Graduate Research Fellowship Program Research Articles

Reimagining the broader impacts criterion in the NSF graduate research fellowship

For graduate students, securing prestigious fellowships provides incredible benefits such as increased job opportunities and likelihood of receiving awards. These benefits can be particularly life-changing for a graduate student who may come from a marginalized background. However, the inequity in fellowship distribution hinders the success of graduate students, especially those who are marginalized. The majority of the National Science Foundation’s Graduate Research Fellowship Program (GRFP) is white and attend top-ranked institutions. Within the GRFP, there is a clear disconnect between the grantee’s proposed broader impacts and follow-through. To value and support communities, and graduate students of color in the process, the GRFP must be reimagined. In this article, we provide a brief background on the relationship between STEM and marginalized communities, and how broader impacts currently function as a band-aid to the issues of justice, equity, diversity, and inclusion (JEDI) in STEM. We then conclude by providing recommendations to improve the broader impacts section and the awardee selection process.

Prioritizing diversity? The allocation of US federal R&D funding

AbstractWe examine the distribution of federal research and development funding across the academy early in the researcher’s pipeline. We use a unique program, the US National Science Foundation’s Graduate Research Fellowship Program (GRFP), to document diversity and disparity in allocation and assess the relative impact of federal funding across four different academic divisions that include engineering, life sciences, math and physical sciences, and social sciences and psychology. After controlling for disciplinary differences in research practices, we find that the impact of federal funding yields similar rates and impact of research. However, we document disparity in how federal funding is allocated across the country to institutions and individuals. Together, these findings prompt a discussion around the trade-offs of funders focusing on national priorities or broadening participation. We conclude with recommendations for the GRFP.

The Circlet Inequalities: A New, Circulant-Based, Facet-Defining Inequality for the TSP

Facet-defining inequalities of the symmetric traveling salesman problem (TSP) polytope play a prominent role in both polyhedral TSP research and state-of-the-art TSP solvers. In this paper, we introduce a new class of facet-defining inequalities, the circlet inequalities. These inequalities were first conjectured in Gutekunst and Williamson [Gutekunst SC, Williamson DP (2019) Characterizing the integrality gap of the subtour LP for the circulant traveling salesman problem. SIAM J. Discrete Math. 33(4):2452–2478] when studying the circulant TSP, and they provide a bridge between polyhedral TSP research and number-theoretic investigations of Hamiltonian cycles stemming from a conjecture from Marco Buratti in 2007. The circlet inequalities exhibit circulant symmetry by placing the same weight on all edges of a given length; our main proof exploits this symmetry to prove the validity of the circlet inequalities. We then show that the circlet inequalities are facet-defining and compute their strength following Goemans [Goemans MX (1995) Worst-case comparison of valid inequalities for the TSP. Math. Programming 69:335–349]; they achieve the same worst case strength as the similarly circulant crown inequalities of Naddef and Rinaldi [Naddef D, Rinaldi G (1992) The crown inequalities for the symmetric traveling salesman polytope. Math. Oper. Res. 17(2):308–326] but are generally stronger. Funding: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program [Grant DGE-1650441] and by the National Science Foundation Division of Computing and Communications Foundations [Grant CCF-1908517].

Predicting Cell Cycling Performance in Redox Flow Batteries Using Reduced-Order Analytical Models

Achieving decarbonization across multiple sectors (e.g., electricity generation, transportation, manufacturing) requires widespread adoption of renewable energy technologies, which demand energy storage solutions to enable sustainable, reliable, and resilient power delivery.1 To this end, redox flow batteries (RFBs) are a promising grid-scale energy storage platform, owing to their improved scalability, simplified manufacturing, and long service life.2 However, state-of-the-art RFBs remain too expensive for broad adoption, motivating the development of novel electrolyte formulations and reactor designs to meet performance, cost, and scale targets for emerging applications.3 While many recently-reported next-generation materials offer short-term performance improvements and the potential for cost reductions when produced at-scale, they often complicate system operation over extended durations due to a multitude of interrelated parasitic processes (e.g., side reactions, crossover, species decomposition) which lead to capacity fade and efficiency losses.3,4 Such processes challenge the establishment of quantitative and unambiguous connections between individual component properties and overall cell behavior. Here, we aim to develop mathematical models that translate fundamental material properties to cell performance metrics, enabling more informed design criteria for system engineering.In this presentation, we introduce an analytically-derived, zero-dimensional modeling framework to predict cell cycling behavior in RFBs. While previously-developed zero- and one-dimensional models demonstrate accurate performance predictions when compared to experimental systems, they must solve coupled differential equations using numerical methods.5,6 As a result, these approaches become computationally expensive for multi-cycle simulations (i.e., 10s – 100s of cycles), frustrating their implementation in system design and optimization. By deriving analytical solutions to these models, we can markedly reduce computation times and enable analyses hitherto unachievable.To demonstrate the utility of this modeling framework, we explore several representative scenarios that examine the connection between RFB material properties, operating conditions, and performance (i.e., power output, accessible capacity, efficiency). Additionally, we investigate the impact of different parasitic processes on capacity fade, highlighting the effects of species decomposition and crossover in durational cell cycling. Finally, we discuss several modalities for expanding this framework to include additional sources of performance losses and for integrating these models into larger computational schemes (e.g., optimization, parameter estimation, techno-economic assessments). The mathematical models developed in this work have potential to advance foundational understanding in RFB design, leading to quantitatively informed selection criteria for emerging candidate materials. Acknowledgments This work was supported by the Joint Center for Energy Storage Research, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences. B.J.N gratefully acknowledges the NSF Graduate Research Fellowship Program under Grant Number 1122374. J.L gratefully acknowledges support from the MIT Materials Research Laboratory REU Program, as part of the MRSEC Program of the NSF under grant number DMR-14-19807. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. References S. Chu and A. Majumdar, Nature, 488, 294–303 (2012).M. L. Perry and A. Z. Weber, J. Electrochem. Soc., 163, A5064–A5067 (2016).F. R. Brushett, M. J. Aziz, and K. E. Rodby, ACS Energy Lett., 5, 879–884 (2020).M. L. Perry, J. D. Saraidaridis, and R. M. Darling, Current Opinion in Electrochemistry, 21, 311–318 (2020).M. Pugach, M. Kondratenko, S. Briola, and A. Bischi, Applied Energy, 226, 560–569 (2018).S. Modak and D. G. Kwabi, J. Electrochem. Soc., 168, 080528 (2021).

(Invited) Modeling Electrochemical and Rheological Characteristics of Suspension-Based Electrolytes for Redox Flow Batteries

Electrochemical energy storage technologies are poised to play a key role in enabling society-wide decarbonization by facilitating the deployment of variable electricity generators and enhancing existing grid infrastructure. Redox flow batteries (RFBs) possess several technology features which are favorable for cost-effective, long-duration energy storage, including independent scaling of power and energy, long service life, and simplified manufacturing.1 In particular, their configuration enables a panoply of electrolyte compositions and cell materials to be considered, either at the beginning of life or during the installation lifetime (e.g., chemistry swaps). While conventional RFBs are based on redox couples dissolved in electrolyte solutions, more recently, suspension-based electrolytes containing solid energy storage materials have emerged as an alternative formulation. Flowable suspensions enable higher charge storage capacities (and thus cell energy densities) and unlock new operating modes (e.g., dissolution and precipitation on suspended particles).2,3 However, such electrolytes also frustrate traditional approaches to cell design and operation, as their complex electrochemical and rheological characteristics present multifaceted operational tradeoffs.4,5 By exploring essential features of these tradeoffs, we aim to better understand fluid dynamic and electrochemical engineering criteria for high-performance flow cells that operate with suspension-based electrolytes.In this presentation, we develop and apply a one-dimensional model to derive scaling relationships for suspension-based electrolytes in RFBs. Specifically, we investigate connections between rheological (i.e., non-Newtonian behavior, shear stress) and electrochemical (i.e., species and charge transport) phenomena for pressure-driven flow through a planar channel. identify key dimensionless groups which describe the relative magnitudes of relevant processes within the flowing suspension-based electrolyte. Through scaling analyses, we assess the importance of each parameter under different dynamic and geometric constraints to enable the identification of favorable materials sets and operating conditions. Ultimately, these dimensionless quantities offer a compact representation of the design considerations for suspension-based electrolytes, allowing more informed materials selection, cell engineering, and system formats. Finally, we hypothesize that these results can be generalized to describe flowable and stationary solid suspensions of utility in multiple electrochemical systems. Acknowledgments This work was funded by the Skoltech – MIT Next Generation Program. B.J.N, N.J.M, and K.R.L gratefully acknowledge the NSF Graduate Research Fellowship Program under Grant Number 1122374. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. References M. L. Perry and A. Z. Weber, J. Electrochem. Soc., 163, A5064–A5067 (2016).H. Parant et al., Carbon, 119, 10–20 (2017).X. Wang, J. Chai, and J. “Jimmy” Jiang, Nano Materials Science, 3, 17–24 (2021).V. E. Brunini, Y.-M. Chiang, and W. C. Carter, Electrochimica Acta, 69, 301–307 (2012).N. C. Hoyt, R. F. Savinell, and J. S. Wainright, Chemical Engineering Science, 144, 288–297 (2016).

TRM and mucosal tissue sites are protected from age-associated phenotypic changes in secondary lymphoid organs

Abstract The persistence and maintenance of immunological memory is critical for long-term immunity generated in response to infection and vaccination. Aging of memory T cells in humans has predominantly been studied in the peripheral blood, and considerably less is known about the aging of memory T cells within tissues. Using tissues obtained from human organ donors, we investigated how tissue localization, expression of the CD103 integrin, and age influence the phenotype of tissue resident memory T cells (TRM). Using multi-parameter flow cytometry, we characterized diverse tissue sites from donors ages 9 to 93 years old and demonstrate that age-associated changes in the T cell compartment exhibit tissue- and subset- specific dynamics. CD8 T cells in blood-rich tissues spleen and lung have elevated expression of replicative senescence markers CD57 and KLRG1 relative to lung-associated lymph nodes (LLN), jejunum, and mesenteric lymph nodes (MLN). CD103+ TRM have the lowest expression of CD57 and KLRG1 across all tissue sites relative to both CD103− TRM and circulating TEM. CD8 T cells in lymphoid tissues spleen, LLN, and MLN exhibit the largest age-associated increases in expression of CD57, KLRG1, CD244, and PD-1. Together, these results demonstrate that age-associated phenotypic changes are most prominent in secondary lymphoid organs, while TRM and mucosal sites exhibit few senescent changes. Supported by the National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) and grants from NIH (P01 AI106697, U19 AI057266)

The National Science Foundation Graduate Research Fellowship Program

The purpose of the National Science Foundation Graduate Research Fellowship Program (NSF-GRFP) is to help ensure the quality, vitality, and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students in NSF-supported STEM disciplines who are pursuing research-based master's and doctoral degrees in any of the eligible fields and subfields at accredited US institutions. The five-year fellowship includes three years of financial support including an annual stipend of $34,000 and a cost of education allowance of $12,000 to the institution. NSF has a strong commitment to diversity and actively encourages women, persons who are members of groups historically underrepresented in STEM, persons with disabilities, veterans, and undergraduate seniors to apply. This session will provide the audience a brief overview of the NSF-GRFP, such as its goal, eligibility requirements, application process, and timeline. Additionally, the session will include information on the NSF-GRFP's efforts to increase representation of women and members of groups historically underrepresented in STEM with a follow-up discussion on how the audience can encourage women and members of groups historically underrepresented in STEM to apply for the program or become reviewers. The last part of the session will be reserved for Q & A. We strongly encourage interaction among the audience and presenters.

The ZFP36 family of RNA-binding proteins regulate homeostatic and autoreactive T cell responses

Abstract The zinc finger 36 (ZFP36) family of RNA-binding proteins, consisting of ZFP36, ZFP36L1, and ZFP36L2, is known to negatively regulate mRNA stability and/or inhibit translation of many transcripts, including cytokines. While there are reports of all three family members regulating T cell cytokine production, delineating the functions of these genes is challenging due to spontaneous phenotypes upon global deletion of single genes and potential redundancy in their functions. To overcome this, we generated Cd4-Cre+ Zfp36fl/fl Zfp36l1fl/fl Zfp36l2fl/fl mice. Only upon triple deletion, but not individual or paired deletions, do mice spontaneously develop an inflammatory disease characterized by early lethality, hypercytokinemia, and immune cell infiltration into some peripheral organs, including the central nervous system. As SNPs in human ZFP36L1 and ZFP36L2 have been linked to susceptibility for multiple sclerosis, we tested ZFP36 family member individual and paired T cell-deficient mice in experimental autoimmune encephalomyelitis (EAE). To our surprise, Cd4-Cre+ Zfp36l1fl/fl Zfp36l2fl/fl mice were markedly protected from EAE clinical disease, while no change in disease severity was seen with any deletion strains involving Zfp36. There was a severe impairment in generating antigen-specific CD4+ T cells in Cd4-Cre+ Zfp36l1fl/fl Zfp36l2fl/fl mice during EAE priming. Our findings demonstrate a novel redundancy of the ZFP family members in regulating T cell homeostasis and a shared role for ZFP36L1 and ZFP36L2 to promote clonal expansion. Understanding the individual and shared functions of the ZFP36 family members may lead to opportunities to target them to suppress T cell-driven autoimmunity. M.E.C. supported by the National Science Foundation Graduate Research Fellowship program (DGE-1745038) and by grant 5T32AI007163 from the NIAID. B.T.E. supported by the NIAID (R01 AI113118).

The NSF Graduate Fellowship Program: An Analysis of Awards in the Ocean Sciences by Gender and Career Stage, 1996–2021

The information published annually by the National Science Foundation on its Graduate Research Fellowship Program (GRFP) awardees was used to create an Awardees in Ocean Sciences (AOS) data set. This data set shows that women have been successful in receiving the fellowship award in the ocean sciences, receiving an overall 69% of the awards from 1996 through 2021 (458 women among 659 awardees). Women comprised at least 50% of awardees in the six ocean sciences disciplines listed as GRFP subfields of study. The highest percentages of awards to women (72%) were in biological oceanography and marine geology/geophysics, followed by marine biology and chemical oceanography (69%), physical oceanography (67%), and ocean engineering (61%). Women were successful both as undergraduate applicants (69% of undergraduate awardees) and as graduate applicants (71% of graduate awardees). We estimate that GRFP women awardees made up 17.8% of the women obtaining doctoral degrees in oceanography from 2017 to 2021, compared with GRFP men awardees comprising 8.5% of the male doctoral recipients for the same period. Our analysis suggests future directions for study of GRFP awardees and highlights the need for data that would help inform community outreach to underserved student populations.

Effect of architecture and process on the ultrasonic mapping of hybrid additively manufactured materials

Hybrid additive manufacturing enables the creation of materials with functional microstructure and mechanical property patterns. While samples with functional patterns provide unique advantages in the overall performance of the material, they present a challenge for nondestructive evaluation. In particular, the nondestructive mapping of the properties imparted by hybrid AM processes is critical. In this work, hybrid 316 stainless steel samples are created using laser powder bed fusion (LPBF) with varying hybrid architectures and with a variety of hybrid processes. The ultrasonic responses of these samples, in terms of wave speed, attenuation, and backscatter amplitude, are evaluated for each architecture and process combination. These responses are compared with those from conventionally manufactured samples and traditional AM samples. This evaluation provides information on the sensitivity of ultrasonic responses to hybrid architecture and process, highlighting the potential of ultrasonic nondestructive methods for the characterization of hybrid AM components. [This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1610400. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.]

Redox-Active Polymers Designed for the Circular Economy of Energy Storage Devices

A.G. and A.S. acknowledge funding from the TomKat Center for Sustainable Energy at Stanford University and the StorageX initiative. A.S. and S.T.M.T. gratefully acknowledge support from the National Science Foundation Award CBET #1804915. T.J.Q. and G.L. acknowledge support from the NSF Graduate Research Fellowship Program under grant DGE-1656518. Part of this work was performed at the Stanford Nanofabrication Facilities (SNF) and Stanford Nano Shared Facilities (SNSF), supported by the National Science Foundation as part of the National Nanotechnology Coordinated Infrastructure under award ECCS-1542152. The authors acknowledge financial support from KAUST, including the Office of Sponsored Research (OSR) award nos. OSR-2018-CRG/CCF-3079, OSR-2019-CRG8-4086, and OSR-2018-CRG7-3749. The authors acknowledge funding from an ERC Synergy Grant SC2 (610115). Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-76SF00515.

Stay Home or Not? Modeling Individuals’ Decisions During the COVID-19 Pandemic

During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future. History: This article was accepted for the Decision Analysis Special Issue on Emerging Topics in Health. Funding: The first two authors’ efforts were supported by the National Natural Science Foundation of China [Grants 71971217 and 71671189], the Key Project of Natural Science Foundation of China [Grants 71790615 and 91846301], and the Independent Exploration of Innovation Project for Postgraduate of Central South University [Grant 2019zzts843]. The third author’s effort was partially supported by the U.S. National Science Foundation Graduate Research Fellowship Program [Grant 2043091].

Abstract 299: Self-assembling peptide hydrogel for delivery and conversion of temozolomide in glioblastoma treatment

Abstract Traditional treatment methods for glioblastoma multiforme (GBM) including resection, radiation, and chemotherapy have been largely unsuccessful, with a current 5-year survival rate of 5.6%. In this project we examine the potential of nanosized self-assembling peptide hydrogels to locally deliver and convert temozolomide (TMZ), an FDA-approved pH-sensitive prodrug, for GBM treatment. The peptide hydrogel is designed to load TMZ into the hydrophobic regions of the hydrogels, and during hydrogel degradation in vivo, convert TMZ into its active form. Hydrogel characterization, drug loading and conversion, and cellular uptake and viability are examined to determine the in vitro efficacy of this delivery method. A combination of dynamic light scattering (DLS), scanning electron microscopy (SEM), and circular dichroism (CD) are used to characterize size and structure of the hydrogels. Loading and conversion of TMZ are quantified using UV-Vis spectroscopy. Fluorescent imaging and cell viability assays are used to determine uptake and anti-cancer effects of the drug-loaded hydrogels on glioblastoma cells. Our results show high uptake in drug-resistant T98G and non-resistant LN-18 glioblastoma cell lines using several of our tunable peptide formulations. CD has shown that all peptide formulations form mostly beta-sheet and random structures during self-assembly. SEM and DLS show that peptide hydrogels formed in a water solvent are more polydisperse than hydrogels in a PBS solvent. Using a pH-meter, we have shown that as the peptides in PBS degrade, there is an increase in local pH. Additionally, TMZ conversion is observed to occur more quickly in drug-loaded hydrogels than TMZ alone. Preliminary cell viability studies have shown that unassembled peptides are not cytotoxic; some of the assembled peptide hydrogels are cytotoxic while others maintain greater than 80% viability when compared to untreated cells. Future studies for the project will include cell viability assays with the most promising peptide formulations loaded with TMZ to determine efficacy of the delivery and conversion system. Finally, this project will culminate in an in vivo study to confirm the overall anti-cancer effect of the drug-loaded peptide hydrogels in a tumor model of GBM. Acknowledgements: This research was supported in part by the National Science Foundation EPSCoR Program under NSF Award # OIA-1655740, the National Institute of Health Award # P30GM131959, and National Science Foundation's Graduate Research Fellowship Program. Citation Format: Megan Pitz, Alexandra Nukovic, Margaret Elpers, Sarah Wilde, Angela Alexander-Bryant. Self-assembling peptide hydrogel for delivery and conversion of temozolomide in glioblastoma treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 299.

(Energy Technology Division Graduate Student Award sponsored by Bio-Logic) Designer Porous Carbon Electrodes for Redox Flow Batteries

Redox flow batteries (RFBs) hold promise for efficiently storing and delivering electricity at the grid-scale, offering opportunities to complement and ultimately supplant fossil fuels with sustainable, but variable, energy sources.[1] However, widespread deployment of RFBs is hindered by their prohibitive cost, which depends, at least in part, on reactor performance. Thus, improving cell performance characteristics by targeting critical system components is an effective strategy towards realizing an energy infrastructure powered by renewable resources. In particular, porous carbon electrodes are vital components of RFBs, simultaneously fulfilling multiple crucial roles.[2] The electrode provides surface area for redox reactions to occur, distributes the electrolyte, determines the pressure drop, and cushions the cell during compression; thus, electrode properties are directly coupled with the RFB electrochemical and fluid dynamic performance. However, the commercial materials utilized in advanced flow batteries – typically papers, cloths, or felts – possess low surface area (~0.1 – 10 m2 g-1), poor aqueous wettability, and suboptimal surface chemistry, motivating efforts into electrode engineering. Current approaches for improving the electrode largely focus on post-process modification of pre-existing fiber-bed substrates which, although effective, may ultimately be incremental, as achievable properties are limited by the underlying material. While findings from prior art have furthered knowledge about the role of electrode interfacial chemistry and microstructure in cell performance, greater paradigm shifts may be necessary to unlock transformative advances and to enable chemistry-specific electrode design.In this talk, I will present three concurrent efforts towards rationally designing electrodes with property sets favorable for RFBs. First, I describe a method of refining the interfacial properties of commercial carbon electrodes through conformal deposition of conductive polymers with nanometric thicknesses, analyzing potential benefits of these coatings towards enhanced performance of iron-based redox couples.[3,4] Second, I discuss a strategy to produce sustainably sourced, elementally diverse, and high surface area electrocatalysts derived from biomass.[5] Findings from this work are coupled with modeling efforts to guide the effective utilization of high surface area electrocatalysts. Lastly, I outline a scalable, bottom-up synthetic method for producing tunable electrode microstructures that achieve pore network configurations inaccessible to classic fibrous electrodes. The fabricated scaffolds offer compelling opportunities as platforms for microstructure-function studies and potentially as performance materials.[6,7] While the focus of these efforts is RFBs, the methods, implications, and techniques for these concepts may ultimately be applicable to a diverse portfolio of convection-driven electrochemical systems that benefit from engineered transport layers. Acknowledgements This work was supported as part of the Joint Center for Energy Storage Research, an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences. CTW acknowledges additional funding from the National Science Foundation Graduate Research Fellowship Program under Grant No. 1122374. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

A Flow-through Microelectrode Sensor for Monitoring in Operando Concentrations in Redox Flow Batteries

The development of next-generation redox flow batteries (RFBs) heavily relies on the advancement of new component materials (e.g., redox electrolytes, membranes/separators) that enable low-cost, high-performance, and long-duration energy storage systems.1 The efficient evaluation of candidate materials thus requires simple and robust methods for investigating the evolution of system components during operation—in particular, near real-time monitoring of the battery state-of-health would enable timely interventions that extend lifetime or prevent safety incidents. Prior work has primarily comprised the measurement of electrolyte state-of-charge,2–4 and while this can qualitatively describe the state of the redox electrolyte, knowledge of the individual active species concentrations is needed to quantitatively assess the causes of performance loss. Accordingly, we have established the use of microelectrodes for studying the ex situ decomposition of RFB active materials, showing that this technique can simultaneously describe contributions from self-discharge reactions and molecular decomposition.5 However, considering the flow disturbances (e.g., pump oscillations, irregular flow, non-uniform mixing, etc.) associated with operating RFBs, it is especially challenging to integrate microelectrodes directly into flow cells, as the steady-state current can be highly variable due to undesired advection. Here, we seek to expand the versatility of microelectrodes by leveraging and directing this flow to study redox electrolytes within an operating cell.In this presentation, we describe the integration of microelectrodes into an in-line, flow-through electrochemical cell for use as an operando diagnostic tool to measure redox species concentrations in RFBs (see Figure). The cell consists of a three-electrode assembly, with a pseudo-reference electrode, to accurately quantify species concentrations via the steady-state current obtained from the microelectrode. First, we validate the proposed working principle using multi-physics simulations, and assess the measurement protocol ex situ under quiescent and flow conditions. Using a model electroactive compound (N-(2-(2-methoxyethoxy)ethyl)phenothiazine, MEEPT) prepared at varying states of charge, voltammetry reveals that the steady-state current can be reliably measured with a platinum wire pseudo-reference electrode, which can be used in place of standard fritted reference electrodes to reduce contamination and drift. Subsequent e x situ current measurements under steady flow yield a stable current response that increases with flow rate, in general agreement with simulation results. Importantly, as long as the flow conditions remain consistent throughout testing, the current remains linear with concentration, allowing the concentration to be determined from the steady-state current using an empirical mass transfer coefficient. As a proof-of-concept, we demonstrate the use of this sensor in a symmetric, non-aqueous redox flow cell using MEEPT. Finally, and perhaps most notably, this diagnostic tool is comprised of commercial off-the-shelf components, making it a readily accessible to any laboratory studying RFBs. Acknowledgments This work was funded by the National Science Foundation (NSF) under Award Number 1805566. B.J.N. and K.M.T. gratefully acknowledge the NSF Graduate Research Fellowship Program under Grant Number 1122374. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. References B. R. Chalamala, T. Soundappan, G. R. Fisher, M. R. Anstey, V. V. Viswanathan, and M. L. Perry, Proceedings of the IEEE, 102, 976–999 (2014).C. Stolze, J. P. Meurer, M. D. Hager, and U. S. Schubert, Chem. Mater., 31, 5363–5369 (2019).M. Skyllas-Kazacos and M. Kazacos, Journal of Power Sources, 196, 8822–8827 (2011).C. Stolze, M. D. Hager, and U. S. Schubert, Journal of Power Sources, 423, 60–67 (2019).J. A. Kowalski, A. M. Fenton, B. J. Neyhouse, and F. R. Brushett, J. Electrochem. Soc., 167, 160513 (2020). Figure 1

Analytical and Numerical Modeling of Microelectrode Voltammetry in Oblate Spheroidal Coordinates

Voltammetry is a ubiquitous electroanalytical technique used to examine electroactive compounds for a range of purposes, such as component characterization of an electrochemical device or mechanistic analyses of electrode reactions.1–3 Although most commonly performed on a macroelectrode (radius ~mm), voltammetry conducted on a microelectrode (radius ~μm) enables interrogation of electrolyte compositions inaccessible to macroelectrodes, as the smaller radius minimizes ohmic distortions, reduces charging currents, and enables near-steady-state measurements at slower scan rates (e.g., 10 mV/s).4 These characteristics also mean that microelectrodes hold promise for the examination of concentrated multi-component electrolytes, potentially enabling in situ or operando analysis in practical embodiments.2,4 Methodologies aimed to evaluate electrolyte behavior in electrochemical cells leverage well-established expressions,1–4 and while physically grounded, they do not account for conditions where migration or non-idealities impact the voltammetric response.3 In these instances, more extensive modeling, often framed in cylindrical coordinates,1,5 is needed to estimate the features of interest (e.g., bulk concentrations) with sufficient accuracy. These methods involve partial differential equations with piecewise boundary conditions, most often resulting in expressions of limited adoptability due to either numerical complexity or lack of physicality.5 The mathematical treatment may be strengthened by obviating the piecewise boundary conditions through the use of oblate spheroidal coordinates. Indeed, with this coordinate transform, closed form steady-state and numerical transient voltammograms are obtainable with greater ease.6,7 Although this change has simplified modeling, to the best of our knowledge, existing treatments using both cylindrical and oblate spheroidal coordinates are only applicable to a restricted set of conditions (e.g., equal diffusion coefficients, no bulk product present) rarely encountered in real devices,5–7 limiting their ability to study practical electrolytes.To extend the applicability of this approach, we use oblate spheroidal coordinates to derive steady-state and transient microelectrode voltammogram models capable of accounting for different electron transfer kinetics, dissimilar diffusion coefficients, and the presence of both reactant and product in the bulk solution (illustrated in the abstract figure). In this presentation, we will discuss the derivation of the closed form steady-state solutions and their evaluation using cases previously described in literature.5,6 We will then describe the development of the finite difference transient models capable of simulating voltammograms over a broader range of conditions (e.g., varying scan rates), which, in turn, are validated using COMSOL®. Finally, we will discuss the application of this procedure to evaluate electrolyte behavior in electrochemical cells, such as examining whether more complex physical phenomena (e.g., migration-induced transport) can be integrated into this framework and whether closed form steady-state solutions can accurately estimate relevant parameters from transient voltammograms.Acknowledgments: This work was funded by the National Science Foundation under Award Number 1805566. B.J.N. and K.M.T. both gratefully acknowledge the National Science Foundation Graduate Research Fellowship Program under grant no. 1122374. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Distributed and localized cooling with thermoelectrics

G. Jeffrey Snyder is a Professor of Materials Science and Engineering at Northwestern University in Evanston Illinois. His interests are focused on engineering of electronic and thermal properties, and he is well known for his work on thermoelectric materials. He has developed new methods of electron band structure engineering and microstructure engineering of thermal and electrical properties of complex materials. His interdisciplinary approach stems from his background in solid state chemistry at Cornell University and the Max Planck Institute for solid state research, applied physics at Stanford University, and thermoelectric materials and device engineering at NASA/Jet Propulsion Laboratory and California Institute of Technology (Caltech).

Training across the academy: The impact of R&D funding on graduate students

This paper measures the impact of external R&D funding on the career trajectory and research productivity of graduate students across the divisions of life sciences, math & physical sciences, engineering, and social sciences & psychology. We contribute to the understanding of the production of science by examining the training regimen for graduate students. We exploit variation between 3,678 awardees and honorable mentions of the U.S. National Science Foundation's Graduate Research Fellowship Program. We find consistent evidence that the award increases degree completion, placement in a post-doctoral or academic research position, research productivity and impact, and network size. We further explore the role of the graduate advisor in this training process and find the award does not disrupt the apprenticeship model, but instead, increases the student's interaction with their advisor.

Spike Protein Cleavage-Activation Mediated by the SARS-CoV-2 P681R Mutation: A Case-Study From Its First Appearance in Variant of Interest (VOI) A.23.1 Identified in Uganda

The African continent like all other parts of the world with high infection/low vaccination rates can, and will, be a source of novel SARS-CoV-2 variants. The A.23 viral lineage, characterized by three spike mutations F157L, V367F and Q613H, was first identified in COVID-19 cases from a Ugandan prison in July 2020, and then was identified in the general population with the additional spike mutation P681R at the S1/S2 cleavage site to comprise lineage A.23.1 by September 2020 with subsequent spread to 26 other countries. The P681R spike substitution of A.23.1 is of note as it increases the number of basic residues in the sub-optimal SARS-CoV-2 spike protein furin cleavage site; as such, this substitution may affect viral replication, transmissibility, or pathogenic properties. The same P681R substitution has also subsequently appeared in B.1.617 variants, including B.1.617.2 (Delta). Here, we performed assays using fluorogenic peptides mimicking the S1/S2 from A.23.1 and B.1.617 and observed significantly increased cleavability with furin, compared to sequences derived from the original Wuhan-Hu1 S1/S2. We performed cell-cell fusion and functional infectivity assays using pseudotyped particles harboring SARS-CoV-2 spike proteins and observed an increase in transduction for A.23.1-pseudotyped particles compared to Wuhan-Hu-1. However, these changes in activity were not reproduced in the original Wuhan-Hu-1 spike bearing only the P681R substitution. Our findings suggest that while A.23.1 has increased furin-mediated cleavage linked to the P681R substitution—which may affect viral infection and transmissibility—this substitution alone needs to occur on the background of other spike protein changes to enable its full functional consequences.Funding: This work was funded in part by the National Institute of Health research grant R01AI35270 (to GW and SD). We thank the global SARS-CoV-2 sequencing groups for their open and rapid sharing of sequence data and GISAID for providing an effective platform to make these data available. DLB, MVTP and MC were funded by the UK Medical Research Council (MRC/UK Research and Innovation) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement (grant agreement no. NC_PC_19060) and Wellcome Trust, UK FCDO—Wellcome Epidemic Preparedness—Coronavirus (grant agreement no. 220977/Z/20/Z). TT was supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1650441 and the Samuel C. Fleming Family Graduate Fellowship. Declaration of Interests: The authors manifest no conflict of interest.

Rapid and Parallel Adaptive Mutations in Spike S1 Drive Clade Success in SARS-CoV-2

Despite the appearance of variant SARS-CoV-2 viruses with altered receptorbinding or antigenic phenotypes, traditional methods for detecting adaptive evolution from sequence data do not pick up strong signals of positive selection. Here, we present a new method for identifying adaptive evolution on short evolutionary time scales with densely-sampled populations. We apply this method to SARS-CoV-2 to perform a comprehensive analysis of adaptively-evolving regions of the genome. We find that spike S1 is a focal point of adaptive evolution, but also identify positivelyselected mutations in other genes that are sculpting the evolutionary trajectory of SARS-CoV-2. Protein-coding mutations in S1 are temporally-clustered and, in 2021, the ratio of nonsynonymous to synonymous divergence in S1 is more than 4 times greater than in the equivalent influenza HA1 subunit. Funding: This work was supported by NIH R35 GM119774. KEK was supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1762114. Declaration of Interests: None to declare.