterization techniques used in this work confirms the presence of these defects in the emitter region. The dopant distribution under the same diffusion condition result in non- uniformity, varying the junction depth of the emitter. A single process step anomaly is sufficient enough to degrade the emitter performance and should be avoided.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Rotational and translational diffusion of liquid n-hexane: EFP-based molecular dynamics analysis

Molecular Dynamics (MD) simulations based on the Effective Fragment Potential (EFP) method are utilized to provide a comprehensive assessment of diffusion in liquid n-hexane. We decompose translational diffusion into components along and orthogonal to the long axis of the molecule. Rotational diffusion is decomposed into tumbling and spinning motions about this axis. Our analysis yields four corresponding diffusion coefficients which are related to diagonal entries in the complete 6 × 6 diffusion tensor accounting for the three rotational and three translational degrees of freedom and for the potential coupling between them. However, coupling between different degrees of freedom is expected to be minimal for a natural choice of the molecular body-fixed axis, so then off-diagonal entries in the tensor are negligible. This expectation is supported by a hydrodynamic analysis of the diffusion tensor which treats the liquid surrounding the molecule being tracked as a viscous continuum. Thus, the EFP MD analysis provides a comprehensive characterization of diffusion and also reveals expected shortcomings of the hydrodynamic treatment, particularly for rotational diffusion, when applied to neat liquids.

74 ATOMIC AND MOLECULAR PHYSICS↗