Rechargeable Batteries Including High-Voltage Cathode and Redox Shuttle Conferring Overcharge Protection

Compounds for use as photoredox catalysts and as redox shuttles in a rechargeable battery having a high-voltage cathode providing overcharge protection capabilities are provided, including a compound according to the formula: (see patent for formula) wherein R is selected from the group consisting of alkyl, aryl, alkylaryl, alkoxyaryl, alkylcarboxyl, aryl carbonyl, haloalkyl, perfluoroalkyl, glycols, haloaryl, a negative electrolyte, and a polymer

Non-Aqueous Redox Flow Batteries Including 3,7-Perfluoroalkylated Phenothiazine Derivatives

A non-aqueous redox flow battery includes a negative electrode immersed in a first non-aqueous liquid electrolyte solution, a positive electrode immersed in a second nonaqueous liquid electrolyte solution, and a semi-permeable separator interposed between the negative and positive electrodes, wherein the second the non-aqueous liquid electrolyte solution comprises a compound of the formula... To see the remainder of this abstract, please download this patent

Designing a Data Science simulation with MERITS: A Primer

Simulations play a crucial role in the modern scientific process. Yet despite (or due to) their ubiquity, the Data Science community shares neither a comprehensive definition for a "high-quality" study nor a consolidated guide to designing one. Inspired by the Predictability-Computability-Stability (PCS) framework for 'veridical' Data Science, we propose six MERITS that a Data Science simulation should satisfy. Modularity and Efficiency support the Computability of a study, encouraging clean and flexible implementation. Realism and Stability address the conceptualization of the research problem: How well does a study Predict reality, such that its conclusions generalize to new data/contexts? Finally, Intuitiveness and Transparency encourage good communication and trustworthiness of study design and results. Drawing an analogy between simulation and cooking, we moreover offer (a) a conceptual framework for thinking about the anatomy of a simulation 'recipe'; (b) a baker's dozen in guidelines to aid the Data Science practitioner in designing one; and (c) a case study deconstructing a simulation through the lens of our framework to demonstrate its practical utility. By contributing this "PCS primer" for high-quality Data Science simulation, we seek to distill and enrich the best practices of simulation across disciplines into a cohesive recipe for trustworthy, veridical Data Science.Comment: 26 pages (main text); 1 figure; 2 tables; *Authors contributed equally to this manuscript; **Authors contributed equally to this manuscrip

1,9,10-Substituted Phenothiazine Derivatives with Strained Radical Cations and Use Thereof

Compounds for use in a rechargeable battery are provided, including a compound according to the formula: (see patent for the formula) wherein R1 and R9 are independently selected from the group consisting of H, alkyl, aryl, perfluoroaryl, perfluoroalkyl, alkylaryl, alkoxyaryl, alkylcarboxyl, aryl carbonyl, haloalkyl, perfluoroalkyl, glycols, haloaryl, a negative electrolyte, and a polymer, so long as when R1 is H, R9 is not H; and R10 is selected from the group consisting of methyl, alkyl, aryl, alkylaryl, alkoxyaryl, alkylcarboxyl, aryl carbonyl, haloalkyl, perfluoroalkyl, perfluoroaryl, glycols, haloaryl, an oligomer, and a polymer

Controlling Oxidation Potentials in Redox Shuttle Candidates for Lithium-Ion Batteries

Overcharge, a condition in which cell voltage rises to undesirably high potentials, can be prevented in lithium-ion batteries by incorporating redox shuttles into the battery electrolyte. Although extensive overcharge protection has been demonstrated in batteries with LiFePO₄ cathodes, the redox shuttles that work in these batteries are incompatible with higher voltage cathodes. Designing stable additives with higher oxidation potentials is necessary to protect high voltage batteries from overcharge. Toward that goal, we synthesized diarylamines with varied structures, including fused heteroaromatic ring systems and electron-withdrawing substituents. We found that trends in oxidation potentials correlated with those in calculated adiabatic ionization potentials. Some diarylamine derivatives protected batteries from overcharge with varying degrees of success

Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis

Importance: Sepsis is a heterogeneous syndrome. Identification of distinct clinical phenotypes may allow more precise therapy and improve care. Objective: To derive sepsis phenotypes from clinical data, determine their reproducibility and correlation with host-response biomarkers and clinical outcomes, and assess the potential causal relationship with results from randomized clinical trials (RCTs). Design, Settings, and Participants: Retrospective analysis of data sets using statistical, machine learning, and simulation tools. Phenotypes were derived among 20189 total patients (16552 unique patients) who met Sepsis-3 criteria within 6 hours of hospital presentation at 12 Pennsylvania hospitals (2010-2012) using consensus k means clustering applied to 29 variables. Reproducibility and correlation with biological parameters and clinical outcomes were assessed in a second database (2013-2014; n = 43086 total patients and n = 31160 unique patients), in a prospective cohort study of sepsis due to pneumonia (n = 583), and in 3 sepsis RCTs (n = 4737). Exposures: All clinical and laboratory variables in the electronic health record. Main Outcomes and Measures: Derived phenotype (α, β, γ, and δ) frequency, host-response biomarkers, 28-day and 365-day mortality, and RCT simulation outputs. Results: The derivation cohort included 20189 patients with sepsis (mean age, 64 [SD, 17] years; 10022 [50%] male; mean maximum 24-hour Sequential Organ Failure Assessment [SOFA] score, 3.9 [SD, 2.4]). The validation cohort included 43086 patients (mean age, 67 [SD, 17] years; 21993 [51%] male; mean maximum 24-hour SOFA score, 3.6 [SD, 2.0]). Of the 4 derived phenotypes, the α phenotype was the most common (n = 6625; 33%) and included patients with the lowest administration of a vasopressor; in the β phenotype (n = 5512; 27%), patients were older and had more chronic illness and renal dysfunction; in the γ phenotype (n = 5385; 27%), patients had more inflammation and pulmonary dysfunction; and in the δ phenotype (n = 2667; 13%), patients had more liver dysfunction and septic shock. Phenotype distributions were similar in the validation cohort. There were consistent differences in biomarker patterns by phenotype. In the derivation cohort, cumulative 28-day mortality was 287 deaths of 5691 unique patients (5%) for the α phenotype; 561 of 4420 (13%) for the β phenotype; 1031 of 4318 (24%) for the γ phenotype; and 897 of 2223 (40%) for the δ phenotype. Across all cohorts and trials, 28-day and 365-day mortality were highest among the δ phenotype vs the other 3 phenotypes (P 33% chance of benefit to >60% chance of harm). Conclusions and Relevance: In this retrospective analysis of data sets from patients with sepsis, 4 clinical phenotypes were identified that correlated with host-response patterns and clinical outcomes, and simulations suggested these phenotypes may help in understanding heterogeneity of treatment effects. Further research is needed to determine the utility of these phenotypes in clinical care and for informing trial design and interpretation.