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Here, we present a novel mechano-spectroscopic atomic force microscopy (AFM-MS) technique that overcomes the limitations of current spectroscopic methods by combining the high-resolution imaging capabilities of AFM with machine learning (ML) classification. AFM-MS employs AFM operating in sub-resonance tapping imaging mode, which enables the collection of multiple physical and mechanical property maps of a sample with sub-nanometer lateral resolution in a highly repeatable manner. By comparing these properties to a database of known materials, the technique identifies the location of constituent materials at each image pixel with the assistance of ML algorithms. We demonstrate AFM-MS on various material mixtures, achieving an unprecedented lateral spectroscopic resolution of 1.6 nm. This powerful approach opens new avenues for nanoscale material study, including the material identification and correlation of nanostructure with macroscopic material properties. The ability to map material composition with such high resolution will significantly advance the understanding and design of complex, nanostructured materials. 

This paper describes an NSF (National Science Foundation) S-STEM-funded scholarship program, representing a collaborative five-year grant project among three prominent universities in the Southeast region of the United States. Its primary objective is to support dedicated scholars in graduating and finding a professional pathway. Each institution recruited a cohort of 15-20 scholars annually for three years. The project offers scholarships and provides curricular and co-curricular support to academically talented but financially challenged students in the computing disciplines, including Computer Science, Computer Engineering, Cybersecurity, and Information Technology majors, starting from their junior years. The program aims to impact 150 scholars, most of whom are underrepresented in computing. Scholars receive support throughout their graduation and beyond should they pursue graduate studies in a STEM (Science, Technology, Engineering, and Math) discipline at any of the three participating institutions. 

The demand for computing professionals has grown exponentially due to the rapid expansion of technology and digitalization in various industries. As a result, understanding the importance of pathways into computing education and professions has become crucial. These pathways serve as structured routes that guide individuals in acquiring the necessary skills and knowledge to pursue careers in the computing field. Hence, it is essential for educational institutions to understand students’ perspectives, particularly those from lower-income socio-economic status, to broaden participation within computing education and professional fields. Though there are various pathways into computing education and professions, for the purposes of this research and the program, we review the existing literature about three primary pathways: graduate school, internship or industry profession, and entrepreneurship. 

The demand for computing professionals has grown exponentially due to the rapid expansion of technology and digitalization in various industries. As a result, understanding the importance of pathways into computing education and professions has become crucial. These pathways serve as structured routes that guide individuals in acquiring the necessary skills and knowledge to pursue careers in the computing field. Hence, it is essential for educational institutions to understand students’ perspectives, particularly those from lower-income socio-economic status, to broaden participation within computing education and professional fields. Though there are various pathways into computing education and professions, for the purposes of this research and the program, we review the existing literature about three primary pathways: graduate school, internship or industry profession, and entrepreneurship. 

There has been a decline in the graduation rate of women in computing since 1984 [2]. Calls to broaden the participation of women have corresponded to funding initiatives, such as the National Science Foundation’s (NSF) Broadening Participation in Computing (BPC) program [3]. As the scholarly community takes up these calls and justifies their work, they tell stories about the problem, the solution, and most importantly, the people involved with broadening participation. Here we review some of those stories as represented by major trends in scholarly literature.