SUNY at Albany

NSF Awards · FY 2024 · 2024-09

Semiconductor-derivative manufacturing in the northeast U.S is expanding, and this expansion is increasing the demand for a highly qualified technical workforce. The Northeast Advanced Technological Education Center (NEATEC) proposes to support the education and training of technicians for the semiconductor and semiconductor-derivative industries (i.e., those industries based on, or incorporating, substantial Si wafer processing, compound semiconductor wafer processing or Si polycrystalline film processing) as well as the broader nanotech-based manufacturing industries in New York State and Western New England. NEATEC will expand opportunities in support of academic programs as well as targeted outreach to recruit and engage underserved and underrepresented populations. All programs will leverage online compatible learning management systems (e.g., Blackboard) to combine online delivery with hands-on laboratory and/or experiential learning components at NEATEC training and lab facilities. This includes a newly proposed ATE user facility at SUNY Polytechnic Institute which will help promote and sustain NEATEC's education/training content and the 'institutionalization' of that content at 2-year and 4-year colleges. This Center will 1) develop multiple academic certificate programs for technological education for a wide range of semiconductor-derivative industries (e.g., Photovoltaic Manufacturing (PVM), LED Lighting Manufacturing (LEDLM), Power Electronics Manufacturing (PEM), and Integrated Photonics Manufacturing (IPM)); 2) expand commitments from industrial collaborators for skill-standard analyses and experiential learning; 3) expand community college and technical high-school partners, including a new NEATEC/Technical High School partnership for at-risk students to adapt curricula to technical high school programs in Central New York with expansion to technical high schools in MA and CT; and 4) develop new technological education programs for underserved and underrepresented groups- specifically newly separated veterans and international refugee communities (permanent U.S. residents) in central New York State. NEATEC's core academic development team includes Hudson Valley Community College, Erie Community College, Jefferson Community College, Mohawk Valley Community College, Onondaga Community College, and Fulton Montgomery Community College in New York State, and Fairfield University in Connecticut. Industry collaborators include GlobalFoundries, Tokyo Electron, General Electric, SolarCity, Soraa, AIM Photonics, United Technologies Research Center, and the Interstate Renewable Energy Council (IREC).

NSF Awards · FY 2024 · 2024-09

This project aims to serve the national interest by providing a long-term professional development pathway for two-year college chemistry faculty across the Northeast region of the country. Specifically, 50 two-year college faculty will participate in a multi-pronged discipline specific professional development initiative that aims to develop transformative learning experiences in first- and second-year chemistry courses. Two annual in person workshops will be followed by the creation of virtual communities of practice using an online learning platform and ongoing engagement with peer mentors. The impact of the activities on participating faculty satisfaction and their students will be assessed and utilized to refine project activities. The project benefits from partnerships between experienced two-year college faculty and chemistry education experts in the region. This work has the potential for significant impact in meeting the learning needs of two-year college students, who represent a considerable portion of science and engineering students that ultimately receive STEM bachelor's and master's degrees. Ultimately, the project is likely to increase student success and make a significant contribution to broadening participation in STEM academic pathways. The goal of this project is to provide two-year college chemistry faculty with professional development support for collaboratively adopting and implementing evidence-based practices to improve the student experience in introductory chemistry courses. Three objectives provide a framework for project implementation: 1) assemble a regional professional community of 50 two-year college chemistry faculty and increase their pedagogical self-efficacy and satisfaction, 2) provide access to chemistry-specific professional training and collaborative opportunities, and 3) support faculty with the incorporation of evidence-based practices through a community of practice and discipline-specific action steps. The established community will address professional isolation, leverage partnerships, and support the development of professional connections between faculty from two-year and four-year institutions. Assessment efforts utilize faculty and student surveys, interviews, and other measures. These instruments seek to provide data and insight on the effectiveness of professional development and networking on transforming teaching practice and ultimately on student learning. The project also aims to study the impact on faculty professional satisfaction and pedagogical self-efficacy. Project outcomes will be disseminated at local, regional, and national STEM education conferences and made available through targeted publication in relevant journals. The NSF IUSE: Innovation in Two-Year College STEM (ITYC) Program seeks to accelerate the impact of and advance knowledge about emerging and evidence-based practices in undergraduate STEM education at two-year colleges. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This award supports research on understanding and predicting decision-making among vulnerable populations in disasters. In most states in the US, more than one type of natural hazard can be present. Several population groups are considered especially vulnerable to these natural hazards, including marginalized racial and ethnic minorities, people with disabilities, low-income households, and older adults. The efforts undertaken in this study are built upon a nationwide survey by the project team on individual disaster preparedness and willingness to use emerging technology to improve preparedness measures, and are framed by well-established decision and cognition theories. Using survey findings, the research team will conduct disaster preparedness experiments across multiple hazards using Virtual Reality (VR). Given differences in risk perception for compounding effect, the project aims to gain insight into decision-making processes across various hazards and age groups. This project deploys and tests an innovative VR-based method to evaluate the decision-making process in disasters. The tasks are four-fold: 1) Examines differences based on the type of hazard using a VR platform to conduct experiments with older adult participants. 2) Investigates the mechanism by which optimal protective action decisions are made, whether fact- or emotion-based. 3) Explores the methodological contribution to advance disaster research with the use of a virtual environment to conduct experiments. 4) Assesses the acceptance of VR to improve preparedness among adults using a between-groups design. The study bridges two topical areas, focusing on hazards induced by natural phenomena and infectious diseases. The outreach activities include public engagement with practitioners on improving well-being of older adults in communities. The project establishes a partnership between academia and the private sector and contributes to undergraduate student capstone courses. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project uses combinatorial models to solve problems and perform computations in algebra (more specifically, representation theory), as well as geometry and topology of flag manifolds; new connections between these areas are also revealed in this process. Combinatorics studies discrete structures (such as permutations and graphs), which are well suited for encoding complex mathematical objects. Representation theory is a fundamental tool for studying symmetry, by realizing the elements of abstract groups/algebras as linear transformations of some vector spaces. The PI studies representations of Lie algebras and quantum groups, which have many applications to physics, such as calculating the probability of a particle system being in a given state at a particular time. In geometry, the PI focuses on modern Schubert calculus on flag manifolds. This area has its origins in enumerative geometry (e.g., counting the lines or planes satisfying a number of generic intersection conditions), and is currently related to modern areas such as quantum cohomology/K-theory and elliptic cohomology. This project includes several research topics for graduate and undergraduate students. In representation theory, the PI will work on new applications and problems involving crystals, which are colored directed graphs encoding representations of quantum algebras when the quantum parameter goes to 0. One such problem is concerned with a refinement of the so-called atomic decomposition of crystals, due to the PI and C. Lecouvey; this refinement is related to the pre-canonical bases of Hecke algebras, recently defined by N. Libedinsky, L. Patimo, and D. Plaza, which interpolate between the standard basis and the Kazhdan-Lusztig basis. The PI will also extend and find new applications of his quantum alcove model, as a uniform combinatorial model for (tensor products of) Kirillov-Reshetikhin crystals, in all affine types. In modern Schubert calculus, the PI has two main projects. The first one involves an application of the Chevalley multiplication formula in the quantum K-theory of flag manifolds, recently proved by the PI, S. Naito, and D. Sagaki. The second one is concerned with the equivariant elliptic cohomology of flag manifolds, and more precisely with the combinatorics of the elliptic classes constructed by R. Rimányi and A. Weber. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Non-technical Description: Gallium nitride (GaN) and related III-nitride alloys (AlGaN) form the basis for modern optoelectronics, including bright blue and white light-emitting diodes (LEDs) and lasers. Bright deep ultraviolet (DUV) LEDs with wavelengths less than 300 nm are the only alternative technology to replace bulky mercury lamps in numerous applications, including gas sensing, phototherapy, air and drinking water purification, large-scale disinfection, and sterilization of public areas. The main obstacle to this semiconductor technology is the need for conductive p-type AlGaN - a semiconductor material with added dopant impurities that greatly improve its properties. Currently, Mg is the only available p-type dopant for these devices. Unfortunately, the efficiency of these LEDs for wavelengths below 270 nm rarely exceeds 1%. The principal investigators and their research team use beryllium (Be) as an alternative p-type dopant for GaN and AlGaN. Their preliminary results show that Be impurity or Be-containing complexes are very promising for the realization of conductive p-type III-nitride materials that could be used in future bright DUV LEDs. The proposed research program impacts the education of under-represented minorities at VCU, which in 2022 has been designated a Minority Serving Institution by the US Department of Education. Collaboration between SUNY-Albany and VCU forms a strong foundation for research and education in both institutions. This project also strengthens international collaboration with researchers at the High Pressure Institute in Poland – the world leaders in the growth of bulk GaN and studies involving ultra-high pressure. Technical Description: This project uses an innovative idea to create Be-related complexes, such as Be-O-Be, to achieve high-conductivity p-type AlGaN semiconductor alloy. The research team’s preliminary experimental and theoretical results indicate that highly efficient p-type III-nitride materials are feasible. Fabrication of conductive p-type AlGaN produced by in-situ Be-O co-doping or ion implantation is a novel approach to significantly improve device performance for solid-state lighting, especially the bright DUV LEDs. SUNY’s team is the only research group in the world to grow Be-doped GaN and AlGaN using the metalorganic chemical vapor deposition (MOCVD) technique, which has proven to be the most efficient method for developing bright white and UV LEDs. First-principles calculations and detailed characterization studies, including temperature-dependent Hall effect, photo- and cathodoluminescence, provide valuable feedback to the growth/implantation efforts. The ultimate goal is to achieve reliable p-type AlGaN and to gain in-depth understanding of the properties of impurities and defects in III-nitride semiconductors. Understanding co-doping mechanisms may lead to breakthroughs in doping other semiconductors. The research also attempts to explain the properties and identity of point defects unintentionally introduced in GaN, AlN, and AlGaN. This project can potentially develop high p-type conductivity ultra-wide-bandgap III-nitrides and bridge the gap between theorists and experimentalists in this field. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

With the support of the Chemical Synthesis program in the Division of Chemistry, Professor Evgeny Dikarev of the SUNY Albany will study prospective battery materials that require a carbon modulation to perform. Rechargeable batteries represent a critical component of the ever-growing energy storage field, facilitating a transition towards energetics based on the renewable and green energy sources. This project is focused on preparing materials that are needed for the next generation of rechargeable battery. The project develops strategies to efficiently replace expensive, rare metals that are presently used with ones that are less expensive and more abundant such as sodium, magnesium, silicon, and iron. Battery safety issues also will be considered. The project lays a solid foundation for an innovative technology that can be broadly adopted by industry for the fabrication of advanced rechargeable battery materials. The project has an important outreach and community efforts component that will focus on a new Emerging Technology and Entrepreneurship program at SUNY Albany and summer program on chemical fingerprinting of “secret” household items designed for local high school students. The project will develop a new synthetic methodology for the preparation of prospective materials that require a carbon modulation to perform. Atomically-precise single-source carbonaceous precursors with functionalized ligands and with the proper A:M:M’:E (A = Li, Na, Mg; M/M’ = transition metals; E = F, P, Si, S) ratios for the target carbon-coated fluoride, phosphate, silicate, fluorophosphate, and fluorosulfate materials will be designed using molecular-architecture concepts based on model structures and synthesized in the course of this work. Such a wide selection of target materials is intended to demonstrate the potential of “all-in-one” heterometallic precursor technique for the preparation of not just a single mixed-metal phase, but rather a composite carbon-coated nanocrystalline architecture required for advanced energy storage applications. The major practical outcome of this research is to demonstrate that single-source precursor approach facilitates multimetallic carbon-coated cathode materials with unique characteristics such as purity, exact stoichiometry, low preparation temperature, nanosized particles morphology, and, especially, highly homogeneous element distribution. In addition, the project will train undergraduate and graduate students in areas related to modern battery technologies. There is also a component that introduces high school students to elemental crystallography. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Kelvin waves are a well-documented synoptic weather phenomenon in the Tropics, accounting for 70% of the rainfall associated with the Madden-Julian oscillation (MJO) near the equator, which is a prominent mode of deep convection in the Tropics in its own right with important impacts on the global circulation and global weather patterns. Kelvin waves can also directly impact circulations beyond the Tropics through teleconnections associated with deep convection coupled to these disturbances. The propagation characteristics of synoptic disturbances in the Tropics including Kelvin waves and the MJO are poorly represented in climate models, which has consequences for the global circulation, water and energy budgets, and the ability of operational global models to optimize the subseasonal to seasonal predictability inherent in the climate system. This project aims to improve fundamental understanding of the phase speed of Kelvin waves, including the influence of background advection by the mean wind, moist processes, and static stability, using gridded data products and satellite observations of deep clouds. Project outcomes include documentation of Kelvin wave phase speed under varying background conditions such as the El Niño Southern Oscillation (ENSO) and the MJO, as well as secular trends in the background state over time present in the observational data sets. The Principal Investigator has a strong background in Kelvin wave dynamics and in training the next generation of scientists for a range of STEM positions including academia, private sector, government laboratories, and forecasting agencies. The project will identify Kelvin waves in satellite outgoing longwave radiation (OLR) using a method well-established by the Principal Investigator and colleagues over many years. Average phase speeds will be estimated from Hovmöller diagrams (longitude vs time) of Kelvin wave filtered OLR for select background conditions including different seasons and ENSO and MJO phases. Results will be assessed at different pressure levels to understand how phase speed changes with height under different background wind, moisture and static stability conditions based on gridded data. Quality control measures will be taken to assure the select wave cases used for compositing are consistent with the expected horizontal structure and equivalent depth for a Kelvin wave. Background advective winds will be defined as the 20-day lowpass filtered wind at each level over the dates of the wave events. Contributions to the phase speed by moist processes will be determined by regressing the advection corrected phase speed onto profiles of atmospheric moisture and satellite rainfall for wave events. Understanding how Kelvin wave phase speed associates with tropospheric background conditions will give us benchmarks to assess how well global models simulate eddy mean flow interactions in the Tropics. Techniques developed to improve models based on these benchmarks could be applicable to mid-latitude eddy mean flow interactions. The results will also provide benchmarks for how convection quantitatively impacts wave phase speeds, providing insight into model representation of coupled convection in Kelvin waves. The project will train two PhD students, who will carry out the analysis as part of their thesis work. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.