Description:

The second ChBE seminar of the Fall Quarter will be Thursday, October 8th at 9am in LR4. Dr. Manos Mavrikakis from University of Wisconsin-Madison will present a seminar titled, “Addressing Selectivity Challenges in Heterogeneous Catalysis: Formic Acid Decomposition on Transition Metals” detailed information is given below:

Speaker: Dr. Manos Mavrikakis from University of Wisconsin-Madison
Title: Addressing Selectivity Challenges in Heterogeneous Catalysis: Formic Acid Decomposition on Transition Metals

Abstract
Besides activity, often times, selectivity is a major challenge in heterogeneous catalysis. By choosing the example of formic acid (HCOOH) decomposition on transition metals and alloys, we demonstrate how a deep mechanistic understanding of selective versus unselective routes can help with designing more selective catalysts. HCOOH is a simple molecule that is an abundant product of biomass processing and can serve as an internal source of hydrogen for oxygen removal and upgrading of biomass to chemicals and fuels. In addition, HCOOH can be used as a fuel for low temperature direct fuel cells. We start by presenting a systematic study of the HCOOH decomposition reaction mechanism starting from first-principles and including reactivity experiments and microkinetic modeling. In particular, periodic self-consistent Density Functional Theory (DFT) calculations are performed to determine the stability of reactive intermediates and activation energy barriers of elementary steps. Mean-field microkinetic models are developed and calculated reaction rates, orders, etc are then compared with experimentally measured ones. These comparisons provide useful insights on the nature of the active site, most-abundant surface intermediates as a function of reaction conditions and feed composition. Trends across metals on the fundamental atomic-scale level up to selectivity trends will be discussed. Finally, we identify from first-principles alloy surfaces, which may possess better catalytic properties for selective dehydrogenation of HCOOH than monometallic surfaces, thereby guiding synthesis towards promising novel catalytic materials.

Biography
Manos Mavrikakis is Chair and Professor of Chemical and Biological Engineering at the University of Wisconsin-Madison. Marikakis received his B.S. at the National Technical University of Athens. He then received two MS degrees (Applied Mathematics and Chemical Engineering & Scientific Computing) and his PhD degree in Chemical Engineering & Scientific Computing at the University of Michigan. The major focus of his current research efforts is on the fundamental reactivity studies for a wide range of important applications, including: fuel cells catalytic electrodes, bimetallic catalysis, selective partial oxidation of hydrocarbons, and the development of novel low temperature and environmentally benign catalytic processes.

Date & Time: Thursday, October 8th 9:00 am – 10:00 am
Location: Tech LR4 (refreshments will be available at 8:45am)

Description:

ChBE's third seminar of the Fall Quarter will be presented by two of our grad students, detailed information is given below:

Speaker: Joao Moreira, PhD candidate, Amaral Lab
Title: How do we quantify the scientific impact of researchers or academic departments?

Abstract
How to quantify the impact of a researcher's or an institution's body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact Factor, have become widespread despite their known limitations. We argue that most existing bibliometric indicators are inconsistent, biased, and, worst of all, susceptible to manipulation. We present a principled approach to the development of an indicator to quantify the scientific impact of both individual researchers and research institutions grounded on the functional form of the distribution of the asymptotic number of citations. We validate our approach using the publication records of 1,283 researchers from seven scientific and engineering disciplines and the chemistry departments at the 106 U.S. research institutions classified as "very high research activity". Our approach has three distinct advantages. First, it accurately captures the overall scientific impact of researchers at all career stages, as measured by asymptotic citation counts. Second, unlike other measures, our indicator is resistant to manipulation and rewards publication quality over quantity. Third, our approach captures the time-evolution of the scientific impact of research institutions.

Speaker: DelRae Haag, PhD candidate, Kung Lab
Title: Investigation of a Graphene Oxide Coating on Nano-Gold Catalysis

Abstract
Gold nanoparticles (GNs) have shown tremendous catalytic activity for a variety of reactions such as, alcohol oxidation, reduction of aromatic nitro-compounds, CO oxidation, and the water gas shift (WGS) reaction. Much is known about the catalytic properties of GNs: the reaction rate and selectivity are highly dependent on the size and the nature of crystallographic orientation of the support. However, experiments are just beginning to understand the effect of other environment factors on catalytic activity.
Graphene and graphene oxide (GO), a highly oxidized form of graphene, are materials with incredibly interesting chemical and mechanical properties. These materials can have high surface areas and electrical properties can be tuned by reducing the amount of oxygenates on the surface. We have begun to explore how graphene oxide can be used to modify properties of gold nanoparticles. We hypothesize that the catalytic activity of gold nanoparticles on a metal oxide support can be modified by a graphene oxide over-coat. The graphene oxide coating could help reduce metal leaching during reaction, control the monodisperisity of the nanoparticles, or influence catalytic properties through electron donation/withdrawal and cooperative effects. Sub-10 nm gold particles are deposited on nonporous silica and treated with ozone to gently remove organic moieties. The silica is then wrapped with GO or reduced-GO via electrostatic or covalent interactions effectively capping the gold and silica. The catalytic activity for these gold nanoparticles versus non coated particles was tested for a variety of reactions including the catalytic reduction of 4-nitrophenol.

Date & Time: Thursday, October 15th 9:00 am – 10:00 am
Location: Tech LR4 (refreshments will be available at 8:45am)

Description:

The fourth ChBE seminar of the Fall Quarter will be Thursday, October 22nd at 9am in LR4. Dr. Mario Eden from Auburn University will present a seminar titled, “Process Systems Engineering Methods for Multi-Scale Chemical Process and Product Design” detailed information is given below:

Date & Time: Thursday, October 22nd 9:00 am – 10:00 am
Location: Tech LR4 (refreshments will be available at 8:45am)

Speaker: Dr. Mario Eden, Department Chair and McMillan Professor of Chemical Engineering, Auburn University

Title: Process Systems Engineering Methods for Multi-Scale Chemical Process and Product Design

Abstract
Process and product design problems by nature are open ended and may yield many solutions that are attractive and near optimal. It is incumbent upon the process systems engineering community to help bridge the gap between fundamental science and engineering applications as new research areas continue to emerge. This presentation will highlight several novel methods for chemical process/product design, specifically: 1) Group contribution based synthesis of process flowsheets, 2) Efficient mixture/blend design using latent variable models; 3) Spatial molecular signature descriptors for generation of non-peptide mimetics; and 4) Modeling the dispersability of polydisperse nanoparticles in gas-expanded liquids.

A systematic group contribution based framework has been developed for synthesis of process flowsheets from a given set of input and output specifications. Analogous to the group contribution methods developed for molecular design, the framework employs process groups to represent different unit operations in the system. Feasible flowsheet configurations are generated using efficient combinatorial algorithms and the performance of each candidate flowsheet is evaluated using a set of flowsheet properties. The design variables for the selected flowsheet(s) are identified through a reverse simulation approach and are used as initial estimates for rigorous simulation to verify the feasibility and performance of the design.

Mixture design is a Design of Experiments (DOE) tool used to determine the optimum combination of chemical constituents that deliver a desired response (or property) using a minimum number of experimental runs. While the approach is sufficient for most experimental designs, it suffers from combinatorial explosion when dealing with the multi-component mixtures found in e.g. pharmaceutical excipients and polymer blends. The property clustering method can alleviate this limitation by transforming the properties to conserved surrogate property clusters described by property operators, which have linear mixing rules even if the operators themselves are nonlinear. Multivariate statistical methods, i.e. principal component analysis (PCA) and partial least squares (PLS), are utilized to generate the property operator models. The methodology is illustrated using several case studies including a polymer blend problem for the formulation of a thermoplastic.

A novel method for incorporating three-dimensional structural information in molecular design algorithms has been developed. The molecular signature descriptor provides a systematic way to encode the atom type and connectivity of a molecular structure, where the signature of a molecule is a linear combination of its atomic signatures. Our earlier works have shown that the signature descriptor is a useful platform for integrating different types of property models, e.g. topological (QSAR/QSPR) and group contribution methods. We have extended this method to include three-dimensional information in the form of a spatial molecular geometry matrix, which can be manipulated to provide several useful descriptors. The ability to include the spatial/topographical (3D) arrangements of the atoms in a molecule is particularly important in applications such as molecular recognition.

The precipitation and size-selective fractionation of nanoparticles is a crucial and exceedingly difficult part of post-synthesis nanomaterial processing. Due to the size-dependent properties of nanoparticles it is often necessary to fine-tune the materials for their intended application, e.g. contrast agents in medical imaging, drug delivery vehicles, highly selective catalysts, etc. Traditionally, these processing steps (particularly the size-selective fractionation) are somewhat trial-and-error in their application, and prediction of the size and size distribution of the recovered nanoparticle fractions is quite difficult. A thermodynamic model has been developed that can accurately predict (typically within 5%) the average size and size distribution of size-selectively fractionated nanoparticles. The application of the model is demonstrated using experimental data for a system of dodecanethiol-stabilized gold nanoparticles in hexane that are precipitated by the addition of CO2.

Biography

Dr. Mario Eden is the Department Chair and Joe T. & Billie Carole McMillan Professor in the Department of Chemical Engineering at Auburn University. Dr. Eden is also the Director of an NSF-IGERT Program on Integrated Biorefining and the Acting Director of the Alabama Center for Paper and Bioresource Engineering. His main areas of expertise include process design, integration and optimization, as well as molecular synthesis and product design. His group focuses on the development of systematic methodologies for process and product synthesis, design, integration, and optimization.

Dr. Eden received his M.Sc. (1999) and Ph.D. (2003) degrees from the Technical University of Denmark, both in Chemical Engineering. He has been an active member of the process systems engineering community for almost 15 years. Dr. Eden was recently elected Director of the CAST Division of AIChE and a Board of Trustee Member of Computer Aids for Chemical Engineering (CACHE) Corporation. Dr. Eden was also selected to co-chair the 2014 Foundations of Computer Aided Process Design (FOCAPD) conference. He serves on the editorial boards for Clean Technologies & Environmental Policy, Chemical Process & Product Modeling, and the Journal of Engineering; the International Peer Review College for the Danish Council for Strategic Research; the advisory board for the Computer Aided Process Engineering Center (CAPEC-PROCESS), and is a member of the International Energy Agency Annex IX on Energy Efficient Separation Systems.

Description:

The fifth ChBE seminar of the Fall Quarter will be Thursday, October 29th at 9am in LR4. Dr. Ryan Gill from the University of Colorado will present a seminar titled,“A Design-Build-Test-Learn Technology Platform for the Multiplex Engineering of Microbial Systems”detailed information is given below:

Date & Time: Thursday, October 29th 9:00 am – 10:00 am

Location: Tech LR4 (refreshments will be available at 8:45am)

Speaker: Dr. Ryan Gill, University of Colorado

Title: A Design-Build-Test-Learn Technology Platform for the Multiplex Engineering of Microbial Systems

Abstract
The era of genome engineering is now well underway. DNA synthesis and sequencing capabilities continue to advance at rates beyond Moore’s law, to the point that reading and writing DNA are no longer the rate limiting step in the engineering of biological systems. Current applications of these technologies seek to construct genomes that can perform increasingly complex functions; ranging from the production of chemicals, fuels, nutraceuticals and pharmaceuticals to the recoding of microbiome relevant organisms for applications in human health, energy, or the environment among others. Such applications will require that we are able to not only identify genes encoding key functions but also combinations of such genes, and combinations of such combinations, that together result in desired organism performance. We are developing a range of new technologies along these lines that include i) the construction and use of “ideal” chassis strains, ii) efficient searching of mutational space for the identification of gene-phenotype relationships, iii) rapid, flexible, and high-throughput genome-editing methods, and iv) construction and parallel interrogation of such combinatorial mutation libraries to identify combinatorial design rules. This presentation will describe the first generation of such technologies, the current state of next-generation approaches, and the most recent application of such tools to the design and engineering of microbial systems.

Biography
Dr. Ryan Gill is a Patten Associate Professor of Chemical and Biological Engineering at the University of Colorado and the Associate Director of Renewable and Sustainable Energy Institute. Gill received his BS in Chemical Engineering from The John Hopkins University in 1993. He then received his MS in 1997and PhD in 1999 from the University of Maryland. Gill’s research falls within the general fields of metabolic engineering, synthetic biology, directed evolution, and genomics and is targeted primarily towards the development biorefining processes for the sustainable production of fuels, commodity chemicals, and pharmaceuticals. We are generally focused on the development of new i) tools for strain engineering (i.e. genome engineering), ii) methods for efficiently determining the genetic basis of so engineered strains (i.e. functional genomics), and iii) frameworks for rationalizing relationships identified between genome structure and function.

Description:

Detailed information TBA