The Science and Technologies for Phosphorus Sustainability (STEPS) Center is a convergence research hub for addressing the fundamental challenges associated with phosphorus sustainability. The vision of STEPS is to develop new scientific and technological solutions to regulating, recovering and reusing phosphorus that can readily be adopted by society through fundamental research conducted by a broad, highly interdisciplinary team. Key outcomes include new atomic-level knowledge of phosphorus interactions with engineered and natural materials, new understanding of phosphorus mobility at industrial, farm, and landscape scales, and prioritization of best management practices and strategies drawn from diverse stakeholder perspectives. Ultimately, STEPS will provide new scientific understanding, enabling new technologies, and transformative improvements in phosphorus sustainability.

This proposal will consider novel classes of organized nanochannel biomolecular nanomaterials for understanding the design principles of efficient organized gel-like adaptive materials with enhanced porosity dimension and topological control, materials and energy transport, chiral biomolecules selection and storage/release, and prospective chiral biocatalytic templates. The team will synthesize, design, and study biomolecular magnetic organic frameworks (BiMOFs) based upon biologically encoded peptides with metal-binding terminal groups for coordination with magnetic ions/clusters.

This fundamental research is motivated by three major global challenges that directly involve the transformation of gas molecules: carbon dioxide (CO2) capture for greenhouse gas mitigation, CO2 conversion to fuels and chemicals, and nitrogen (N2) gas conversion to biologically available ammonia to meet growing fertilizer demand. The research focuses on creating and investigating multi-functional interfaces that durably immobilize enzymes near their gaseous substrates while simultaneously delivering essential chemical and electrical reducing equivalents and removing reaction products to achieve maximum catalytic rates. Biocatalytic systems to be explored are: conversion of CO2 to bicarbonate catalyzed by carbonic anhydrase, reduction of CO2 to formate catalyzed by formate dehydrogenase, and reduction of N2 to ammonia catalyzed by nitrogenase. We envision that minimization of reaction barriers near immobilized biocatalyst interfaces involving gas molecule conversions will lead to transformative innovations that help overcome global sustainability challenges.

The goal of this work is to develop a high-throughput methodology that enables evaluation of macromolecular structure, self-assembly, and mechanical functionality in silico and facilitates concomitant iterative experimental validation and improvement of the computational predictions ex silico, with hybrid biomacromolecular polyquinoline-reflectin materials serving as the model system for verification and validation of the overall approach.

The REU site: Materials Engineering with Data Science (MATDAT) at North Carolina State University focuses on an emergent intersection between materials science and engineering and data science, which are traditionally disparate fields. The demand by the materials community for data-driven research for the analysis, design and development of materials has grown in the past few years, motivating a new, interdisciplinary approach to materials education and research. We seek to introduce such training through an interdisciplinary materials and data science REU. Ten (10) participants classified as rising juniors and seniors from various academic backgrounds in the physical mathematical sciences, and engineering will be recruited to spend ten summer weeks of mentor-guided research experiences. Projects will integrate machine learning, informatics, statistical and mathematical methods, and other data science tools in experimental and computational-based materials discovery. A diverse cohort of participants will be recruited each year, leveraging established relationships with minority-serving institutions such as the University of Puerto Rico- Mayaguez and North Carolina Central University (NCCU), a historically black college, which is the collaborating institution of the NRT to attract students historically underrepresented in STEM disciplines. Additional recruitment efforts will focus on students enrolled in institutions with limited research opportunities. Students will be supported by state-of-the-art resources such as the Analytical Instrumentation Facility (AIF), computing facilities, laboratories, and the NCSU Hunt Library, which provides a number of data visualization and coding resources that are available to all participants. Research activities will be supported by training in data science tools, responsible code of conduct, ethics, and cultivate a safe and productive environment. A range of professional skills seminars complement technical training, increasing participant������������������s self-efficacy, engineering identities, problem-solving skills, literacy in other disciplines as related to data science, scientific communication, time management, and preparation for graduate studies. Exposing the students to relevant concepts and tools in data science through this REU program is aimed at encouraging them to pursue careers in STEM-related fields.

Currently, there is a lack of understanding how to efficiently engineer multi-stranded NANP networks with controlled mechanical, physicochemical, and biological properties. Despite the existence of computational tools for NANP design19, the use of NANPs as modular building blocks for supra-assemblies has never been systematically investigated. Therefore, the long-term goal of our team is to address this gap in knowledge and shift the existing paradigm by developing a generalizable NANP-based programmable platform that simultaneously encodes targeted physicochemical, mechanical, and biological properties through networks of independently programmable architectural parameters.

The proposed research is based on the design of a supramolecular assemblies that will enable systematically and iteratively probing the impact of the proximity and orientation of metal coordinating moieties; this conformation is naturally provided by protein tertiary and quaternary structure. The proposed work will serve as a model system: peptides from native protein metal-binding sites will be synthesized and coupled to a hydrophobic polymer tail to drive the self-assembly into a nanostructure that recreates the natural binding site. The chemical versatility of polymers offers distinct advantages for the proposed studies since the length, pendant groups, and architecture can be varied independently. The complexity of the processes in such amphiphilic nanostructures calls for an iterative computational-experimental study, which represents the most efficient strategy for systematic investigations of complex nanomaterials. The ultimate goal of this experimental/computational research is to provide a fundamental understanding of inter-and intramolecular interactions that contribute to metal binding specificity, unlocking rules of metal ion homeostasis and providing insight into the design of proteins and nanomaterials with complex metal-binding profiles in order to design novel complex hierarchical nanostructures with tunable architectures

This is a proposal in response to a new FOA including calls for proposed renewal of existing Energy Frontier Research Centers. At NC State, we work in a multi-disciplinary collaboration between the College of Agriculture and Life Sciences and the College of Engineering to understand how cellulose is made by plants. Cellulose within plant cell walls is a major renewable resource with importance to many biomaterials and biomass feedstocks. We will combine advanced microscopy, genetics, and computational modeling to uncover the mechanisms regulating the formation of cellulose microfibrils and their biophysical properties.

This proposal is to study the use of heteroaggregation as a simple method for assembly of multifunctional nanoparticles.

Polymer dispersions are a general class of materials in which fine (nano- and micro-sized) polymeric particles are dispersed in an aqueous phase. Such materials are commonly used in several industries, including medicine, paints and coatings, automobiles, and plastics. The application of polymer dispersions to emerging technologies, such as organic optoelectronic devices (e.g., solar cells, light emitting diodes, or photodetectors), could take advantage of existing industrial infrastructure to help catapult polymer dispersions into the consumer electronics market. This potential new application area poses a significant challenge for traditional polymer dispersions because of the great diversity of organic materials that constitute optoelectronic devices. In addition, a priori predictions of the structure of polymer dispersions and the resultant film properties are extremely difficult due to known correlations that exist among constituent material properties, emulsion processing parameters, polymer dispersion structure/morphology, thin-film deposition parameters, and film properties. This challenge is exacerbated by the mesoscale nature of the material system that prevents application of first-principles theoretical approaches. As a result, it is difficult to design a polymer dispersion that will yield specified film characteristics. Therefore, the overall goal of the proposed work is to establish fundamental process-structure-property relationships to guide the predictive design of a new class of polymer dispersions applicable to organic optoelectronic devices.