Removing Barriers

Stallings, Dontarie; Iyer, Srikant Kamesh; Hernandez, Rigoberto

doi:10.1021/bk-2020-1354.ch006

Cited by 2 publications

(2 citation statements)

References 48 publications

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“…To achieve this commonality, graduate students, postdocs, and faculty must collaborate closely, bridging highly interdisciplinary spaces and communicating across boundaries between traditional disciplines, in order to define and evolve a new language or common vernacular for interdisciplinary materials and computational science. Diversity should be encouraged in student, staff, and faculty backgrounds, training, genders, and ethnicities, to ensure creative and productive teams. , Second, transferability across material systems is required, so that discoveries and inventions made in one domain, such as photonics and DNA-based materials, networked ENPs, or phononics and silicon-based materials, may interchange readily. As data-driven materials discovery frameworks are explored, invented, and deployed, iteration between distinct materials domains is needed to achieve transferability.…”

Section: Harnessing the Data Revolutionmentioning

confidence: 99%

Autonomous Computing Materials

et al. 2021

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Conventional materials are reaching their limits in computation, sensing, and data storage capabilities, ushered in by the end of Moore’s law, myriad sensing applications, and the continuing exponential rise in worldwide data storage demand. Conventional materials are also limited by the controlled environments in which they must operate, their high energy consumption, and their limited capacity to perform simultaneous, integrated sensing, computation, and data storage and retrieval. In contrast, the human brain is capable of multimodal sensing, complex computation, and both short- and long-term data storage simultaneously, with near instantaneous rate of recall, seamless integration, and minimal energy consumption. Motivated by the brain and the need for revolutionary new computing materials, we recently proposed the data-driven materials discovery framework, autonomous computing materials. This framework aims to mimic the brain’s capabilities for integrated sensing, computation, and data storage by programming excitonic, phononic, photonic, and dynamic structural nanoscale materials, without attempting to mimic the unknown implementational details of the brain. If realized, such materials would offer transformative opportunities for distributed, multimodal sensing, computation, and data storage in an integrated manner in biological and other nonconventional environments, including interfacing with biological sensors and computers such as the brain itself.

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Section: Harnessing the Data Revolutionmentioning

confidence: 99%

Autonomous Computing Materials

et al. 2021

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“… Removing BarriersStallingsD.IyerS. K.HernandezR. Stallings, D. Iyer, S. K. Hernandez, R. Azad, S. 10.1021/bk-2020-1354.ch006Addressing Gender Bias in Science & TechnologyAmerican Chemical SocietyWashington, D.C.2020135491108 A consensus analysis of diversity solutions based on the expert evaluation by department chairs and diversity subject matter experts. A Cuban Campesino in Chemistry’s Academic CourtHernandezR. Hernandez, R. 10.1021/acs.jpcb.1c06073J.…”

Section: Key Referencesmentioning

confidence: 99%

Discipline-Based Diversity Research in Chemistry

Hernandez

2023

Acc. Chem. Res.

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Metrics & MoreArticle Recommendations CONSPECTUS:We introduce the term discipline-based diversity research (DBDR) to capture the emerging field of research advancing diversity, equity, inclusion, and belonging with specificity to a given discipline. Contextualizing a human dynamic through a disciplinary lens has already given rise to discipline-based education research (DBER). The modalities through which students and practitioners think and process information are a reflection of a given discipline, and it tends to give rise to its professional practices. Through DBER, such specification is necessary in addressing evidence-based practices that are effective for teaching a particular subject. Likewise, the inequities and opportunities within a given field (and its professional culture) must be addressed within a disciplinary lens. Thus, the findings from social science in diversity in arbitrary contexts must be analyzed, interpreted, applied, and researched within a given discipline.One specific challenge to academic chemistry is the lack of inclusion in the sense that the faculties in research-active chemistry departments are far from diverse. We recapitulate the percentage of women and under-represented person of color (URPOC) professors over the past 20 years reported by us and other sources. The data admits to linear fits with high confidence. Assuming this linearity holds, the gender gap in representation would be bridged only in 2062, and the threshold of 20% of the faculty as URPOC would be reached only in 2113. While the community has actively engaged in modifying practices and procedures to redress this grim projection, it should be clear that more needs to be done. Toward this objective, we have been driven by the top-down hypothesis that solutions must be led intentionally through the top� that is, by department heads and chairs�because they are the stewards of the infrastructure. Department chairs and the chemistry community have engaged in DBDR through biennial workshops�that is, through the Open Chemistry Collaborative in Diversity Equity (OXIDE)'s National Diversity Equity Workshops (NDEWs)�to survey and evaluate existing policies and practices aimed at advancing inclusive excellence. This has led to research-based recommendations for the implementation of solutions in chemistry departments. This includes (i) engaging in community, (ii) conducting authentic and open searches, and (iii) recognizing and rewarding inclusive excellence. What makes them DBDR in chemistry is that we have to articulate and contextualize these solutions in terms of practices and procedures that we conduct in chemistry, assess their efficacy, and promote them across our discipline. Furthermore, we must offer theories of change for reforming them while offering frameworks that fit within how chemists think and practice.In this Account, we demonstrate how DBDR has taken root in chemistry, forecast where this emerging field may go, and provide a blueprint for how it might be replicated in other disciplines.

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Removing Barriers

Cited by 2 publications

References 48 publications

Autonomous Computing Materials

Autonomous Computing Materials

Discipline-Based Diversity Research in Chemistry

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