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DOE OSTI2019

Multiscale Computational Model for Particle Size Evolution during Coprecipitation of Li-Ion Battery Cathode Precursors

Next generation lithium ion batteries require higher energy and power density, which can be achieved by tailoring the cathode particle morphology, such as particle size, size distribution, and internal porosity. All these morphological features are determined during the cathode synthesis process, which consists of two steps, (i) coprecipitation and (ii) calcination. Transition metal hydroxide precursors are synthesized during the coprecipitation process, whereas their oxidation and lithiation occur during calcination. The size and size distribution of crystalline primary and aggregated secondary particles and their internal porosity are determined during coprecipitation. Operating conditions of the chemical reactor, such as solution pH, ammonia concentration, and stirring speed control the final morphological features. Here, a multiscale computational model has been developed to capture the nucleation and growth of crystalline primary particles and their aggregation into secondary transition metal hydroxide precursor particles. The simulations indicate that increasing solution pH and decreasing ammonia concentration lead to smaller sizes of the secondary particles. Finally, a phase map has been developed that can help identify the synthesis conditions needed for a specified particle size and size distribution.

25 ENERGY STORAGE↗

DOE OSTI2024

Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO

Abstract Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.

58 GEOSCIENCES↗

DOE OSTI2014

Size exclusion deep bed filtration: Experimental and modelling uncertainties

A detailed uncertainty analysis associated with carboxyl-modified latex particle capture in glass bead-formed porous media enabled verification of the two theoretical stochastic models for prediction of particle retention due to size exclusion. At the beginning of this analysis it is established that size exclusion is a dominant particle capture mechanism in the present study: calculated significant repulsive Derjaguin-Landau-Verwey-Overbeek potential between latex particles and glass beads is an indication of their mutual repulsion, thus, fulfilling the necessary condition for size exclusion. Applying linear uncertainty propagation method in the form of truncated Taylor's series expansion, combined standard uncertainties (CSUs) in normalised suspended particle concentrations are calculated using CSUs in experimentally determined parameters such as: an inlet volumetric flowrate of suspension, particle number in suspensions, particle concentrations in inlet and outlet streams, particle and pore throat size distributions. Weathering of glass beads in high alkaline solutions does not appreciably change particle size distribution, and, therefore, is not considered as an additional contributor to the weighted mean particle radius and corresponded weighted mean standard deviation. Weighted mean particle radius and LogNormal mean pore throat radius are characterised by the highest CSUs among all experimental parameters translating to high CSU in the jamming ratio factor (dimensionless particle size). Normalised suspended particle concentrations calculated via two theoretical models are characterised by higher CSUs than those for experimental data. The model accounting the fraction of inaccessible flow as a function of latex particle radius excellently predicts normalised suspended particle concentrations for the whole range of jamming ratios. The presented uncertainty analysis can be also used for comparison of intra- and inter-laboratory particle size exclusion data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Observations on size confinement effect in B-C-N nanoparticles embedded in mesoporous silica channels

Fluorescent B-C-N/silica nanoparticles were synthesized by solution impregnation method. Effect of B-C-N particle size on the optical properties was investigated by varying the silica pore sizes. Formation of B-C-N nanoparticles within the mesoporous matrix is confirmed by x-ray diffraction, transmission electron microscopy, and Fourier transform infrared spectroscopy. Furthermore, a remarkable blue-shift in emission peak centres with decreasing pore size in conjugation with band gap modification, ascribed to the size confinement effect. A detailed analysis of experimental results by theoretically defined confinement models demonstrates that the B-C-N nanoparticles in the size range of 3–13 nm falls within the confinement regime. This work demonstrated the experimental evidence of the size confinement effect in smaller size B-C-N nanoparticles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2014

Direct observation of metal nanoparticles as heterogeneous nuclei for the condensation of supersaturated organic vapors: Nucleation of size-selected aluminum nanoparticles in acetonitrile and n-hexane vapors

This work reports the direct observation and separation of size-selected aluminum nanoparticles acting as heterogeneous nuclei for the condensation of supersaturated vapors of both polar and nonpolar molecules. In the experiment, we study the condensation of supersaturated acetonitrile and n-hexane vapors on charged and neutral Al nanoparticles by activation of the metal nanoparticles to act as heterogeneous nuclei for the condensation of the organic vapor. Aluminum seed nanoparticles with diameters of 1 and 2 nm are capable of acting as heterogeneous nuclei for the condensation of supersaturated acetonitrile and hexane vapors. The comparison between the Kelvin and Fletcher diameters indicates that for the heterogeneous nucleation of both acetonitrile and hexane vapors, particles are activated at significantly smaller sizes than predicted by the Kelvin equation. The activation of the Al nanoparticles occurs at nearly 40% and 65% of the onset of homogeneous nucleation of acetonitrile and hexane supersaturated vapors, respectively. The lower activation of the charged Al nanoparticles in acetonitrile vapor is due to the charge-dipole interaction which results in rapid condensation of the highly polar acetonitrile molecules on the charged Al nanoparticles. The charge-dipole interaction decreases with increasing the size of the Al nanoparticles and therefore at low supersaturations, most of the heterogeneous nucleation events are occurring on neutral nanoparticles. No sign effect has been observed for the condensation of the organic vapors on the positively and negatively charged Al nanoparticles. The present approach of generating metal nanoparticles by pulsed laser vaporization within a supersaturated organic vapor allows for efficient separation between nucleation and growth of the metal nanoparticles and, consequently controls the average particle size, particle density, and particle size distribution within the liquid droplets of the condensing vapor. Strong correlation is found between the seed nanoparticle's size and the degree of the supersaturation of the condensing vapor. This result and the agreement among the calculated Kelvin diameters and the size of the nucleating Al nanoparticles determined by transmission electron microscopy provide strong proof for the development of a new approach for the separation and characterization of heterogeneous nuclei formed in organic vapors. These processes can take place in the atmosphere by a combination of several organic species including polar compounds which could be very efficient in activating charged nanoparticles and cluster ions of atmospheric relevance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Distinguishing magnetic particle size of iron oxide nanoparticles with first-order reversal curves

Magnetic nanoparticles encompass a wide range of scientific study and technological applications. The success of using the nanoparticles in various applications demands control over size, dispersibility, and magnetics. Hence, the nanoparticles are often characterized by transmission electron microscopy (TEM), X-ray diffraction, and magnetic hysteresis loops. TEM analysis requires a thin layer of dispersed particles on the grid, which may often lead to particle aggregation thus making size analysis difficult. Magnetic hysteresis loops on the other hand provide information on the bulk property of the material without discriminating size, composition, and interaction effects. First order reversal curves (FORCs), described as an assembly of partial hysteresis loops originating from the major loop are efficient in identifying the domain size, composition, and interaction in a magnetic system. This study presents FORC diagrams on a variety of well-characterized biogenic and synthetic magnetite nanoparticles. It also introduces deconvoluted reversible and irreversible components from FORC as an important method for obtaining a semi-quantitative measure of the effective magnetic particle size. This is particularly important in a system with aggregation and interaction among the particles that often leads to either the differences between physical size and effective magnetic size. We also emphasize the extraction of secondary components by masking dominant coercivity fraction on FORC diagram to explore more detailed characterization of nanoparticle systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2016

Note: Evaluation of slurry particle size analyzers for chemical mechanical planarization process

In the chemical mechanical planarization (CMP) process, slurry particle size is important because large particles can cause defects. Hence, selection of an appropriate particle measuring system is necessary in the CMP process. In this study, a scanning mobility particle sizer (SMPS) and dynamic light scattering (DLS) were compared for particle size distribution (PSD) measurements. In addition, the actual particle size and shape were confirmed by transmission electron microscope (TEM) results. SMPS classifies the particle size according to the electrical mobility, and measures the particle concentration (single particle measurement). On the other hand, the DLS measures the particle size distribution by analyzing scattered light from multiple particles (multiple particle measurement). For the slurry particles selected for evaluation, it is observed that SMPS shows bi-modal particle sizes 30 nm and 80 nm, which closely matches with the TEM measurements, whereas DLS shows only single mode distribution in the range of 90 nm to 100 nm and showing incapability of measuring small particles. Hence, SMPS can be a better choice for the evaluation of CMP slurry particle size and concentration measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

The Influence of Particle Size on Infrared Reflectance Spectra

Reflectance spectra of solids are influenced by the absorption coefficient as well as the particle size and morphology. In the infrared, spectral features may be observed as either maxima or minima: in general, the upward-going peaks in the reflectance spectrum result from surface scattering, which are rays that have reflected from the surface without penetration, whereas downward-going peaks result from either absorption or volume scattering, i.e. rays that have penetrated into the sample or refracted into the sample interior and are not reflected. The light signal reflected from solids usually encompasses all these effects which include dependencies on particle size, morphology and sample density. This paper measures the reflectance spectra in the 1.3 – 16 micron range for various bulk materials that have a combination of strong and weak absorption bands in order to understand the effects on the spectral features as a function of the mean grain size of the sample. The bulk materials were ground with a mortar and pestle and then sieved to separate the samples into various size fractions: 0-45, 45-90, 90-180, 180-250, 250-500, and >500 microns. The directional-hemispherical spectra were recorded using a Fourier transform infrared spectrometer equipped with an integrating sphere to measure the reflectance for all of the particle-size fractions. We have studied both organic and inorganic materials, but this paper focuses on inorganic salts, NaNO3 in particular. Our studies clearly show that particle size has an enormous influence on the measured reflectance spectra for bulk materials and that successful identification requires sufficient representative reflectance data so as to include the particle size(s) of interest. Origins of the effects are discussed.

FTIR↗

DOE OSTI2020

Data Report: UT-GOM2-1 Sediment Grain Size Measurements at Site GC 955, Holes H002 and H005

Sediment grain size measurement in marine sediments provides a record of the stratigraphic variation in grain size and thus energy regime at the time of deposition. In addition to the grain size distribution, the degree of sediment sorting can also be calculated, and together they both influence primary sediment porosity and permeability. Here we present sediment grain size results from laser diffraction particle size analysis of samples from pressure cores collected during the 2017 UT GOM2-1 Expedition. We measured both bulk sediment and organic carbon-free sediment fractions for 46 samples and organic carbon-free sediment for 5 samples at Site GC 955, Holes H002 and H005. Differences between the bulk sediment and organic carbon-free fractions reflect the relative amount and size fraction of the organic carbon. The sample results presented here represent the grain size variation of the host lithology across the Green Canyon (GC) 955 gas hydrate reservoir.

03 NATURAL GAS↗

DOE OSTI2022

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗

DOE OSTI2023

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Spatial Mapping of Riverbed Grain-Size Distribution Using Machine Learning

Recent alluvial sediments in riverbeds play a significant role in controlling hydrologic exchange flows (HEFs) in river systems. The alluvial layer is usually associated with strong heterogeneity in physical properties (e.g., permeability and hydraulic conductivity), which affects local HEFs and therefore biogeochemical processes. The spatial distribution of these physical properties needs to be determined to inform the numerical models used to reveal the realistic hydro-biogeochemical behaviors. Such information can be obtained based on the intrinsic link between sediment grain-size distribution and hydraulic properties where sediment texture information is available. However, grain-size measurements are usually spatially sparse and do not have adequate coverage and resolution, particularly for a relatively large domain such as the Hanford Reach of the Columbia River. In this paper, we adopted machine learning (ML) approaches for categorizing and mapping the spatial distributions of riverbed substrate grain size and filling in missing areas of substrate data using the ML models along the reach. Such ML models for substrate size mapping were trained at 13,372 locations using measured substrate sizes along with observed and simulated attributes, including bathymetric attributes (e.g., elevation, slope, and aspect ratio) from LIDAR and bathymetric surveys, and hydrodynamic properties (e.g., water depth, velocity, shear stress, and their statistical moments). An ensemble bagging-based ML technique, Random Forest, was adopted to identify the most influential factors as predictors to develop the predictive models with over-fitting issues addressed. The models were evaluated with respect to each individual substrate size class and the lumped group, and then used to generate the final substrate size maps covering all the grid cells in the numerical modeling domain.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗

DOE OSTI2023

On the Interplay between Size and Disorder in Suppressing Intercalation-Induced Phase Transitions in Pseudocapacitive Nanostructured MoS 2

Pseudocapacitors are an emerging class of energy storage materials that offer an attractive compromise between the energy density of batteries and power density of electric double-layer capacitors. Decreasing particle size and increasing surface area of battery materials is a common approach for introducing pseudocapacitive behavior and increasing power density. However, in many cases, as the crystal size is reduced, lattice disorder of unknown extent is also introduced, making it difficult to characterize the relative contribution of size and disorder to fast-charging performance. Here, in this work, a series of nanostructured MoS 2 materials are synthesized with different crystallite sizes and degrees of crystallinity to decouple the effects of size and disorder on charge/discharge kinetics. The extent and type of disorder in each material is quantified by total X-ray scattering experiments and pair distribution function analyses. Electrochemical characterization, including galvanostatic rate capability, cyclic voltammetry, and various kinetic analyses, are used to demonstrate that both decreasing particle size and introducing lattice disorder are effective strategies for increasing charge storage kinetics, and that the effects are additive. Finally, operando X-ray diffraction measurements show that both size and disorder can be used suppress first-order Li + intercalation-induced phase transitions, a key feature for enabling pseudocapacitive charge storage.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Electronic Detection of Oxygen Adsorption and Size-Specific Doping of Few-Atom Gold Clusters on Graphene

Graphene's sensitivity to adsorbed particles has attracted widespread attention because of its potential sensor applications. Size-selected few-atom clusters are promising candidates as adparticles to graphene. Due to their small size, physicochemical properties are dominated by quantum size effects. In particular, few-atom gold clusters demonstrate a significant catalytic activity in various oxidation reactions. In this joint experimental and computational work, size-selected gold clusters with 3 and 6 atoms adsorbed on graphene field-effect transistors and their interaction with molecular oxygen are investigated. While oxygen adsorbs at both cluster sizes, there is a pronounced cluster size dependence in the corresponding doping, as demonstrated via first-principle calculations and electronic transport measurements. Furthermore, the doping of gold cluster decorated graphene changes sign from n- to p-doping upon oxygen adsorption, directly evidencing electron transfer to the oxygen molecules and hence their activation. These observations pinpoint graphene as a valuable platform to investigate and exploit size-dependent cluster properties.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Interlaminar improvement of carbon fiber/epoxy composites via fluorine‐containing high‐epoxy‐value sizing agent

Abstract To improve the interfacial bonding effect of carbon fibers (CFs) and epoxy resins, we prepared a fluorine‐containing high‐epoxy‐value sizing agent (named TS) in this article. It is an emulsion with a more uniform particle size distribution and higher stability better than a commercial Takemoto sizing agent. In addition, sulfonic acid groups can improve the hydrophilicity of the TS, and the presence of epoxy groups enhances the wettability between CFs and the matrix. The properties of the sizing agents were examined by Fourier transform infrared spectroscopy, dynamic light scattering, and thermogravimetric analysis. The sized CFs were evaluated by scanning electron microscopy, x‐ray photoelectron spectroscopy, monofilament tensile test, and dynamic contact angle. Afterward, CF/epoxy composites were prepared, and their fracture morphology and interlaminar shear strength (ILSS) were examined. Results indicated that the TS sizing significantly increased the content of activated carbon on the surface of the CFs and improved the bonding effect between the fiber and the matrix. After TS was sized, the ILSS increased from 49.64 to 58.74 MPa, 18.34% higher than unsized CF/epoxy composites, showing the prominent interfacial reinforcement better than commercial Takemoto.

Qiu, Zhijie↗

DOE OSTI2013

Margin Size is an Independent Predictor of Local Tumor Progression After Ablation of Colon Cancer Liver Metastases

This study was designed to evaluate the relationship between the minimal margin size and local tumor progression (LTP) following CT-guided radiofrequency ablation (RFA) of colorectal cancer liver metastases (CLM). An institutional review board-approved, HIPPA-compliant review identified 73 patients with 94 previously untreated CLM that underwent RFA between March 2003 and May 2010, resulting in an ablation zone completely covering the tumor 4-8 weeks after RFA dynamic CT. Comparing the pre- with the post-RFA CT, the minimal margin size was categorized to 0, 1-5, 6-10, and 11-15 mm. Follow-up included CT every 2-4 months. Kaplan-Meier methodology and Cox regression analysis were used to evaluate the effect of the minimal margin size, tumor location, size, and proximity to a vessel on LTP. Forty-five of 94 (47.9 %) CLM progressed locally. Median LTP-free survival (LPFS) was 16 months. Two-year LPFS rates for ablated CLM with minimal margin of 0, 1-5 mm, 6-10 mm, 11-15 mm were 26, 46, 74, and 80 % (p < 0.011). Minimal margin (p = 0.002) and tumor size (p = 0.028) were independent risk factors for LTP. The risk for LTP decreased by 46 % for each 5-mm increase in minimal margin size, whereas each additional 5-mm increase in tumor size increased the risk of LTP by 22 %. An ablation zone with a minimal margin uniformly larger than 5 mm 4-8 weeks postablation CT is associated with the best local tumor control.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Scaling laws and stability of nano-sized defect clusters in niobium via atomistic simulations and statistical analysis

The predictions of scaling laws for the structure and properties of defect clusters are generally limited to small defect clusters in their ground-state configurations. We investigated the size and geometrical configuration dependence of nano-sized defect clusters in niobium (Nb) using molecular dynamics. We studied the structure and stability of large clusters of size up to fifty defects for vacancies and one hundred defects for interstitials, as well as the role of helium and metastable configurations on the stability of these clusters. We compared three different interatomic potentials in order to determine the relative stability of these clusters as a function of their size and geometrical configurations. Additionally, we conducted a statistical analysis to predict the formation and binding energies of interstitial clusters as a function of both their size and configuration. We find that the size dependence of vacancy and interstitial clusters can be approximated by functional forms that account for bulk and surface effects as well as some considerations of elastic interactions. We also find that helium and metastable configurations can make vacancy and interstitial clusters thermally stable depending on the configuration. Our parameterized functional forms for the formation and binding energies are valid for a very broad range of defect sizes and configurations making it possible to be used directly in a coarse-grained modeling strategy such as Monte Carlo, cluster dynamics or dislocation dynamics which look at defect accumulation and evolution in microstructures.

36 MATERIALS SCIENCE↗