CCI Technical Projects

2022 Spring Technical Projects

Under Consideration

2021 Fall Technical Project

Coming Soon

2021 Summer Technical Projects

Density Functional Theory (DFT) Calculations for Rare Earths

The rare-earth based materials are becoming increasingly applicable in our everyday life.
The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earth magnets and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Materials Technology
Mentor: Durga Paudyal

Materials discovery and design using machine learning

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modeling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Materials Technology
Mentor:  Durga Paudyal


 

2021 Spring Technical Projects

Density Functional Theory (DFT) Calculations for Rare Earths

The rare-earth based materials are becoming increasingly applicable in our everyday life.
The enormous importance of rare-earths in the technology, environment, and economy is attracting scientists all over the world to investigate them starting from the extraction to the physical and chemical properties measurements. Although a lot of works have been done on the experimentation of rare-earths, the true understanding from theory and modeling on these materials is lagging behind. Here, we propose to perform systematic theoretical research from the density functional theory applicable to rare-earth magnets and also study suitable models in order to compare their finite temperature properties obtained from precise experiments.

Research area: Materials Technology
Mentor: Durga Paudyal

2020 Summer Technical projects

Facilities Engineering Internship

Intern candidate could assist with the design, fabrication, testing, and assembly of research equipment and systems for scientific staff at the Ames Laboratory. Duties might also include incorporating as-built changes into original shop drawings and archiving drawings into database. Individual will learn to work with computer aided design (CAD) software and participate in the conceptual design phase of project development and provide feedback on system design. Intern candidate could assist with facilities plant engineering related projects that might include laboratory renovations, floorplan layouts for infrastructure projects, and drawing database management tasks.  Intern would utilize 2D and 3D CAD software and participate in most phases of an facilities related engineering project. Intern would choose area of most interest (i.e., Research Equipment Design or Facilities Design) for the term.

Mentor:  Terry Herrmann

Aptamer Selection and Optimization

Aptamers are short single stranded nucleic acids that fold in specific ways to selectively bind their target molecules. Like antibodies, they have high affinities and specificities for their target molecules. But, unlike antibodies, aptamers are selected in vitro. We will be selecting and maturing nucleic acid aptamers that specifically recognize a group of proteins that are released underground by plant roots. Similar in their function to antibodies, aptamers can be used in biosensors to detect the proteins to which they have been selected. Once selected and matured, the aptamers we select will be integrated into a nanoporous anodized aluminum oxide sensing platform to create an aptasensor that will be placed near roots in soil for molecular recognition to report on activities under the ground. 

Research area:  Engineering Technology - Chemical
Mentor:  Marit Nilsen-Hamilton

DNA Oragami and the Analysis of Nanostructures

The DNA of our chromosomes is base paired in a very predictable manner to form a double-stranded structure. This reliability of DNA base pairing can be used to prepare nanostructures of DNA. The process of designing and preparing these nanostructures is called DNA origami. DNA origami structures are being designed for purposes that range from carrying drugs to a target in the body to providing a structural basis for metamaterials. This project involves the development of strategies for designing DNA origami shapes, preparing the nanostructures and analyzing them to determine which structures that are formed. The shapes are intended to be coated with metal to become split ring resonators that will be arrayed to form a metamaterial that will take on the properties of the mythical invisible cloak.

Research area: Engineering Technology - Biological (nonmedical)
Mentor:  Marit Nilsen-Hamilton

Materials discovery and design using machine learning

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Engineering Technology - Materials
Mentor: Durga Paudyal
Chemical Composition Analysis

The student in this CCI internship will majorly focus on identifying the composition of chemicals from catalytic reactions. The student will be highly involved with analytical instrumentations, such as gas chromatograph, liquid chromatograph, mass spectrometer, and Fourier transform infrared spectroscopy (FTIR). The student will also learn how to identify the chemical formula and structure from the spectra using standards and structure database.

Research area:  Chemical composition and analysis
Mentor:  Wenyu Huang

Materials Structure Characterization

MATERIAL STRUCTURE CHARACTERIZATION

 

The student in this CCI internship will focus on identifying the elemental composition and structure of nanomaterials synthesized for catalytic reactions. The student will be highly involved with instrumentations for composition and structure analysis, such as Inductively coupled plasma mass spectrometry (ICP-MS), Inductively coupled plasma atomic emission spectroscopy (ICP-AES), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). The student will also learn how to identify the structure of the nanomaterial from the spectra using standards and structure database.

 

Research Area:  Materials Technology
Mentor:  Wenyu Huang

Nanostructured Catalysts

Students will participate in a project aimed to prepare smart multifunctional nanodevices for catalyzing sequences of chemical reactions to convert biomass related products into biorenewable fuels and chemical commodities. The nanostructured materials will be composed of organic and inorganic species that will work cooperatively to effectively promote chemical conversions behaving like nanosized assembly lines. The students will be trained in the synthesis and characterization of hybrid mesoporous materials. They will use a series of analytical methods including powder x-ray diffraction, gas physi- and chemisorption and spectroscopy. Training will be provided as needed.

Research area: Nanotechnology
Mentor:  Igor Slowing

Catalytic Conversion of Carbon Dioxide

Carbon Capture, Utilization and Storage is a highly-sought goal by Department of Energy. We would like to target the catalytic conversion of carbon dioxide to produce value-added oxygenates as advanced fuels and chemicals.

Highly selective catalysts will be synthesized with first-row transition metals. The metal-based nanoparticles will be supported on a water-tolerant porous catalyst. A plug-flow reactor will be designed and custom-made, which should be readily scalable. The reactor will be coupled with the fully-automated chromatographic techniques for online analysis. Hydrogen gas will be used as the reducing agents for the production of aliphatic alcohols. Reactions of CO2 with epoxides will be studied as well for the production of organic carbonates. In both cases, reaction conditions, including flow rate, temperature, system pressure, etc., will be investigated to evaluate the selectivities of various catalysts in a continuous flow mode.

Research area:  Chemical Technology
Mentor:  Long Qi

Mechanical Engineering

Intern candidate will work under the guidance of a Mechanical Design engineer and could assist with the design, fabrication, testing, and assembly of research equipment and systems for scientific staff at the Ames Laboratory. Duties might also include incorporating as-built changes into original shop drawings and archiving drawings into database. Individual will learn to work with computer aided design (CAD) software and participate in the conceptual design phase of project development and provide feedback on system design. Intern will observe manufacturing services and capabilities available at the Ames Laboratory Machine Shop, including lathe turning, mill work, and electrical discharge machining, as applied to a variety of materials. Intern candidate could assist with facilities plant engineering related projects that might include laboratory renovations, floorplan layouts for infrastructure projects, and drawing database management tasks.  Intern would utilize 2D and 3D CAD software and participate in most phases of a facilities related engineering project.

 

Research Area:  Engineering Technology - Mechanical
Mentor:  John Misra

Plastic Upcycling Through Chemical Catalysis

We are developing catalysts for conversion of polymers, the principle component in plastics, from waste materials into new polymers, monomers for repolymerization (recycling), or new valuable chemicals. The vision is that such chemical transformations will provide incentives for collection and processing of plastic waste, which currently are landfilled or discarded on hundred megaton scale. Our approach involves synthesis of supported catalysts and investigation of reactions that break the carbon-carbon bonds polymer chain backbones.

Research Area:  Chemical Technology
Mentor:  Aaron Sadow

 

2020 Spring Technical Projects

Facilities Engineering Internship

Intern candidate could assist with the design, fabrication, testing, and assembly of research equipment and systems for scientific staff at the Ames Laboratory. Duties might also include incorporating as-built changes into original shop drawings and archiving drawings into database. Individual will learn to work with computer aided design (CAD) software and participate in the conceptual design phase of project development and provide feedback on system design. Intern candidate could assist with facilities plant engineering related projects that might include laboratory renovations, floorplan layouts for infrastructure projects, and drawing database management tasks.  Intern would utilize 2D and 3D CAD software and participate in most phases of an facilities related engineering project. Intern would choose area of most interest (i.e., Research Equipment Design or Facilities Design) for the term.

Mentor:  Terry Herrmann

Aptamer Selection and Optimization

Aptamers are short single stranded nucleic acids that fold in specific ways to selectively bind their target molecules. Like antibodies, they have high affinities and specificities for their target molecules. But, unlike antibodies, aptamers are selected in vitro. We will be selecting and maturing nucleic acid aptamers that specifically recognize a group of proteins that are released underground by plant roots. Similar in their function to antibodies, aptamers can be used in biosensors to detect the proteins to which they have been selected. Once selected and matured, the aptamers we select will be integrated into a nanoporous anodized aluminum oxide sensing platform to create an aptasensor that will be placed near roots in soil for molecular recognition to report on activities under the ground. 

Research area:  Engineering Technology - Chemical
Mentor:  Marit Nilsen-Hamilton

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DNA Oragami and the Analysis of Nanostructures

The DNA of our chromosomes is base paired in a very predictable manner to form a double-stranded structure. This reliability of DNA base pairing can be used to prepare nanostructures of DNA. The process of designing and preparing these nanostructures is called DNA origami. DNA origami structures are being designed for purposes that range from carrying drugs to a target in the body to providing a structural basis for metamaterials. This project involves the development of strategies for designing DNA origami shapes, preparing the nanostructures and analyzing them to determine which structures that are formed. The shapes are intended to be coated with metal to become split ring resonators that will be arrayed to form a metamaterial that will take on the properties of the mythical invisible cloak.

Research area: Engineering Technology - Biological (nonmedical)
Mentor:  Marit Nilsen-Hamilton

Materials discovery and design using machine learning

The screening of novel materials with good performance and the modelling of quantitative structure-property relationships, among other issues, are hot topics in the field of materials science. Traditional computational modelling often consume tremendous time and resources and are limited by their theoretical foundations. Thus, it is imperative to develop a new method of accelerating the discovery and design process for novel materials. Recently, materials discovery and design using machine learning have been receiving increasing attention and have achieved great improvements in both time efficiency and prediction accuracy. Here we intend to introduce machine learning for rare earth containing materials, propose possible algorithms to predict new materials. By directly combining computational studies with available experimental data, we hope to provide insight into the parameters that affect the properties of materials, thereby enabling more efficient and target oriented research on materials discovery and design.

Research area: Engineering Technology - Materials
Mentor: Durga Paudyal

Chemical Composition Analysis

The student in this CCI internship will majorly focus on identifying the composition of chemicals from catalytic reactions. The student will be highly involved with analytical instrumentations, such as gas chromatograph, liquid chromatograph, mass spectrometer, and Fourier transform infrared spectroscopy (FTIR). The student will also learn how to identify the chemical formula and structure from the spectra using standards and structure database.

Research area:  Chemical composition and analysis
Mentor:  Wenyu Huang

Materials Structure Characterization

MATERIAL STRUCTURE CHARACTERIZATION

 

The student in this CCI internship will focus on identifying the elemental composition and structure of nanomaterials synthesized for catalytic reactions. The student will be highly involved with instrumentations for composition and structure analysis, such as Inductively coupled plasma mass spectrometry (ICP-MS), Inductively coupled plasma atomic emission spectroscopy (ICP-AES), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). The student will also learn how to identify the structure of the nanomaterial from the spectra using standards and structure database.

 

Research Area:  Materials Technology
Mentor:  Wenyu Huang

Nanostructured Catalysts

Students will participate in a project aimed to prepare smart multifunctional nanodevices for catalyzing sequences of chemical reactions to convert biomass related products into biorenewable fuels and chemical commodities. The nanostructured materials will be composed of organic and inorganic species that will work cooperatively to effectively promote chemical conversions behaving like nanosized assembly lines. The students will be trained in the synthesis and characterization of hybrid mesoporous materials. They will use a series of analytical methods including powder x-ray diffraction, gas physi- and chemisorption and spectroscopy. Training will be provided as needed.

Research area: Nanotechnology
Mentor:  Igor Slowing

Catalytic Conversion of Carbon Dioxide

Carbon Capture, Utilization and Storage is a highly-sought goal by Department of Energy. We would like to target the catalytic conversion of carbon dioxide to produce value-added oxygenates as advanced fuels and chemicals.

Highly selective catalysts will be synthesized with first-row transition metals. The metal-based nanoparticles will be supported on a water-tolerant porous catalyst. A plug-flow reactor will be designed and custom-made, which should be readily scalable. The reactor will be coupled with the fully-automated chromatographic techniques for online analysis. Hydrogen gas will be used as the reducing agents for the production of aliphatic alcohols. Reactions of CO2 with epoxides will be studied as well for the production of organic carbonates. In both cases, reaction conditions, including flow rate, temperature, system pressure, etc., will be investigated to evaluate the selectivities of various catalysts in a continuous flow mode.

Research area:  Chemical Technology
Mentor:  Long Qi