Operando insights into ammonium-mediated lithium metal stabilization: surface morphology modulation and enhanced SEI development.

Lithium-ion batteries (LiBs) with graphite as an anode and lithiated transition metal oxide as a cathode are approaching their specific energy and power theoretical values. To overcome the limitations of LiBs, lithium metal anode with high specific capacity and low negative redox potential is necessary. However, practical application in rechargeable cells is hindered by uncontrolled lithium deposition manifesting, for instance, as Li dendrite growth which can cause formation of dead Li, short circuits and cell failure. The electrochemical behaviour of a protic additive (NH4PF6) in a carbonate-based electrolyte has been investigated by operando confocal Raman spectroscopy, in situ optical microscopy, and X-ray photoelectron spectroscopy, elucidating its functional mechanism. The ammonium cation promotes a chemical modification of the lithium metal anode-electrolyte interphase by producing an N-rich solid electrolyte interphase and chemically modifying the lithium surface morphology by electrochemical pitting. This novel method results in stable lithium deposition and stripping by a decreasing the local current density on the electrode, thus limiting dendritic deposition.

Combining clinical notes with structured electronic health records enhances the prediction of mental health crises.

An automatic prediction of mental health crises can improve caseload prioritization and enable preventative interventions, improving patient outcomes and reducing costs. We combine structured electronic health records (EHRs) with clinical notes from 59,750 de-identified patients to predict the risk of mental health crisis relapse within the next 28 days. The results suggest that an ensemble machine learning model that relies on structured EHRs and clinical notes when available, and relying solely on structured data when the notes are unavailable, offers superior performance over models trained with either of the two data streams alone. Furthermore, the study provides key takeaways related to the required amount of clinical notes to add value in predictive analytics. This study sheds light on the untapped potential of clinical notes in the prediction of mental health crises and highlights the importance of choosing an appropriate machine learning method to combine structured and unstructured EHRs.

Toward Operando Characterization of Interphases in Batteries.

Electrode/electrolyte interfaces are the most important and least understood components of Li-ion and next-generation batteries. An improved understanding of interphases in batteries will undoubtedly lead to breakthroughs in the field. Traditionally, evaluating those interphases involves using ex situ surface sensitive and/or imaging techniques. Due to their very dynamic and reactive nature, ex situ sample manipulation is undesirable. From this point of view, operando surface sensitive techniques represent a major opportunity to push boundaries in battery development. While numerous bulk spectroscopic, scattering, and imaging techniques are well established and widely used, surface sensitive operando techniques remain challenging and, to a larger extent, restricted to the model systems. Here, we give a perspective on techniques with the potential to characterize solid/liquid interfaces in both model and realistic battery configurations. The focus is on techniques that provide chemical and structural information at length and time scales relevant for the solid electrolyte interphase (SEI) formation and evolution, while also probing representative electrode areas. We highlight the following techniques: vibrational spectroscopy, X-ray photoelectron spectroscopy (XPS), neutron and X-ray reflectometry, and grazing incidence scattering techniques. Comprehensive overviews, as well as promises and challenges, of these techniques when used operando on battery interphases are discussed in detail.

Multiscale X-ray imaging and characterisation of pharmaceutical dosage forms.

A correlative, multiscale imaging methodology for visualising and quantifying the morphology of solid dosage forms by combining ptychographic X-ray computed nanotomography (PXCT) and scanning small- and wide-angle X-ray scattering (S/WAXS) is presented. The methodology presents a workflow for multiscale analysis, where structures are characterised from the nanometre to millimetre regime. Here, the method is demonstrated by characterising a hot-melt extruded, partly crystalline, solid dispersion of carbamazepine in ethyl cellulose. Characterisation of the morphology and solid-state phase of the drug in solid dosage forms is central as this affects the performance of the final formulation. The 3D morphology was visualised at a resolution of 80 nm over an extended volume through PXCT, revealing an oriented structure of crystalline drug domains aligned in the direction of extrusion. Scanning S/WAXS showed that the nanostructure is similar over the cross section of the extruded filament, with minor radial changes in domain sizes and degree of orientation. The polymorphic forms of carbamazepine were qualified with WAXS, showing a heterogeneous distribution of the metastable forms I and II. This demonstrates the methodology for multiscale structural characterization and imaging to enable a better understanding of the relationships between morphology, performance, and processing conditions of solid dosage forms.

Mechanistic understanding of the correlation between structure and dynamics of liquid carbonate electrolytes: impact of polarization.

Liquid electrolyte design and modelling is an essential part of the development of improved lithium ion batteries. For mixed organic carbonates (ethylene carbonate (EC) and ethyl-methyl carbonate (EMC) mixtures)-based electrolytes with LiPF6 as salt, we have compared a polarizable force field with the standard non-polarizable force field with and without charge rescaling to model the structural and dynamic properties. The result of our molecular dynamics simulations shows that both polarizable and non-polarizable force fields have similar structural factors, which are also in agreement with X-ray diffraction experimental results. In contrast, structural differences are observed for the lithium neighborhood, while the lithium-anion neighbourhood is much more pronounced for the polarizable force field. Comparison of EC/EMC coordination statistics with Fourier transformed infrared spectroscopy (FTIR) shows the best agreement for the polarizable force field. Also for transport quantities such as ionic conductivities, transference numbers, and viscosities, the agreement with the polarizable force field is by far better for a large range of salt concentrations and EC : EMC ratios. In contrast, for the non-polarizable variants, the dynamics are largely underestimated. The excellent performance of the polarizable force field is explored in different ways to pave the way to a realistic description of the structure-dynamics relationships for a wide range of salt and solvent compositions for this standard electrolyte. In particular, we can characterize the distinct correlation terms between like and unlike ions, relate them to structural properties, and explore to which degree the transport in this electrolyte is mass or charge limited.

Two edges of the screen: Unpacking positive and negative associations between phone use in everyday contexts and subjective well-being.

A plethora of past studies have highlighted a negative association between phone use and well-being. Recent studies claimed that there is a lack of strong evidence on the deleterious effects of smartphones on our health, and that previous systematic reviews overestimated the negative link between phone use and well-being. In a three-week long in-the-wild study with 352 participants, we captured 15,607 instances of smartphone use in tandem with rich contextual information (activity, location, company) as well as self-reported well-being measures. We conducted an additional study to gather users' perception of the impact of phone use on their well-being in different daily contexts. Our findings show that context and personal characteristics greatly impact the association between screen time and subjective well-being. This study highlights the complexity of the relationship between phone use and well-being and it deepens our understanding of this problem.

Characterizing observed and effective behavioral engagement with smartphone cognitive behavioral therapy for body dysmorphic disorder: A methods roadmap and use case.

Smartphone psychotherapies are growing in popularity, yet little is understood about (1) how people prefer to engage with psychotherapy apps, or (2) which engagement patterns constitute effective engagement. The present study uses secondary data from a 12-week randomized waitlist-controlled trial of smartphone-delivered cognitive behavioral therapy (CBT) for body dysmorphic disorder (BDD) (N = 77) to address these aims. Additionally, using the present study as a use-case, we seek to provide a roadmap for how researchers may improve upon methodological limitations of existing smartphone psychotherapy engagement research. We measured behavioral engagement via 19 objective variables derived from phone analytics data, which we reduced via factor analysis into two factors: 1) use volume and frequency, and 2) session duration. Cluster analysis based on engagement factors yielded three engager types, which mapped onto "deep" users, "samplers," and "light" users. The clusters did not differ significantly in improvement in BDD severity across treatment, although deep users improved more than light users at a marginally significant level. Results suggest that varying patterns of preferred engagement may be efficacious. Moreover, the study's methods provide an example of how researchers can measure and study behavioral engagement comprehensively and objectively. Trial Registration: ClinicalTrials.gov Identifier: NCT04034693.

Investigating microstructure evolution of lithium metal during plating and stripping via operando X-ray tomographic microscopy.

Efficient lithium metal stripping and plating operation capable of maintaining electronic and ionic conductivity is crucial to develop safe lithium metal batteries. However, monitoring lithium metal microstructure evolution during cell cycling is challenging. Here, we report the development of an operando synchrotron X-ray tomographic microscopy method capable of probing in real-time the formation, growth, and dissolution of Li microstructures during the cycling of a Li||Cu cell containing a standard non-aqueous liquid electrolyte solution. The analyses of the operando X-ray tomographic microscopy measurements enable tracking the evolution of deposited Li metal as a function of time and applied current density and distinguishing the formation of electrochemically inactive Li from the active bulk of Li microstructures. Furthermore, in-depth analyses of the Li microstructures shed some light on the structural connectivity of deposited Li at different current densities as well as the formation mechanism of fast-growing fractal Li microstructures, which are ultimately responsible for cell failure.

The influence of vitamin D supplementation on the expression of mediators of inflammation in knee osteoarthritis.

This trial aimed to determine the possible therapeutic and immunomodulatory effects of vitamin D3 in patients with knee OA. In this open-label clinical trial, symptoms were assessed over 3 months in patients with primary knee OA receiving oral vitamin D3 4000 IU/day. Clinical response was evaluated at baseline and 3 months using WOMAC subscores and VAS. Serum levels of cytokines IL-1ß, TNF-α, IL-13, IL-17, IL-33, IL-4, and IL-10 were determined by ELISA method. Eighty patients with knee OA were included. All 80 completed the study; the median 25(OH)D3 level was 23.1 ng/ml at baseline and increased by 12.3 ng/ml after treatment. Vitamin D3 after 3 months of supplementation induced a significant reduction in VAS pain and WOMAC subscores. Using OMERACT-OARSI criteria, 86.7% of patients treated with vitamin D3 responded to treatment. At the end of 3 months, systemic values of IL-1ß (p < 0.01), IL-23 (p < 0.01), and IL-33 (p < 0.01) were significantly increased, values of TNF-α (p < 0.01), IL-13 (p < 0.01), and IL-17 (p < 0.01) were significantly decreased, while value of IL-4 was not significantly changed. No adverse events were detected. Treatment with vitamin D is associated with improvement in pain, as well as stiffness and physical function. Vitamin D supplementation increased systemic values of IL-33. Our results indicate that vitamin D3 supplementation may be used as a novel therapeutic in knee OA. Future studies are needed to investigate a potential role of IL-33 in the pathogenesis of knee OA.

Crystallisation Kinetics and Associated Electrical Conductivity Dynamics of Poly(Ethylene Vinyl Acetate) Nanocomposites in the Melt State.

Nanocomposite systems comprised of a poly(ethylene vinyl acetate) (EVA) matrix and carbon black (CB) or graphene nanoplatelets (GNPs) were used to investigate conductivity and crystallisation dynamics using a commercially relevant melt-state mixing process. Crystallisation kinetics and morphology, as investigated by DSC and SEM, turn out to depend on the interplay of (i) the interphase interactions between matrix and filler, and (ii) the degree of filler agglomeration. For the GNP-based systems, an almost constant conductivity value was observed for all compositions upon cooling, something not observed for the CB-based compositions. These conductivity changes reflect structural and morphological changes that can be associated with positive and negative thermal expansion coefficients. GNP-based systems were observed to exhibit a percolation threshold of approximately 2.2 vol%, lower than the 4.4 vol% observed for the CB-based systems.

Foundations for fairness in digital health apps.

Digital mental health applications promise scalable and cost-effective solutions to mitigate the gap between the demand and supply of mental healthcare services. However, very little attention is paid on differential impact and potential discrimination in digital mental health services with respect to different sensitive user groups (e.g., race, age, gender, ethnicity, socio-economic status) as the extant literature as well as the market lack the corresponding evidence. In this paper, we outline a 7-step model to assess algorithmic discrimination in digital mental health services, focusing on algorithmic bias assessment and differential impact. We conduct a pilot analysis with 610 users of the model applied on a digital wellbeing service called Foundations that incorporates a rich set of 150 proposed activities designed to increase wellbeing and reduce stress. We further apply the 7-step model on the evaluation of two algorithms that could extend the current service: monitoring step-up model, and a popularity-based activities recommender system. This study applies an algorithmic fairness analysis framework for digital mental health and explores differences in the outcome metrics for the interventions, monitoring model, and recommender engine for the users of different age, gender, type of work, country of residence, employment status and monthly income. Systematic Review Registration: The study with main hypotheses is registered at: https://osf.io/hvtf8.

Effects of Combined Allogenic Adipose Stem Cells and Hyperbaric Oxygenation Treatment on Pathogenesis of Osteoarthritis in Knee Joint Induced by Monoiodoacetate.

The beneficial effects of HBO in inflammatory processes make it an attractive type of treatment for chronic arthritis. In addition, the effects of combination therapy based on adipose stem cells and HBO on OA progression have not been fully investigated. The current study explored the efficacy of intra-articular injection of allogeneic adipose-derived mesenchymal stem cells (ADMSCs) combined with hyperbaric oxygenation treatment (HBO) in a rat osteoarthritis (OA) model. The rat OA model was induced by intra-articular injection of monoiodoacetate (MIA) and 7 days after application of MIA rats were divided into five groups: healthy control (CTRL), osteoarthritis (OA), ADMSCs (ADS), the HBO+ADS21day and HBO+ADS28day groups. A single dose of 1 × 106 allogeneic ADMSCs suspended in sterile saline was injected into the knee joint alone or in combination with HBO treatment. Rats were sacrificed at 3 or 4 weeks after MIA injection. Treatment outcomes were evaluated by radiographic, morphological and histological analysis and by specific staining of articular cartilage. We also measured the level of inflammatory and pro/antioxidative markers. We confirmed that combined treatment of ADMSCs and HBO significantly improved the regeneration of cartilage in the knee joint. Rtg score of knee joint damage was significantly decreased in the HBO+ADS21day and HBO+ADS28day groups compared to the OA. However, the positive effect in the HBO+ADS28day group was greater than the HBO+ADS21day group. The articular cartilage was relatively normal in the HBO+ADS28day group, but moderate degeneration was observed in the HBO+ADS21day compared to the OA group. These findings are in line with the histopathological results. A significantly lower level of O2-. was observed in the HBO+ADS28day group but a higher NO level compared to the HBO+ADS21day group. Moreover, in the HBO+ADS28day group significantly higher concentrations of IL-10 were observed but there was no significant difference in proinflammatory cytokine in serum samples. These results indicate that a single intra-articular injection of allogeneic ADMSCs combined with HBO efficiently attenuated OA progression after 28 days with greater therapeutic effect compared to alone ADMSCs or after 3 weeks of combined treatment. Combined treatment might be an effective treatment for OA in humans.

Machine learning model to predict mental health crises from electronic health records.

The timely identification of patients who are at risk of a mental health crisis can lead to improved outcomes and to the mitigation of burdens and costs. However, the high prevalence of mental health problems means that the manual review of complex patient records to make proactive care decisions is not feasible in practice. Therefore, we developed a machine learning model that uses electronic health records to continuously monitor patients for risk of a mental health crisis over a period of 28 days. The model achieves an area under the receiver operating characteristic curve of 0.797 and an area under the precision-recall curve of 0.159, predicting crises with a sensitivity of 58% at a specificity of 85%. A follow-up 6-month prospective study evaluated our algorithm's use in clinical practice and observed predictions to be clinically valuable in terms of either managing caseloads or mitigating the risk of crisis in 64% of cases. To our knowledge, this study is the first to continuously predict the risk of a wide range of mental health crises and to explore the added value of such predictions in clinical practice.

Screening of hydrogen bonds in modified cellulose acetates with alkyl chain substitutions.

This study aimed to elucidate how the glass transition temperature and water interactions in cellulose esters are affected by the structures of their side chains. Cellulose acetate, cellulose acetate propionate and cellulose acetate butyrate with three fractions of butyrates, all having the same total degree of substitution, were selected, and hot-melt pressed. The degree of substitution, structural properties, and water interactions were determined. The Hansen solubility parameters were calculated and showed that the dispersive energy dominates the total cohesive energy, followed by hydrogen bonding and polar energy. The glass transition temperature (Tg) decreased, counter-intuitively, with an increased total cohesive energy, which can be explained by the short-range hydrogen bonds being screened by the increased length of the substituents. The solubility and penetration of water in the cellulose esters decreased with increased side chain length, although the hydrogen bonding energies for all the esters were approximately constant.

The duration of daily activities has no impact on measures of overall wellbeing.

It is widely assumed that the longer we spend in happier activities the happier we will be. In an intensive study of momentary happiness, we show that, in fact, longer time spent in happier activities does not lead to higher levels of reported happiness overall. This finding is replicated with different samples (student and diverse, multi-national panel), measures and methods of analysis. We explore different explanations for this seemingly paradoxical finding, providing fresh insight into the factors that do and do not affect the relationship between how happy we report feeling as a function of how long it lasts. This work calls into question the assumption that spending more time doing what we like will show up in making us happier, presenting a fundamental challenge to the validity of current tools used to measure happiness.

Polysulfide Speciation and Migration in Catholyte Lithium-Sulfur Cells.

Semi-liquid catholyte Lithium-Sulfur (Li-S) cells have shown to be a promising path to realize high energy density energy storage devices. In general, Li-S cells rely on the conversion of elemental sulfur to soluble polysulfide species. In the case of catholyte cells, the active material is added through polysulfide species dissolved in the electrolyte. Herein, we use operando Raman spectroscopy to track the speciation and migration of polysulfides in the catholyte to shed light on the processes taking place. Combined with ex-situ surface and electrochemical analysis we show that the migration of polysulfides is central in order to maximize the performance in terms of capacity (active material utilization) as well as interphase stability on the Li-metal anode during cycling. More specifically we show that using a catholyte where the polysulfides have the dual roles of active material and conducting species, e. g. no traditional Li-salt (such as LiTFSI) is present, results in a higher mobility and faster migration of polysulfides. We also reveal how the formation of long chain polysulfides in the catholyte is delayed during charge as a result of rapid formation and migration of shorter chain species, beneficial for reaching higher capacities. However, the depletion of ionic species during the last stage of charge, due to the conversion to and precipitation of elemental sulfur on the cathode support, results in polarization of the cell before full conversion can be achieved.

Structure and dynamics of highly concentrated LiTFSI/acetonitrile electrolytes.

High salt concentration has been shown to induce increased electrochemical stability in organic solvent-based electrolytes. Accompanying the change in bulk properties is a structural ordering on mesoscopic length scales and changes in the ion transport mechanism have also been suggested. Here we investigate the local structure and dynamics in highly concentrated acetonitrile electrolytes as a function of salt concentration. Already at low concentrations ordering on microscopic length scales in the electrolytes is revealed by small angle X-ray scattering, as a result of correlations of Li+ coordinating clusters. For higher salt concentrations a charge alternation-like ordering is found as anions start to take part in the solvation. Results from quasi-elastic neutron spectroscopy reveal a jump diffusion dynamical process with jump lengths virtually independent of both temperature and Li-salt concentration. The jump can be envisaged as dissociation of a solvent molecule or anion from a particular Li+ solvation structure. The residence time, 50-800 ps, between the jumps is found to be highly temperature and Li-salt concentration dependent, with shorter residence times for higher temperature and lower concentrations. The increased residence time at high Li-salt concentration can be attributed to changes in the interaction of the solvation shell as a larger fraction of TFSI anions take part in the solvation, forming more stable solvation shells.

Real-time imaging of Na+ reversible intercalation in "Janus" graphene stacks for battery applications.

Sodium, in contrast to other metals, cannot intercalate in graphite, hindering the use of this cheap, abundant element in rechargeable batteries. Here, we report a nanometric graphite-like anode for Na+ storage, formed by stacked graphene sheets functionalized only on one side, termed Janus graphene. The asymmetric functionalization allows reversible intercalation of Na+, as monitored by operando Raman spectroelectrochemistry and visualized by imaging ellipsometry. Our Janus graphene has uniform pore size, controllable functionalization density, and few edges; it can store Na+ differently from graphite and stacked graphene. Density functional theory calculations demonstrate that Na+ preferably rests close to -NH2 group forming synergic ionic bonds to graphene, making the interaction process energetically favorable. The estimated sodium storage up to C6.9Na is comparable to graphite for standard lithium ion batteries. Given such encouraging Na+ reversible intercalation behavior, our approach provides a way to design carbon-based materials for sodium ion batteries.

Insight into the Critical Role of Exchange Current Density on Electrodeposition Behavior of Lithium Metal.

Due to an ultrahigh theoretical specific capacity of 3860 mAh g-1, lithium (Li) is regarded as the ultimate anode for high-energy-density batteries. However, the practical application of Li metal anode is hindered by safety concerns and low Coulombic efficiency both of which are resulted fromunavoidable dendrite growth during electrodeposition. This study focuses on a critical parameter for electrodeposition, the exchange current density, which has attracted only little attention in research on Li metal batteries. A phase-field model is presented to show the effect of exchange current density on electrodeposition behavior of Li. The results show that a uniform distribution of cathodic current density, hence uniform electrodeposition, on electrode is obtained with lower exchange current density. Furthermore, it is demonstrated that lower exchange current density contributes to form a larger critical radius of nucleation in the initial electrocrystallization that results in a dense deposition of Li, which is a foundation for improved Coulombic efficiency and dendrite-free morphology. The findings not only pave the way to practical rechargeable Li metal batteries but can also be translated to the design of stable metal anodes, e.g., for sodium (Na), magnesium (Mg), and zinc (Zn) batteries.

Critical Role of Functional Groups Containing N, S, and O on Graphene Surface for Stable and Fast Charging Li-S Batteries.

Lithium-sulfur (Li-S) batteries are considered one of the most promising energy storage technologies, possibly replacing the state-of-the-art lithium-ion (Li-ion) batteries owing to their high energy density, low cost, and eco-compatibility. However, the migration of high-order lithium polysulfides (LiPs) to the lithium surface and the sluggish electrochemical kinetics pose challenges to their commercialization. The interactions between the cathode and LiPs can be enhanced by the doping of the carbon host with heteroatoms, however with relatively low doping content (<10%) in the bulk of the carbon, which can hardly interact with LiPs at the host surface. In this study, the grafting of versatile functional groups with designable properties (e.g., catalytic effects) directly on the surface of the carbon host is proposed to enhance interactions with LiPs. As model systems, benzene groups containing N/O and S/O atoms are vertically grafted and uniformly distributed on the surface of expanded reduced graphene oxide, fostering a stable interface between the cathode and LiPs. The combination of experiments and density functional theory calculations demonstrate improvements in chemical interactions between graphene and LiPs, with an enhancement in the electrochemical kinetics, power, and energy densities.