Solubilities of Ethylene and Carbon Dioxide Gases in Lithium-Ion Battery Electrolyte.

During Li-ion battery operation, (electro)chemical side reactions occur within the cell that can promote or degrade performance. These complex reactions produce byproducts in the solid, liquid, and gas phases. Studying byproducts in these three phases can help optimize battery lifetimes. To relate the measured gas-phase byproducts to species dissolved in the liquid-phase, equilibrium proprieties such as the Henry's law constants are required. The present work implements a pressure decay experiment to determine the thermodynamic equilibrium concentrations between the gas and liquid phases for ethylene (C2H4) and carbon dioxide (CO2), which are two gases commonly produced in Li-ion batteries, with an electrolyte of 1.2 M LiPF6 in 3:7 wt/wt ethylene carbonate/ethyl methyl carbonate and 3 wt % fluoroethylene carbonate (15:25:57:3 wt % total composition). The experimentally measured pressure decay curve is fit to an analytical dissolution model and extrapolated to predict the final pressure at equilibrium. The relationship between the partial pressures and concentration of dissolved gas in electrolyte at equilibrium is then used to determine Henry's law constants of 2.0 × 104 kPa for C2H4 and k CO2 = 1.1 × 104 kPa for CO2. These values are compared to Henry's law constants predicted from density functional theory and show good agreement within a factor of 3.

Design Principles and Routes for Calcium Alkoxyaluminate Electrolytes.

Multivalent-ion battery technologies are increasingly attractive options for meeting diverse energy storage needs. Calcium ion batteries (CIB) are particularly appealing candidates for their earthly abundance, high theoretical volumetric energy density, and relative safety advantages. At present, only a few Ca-ion electrolyte systems are reported to reversibly plate at room temperature: for example, aluminates and borates, including Ca[TPFA]2, where [TPFA]- = [Al(OC(CF3)3)4]- and Ca[B(hfip)4]2, [B(hfip)4]2- = [B(OCH(CF3)2)4]-. Analyzing the structure of these salts reveals a common theme: the prevalent use of a weakly coordinating anion (WCA) consisting of a tetracoordinate aluminum/boron (Al/B) center with fluorinated alkoxides. Leveraging the concept of theory-aided design, we report an innovative, one-pot synthesis of two new calcium-ion electrolyte salts (Ca[Al(tftb)4]2, Ca[Al(hftb)4]2) and two reported salts (Ca[Al(hfip)4]2 and Ca[TPFA]2) where hfip = (-OCH(CF3)2), tftb = (-OC(CF3)(Me)2), hftb = (-OC(CF3)2(Me)), [TPFA]- = [Al(OC(CF3)3)4]-. We also reveal the dependence of Coulombic efficiency on their inherent propensity for cation-anion coordination.

Virtual Screening of a Chemically Diverse "Superscaffold" Library Enables Ligand Discovery for a Key GPCR Target.

The advent of ultra-large libraries of drug-like compounds has significantly broadened the possibilities in structure-based virtual screening, accelerating the discovery and optimization of high-quality lead chemotypes for diverse clinical targets. Compared to traditional high-throughput screening, which is constrained to libraries of approximately one million compounds, the ultra-large virtual screening approach offers substantial advantages in both cost and time efficiency. By expanding the chemical space with compounds synthesized from easily accessible and reproducible reactions and utilizing a large, diverse set of building blocks, we can enhance both the diversity and quality of the discovered lead chemotypes. In this study, we explore new chemical spaces using reactions of sulfur(VI) fluorides to create a combinatorial library consisting of several hundred million compounds. We screened this virtual library for cannabinoid type II receptor (CB2) antagonists using the high-resolution structure in conjunction with a rationally designed antagonist, AM10257. The top-predicted compounds were then synthesized and tested in vitro for CB2 binding and functional antagonism, achieving an experimentally validated hit rate of 55%. Our findings demonstrate the effectiveness of reliable reactions, such as sulfur fluoride exchange, in diversifying ultra-large chemical spaces and facilitate the discovery of new lead compounds for important biological targets.

The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging.

OBJECTIVES: Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults. METHODS: One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64). RESULTS: After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure. DISCUSSION: Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT. CLINICAL TRIAL REGISTRATION: NCT03197454.

Uterine washings as a novel method for early detection of ovarian cancer: Trials and tribulations.

Given the tubal origin of high-grade serous ovarian cancer (HGSC), we sought to investigate intrauterine lavage (IUL) as a novel method of biomarker detection. IUL and serum samples were collected from patients with HGSC or benign pathology. Although CA-125 and HE4 concentrations were significantly higher in IUL samples compared to serum, they were similar between IUL samples from patients with HGSC vs benign conditions. In contrast, CA-125 and HE4 serum concentrations differed between HGSC and benign pathology (P =.002 for both). IUL and tumor samples from patients with HGSC were subjected to targeted panel sequencing and droplet digital PCR (ddPCR). Tumor mutations were found in 75 % of matched IUL samples. Serum CA-125 and HE4 biomarker levels allowed for better differentiation of HGSC and benign pathology compared to IUL samples. We believe using IUL for early detection of HGSC requires optimization, and current strategies should focus on prevention until early detection strategies improve.

CoeffNet: predicting activation barriers through a chemically-interpretable, equivariant and physically constrained graph neural network.

Activation barriers of elementary reactions are essential to predict molecular reaction mechanisms and kinetics. However, computing these energy barriers by identifying transition states with electronic structure methods (e.g., density functional theory) can be time-consuming and computationally expensive. In this work, we introduce CoeffNet, an equivariant graph neural network that predicts activation barriers using coefficients of any frontier molecular orbital (such as the highest occupied molecular orbital) of reactant and product complexes as graph node features. We show that using coefficients as features offer several advantages, such as chemical interpretability and physical constraints on the network's behaviour and numerical range. Model outputs are either activation barriers or coefficients of the chosen molecular orbital of the transition state; the latter quantity allows us to interpret the results of the neural network through chemical intuition. We test CoeffNet on a dataset of SN2 reactions as a proof-of-concept and show that the activation barriers are predicted with a mean absolute error of less than 0.025 eV. The highest occupied molecular orbital of the transition state is visualized and the distribution of the orbital densities of the transition states is described for a few prototype SN2 reactions.

Is Hey Jude in the right key? Cognitive components of absolute pitch memory.

Most individuals, regardless of formal musical training, have long-term absolute pitch memory (APM) for familiar musical recordings, though with varying levels of accuracy. The present study followed up on recent evidence suggesting an association between singing accuracy and APM (Halpern & Pfordresher, 2022, Attention, Perception, & Psychophysics, 84(1), 260-269), as well as tonal short-term memory (STM) and APM (Van Hedger et al., 2018, Quarterly Journal of Experimental Psychology, 71(4), 879-891). Participants from three research sites (n = 108) completed a battery of tasks including APM, tonal STM, singing accuracy, and self-reported auditory imagery. Both tonal STM and singing accuracy predicted APM, replicating prior results. Tonal STM also predicted singing accuracy, music training, and auditory imagery. Further tests suggested that the association between APM and singing accuracy was fully mediated by tonal STM. This pattern comports well with models of vocal pitch matching that include STM for pitch as a mechanism for sensorimotor translation.

A Critical Analysis of Chemical and Electrochemical Oxidation Mechanisms in Li-Ion Batteries.

Electrolyte decomposition limits the lifetime of commercial lithium-ion batteries (LIBs) and slows the adoption of next-generation energy storage technologies. A fundamental understanding of electrolyte degradation is critical to rationally design stable and energy-dense LIBs. To date, most explanations for electrolyte decomposition at LIB positive electrodes have relied on ethylene carbonate (EC) being chemically oxidized by evolved singlet oxygen (1O2) or electrochemically oxidized. In this work, we apply density functional theory to assess the feasibility of these mechanisms. We find that electrochemical oxidation is unfavorable at any potential reached during normal LIB operation, and we predict that previously reported reactions between the EC and 1O2 are kinetically limited at room temperature. Our calculations suggest an alternative mechanism in which EC reacts with superoxide (O2-) and/or peroxide (O22-) anions. This work provides a new perspective on LIB electrolyte decomposition and motivates further studies to understand the reactivity at positive electrodes.

Complex 33-beam simulated galactic cosmic radiation exposure impacts cognitive function and prefrontal cortex neurotransmitter networks in male mice.

Astronauts will encounter extended exposure to galactic cosmic radiation (GCR) during deep space exploration, which could impair brain function. Here, we report that in male mice, acute or chronic GCR exposure did not modify reward sensitivity but did adversely affect attentional processes and increased reaction times. Potassium (K+)-stimulation in the prefrontal cortex (PFC) elevated dopamine (DA) but abolished temporal DA responsiveness after acute and chronic GCR exposure. Unlike acute GCR, chronic GCR increased levels of all other neurotransmitters, with differences evident between groups after higher K+-stimulation. Correlational and machine learning analysis showed that acute and chronic GCR exposure differentially reorganized the connection strength and causation of DA and other PFC neurotransmitter networks compared to controls which may explain space radiation-induced neurocognitive deficits.

Plasma Environment, Radiation, Structure, and Evolution of the Uranian System (PERSEUS): A Dedicated Orbiter Mission Concept to Study Space Physics at Uranus.

The Plasma Environment, Radiation, Structure, and Evolution of the Uranian System (PERSEUS) mission concept defines the feasibility and potential scope of a dedicated, standalone Heliophysics orbiter mission to study multiple space physics science objectives at Uranus. Uranus's complex and dynamic magnetosphere presents a unique laboratory to study magnetospheric physics as well as its coupling to the solar wind and the planet's atmosphere, satellites, and rings. From the planet's tilted and offset, rapidly-rotating non-dipolar magnetic field to its seasonally-extreme interactions with the solar wind to its unexpectedly intense electron radiation belts, Uranus hosts a range of outstanding and compelling mysteries relevant to the space physics community. While the exploration of planets other than Earth has largely fallen within the purview of NASA's Planetary Science Division, many targets, like Uranus, also hold immense scientific value and interest to NASA's Heliophysics Division. Exploring and understanding Uranus's magnetosphere is critical to make fundamental gains in magnetospheric physics and the understanding of potential exoplanetary systems and to test the validity of our knowledge of magnetospheric dynamics, moon-magnetosphere interactions, magnetosphere-ionosphere coupling, and solar wind-planetary coupling. The PERSEUS mission concept study, currently at Concept Maturity Level (CML) 4, comprises a feasible payload that provides closure to a range of space physics science objectives in a reliable and mature spacecraft and mission design architecture. The mission is able to close using only a single Mod-1 Next-Generation Radioisotope Thermoelectric Generator (NG-RTG) by leveraging a concept of operations that relies of a significant hibernation mode for a large portion of its 22-day orbit.

A game-factors approach to cognitive benefits from video-game training: A meta-analysis.

This current study is a meta-analysis conducted on 63 studies on video-game based cognitive interventions (118 investigations, N = 2,079), which demonstrated a moderate and significant training effect on overall gains in cognition, g = 0.25, p < .001. Significant evidence of transfer was found to overall cognition, as well as to attention/perception and higher-order cognition constructs. Examination of specific gameplay features however showed selective and differential transfer to these outcome measures, whereas the genre labels of "action", "strategy", "casual", and "non-casual" were not similarly predictive of outcomes. We therefore recommend that future video-game interventions targeting cognitive enhancements should consider gameplay feature classification approach over existing genre classification, which may provide more fruitful training-related benefits to cognition.

Optimized electronic properties and nano-structural features for securing high thermoelectric performance in doped GeTe.

Recently, thermoelectric (TE) materials have been attracting great attention due to their improved capability to convert heat directly into electricity. PbTe-based TE materials are among the most competitive ones; however, lead toxicity limits their potential applications. Thus, the current focus in the field is on the discovery of lead-free analogues. GeTe is considered to be a promising candidate, however, its thermoelectric performance is limited by a non-ideal band structure and intrinsic Ge vacancies. In this work, GeTe was co-doped with Bi, Zn, and In. Initial doping with Bi enhances the performance by tuning the electronic properties and bringing down the thermal conductivity. Subsequent Zn doping permits to maintain the high power factor by increasing carrier mobility and reducing carrier concentration. Additionally, Zn incorporation lowers thermal conductivity and, thus, increases the performance. Subsequent In doping in (Ge0.97Zn0.02In0.01Te)0.97(Bi2Te3)0.03 reduces thermal conductivity even further and makes this material the best performing one. Scanning transmission electron microscopy shows the presence of nano twinning, defect layers, and dislocation bands that contribute to the suppression of the lattice thermal conductivity. A peak zT value of 2.06 and an average zT value of 1.30 have been achieved in (Ge0.97Zn0.02In0.01Te)0.97(Bi2Te3)0.03. These results are among the best state-of-the-art thermoelectric materials.

Chemical Reaction Networks Explain Gas Evolution Mechanisms in Mg-Ion Batteries.

Out-of-equilibrium electrochemical reaction mechanisms are notoriously difficult to characterize. However, such reactions are critical for a range of technological applications. For instance, in metal-ion batteries, spontaneous electrolyte degradation controls electrode passivation and battery cycle life. Here, to improve our ability to elucidate electrochemical reactivity, we for the first time combine computational chemical reaction network (CRN) analysis based on density functional theory (DFT) and differential electrochemical mass spectroscopy (DEMS) to study gas evolution from a model Mg-ion battery electrolyte─magnesium bistriflimide (Mg(TFSI)2) dissolved in diglyme (G2). Automated CRN analysis allows for the facile interpretation of DEMS data, revealing H2O, C2H4, and CH3OH as major products of G2 decomposition. These findings are further explained by identifying elementary mechanisms using DFT. While TFSI- is reactive at Mg electrodes, we find that it does not meaningfully contribute to gas evolution. The combined theoretical-experimental approach developed here provides a means to effectively predict electrolyte decomposition products and pathways when initially unknown.

Longitudinal changes in gray matter correspond to changes in cognition across the lifespan: implications for theories of cognition.

The present study examines the association between gray matter volume and cognition. Studies that have examined this issue have focused primarily on older adults, whereas the present study examines the issue across the entire adult lifespan. A total of 463 adults, ages 20-88 at first assessment, were followed longitudinally across three assessments over 8-10years. Significant individual differences in a general cognition measure comprised of measures of speed of processing, working memory, and episodic memory were observed, as well as in measures of cortical and subcortical gray matter. Parallel process latent growth curve modeling showed a reliable relationship between decreases in cortical matter and cognitive decline across the entire adult lifespan, which persisted after controlling for age effects. Implications of these findings in relation to progression toward dementia, risk assessment, cognitive intervention, and environmental factors are discussed, as well as implications for theories of cognitive aging.

Assessing the Accuracy of Density Functional Approximations for Predicting Hydrolysis Reaction Kinetics.

Hydrolysis reactions are ubiquitous in biological, environmental, and industrial chemistry. Density functional theory (DFT) is commonly employed to study the kinetics and reaction mechanisms of hydrolysis processes. Here, we present a new data set, Barrier Heights for HydrOlysis - 36 (BH2O-36), to enable the design of density functional approximations (DFAs) and the rational selection of DFAs for applications in aqueous chemistry. BH2O-36 consists of 36 diverse organic and inorganic forward and reverse hydrolysis reactions with reference energy barriers ΔE‡ calculated at the CCSD(T)/CBS level. Using BH2O-36, we evaluate 63 DFAs. In terms of mean absolute error (MAE) and mean relative absolute error (MRAE), ωB97M-V is the best-performing DFA tested, while MN12-L-D3(BJ) is the best-performing pure (nonhybrid) DFA. Broadly, we find that range-separated hybrid DFAs are necessary to approach chemical accuracy (0.043 eV). Although the best-performing DFAs include a dispersion correction to account for long-range interactions, we find that dispersion corrections do not generally improve MAE or MRAE for this data set.

Negative modulation of AMPA receptors bound to transmembrane AMPA receptor regulatory protein γ-8 blunts the positive reinforcing properties of alcohol and sucrose in a brain region-dependent manner in male mice.

RATIONALE: The development and progression of alcohol use disorder (AUD) are widely viewed as maladaptive neuroplasticity. The transmembrane alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) regulatory protein γ8 (TARP γ-8) is a molecular mechanism of neuroplasticity that has not been evaluated in AUD or other addictions. OBJECTIVE: To address this gap in knowledge, we evaluated the mechanistic role of TARP γ-8 bound AMPAR activity in the basolateral amygdala (BLA) and ventral hippocampus (vHPC) in the positive reinforcing effects of alcohol, which drive repetitive alcohol use throughout the course of AUD, in male C57BL/6 J mice. These brain regions were selected because they exhibit high levels of TARP γ-8 expression and send glutamate projections to the nucleus accumbens (NAc), which is a key nucleus in the brain reward pathway. METHODS AND RESULTS: Site-specific pharmacological inhibition of AMPARs bound to TARP γ-8 in the BLA via bilateral infusion of the selective negative modulator JNJ-55511118 (0-2 µg/µl/side) significantly decreased operant alcohol self-administration with no effect on sucrose self-administration in behavior-matched controls. Temporal analysis showed that reductions in alcohol-reinforced response rate occurred > 25 min after the onset of responding, consistent with a blunting of the positive reinforcing effects of alcohol in the absence of nonspecific behavioral effects. In contrast, inhibition of TARP γ-8 bound AMPARs in the vHPC selectively decreased sucrose self-administration with no effect on alcohol. CONCLUSIONS: This study reveals a novel brain region-specific role of TARP γ-8 bound AMPARs as a molecular mechanism of the positive reinforcing effects of alcohol and non-drug rewards.

Complete blood platelet and lymphocyte ratios increase diagnostic accuracy of periprosthetic joint infection following total hip arthroplasty.

INTRODUCTION: Systemically, changes in serum platelet to lymphocyte ratio (PLR), platelet count to mean platelet volume ratio (PVR), neutrophil to lymphocyte ratio (NLR) and monocyte to lymphocyte (MLR) represent primary responses to early inflammation and infection. This study aimed to determine whether PLR, PVR, NLR, and MLR can be useful in diagnosing periprosthetic joint infection (PJI) in total hip arthroplasty (THA) patients. METHODS: A total of 464 patients that underwent revision THA with calculable PLR, PVR, NLR, and MLR in 2 groups was evaluated: 1) 191 patients with a pre-operative diagnosis of PJI, and 2) 273 matched patients treated for revision THA for aseptic complications. RESULTS: The sensitivity and specificity of PLR combined with erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), synovial white blood cell count (WBC) and synovial polymorphonuclear leukocytes (PMN) (97.9%; 98.5%) is significantly higher than only ESR combined with CRP, synovial WBC and synovial PMN (94.2%; 94.5%; p < 0.01). The sensitivity and specificity of PVR combined with ESR, CRP and synovial WBC, and synovial PMN (98.4%; 98.2%) is higher than only ESR combined with CRP, synovial WBC and synovial PMN (94.2%; 94.5%; p < 0.01). CONCLUSION: The study results demonstrate that both PLR and PVR calculated from complete blood counts when combined with serum and synovial fluid markers have increased diagnostic sensitivity and specificity in diagnosing periprosthetic joint infection in THA patients. LEVEL OF EVIDENCE: III, case-control retrospective analysis.

Elevated ESR and CRP Prior to Second-Stage Reimplantation Knee Revision Surgery for Periprosthetic Joint Infection Are Associated with Increased Reinfection Rates.

Although two-stage revision surgery is considered as the most effective treatment for managing chronic periprosthetic joint infection (PJI), there is no current consensus on the predictors of optimal timing to second-stage reimplantation. This study aimed to compare clinical outcomes between patients with elevated erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) prior to second-stage reimplantation and those with normalized ESR and CRP prior to second-stage reimplantation. We retrospectively reviewed 198 patients treated with two-stage revision total knee arthroplasty for chronic PJI. Cohorts included patients with: (1) normal level of serum ESR and CRP (n = 96) and (2) elevated level of serum ESR and CRP prior to second-stage reimplantation (n = 102). Outcomes including reinfection rates and readmission rates were compared between both cohorts. At a mean follow-up of 4.4 years (2.8-6.5 years), the elevated ESR and CRP cohort demonstrated significantly higher reinfection rates compared with patients with normalized ESR and CRP prior to second-stage reimplantation (33.3% vs. 14.5%, p < 0.01). Patients with both elevated ESR and CRP demonstrated significantly higher reinfection rates, when compared with patients with elevated ESR and normalized CRP (33.3% vs. 27.6%, p = 0.02) as well as normalized ESR and elevated CRP (33.3% vs. 26.3%, p < 0.01). This study demonstrates that elevated serum ESR and/or CRP levels prior to reimplantation in two-stage knee revision surgery for chronic PJI are associated with increased reinfection rate after surgery. Elevation of both ESR and CRP were associated with a higher risk of reinfection compared with elevation of either ESR or CRP, suggesting the potential benefits of normalizing ESR and CRP prior to reimplantation in treatment of chronic PJI.

Chemical reaction networks and opportunities for machine learning.

Chemical reaction networks (CRNs), defined by sets of species and possible reactions between them, are widely used to interrogate chemical systems. To capture increasingly complex phenomena, CRNs can be leveraged alongside data-driven methods and machine learning (ML). In this Perspective, we assess the diverse strategies available for CRN construction and analysis in pursuit of a wide range of scientific goals, discuss ML techniques currently being applied to CRNs and outline future CRN-ML approaches, presenting scientific and technical challenges to overcome.

Cognitive and structural predictors of novel task learning, and contextual predictors of time series of daily task performance during the learning period.

Investigation into methods of addressing cognitive loss exhibited later in life is of paramount importance to the field of cognitive aging. The field continues to make significant strides in designing efficacious cognitive interventions to mitigate cognitive decline, and the very act of learning a demanding task has been implicated as a potential mechanism of augmenting cognition in both the field of cognitive intervention and studies of cognitive reserve. The present study examines individual-level predictors of complex skill learning and day-to-day performance on a gamified working memory updating task, the BirdWatch Game, intended for use as a cognitive intervention tool in older adults. A measure of verbal episodic memory and the volume of a brain region involved in verbal working memory and cognitive control (the left inferior frontal gyrus) were identified as predictors of learning rates on the BirdWatch Game. These two neuro-cognitive measures were more predictive of learning when considered in conjunction than when considered separately, indicating a complementary effect. Additionally, auto-regressive time series forecasting analyses were able to identify meaningful daily predictors (that is, mood, stress, busyness, and hours of sleep) of performance-over-time on the BirdWatch Game in 50% of cases, with the specific pattern of contextual influences on performance being highly idiosyncratic between participants. These results highlight the specific contribution of language processing and cognitive control abilities to the learning of the novel task examined in this study, as well as the variability of subject-level influences on task performance during task learning.