June 17, 2021

Download Ebook Free Computational Modelling Of Nanoparticles

Computational Modelling of Nanomaterials

Computational Modelling of Nanomaterials
Author : Panagiotis Grammatikopoulos
Publisher : Elsevier
Release Date : 2020-10-01
Category : Technology & Engineering
Total pages :244
GET BOOK

Due to their small size and their dependence on very fast phenomena, nanomaterials are ideal systems for computational modelling. This book provides an overview of various nanosystems classified by their dimensions: 0D (nanoparticles, QDs, etc.), 1D (nanowires, nanotubes), 2D (thin films, graphene, etc.), 3D (nanostructured bulk materials, devices). Fractal dimensions, such as nanoparticle agglomerates, percolating films and combinations of materials of different dimensionalities are also covered (e.g. epitaxial decoration of nanowires by nanoparticles, i.e. 0D+1D nanomaterials). For each class, the focus will be on growth, structure, and physical/chemical properties. The book presents a broad range of techniques, including density functional theory, molecular dynamics, non-equilibrium molecular dynamics, finite element modelling (FEM), numerical modelling and meso-scale modelling. The focus is on each method’s relevance and suitability for the study of materials and phenomena in the nanoscale. This book is an important resource for understanding the mechanisms behind basic properties of nanomaterials, and the major techniques for computational modelling of nanomaterials. Explores the major modelling techniques used for different classes of nanomaterial Assesses the best modelling technique to use for each different type of nanomaterials Discusses the challenges of using certain modelling techniques with specific nanomaterials

Computational Modelling of Nanoparticles

Computational Modelling of Nanoparticles
Author : Stefan T. Bromley,Scott M. Woodley
Publisher : Elsevier
Release Date : 2018-09-12
Category : Science
Total pages :351
GET BOOK

Computational Modelling of Nanoparticles highlights recent advances in the power and versatility of computational modelling, experimental techniques, and how new progress has opened the door to a more detailed and comprehensive understanding of the world of nanomaterials. Nanoparticles, having dimensions of 100 nanometers or less, are increasingly being used in applications in medicine, materials and manufacturing, and energy. Spanning the smallest sub-nanometer nanoclusters to nanocrystals with diameters of 10s of nanometers, this book provides a state-of-the-art overview on how computational modelling can provide, often otherwise unobtainable, insights into nanoparticulate structure and properties. This comprehensive, single resource is ideal for researchers who want to start/improve their nanoparticle modelling efforts, learn what can be (and what cannot) achieved with computational modelling, and understand more clearly the value and details of computational modelling efforts in their area of research. Explores how computational modelling can be successfully applied at the nanoscale level Includes techniques for the computation modelling of different types of nanoclusters, including nanoalloy clusters, fullerines and Ligated and/or solvated nanoclusters Offers complete coverage of the use of computational modelling at the nanoscale, from characterization and processing, to applications

Computational Modeling of Inorganic Nanomaterials

Computational Modeling of Inorganic Nanomaterials
Author : Stefan T. Bromley,Martijn A. Zwijnenburg
Publisher : CRC Press
Release Date : 2016-04-06
Category : Science
Total pages :423
GET BOOK

Computational Modeling of Inorganic Nanomaterials provides an accessible, unified introduction to a variety of methods for modeling inorganic materials as their dimensions approach the nanoscale. With contributions from a team of international experts, the book guides readers on choosing the most appropriate models and methods for studying the structure and properties (such as atomic structure, optical absorption and luminescence, and electrical and heat transport) of a varied range of inorganic nanomaterial systems. Divided into three sections, the book first covers different types of inorganic nanosystems with increasing dimensionality. The second section explains how to computationally describe properties and phenomena associated with inorganic nanomaterials, including the modeling of melting and phase transitions, crystallization, and thermal, mechanical, optical, and excited state properties. The final section highlights a diverse range of important recent case studies of systems where modeling the properties and structures of inorganic nanomaterials is fundamental to their understanding. These case studies illustrate the use of computational techniques to model nanostructures in a range of applications and environments, from heterogeneous catalysis to astrochemistry. Largely due to their extremely reduced dimensions, inorganic nanomaterials are difficult to characterize accurately in experiments. Computational modeling, therefore, often provides unrivaled, detailed insights to complement and guide experimental research on these small-scale materials. This book shows how computational modeling is critical for understanding inorganic nanomaterials and their future development.

A Computational Model of Nanoparticle Transport and Delivery in Tumor Tissue

A Computational Model of Nanoparticle Transport and Delivery in Tumor Tissue
Author : Vishwa Priya Podduturi
Publisher : Unknown
Release Date : 2013
Category : Capillaries
Total pages :184
GET BOOK

Computational Modelling of TiO2 and Mg-silicate Nanoclusters and Nanoparticles - Crystallinity and Astrophysical Implications

Computational Modelling of TiO2 and Mg-silicate Nanoclusters and Nanoparticles - Crystallinity and Astrophysical Implications
Author : Antoni Macià Escatllar
Publisher : Unknown
Release Date : 2020
Category :
Total pages :166
GET BOOK

"The research presented in this thesis contributes to the understanding of both titania and silicate nanosystems by providing new information on energetic stability and properties of nanometer sized particles using computational modelling. Particular emphasis is placed on the importance of two nanosized regimes: i) tens of atoms, and ii) several hundred up to thousands of atoms. We differentiate these two size regimes by naming nanoclusters the structures containing between tens up to a hundred of atoms, and using the term nanoparticles (NPs) for the structures containing hundreds to thousands of atoms.Titania (TiO2) is the most studied photocatalyst, and thus research is mostly focused on understanding the electronic properties of different morphologies of TiO2 NPs. In detail, for TiO2 the present thesis benchmarks the ability of several interatomic potentials (IPs) to reduce the computational cost of Density Functional Theory (DFT) calculations, as well as a detailed analysis of the energetic stability of three different morphologies of NPs together with an analysis of their band-gap. We show that the Anatase crystal structure becomes the most stable for particle sizes of ̃2-3 nm in diameter, while for smaller sizes amorphous particles are the most stable. Within the Anatase structure, we see that Wulff construction is the most stable for large sizes (above 2 nm), but amorphous shell-crystalline core nanoparticles are within the same energy range below a radius of 2 nm. We also find that spherical particles have a band-gap consistent with the so-called black TiO2.On the other hand, research on silicates is mainly focused on calculating the properties of nanoclusters and NPs, with the objective of obtaining a better understanding of the relevance of such species in interstellar space. In detail, we propose global minima (GM) candidates for numerous nanoclusters based on extensive global optimization (GO) searches and compare their spectroscopic and chemical properties with literature values, where the later values are mostly derived from extrapolation using macroscale laboratory samples. The GO searches were done with a reparameterization of the FFSiOH where we included the Mg element. We also evaluate whether silicate nanoclusters can be the origin of the anomalous microwave emission (AME), a foreground emission in the microwave (MW) region of the spectra from an unknown source and find that indeed nano silicates have the appropriate dipole moments in order to be a strong source of the AME. We indicate that the amount of nano silicates in the interstellar medium is constrained by the AME emission. Finally, the IR spectra of large NPs of around 4 nm in diameter is compared on the basis of their crystallinity. We find that for such sizes, the IR spectra of the crystalline particle corresponds to a broad band similar to the amorphous material, which we ascribe to the large fraction of surface atoms. We conclude that the IR spectra is not sufficient to characterize the crystallinity of astronomical silicates with sizes of several nanometers in diameter. We also show that amorphous silicate nano particles with sizes of ̃1 nm in diameter are more stable than their crystalline counterparts. We extrapolate the tendency and propose that the crystalline nanoparticles become more stable than amorphous particles at particle sizes of ̃12 nm in diameter." -- TDX.

Computational Modeling of Nanoparticle Distribution and Toxicity in Biological Systems

Computational Modeling of Nanoparticle Distribution and Toxicity in Biological Systems
Author : Dwaipayan Mukherjee
Publisher : Unknown
Release Date : 2015
Category : Nanoparticles
Total pages :220
GET BOOK

Engineered Nanoparticles are increasingly becoming a part of our daily lives due to their presence in an overwhelming majority of consumer products. Potential health risks due to chronic exposure to such particulate matter have not been properly evaluated. A multiscale, mechanistic, toxicodynamic model was developed as part of this dissertation, for studying the impact of inhaled nanoparticles on lung function in mammalian biological systems. The biologically-based model was developed in a modular fashion, with separate consideration given to NP distribution in the entire organism as well as various mechanisms at the cell, tissue, organ, and organism levels. Specifically the effect of inhaled nanoparticles on pulmonary function is evaluated and estimated based on resultant surfactant dysfunction. Pulmonary surfactant depletion is explicitly modeled by incorporating dynamics of surfactant constituents such as phospholipids and various lipoproteins. Various nanoparticle transformation processes such as agglomeration, dissolution, diffusion, and lipid adsorption inside biological systems, are explicitly considered and their effects on surfactant modification assessed. The model relates pulmonary mechanics at the organ level with cellular level surfactant dynamics in the lung, both of which are affected by nanoparticle inhalation. The model was evaluated with data from in vitro and in vivo measurements of surfactant levels, cell counts, and overall dynamic impedance in rodent lungs. The model was also extrapolated to adult humans and prediction of changes in pulmonary tissue resistance and elastance in humans are presented based on comparable one-time nanoparticle exposure. This is the first instance of a comprehensive modeling framework integrating research and mechanistic information regarding nanoparticle-biosystem interactions at multiple scales and linking pulmonary mechanisms and processes due to interaction with particulate matter with pulmonary function in human subjects.

Computational Finite Element Methods in Nanotechnology

Computational Finite Element Methods in Nanotechnology
Author : Sarhan M. Musa
Publisher : CRC Press
Release Date : 2017-12-19
Category : Science
Total pages :640
GET BOOK

Computational Finite Element Methods in Nanotechnology demonstrates the capabilities of finite element methods in nanotechnology for a range of fields. Bringing together contributions from researchers around the world, it covers key concepts as well as cutting-edge research and applications to inspire new developments and future interdisciplinary research. In particular, it emphasizes the importance of finite element methods (FEMs) for computational tools in the development of efficient nanoscale systems. The book explores a variety of topics, including: A novel FE-based thermo-electrical-mechanical-coupled model to study mechanical stress, temperature, and electric fields in nano- and microelectronics The integration of distributed element, lumped element, and system-level methods for the design, modeling, and simulation of nano- and micro-electromechanical systems (N/MEMS) Challenges in the simulation of nanorobotic systems and macro-dimensions The simulation of structures and processes such as dislocations, growth of epitaxial films, and precipitation Modeling of self-positioning nanostructures, nanocomposites, and carbon nanotubes and their composites Progress in using FEM to analyze the electric field formed in needleless electrospinning How molecular dynamic (MD) simulations can be integrated into the FEM Applications of finite element analysis in nanomaterials and systems used in medicine, dentistry, biotechnology, and other areas The book includes numerous examples and case studies, as well as recent applications of microscale and nanoscale modeling systems with FEMs using COMSOL Multiphysics® and MATLAB®. A one-stop reference for professionals, researchers, and students, this is also an accessible introduction to computational FEMs in nanotechnology for those new to the field.

Computational Modeling of Silicon Nanoparticle Formation and Inversion of Differential Mobility Analyzer Data to Obtain Particle Size Distributions

Computational Modeling of Silicon Nanoparticle Formation and Inversion of Differential Mobility Analyzer Data to Obtain Particle Size Distributions
Author : Suddha S. Talukdar
Publisher : Unknown
Release Date : 2003
Category :
Total pages :227
GET BOOK

The main objective of the work described in this dissertation was to develop a framework for integrating detailed chemical kinetics, heat transfer and fluid-flow modeling of reactors with aerosol dynamics models that predict the evolution of particle size distributions and, ultimately, particle morphology. A numerical model has been developed to predict gas-phase nucleation, growth, and coagulation of silicon nanoparticles formed during thermal decomposition of silane. Solution of the aerosol general dynamic equation was handled by three approaches: (1) the efficient and reasonably accurate method of moments (MOM); (2) the quadrature method of moments (QMOM), which requires no prior assumption for the shape of the particle size distribution; and (3) a computationally more expensive sectional method (SM). The sectional method developed was then extended to include surface area concentration within each volume bin as well as number concentration and to explicitly account for the finite rate of sintering between coagulating particles. A Computational Fluid Dynamics (CFD) model has been developed using both a commercial package, FIDAP, and a code developed at Sandia National Laboratories, MPSalsa, to model the fluid flow and heat transfer in a laser-driven aerosol synthesis reactor used for preparing nanoparticles of silicon and other materials. From the detailed 3-D model of the reactor, temperature and velocity profiles along the axis of the reactor, in the zone where particle formation takes place, have been extracted and coupled with the one-dimensional aerosol dynamics model developed earlier. A data inversion program was written to obtain particle size distributions from differential mobility analyzer (DMA) data. Multiply charged particles have the same electrical mobility as smaller singly charged particles, such that there is not a unique relationship between particle size and electrical mobility. This ill-posedness was managed using a regularization algorithm that forces the solution (the size distribution) to be as smooth as possible while maintaining fidelity to the mobility data. The inversion program was tested with both synthetic data and experimental data and worked well for both cases.

Carbon Nanomaterials: Modeling, Design, and Applications

Carbon Nanomaterials: Modeling, Design, and Applications
Author : Kun Zhou
Publisher : CRC Press
Release Date : 2019-07-17
Category : Technology & Engineering
Total pages :468
GET BOOK

Carbon Nanomaterials: Modeling, Design, and Applications provides an in-depth review and analysis of the most popular carbon nanomaterials, including fullerenes, carbon nanotubes, graphene and novel carbon nanomaterial-based membranes and thin films, with emphasis on their modeling, design and applications. This book provides basic knowledge of the structures, properties and applications of carbon-based nanomaterials. It illustrates the fundamental structure-property relationships of the materials in both experimental and modeling aspects, offers technical guidance in computational simulation of nanomaterials, and delivers an extensive view on current achievements in research and practice, while presenting new possibilities in the design and usage of carbon nanomaterials. This book is aimed at both undergraduate and graduate students, researchers, designers, professors, and professionals within the fields of materials science and engineering, mechanical engineering, applied physics, and chemical engineering.

Metallic Nanoparticles

Metallic Nanoparticles
Author : Anonim
Publisher : Elsevier
Release Date : 2008-11-21
Category : Technology & Engineering
Total pages :408
GET BOOK

Metallic nanoparticles display fascinating properties that are quite different from those of individual atoms, surfaces or bulk rmaterials. They are a focus of interest for fundamental science and, because of their huge potential in nanotechnology, they are the subject of intense research effort in a range of disciplines. Applications, or potential applications, are diverse and interdisciplinary. They include, for example, use in biochemistry, in catalysis and as chemical and biological sensors, as systems for nanoelectronics and nanostructured magnetism (e.g. data storage devices), where the drive for further miniaturization provides tremendous technological challenges and, in medicine, there is interest in their potential as agents for drug delivery. The book describes the structure of metallic nanoparticles, the experimental and theoretical techniques by which this is determined, and the models employed to facilitate understanding. The various methods for the production of nanoparticles are outlined. It surveys the properties of clusters and the methods of characterisation, such as photoionization, optical spectroscopy, chemical reactivity and magnetic behaviour, and discusses element-specific information that can be extracted by synchrotron-based techniques such as EXAFS, XMCD and XMLD. The properties of clusters can vary depending on whether they are free, deposited on a surface or embedded in a matrix of another material; these issues are explored. Clusters on a surface can be formed by the diffusion and aggregation of atoms; ways of modelling these processes are described. Finally we look at nanotechnology and examine the science behind the potential of metallic nanoparticles in chemical synthesis, catalysis, the magnetic separation of biomolecules, the detection of DNA, the controlled release of molecules and their relevance to data storage. The book addresses a wide audience. There was a huge development of the subject beginning in the mid-1980s where researchers began to study the properties of free nanoparticle and models were developed to describe the observations. The newcomer is introduced to the established models and techniques of the field without the need to refer to other sources to make the material accessible. It then takes the reader through to the latest research and provides a comprehensive list of references for those who wish to pursue particular aspects in more detail. It will also be an invaluable handbook for the expert in a particular aspect of nanoscale research who wishes to acquire knowledge of other areas. The authors are specialists in different aspects of the subject with expertise in physics and chemistry, experimental techniques and computational modelling, and in interdisciplinary research. They have collaborated in research. They have also collaborated in writing this book, with the aim from the outset of making it is a coherent whole rather than a series of independent loosely connected articles. * Appeals to a wide audience * Provides an introduction to established models and techniques in the field * Comprehensive list of references

Computational Modeling of A-SiO2 Nanoparticles and Their Electronic Structure Calculation

Computational Modeling of A-SiO2 Nanoparticles and Their Electronic Structure Calculation
Author : Chandra Dhakal
Publisher : Unknown
Release Date : 2015
Category : Amorphous substances
Total pages :65
GET BOOK

The spherical amorphous silica (a-SiO2) nanoparticles (NPs) are constructed from a previous continuous random network (CRN) model of a-SiO2 with the periodic boundary. The models of radii 12 Å, 15 Å, 18 Å, 20 Å, 22 Å, 24 Å and 25 Å are built from the CRN structure. Then, three types of models are constructed. Type I has the surface dangling bonds not pacified. In type II models, the dangling bonds are pacified by hydrogen atoms. In type III models, the dangling bonds are pacified by the OH groups. These large models are used to perform the electronic structure calculation of NPs by using the orthogonalized linear combination of atomic orbital (OLCAO) method. The results show some trends in band gap variation for Type I models. The trends in band gap variation for other two types are less clear. A series of NP models with a spherical pore in the middle of a solid NP model are constructed and studied. Spherical pores of radii of 6 Å, 8 Å, 10 Å, 12 Å, 14 Å, 16 Å and 18 Å are introduced within the spherical model of radius 20 Å. After OLCAO calculation, it is found that the band gap values remain constant (5 eV) up to 21.6% porosity and then decreases with increased in porosity. The relation with thickness of the porous NP shell and the surface to volume ratio (S/V) with the calculated band gap are studied in the same manner and will be discussed.

Computational Approaches in Biomedical Nano-Engineering

Computational Approaches in Biomedical Nano-Engineering
Author : Ayesha Sohail,Zhiwu Li
Publisher : John Wiley & Sons
Release Date : 2019-01-14
Category : Science
Total pages :296
GET BOOK

This book comprehensively and systematically treats modern understanding of the Nano-Bio-Technology and its therapeutic applications. The contents range from the nanomedicine, imaging, targeted therapeutic applications, experimental results along with modelling approaches. It will provide the readers with fundamentals on computational and modelling aspects of advanced nano-materials and nano-technology specifically in the field of biomedicine, and also provide the readers with inspirations for new development of diagnostic imaging and targeted therapeutic applications.

Computational Nanotoxicology

Computational Nanotoxicology
Author : Agnieszka Gajewicz,Tomasz Puzyn
Publisher : CRC Press
Release Date : 2019-12-20
Category : Medical
Total pages :552
GET BOOK

The development of computational methods that support human health and environmental risk assessment of engineered nanomaterials has attracted great interest because the application of these methods enables us to fill existing experimental data gaps. However, considering the high degree of complexity and multifunctionality of engineered nanoparticles, computational methods originally developed for regular (i.e., classic) chemicals cannot always be applied explicitly in nanotoxicology. Thus, the main idea of this book is to discuss the current state of the art and future needs in the development of computational modeling techniques for nanotoxicology. The book focuses on methodology. Among various in silico techniques, special attention is given to (i) computational chemistry (quantum mechanics, semi-empirical methods, density functional theory, molecular mechanics, molecular dynamics); (ii) nanochemoinformatic methods (quantitative structure–activity relationship modeling, grouping, read-across); and (iii) nanobioinformatic methods (genomics, transcriptomics, proteomics, metabolomics).

Photonic Sintering of Nanoparticle Inks

Photonic Sintering of Nanoparticle Inks
Author : William D. MacNeill
Publisher : Unknown
Release Date : 2015
Category : Ink
Total pages :196
GET BOOK

Photonic sintering of nanoparticles is a relatively new process for sintering of nanoparticles, deposited on a substrate, into functional solid structures. The working principle of this process is the incidence of large-area broad-spectrum light onto deposited nanoparticles, which results in heat generation in the nanoparticles and their subsequent densification. Key advantages of photonic sintering include rapid, scalable and ambient condition operation. For these reasons there is significant interest in using this process as a manufacturing solution for nanoparticle sintering in emerging applications like RFID tags, flexible electronics, solar cells, and sensors. Despite preliminary demonstrations of photonic sintering, there is little knowledge on the underlying process physics, which results in limited physics-based control of the process. The goals of this work are to (1) expand the state of knowledge on the physics of photonic sintering; and (2) develop a system that can leverage the advantages of photonic sintering for low-cost additive manufacturing using nanoparticle building blocks. Four key topics in photonic sintering are investigated. First, the effects of nanoparticle size on densification and the temperature (of deposited nanomaterial and substrate) are experimentally characterized. Both the temperature and nanoparticle densification are found to be highly dependent on the nanoparticle sizes used. Secondly, a multiphysical model of photonic sintering is developed to link particle size, optically-induced heat generation, resulting temperature rise and consequent interparticle necking. In addition to reflecting experimentally observed trends, the developed model also provides an improved understanding of the underlying physics behind photonic sintering. Thirdly, densification and temperature evolution in photonic sintering of non-metallic nanoparticles is characterized. Lastly, photonic sintering and inkjet deposition are combined into one system to demonstrate the potential of using photonic sintering for a low-cost, multi-material, desktop additive manufacturing system. With further hardware and software development and greater understanding of the physics behind photonic sintering, the developed additive manufacturing system can be further refined. Further development and commercialization of the system developed here has the potential to increase accessibility of low-cost, multi-material additive manufacturing (metals, semi-conductors and ceramics) similar to the currently increased accessibility of polymer 3D printing.

Computational Modeling of the Structure and Catalytic Behavior of Graphene-supported Pt and PtRu Nanoparticles

Computational Modeling of the Structure and Catalytic Behavior of Graphene-supported Pt and PtRu Nanoparticles
Author : Raymond Gasper
Publisher : Unknown
Release Date : 2018
Category :
Total pages :129
GET BOOK

Computer modeling has the potential to revolutionize the search for new catalysts for specific applications primarily via high-throughput methodologies that allow researchers to scan through thousands or millions of potential catalysts in search of an optimal candidate. To date, the bulk of the literature on computational studies of heterogeneous catalysis has focused on idealized systems with near-perfect crystalline surfaces that are representative of macroscopic catalysts. Advancing the frontier to nanoscale catalysis, in particular, heterogeneous catalysis on nanoclusters, requires consideration of low-symmetry nanoparticles with realistic structures including the attendant complexity arising from under-coordination of catalyst atoms and dynamic fluxionality of clusters. In this thesis, we focus on understanding structure - property - function relationships of Platinum and Platinum-Ruthenium alloy nanoclusters on defective graphene supports, which are highly effective catalysts for methanol fuel cells. In particular, we focus on understanding the interplay between support defects and the electronic structure of supported nanoclusters, and the consequent impact on the thermodynamics and kinetics of the methanol decomposition reaction (MDR), a reaction of interest for renewable energy technologies such as direct-methanol fuel cells. Using density functional theory (DFT) modeling, we first investigate the adsorption and reaction thermodynamics of MDR intermediates on defective graphene-supported Pt13 nanoclusters with realistic, low-symmetry morphologies. We find that the support-induced shifts in catalyst electronic structure correlate well with an overall change in adsorption behavior of MDR intermediates. The reaction thermodynamics are modified by the support interaction to more favorable reaction free energies, suggesting greater catalytic activity. We also show that adsorption energy predictors established for traditional heterogeneous catalysis studies of MDR on macroscopic crystalline facets are equally valid on catalyst nanoclusters (supported or otherwise) with irregular, low-symmetry surface morphologies. To understand the kinetics of MDR on graphene-supported Pt13 clusters, we implement and apply a microkinetic model within a batch reactor setup. The microkinetic model predicts high activity for the MDR over nanoparticles that interact strongly with support defects, in comparison to larger nanoparticles that are only weakly influenced by the support which exhibit much lower activity; these results agree with fuel-cell level experimental results. We also find that the support effect induces changes in the most favorable reaction pathway, and in the populations of dominant surface species under realistic reaction conditions. Our studies provide molecular-level insights into experimental observations of enhanced catalytic activity of graphene-supported Pt nanoclusters for MDR and suggest promising avenues for further tuning of catalytic activity through computer-aided-engineering of catalyst-support interactions. An associated problem with modeling supported nanoclusters involves being able to generate, at the outset, realistic structures of nanoparticles. Using an empirical-potential-based genetic algorithm (developed by my colleague Dr. Hongbo Shi) and DFT modeling, we identify low-energy structures of Pt nanoparticles over the range of 10-100 atoms. We then show that there exists a size window (40-70 atoms) over which Pt nanoclusters bind CO weakly, the binding energies being comparable to those on Pt(111) or Pt(100) facets. The size-dependent adsorption energy trends are, however, distinctly non-monotonic and are not readily captured using traditional descriptors such as d-band energies or (generalized) coordination numbers of the Pt binding sites. Instead, by applying machine-learning algorithms (collaborative work with Dr. Hongbo Shi), we show that multiple descriptors, broadly categorized as structural and electronic descriptors, are essential for qualitatively capturing the CO adsorption trends. Our approach allows for building quantitatively predictive models of site-specific adsorbate binding on realistic, low-symmetry nanostructures, which is an important step in modeling reaction networks as well as for rational catalyst design in general. We also extend the Pt-C empirical potential to the Pt-Ru-C system that will allow for future studies of supported Pt-Ru nanoclusters that are among the best known catalysts for MDR. Developing the Pt-Ru-C empirical potential was based on previously established potentials for the Pt-C and Ru-C system. Achieving an accurate Pt-Ru-C potential required careful benchmarking against experimental and DFT data, resulting in targeted adjustment of the Pt-Ru and Ru-C bond parameters.