Risk of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Following Prior Infection or Vaccination.

BACKGROUND: The extent to which infection versus vaccination has conferred similarly durable severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunity during the Omicron era remains unclear. METHODS: In a cohort of 4496 adults under continued serological surveillance throughout the first year of Omicron-predominant SARS-CoV-2 transmission, we examined incidence of new infection among individuals whose last known antigenic exposure was either recent (<90 days) or remote (≥90 days) infection or vaccination. RESULTS: We adjudicated 2053 new-onset infections occurring between 15 December 2021 through 22 December 2022. In multivariable-adjusted analyses, compared to individuals whose last known exposure was remote vaccination, those with recent vaccination (odds ratio [OR], 0.82 [95% confidence interval {CI}, .73-.93]; P = .002) or recent infection (OR, 0.14 [95% CI, .05-.45]; P = .001) had lower risk for new infection within the subsequent 90-day period. Given a significant age interaction (P = .004), we found that remote infection compared to remote vaccination was associated with significantly greater new infection risk in persons aged ≥60 years (OR, 1.88 [95% CI, 1.13-3.14]; P = .015) with no difference seen in those <60 years (1.03 [95% CI, .69-1.53]; P = .88). CONCLUSIONS: During the initial year of Omicron, prior infection and vaccination both offered protection against new infection. However, remote prior infection was less protective than remote vaccination for individuals aged ≥60 years. In older adults, immunity gained from vaccination appeared more durable than immunity gained from infection.

Managing Implanted Cardiac Electronic Devices in Patients With Severe Tricuspid Regurgitation: JACC State-of-the-Art Review.

Orthotopic transcatheter tricuspid valve replacement (TTVR) devices have been shown to be highly effective in reducing tricuspid regurgitation (TR), and interest in this therapy is growing with the recent commercial approval of the first orthotopic TTVR. Recent TTVR studies report preexisting cardiac implantable electronic device (CIED) transvalvular leads in ∼35% of patients, with entrapment during valve implantation. Concerns have been raised regarding the safety of entrapping leads and counterbalanced against the risks of transvenous lead extraction (TLE) when indicated. This Heart Valve Collaboratory consensus document attempts to define the patient population with CIED lead-associated or lead-induced TR, describe the risks of lead entrapment during TTVR, delineate the risks and benefits of TLE in this setting, and develop a management algorithm for patients considered for TTVR. An electrophysiologist experienced in CIED management should be part of the multidisciplinary heart team and involved in shared decision making.

Arginine-Functional Methacrylic Block Copolymer Nanoparticles: Synthesis, Characterization, and Adsorption onto a Model Planar Substrate.

Recently, we reported the synthesis of a hydrophilic aldehyde-functional methacrylic polymer (Angew. Chem., 2021, 60, 12032-12037). Herein we demonstrate that such polymers can be reacted with arginine in aqueous solution to produce arginine-functional methacrylic polymers without recourse to protecting group chemistry. Careful control of the solution pH is essential to ensure regioselective imine bond formation; subsequent reductive amination leads to a hydrolytically stable amide linkage. This new protocol was used to prepare a series of arginine-functionalized diblock copolymer nanoparticles of varying size via polymerization-induced self-assembly in aqueous media. Adsorption of these cationic nanoparticles onto silica was monitored using a quartz crystal microbalance. Strong electrostatic adsorption occurred at pH 7 (Γ = 14.7 mg m-2), whereas much weaker adsorption occurred at pH 3 (Γ = 1.9 mg m-2). These findings were corroborated by electron microscopy, which indicated a surface coverage of 42% at pH 7 but only 5% at pH 3.

Environmental Surveillance of Flood Control Infrastructure Impacted by Unsheltered Individuals Leads to the Detection of SARS-CoV-2 and Novel Mutations in the Spike Gene.

In the United States, the growing number of people experiencing homelessness has become a socioeconomic crisis with public health ramifications, recently exacerbated by the COVID-19 pandemic. We hypothesized that the environmental surveillance of flood control infrastructure may be an effective approach to understand the prevalence of infectious disease. From December 2021 through July 2022, we tested for SARS-CoV-2 RNA from two flood control channels known to be impacted by unsheltered individuals residing in upstream tunnels. Using qPCR, we detected SARS-CoV-2 RNA in these environmental water samples when significant COVID-19 outbreaks were occurring in the surrounding community. We also performed whole genome sequencing to identify SARS-CoV-2 lineages. Variant compositions were consistent with those of geographically and temporally matched municipal wastewater samples and clinical specimens. However, we also detected 10 of 22 mutations specific to the Alpha variant in the environmental water samples collected during January 2022-one year after the Alpha infection peak. We also identified mutations in the spike gene that have never been identified in published reports. Our findings demonstrate that environmental surveillance of flood control infrastructure may be an effective tool to understand public health conditions among unsheltered individuals-a vulnerable population that is underrepresented in clinical surveillance data.

Exploring the PET in vivo generator 134Ce as a theranostic match for 225Ac.

Purpose: The radionuclide pair cerium-134/lanthanum-134 (134Ce/134La) was recently proposed as a suitable diagnostic counterpart for the therapeutic alpha-emitter actinium-225 (225Ac). The unique properties of 134Ce offer perspectives for developing innovative in vivo investigations not possible with 225Ac. In this work, 225Ac- and 134Ce-labeled tracers were directly compared using internalizing and slow-internalizing cancer models to evaluate their in vivo comparability, progeny meandering, and potential as a matched theranostic pair for clinical translation. Despite being an excellent chemical match, 134Ce/134La has limitations to the setting of quantitative positron emission tomography imaging. Methods: The precursor PSMA-617 and a macropa-based tetrazine-conjugate (mcp-PEG8-Tz) were radiolabelled with 225Ac or 134Ce and compared in vitro and in vivo using standard (radio)chemical methods. Employing biodistribution studies and positron emission tomography (PET) imaging in athymic nude mice, the radiolabelled PSMA-617 tracers were evaluated in a PC3/PIP (PC3 engineered to express a high level of prostate-specific membrane antigen) prostate cancer mouse model. The 225Ac and 134Ce-labeled mcp-PEG8-Tz were investigated in a BxPC-3 pancreatic tumour model harnessing the pretargeting strategy based on a trans-cyclooctene-modified 5B1 monoclonal antibody. Results: In vitro and in vivo studies with both 225Ac and 134Ce-labelled tracers led to comparable results, confirming the matching pharmacokinetics of this theranostic pair. However, PET imaging of the 134Ce-labelled precursors indicated that quantification is highly dependent on tracer internalization due to the redistribution of 134Ce's PET-compatible daughter 134La. Consequently, radiotracers based on internalizing vectors like PSMA-617 are suited for this theranostic pair, while slow-internalizing 225Ac-labelled tracers are not quantitatively represented by 134Ce PET imaging. Conclusion: When employing slow-internalizing vectors, 134Ce might not be an ideal match for 225Ac due to the underestimation of tumour uptake caused by the in vivo redistribution of 134La. However, this same characteristic makes it possible to estimate the redistribution of 225Ac's progeny noninvasively. In future studies, this unique PET in vivo generator will further be harnessed to study tracer internalization, trafficking of receptors, and the progression of the tumour microenvironment.

Deep learning unlocks label-free viability assessment of cancer spheroids in microfluidics.

Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for oncologists. Precise evaluation of drug effectiveness necessitates the use of 3D cell culture instead of traditional 2D monolayers. Microfluidic platforms have enabled high-throughput drug screening with 3D models, but current viability assays for 3D cancer spheroids have limitations in reliability and cytotoxicity. This study introduces a deep learning model for non-destructive, label-free viability estimation based on phase-contrast images, providing a cost-effective, high-throughput solution for continuous spheroid monitoring in microfluidics. Microfluidic technology facilitated the creation of a high-throughput cancer spheroid platform with approximately 12 000 spheroids per chip for drug screening. Validation involved tests with eight conventional chemotherapeutic drugs, revealing a strong correlation between viability assessed via LIVE/DEAD staining and phase-contrast morphology. Extending the model's application to novel compounds and cell lines not in the training dataset yielded promising results, implying the potential for a universal viability estimation model. Experiments with an alternative microscopy setup supported the model's transferability across different laboratories. Using this method, we also tracked the dynamic changes in spheroid viability during the course of drug administration. In summary, this research integrates a robust platform with high-throughput microfluidic cancer spheroid assays and deep learning-based viability estimation, with broad applicability to various cell lines, compounds, and research settings.

Early Detection of Novel SARS-CoV-2 Variants from Urban and Rural Wastewater through Genome Sequencing and Machine Learning.

Genome sequencing from wastewater has emerged as an accurate and cost-effective tool for identifying SARS-CoV-2 variants. However, existing methods for analyzing wastewater sequencing data are not designed to detect novel variants that have not been characterized in humans. Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns leading to the identification of SARS-CoV-2 variants. To build our model, we sequenced 3,659 wastewater samples collected over a span of more than two years from urban and rural locations in Southern Nevada. We then developed a multivariate independent component analysis (ICA)-based pipeline to transform mutation frequencies into independent sources with co-varying and time-evolving patterns and compared variant predictions to >5,000 SARS-CoV-2 clinical genomes isolated from Nevadans. Using the source patterns as data-driven reference "barcodes", we demonstrated the model's accuracy by successfully detecting the Delta variant in late 2021, Omicron variants in 2022, and emerging recombinant XBB variants in 2023. Our approach revealed the spatial and temporal dynamics of variants in both urban and rural regions; achieved earlier detection of most variants compared to other computational tools; and uncovered unique co-varying mutation patterns not associated with any known variant. The multivariate nature of our pipeline boosts statistical power and can support accurate and early detection of SARS-CoV-2 variants. This feature offers a unique opportunity for novel variant and pathogen detection, even in the absence of clinical testing.

Exploring the link between comorbidities and Alzheimer's dementia in the Australian Imaging, Biomarker & Lifestyle (AIBL) study.

INTRODUCTION: Mounting evidence suggests that certain comorbidities may influence the clinical evolution of Alzheimer's dementia (AD). METHODS: We conducted logistic regression analyses on the medical history and cognitive health diagnoses of participants in the Australian Imaging, Biomarker & Lifestyle study (n = 2443) to investigate cross-sectional associations between various comorbidities and mild cognitive impairment (MCI)/AD. RESULTS: A mixture of associations were observed. Higher comorbidity of anxiety and other neurological disorders was associated with higher odds of AD, while arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD. DISCUSSION: This study underscores the links between specific comorbidities and MCI/AD. Further research is needed to elucidate the longitudinal comorbidity-MCI/AD associations and underlying mechanisms of these associations. Highlights: Comorbidities that significantly increased AD odds included anxiety and other neurological disorders.Arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.Alcohol consumption had the most significant confounding effect in the study.Visual-AD association was modified by age, sex, and APOE ε4 allele status.Anxiety-AD and depression-AD associations were modified by sex.

Controlled release of vancomycin from PEGylated fibrinogen polyethylene glycol diacrylate hydrogel.

Surgical site infection (SSI) is a common issue post-surgery which often prolongs hospitalization and can lead to serious complications such as sternal wound infection following cardiac surgery via median sternotomy. Controlled release of suitable antibiotics could allow maximizing drug efficacy and safety, and therefore achieving a desired therapeutic response. In this study, we have developed a vancomycin laden PEGylated fibrinogen-polyethylene glycol diacrylate (PF-PEGDA) hydrogel system that can release vancomycin at a controlled and predictable rate to be applied in SSI prevention. Two configurations were developed to study effect of the hydrogel on drug release, namely, vancomycin laden hydrogel and vancomycin solution on top of blank hydrogel. The relationship between the rigidity of the hydrogel and drug diffusion was found to comply with a universal power law, i.e., softer hydrogels result in a greater diffusion coefficient hence faster release rate. Besides, vancomycin laden hydrogels exhibited burst release, whereas the vancomycin solution on top of blank hydrogels exhibited lag release. A mathematical model was developed to simulate vancomycin permeation through the hydrogels. The permeation of vancomycin can be predicted accurately by using the mathematical model, which provided a useful tool to customize drug loading, hydrogel thickness and stiffness for personalized medication to manage SSI. To evaluate the potential of hydrogels for bone healing applications in cardiovascular medicine, we performed a proof-of-concept median sternotomy in rabbits and applied the hydrogels. The hydrogel formulations accelerated the onset of osteo-genetic processes in rabbits, demonstrating its potential to be used in human.

The Tricuspid Valve: A Review of Pathology, Imaging, and Current Treatment Options: A Scientific Statement From the American Heart Association.

Tricuspid valve disease is an often underrecognized clinical problem that is associated with significant morbidity and mortality. Unfortunately, patients will often present late in their disease course with severe right-sided heart failure, pulmonary hypertension, and life-limiting symptoms that have few durable treatment options. Traditionally, the only treatment for tricuspid valve disease has been medical therapy or surgery; however, there have been increasing interest and success with the use of transcatheter tricuspid valve therapies over the past several years to treat patients with previously limited therapeutic options. The tricuspid valve is complex anatomically, lying adjacent to important anatomic structures such as the right coronary artery and the atrioventricular node, and is the passageway for permanent pacemaker leads into the right ventricle. In addition, the mechanism of tricuspid pathology varies widely between patients, which can be due to primary, secondary, or a combination of causes, meaning that it is not possible for 1 type of device to be suitable for treatment of all cases of tricuspid valve disease. To best visualize the pathology, several modalities of advanced cardiac imaging are often required, including transthoracic echocardiography, transesophageal echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging, to best visualize the pathology. This detailed imaging provides important information for choosing the ideal transcatheter treatment options for patients with tricuspid valve disease, taking into account the need for the lifetime management of the patient. This review highlights the important background, anatomic considerations, therapeutic options, and future directions with regard to treatment of tricuspid valve disease.

RETROSPECTIVE VARYING COEFFICIENT ASSOCIATION ANALYSIS OF LONGITUDINAL BINARY TRAITS: APPLICATION TO THE IDENTIFICATION OF GENETIC LOCI ASSOCIATED WITH HYPERTENSION.

Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fail to capture the dynamic pattern of disease progression. However, the relative influence of genetic variants on complex traits fluctuates over time. In this study, we propose a retrospective varying coefficient mixed model association test, RVMMAT, to detect time-varying genetic effect on longitudinal binary traits. We model dynamic genetic effect using smoothing splines, estimate model parameters by maximizing a double penalized quasi-likelihood function, design a joint test using a Cauchy combination method, and evaluate statistical significance via a retrospective approach to achieve robustness to model misspecification. Through simulations we illustrated that the retrospective varying-coefficient test was robust to model misspecification under different ascertainment schemes and gained power over the association methods assuming constant genetic effect. We applied RVMMAT to a genome-wide association analysis of longitudinal measure of hypertension in the Multi-Ethnic Study of Atherosclerosis. Pathway analysis identified two important pathways related to G-protein signaling and DNA damage. Our results demonstrated that RVMMAT could detect biologically relevant loci and pathways in a genome scan and provided insight into the genetic architecture of hypertension.

Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models.

The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health in silico. A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (ρ = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and ß-cell functionality. Moreover, we show that personalized Mixed Meal Models can be used to evaluate the impact of a dietary intervention on multiple aspects of metabolic health at the individual level.

Characterisation of colistin resistance in Gram-negative microbiota of pregnant women and neonates in Nigeria.

A mobile colistin resistance gene mcr was first reported in 2016 in China and has since been found with increasing prevalence across South-East Asia. Here we survey the presence of mcr genes in 4907 rectal swabs from mothers and neonates from three hospital sites across Nigeria; a country with limited availability or history of colistin use clinically. Forty mother and seven neonatal swabs carried mcr genes in a range of bacterial species: 46 Enterobacter spp. and single isolates of; Shigella, E. coli and Klebsiella quasipneumoniae. Ninety percent of the genes were mcr-10 (n = 45) we also found mcr-1 (n = 3) and mcr-9 (n = 1). While the prevalence during this collection (2015-2016) was low, the widespread diversity of mcr-gene type and range of bacterial species in this sentinel population sampling is concerning. It suggests that agricultural colistin use was likely encouraging sustainment of mcr-positive isolates in the community and implementation of medical colistin use will rapidly select and expand resistant isolates.

Science Education for the Youth (SEFTY): A Neuroscience Outreach Program for High School Students in Southern Nevada during the COVID-19 Pandemic.

Laboratory outreach programs for K-12 students in the United States from 2020 to 2022 were suspended or delayed due to COVID-19 restrictions. While Southern Nevada also observed similar closures for onsite programs, we and others hypothesized that in-person laboratory activities could be prioritized after increasing vaccine doses were available to the public and masking was encouraged. Here, we describe how the Laboratory of Neurogenetics and Precision Medicine at the University of Nevada Las Vegas (UNLV) collaborated with administrators from a local school district to conduct training activities for high school students during the COVID-19 pandemic. The Science Education for the Youth (SEFTY) program's curriculum was constructed to incorporate experiential learning, fostering collaboration and peer-to-peer knowledge exchange. Leveraging neuroscience tools from our UNLV laboratory, we engaged with 117 high school applicants from 2021 to 2022. Our recruitment efforts yielded a diverse cohort, with >41% Pacific Islander and Asian students, >9% African American students, and >12% multiracial students. We assessed the impact of the SEFTY program through pre- and postassessment student evaluations, revealing a significant improvement of 20.3% in science proficiency (p < 0.001) after participating in the program. Collectively, our laboratory curriculum offers valuable insights into the capacity of an outreach program to actively foster diversity and cultivate opportunities for academic excellence, even in the challenging context of a global pandemic.

Exploring the association between cancer and cognitive impairment in the Australian Imaging Biomarkers and Lifestyle (AIBL) study.

An inverse association between cancer and Alzheimer's disease (AD) has been demonstrated; however, the association between cancer and mild cognitive impairment (MCI), and the association between cancer and cognitive decline are yet to be clarified. The AIBL dataset was used to address these knowledge gaps. The crude and adjusted odds ratios for MCI/AD and cognitive decline were compared between participants with/without cancer (referred to as C+ and C- participants). A 37% reduction in odds for AD was observed in C+ participants compared to C- participants after adjusting for all confounders. The overall risk for MCI and AD in C+ participants was reduced by 27% and 31%, respectively. The odds of cognitive decline from MCI to AD was reduced by 59% in C+ participants after adjusting for all confounders. The risk of cognitive decline from MCI to AD was halved in C+ participants. The estimated mean change in Clinical Dementia Rating-Sum of boxes (CDR-SOB) score per year was 0.23 units/year higher in C- participants than in C+ participants. Overall, an inverse association between cancer and MCI/AD was observed in AIBL, which is in line with previous reports. Importantly, an inverse association between cancer and cognitive decline has also been identified.

Introducing sterically demanding substituents and π-π-interactions into [Cu(P

A series of ten N^N chelating ligands based on a 2,2'-bipyridine (bpy) metal-binding domain and featuring sterically hindering substituents in the 6- and 6,6'-positions has been synthesized and characterized. The ligands have been incorporated into a family of 15 heteroleptic complexes of type [Cu(P^P)(N^N)][PF6] where P^P is the wide bite-angle bisphosphane ligand bis(2(diphenylphosphanyl)phenyl)ether (POP) or (9,9-dimethyl-9H-xanthene-4,5-diyl)bis(diphenylphosphane) (xantphos). Substituents in several of the N^N ligands ligands possess phenyl rings remotely tethered to enable intra- and intermolecular π-π-interactions in the [Cu(P^P)(N^N)]+ cations. Single crystal X-ray structures of 12 complexes are reported. The effects of the functional groups in the bpy ligand on the photophysical properties of the complexes have been studied; solid-state emission maxima range from 518 to 567 nm. Values of the solid-state photoluminescence quantum yields (PLQYs) of the [Cu(P^P)(N^N)][PF6] compounds respond to the nature of the N^N ligand. In general, we observed that the [Cu(P^P)(N^N)]+ complexes containing 6,6'-disubstituted complexes with phenyl moieties connected via a CH2CH2 or CH2CH2CH2 spacer to the bpy domain have the highest values of PLQY. The most significant compounds are [Cu(POP)((2-PhEt)2bpy)][PF6] (PLQY = 67%) and [Cu(POP)((3-PhPr)2bpy)][PF6] (PLQY = 72%) where (2-PhEt)2bpy = 6,6'-bis(2-phenylethyl)-2,2'-bipyridine and (3-PhPr)2bpy = 6,6'-bis(3-phenylpropyl)-2,2'-bipyridine. These PLQY values are among the best performing previously reported families of [Cu(P^P)(N^N)][PF6] compounds.

Controlling Adsorption of Diblock Copolymer Nanoparticles onto an Aldehyde-Functionalized Hydrophilic Polymer Brush via pH Modulation.

Sterically stabilized diblock copolymer nanoparticles with a well-defined spherical morphology and tunable diameter were prepared by RAFT aqueous emulsion polymerization of benzyl methacrylate at 70 °C. The steric stabilizer precursor used for these syntheses contained pendent cis-diol groups, which means that such nanoparticles can react with a suitable aldehyde-functional surface via acetal bond formation. This principle is examined herein by growing an aldehyde-functionalized polymer brush from a planar silicon wafer and studying the extent of nanoparticle adsorption onto this model substrate from aqueous solution at 25 °C using a quartz crystal microbalance (QCM). The adsorbed amount, Γ, depends on both the nanoparticle diameter and the solution pH, with minimal adsorption observed at pH 7 or 10 and substantial adsorption achieved at pH 4. Variable-temperature QCM studies provide strong evidence for chemical adsorption, while scanning electron microscopy images recorded for the nanoparticle-coated brush surface after drying indicate mean surface coverages of up to 62%. This fundamental study extends our understanding of the chemical adsorption of nanoparticles on soft substrates.

Spatial and Temporal Drug Usage Patterns in Wastewater Correlate with Socioeconomic and Demographic Indicators in Southern Nevada.

Evaluating drug use within populations in the United States poses significant challenges due to various social, ethical, and legal constraints, often impeding the collection of accurate and timely data. Here, we aimed to overcome these barriers by conducting a comprehensive analysis of drug consumption trends and measuring their association with socioeconomic and demographic factors. From May 2022 to April 2023, we analyzed 208 wastewater samples from eight sampling locations across six wastewater treatment plants in Southern Nevada, covering a population of 2.4 million residents with 50 million annual tourists. Using bi-weekly influent wastewater samples, we employed mass spectrometry to detect 39 analytes, including pharmaceuticals and personal care products (PPCPs) and high risk substances (HRS). Our results revealed a significant increase over time in the level of stimulants such as cocaine (pFDR=1.40×10-10) and opioids, particularly norfentanyl (pFDR =1.66×10-12), while PPCPs exhibited seasonal variation such as peak usage of DEET, an active ingredient in insect repellents, during the summer (pFDR =0.05). Wastewater from socioeconomically disadvantaged or rural areas, as determined by Area Deprivation Index (ADI) and Rural-Urban Commuting Area Codes (RUCA) scores, demonstrated distinct overall usage patterns, such as higher usage/concentration of HRS, including cocaine (p=0.05) and norfentanyl (p=1.64×10-5). Our approach offers a near real-time, comprehensive tool to assess drug consumption and personal care product usage at a community level, linking wastewater patterns to socioeconomic and demographic factors. This approach has the potential to significantly enhance public health monitoring strategies in the United States.

Coupled Experimental-Theoretical Characterization of a Carbon Electrode in Vanadium Redox Flow Batteries using X-ray Absorption Spectroscopy.

Vanadium redox flow batteries (VRFBs) have emerged as promising solutions for stationary grid energy storage due to their high efficiency, scalability, safety, near room-temperature operation conditions, and the ability to independently size power and energy capacities. The performance of VRFBs heavily relies on the redox couple reactions of V2+/V3+ and VO2+/VO2+ on carbon electrodes. Therefore, a thorough understanding of the surface functionality of carbon electrodes and their propensity for degradation during electrochemical cycles is crucial for designing VRFBs with extended lifespans. In this study, we present a coupled experimental-theoretical approach based on carbon K edge X-ray absorption spectroscopy (XAS) to characterize carbon electrodes prepared under different conditions and identify relevant functional groups that contribute to unique spectroscopic features. Atomic models were created to represent functional groups, such as hydroxyl, carboxyl, methyl, and aldehyde, bonded to carbon atoms in either sp2 or sp3 environments. The interactions between functionalized carbon and various solvated vanadium complexes were modeled using density functional theory. A library of carbon K-edge XAS spectra was generated for distinct carbon atoms in different functional groups, both before and after interacting with solvated vanadium complexes. We demonstrate how these simulated spectra can be used to deconvolve ex situ experimental spectra measured from carbon electrodes and to track changes in the electrode composition following immersion in different electrolytes or extended cycling within a functional VRFB. By doing so, we identify the active species present on the carbon electrodes, which play a crucial role in determining their electrochemical performance.