Structure and dynamics of Li1.24K0.76CO3 molten carbonate electrolyte from molecular simulations with explicit polarization.

Molten carbonate electrolysis cells represent a key technology for harnessing surplus energy from renewable sources and converting it into gaseous energy carriers. To optimize their efficiency, a comprehensive understanding of each step in the operational process is essential. Here, we focus on the electrolyte of choice in molten carbonate cells: the Li1.24K0.76CO3 melt. Utilizing molecular dynamics with explicit polarization, we demonstrate that the structure of this molten mixture is characterized by a dense network of lithium-carbonate complexes, with K+ ions loosely embedded within this network. This structural insight enables us to rationalize from an atomistic perspective the conductivity trends observed experimentally in molten carbonates. Moreover, our work highlights the importance of including polarization for the simulations of dense liquid carbonates. It also acts as a foundational step towards more advanced theoretical studies for elucidating the role of the electrolyte in these devices.

Exploring zinc oxide morphologies for aqueous solar cells by a photoelectrochemical, computational, and multivariate approach.

Dye-sensitized solar cells assembled with aqueous electrolytes are emerging as a sustainable photovoltaic technology suitable for safe indoor and portable electronics use. While the scientific community is exploring unconventional materials for preparing electrodes and electrolytes, this work presents the first study on zinc oxide as a semiconductor material to fabricate photoanodes for aqueous solar cells. Different morphologies (i.e., nanoparticles, multipods, and desert roses) are synthesized, characterized, and tested in laboratory-scale prototypes. This exploratory work, also integrated by a computational study and a multivariate investigation on the factors that influence electrode sensitization, confirms the possibility of using zinc oxide in the field of aqueous photovoltaics and opens the way to new morphologies and processes of functionalization or surface activation to boost the overall cell efficiency.

Exotic hexagonal NaCl atom-thin layer on methylammonium lead iodide perovskite: new hints for perovskite solar cells from first-principles calculations.

Alkali halides are simple inorganic compounds extensively used as surface modifiers in optoelectronic devices. In perovskite solar cells (PSCs), they act as interlayers between the light absorber material and the charge selective layers improving their contact quality. They introduce surface dipoles that enable the fine tuning of the relative band alignment and passivate surface defects, a well-known drawback of hybrid organic-inorganic perovskites, that is responsible for most of the issues hampering the long-term performances. Reducing the thickness of such salt-based insulating layer might be beneficial in terms of charge transfer between the perovskite and the electron/hole transport layers. In this context, here we apply density functional theory (DFT) to characterize the structure and the electronic features of atom-thin layers of NaCl adsorbed on the methylammonium lead iodide (MAPI) perovskite. We analyze two different models of MAPI surface terminations and find unexpected structural reconstructions arising at the interface. Unexpectedly, we find an exotic honeycomb-like structuring of the salt, also recently observed in experiments on a diamond substrate. We also investigate how the salt affects the perovskite electronic properties that are key to control the charge dynamics at the interface. Moreover, we also assess the salt ability to improve the defect tolerance of the perovskite surface. With these results, we derive new hints regarding the potential benefits of using an atom-thin layer of alkali halides in PSCs.

A multivariable prediction model for intra-amniotic infection in patients with preterm labor and intact membranes including a point of care system that measures amniotic fluid MMP-8.

OBJECTIVES: Among patients with preterm labor and intact membranes (PTL), those with intra-amniotic infection (IAI) present the highest risk of adverse perinatal outcomes. Current identification of IAI, based on microbiological cultures and/or polymerase chain reaction amplification of the 16S ribosomal RNA gene, delay diagnosis and, consequently, antenatal management. The aim to of the study was to assess the performance of a multivariable prediction model for diagnosing IAI in patients with PTL below 34.0 weeks using clinical, sonographic and biochemical biomarkers. METHODS: From 2019 to 2022, we prospectively included pregnant patients admitted below 34.0 weeks with diagnosis of PTL and had undergone amniocentesis to rule in/out IAI. The main outcome was IAI, defined by a positive culture and/or 16S ribosomal RNA gene in amniotic fluid. Based on the date of admission, the sample (n=98) was divided into a derivation (2019-2020, n=49) and validation cohort (2021-2022, n=49). Logistic regression models were developed for the outcomes evaluated. As predictive variables we explored ultrasound cervical length measurement at admission, maternal C-reactive protein, gestational age, and amniotic fluid glucose and matrix metalloproteinase-8 (MMP-8) levels. The model was developed in the derivation cohort and applied to the validation cohort and diagnostic performance was evaluated. Clinical management was blinded to the model results. RESULTS: During the study period, we included 98 patients admitted with a diagnosis of PTL. Of these, 10 % had IAI. The final model included MMP-8 and amniotic fluid glucose levels and showed an area under the receiver operating characteristic curve to predict the risk of IAI of 0.961 (95 % confidence interval: 0.860-0.995) with a sensitivity of 75 %, specificity of 93.3 %, positive likelihood ratio (LR) of 11.3 and negative LR of 0.27 in the validation cohort. CONCLUSIONS: In patients with PTL, a multivariable prediction model including amniotic fluid MMP-8 and glucose levels might help in the clinical management of patients undergoing amniocentesis to rule in/out IAI, providing results within a few minutes.

Azobenzene-based optoelectronic transistors for neurohybrid building blocks.

Exploiting the light-matter interplay to realize advanced light responsive multimodal platforms is an emerging strategy to engineer bioinspired systems such as optoelectronic synaptic devices. However, existing neuroinspired optoelectronic devices rely on complex processing of hybrid materials which often do not exhibit the required features for biological interfacing such as biocompatibility and low Young's modulus. Recently, organic photoelectrochemical transistors (OPECTs) have paved the way towards multimodal devices that can better couple to biological systems benefiting from the characteristics of conjugated polymers. Neurohybrid OPECTs can be designed to optimally interface neuronal systems while resembling typical plasticity-driven processes to create more sophisticated integrated architectures between neuron and neuromorphic ends. Here, an innovative photo-switchable PEDOT:PSS was synthesized and successfully integrated into an OPECT. The OPECT device uses an azobenzene-based organic neuro-hybrid building block to mimic the retina's structure exhibiting the capability to emulate visual pathways. Moreover, dually operating the device with opto- and electrical functions, a light-dependent conditioning and extinction processes were achieved faithful mimicking synaptic neural functions such as short- and long-term plasticity.

New Insights on Singlet Oxygen Release from Li-Air Battery Cathode: Periodic DFT Versus CASPT2 Embedded Cluster Calculations.

Li-air batteries are a promising energy storage technology for large-scale applications, but the release of highly reactive singlet oxygen (1O2) during battery operation represents a main concern that sensibly limits their effective deployment. An in-depth understanding of the reaction mechanisms underlying the 1O2 formation is crucial to prevent its detrimental reactions with the electrolyte species. However, describing the elusive chemistry of highly correlated species such as singlet oxygen represents a challenging task for state-of-the-art theoretical tools based on density functional theory. Thus, in this study, we apply an embedded cluster approach, based on CASPT2 and effective point charges, to address the evolution of 1O2 at the Li2O2 surface during oxidation, i.e., the battery charging process. Based on recent hypothesis, we depict a feasible O22-/O2-/O2 mechanisms occurring from the (112̅0)-Li2O2 surface termination. Our highly accurate calculations allow for the identification of a stable superoxide as local minimum along the potential energy surface (PES) for 1O2 release, which is not detected by periodic DFT. We find that 1O2 release proceeds via a superoxide intermediate in a two-step one-electron process or another still accessible pathway featuring a one-step two-electron mechanism. In both cases, it represents a feasible product of Li2O2 oxidation upon battery charging. Thus, tuning the relative stability of the intermediate superoxide species can enable key strategies aiming at controlling the detrimental development of 1O2 for new and highly performing Li-air batteries.

First-principles design of nanostructured electrode materials for Na-ion batteries: challenges and perspectives.

Post-lithium batteries are emerging as viable solutions for sustainable energy transition. Effective deployment in the market calls for great research efforts in the identification of novel component materials and the assessment of related working principles. Computational modelling can be a key player in boosting innovation and development by enabling rational strategies for the design of appropriately tuned materials with optimized activity towards battery operating processes. By gaining access to the structural and electronic features of functional electrodes, state-of-the-art DFT methods can unveil the subtle structure-property relationship that affects the uptake, transport, and storage efficiency. Hereby, we aim at reviewing the research status of theoretical advances in the field of Na-ion batteries (NIBs) and illustrating to what extent atomistic insights into sodiation/desodiation mechanisms of nanostructured materials can assist the development of effective anodes and cathodes for stable and highly performing devices. Thanks to increasing computer power and fruitful cooperation between theory and experiments, the route for effective design methodologies is being paved and will feed the upcoming developments in NIB technology.

Development and Validation of a Duplex RT-qPCR for Detection of Peach Latent Mosaic Viroid and Comparison of Different Nucleic-Acid-Extraction Protocols.

Peach latent mosaic viroid (PLMVd) is an important pathogen that causes disease in peaches. Control of this viroid remains problematic because most PLMVd variants are symptomless, and although there are many detection tests in use, the reliability of PCR-based methods is compromised by the complex, branched secondary RNA structure of the viroid and its genetic diversity. In this study, a duplex RT-qPCR method was developed and validated against two previously published single RT-qPCRs, which were potentially able to detect all known PLMVd variants when used in tandem. In addition, in order to simplify the sample preparation, rapid-extraction protocols based on the use of crude sap or tissue printing were compared with commercially available RNA purification kits. The performance of the new procedure was evaluated in a test performance study involving five participant laboratories. The new method, in combination with rapid-sample-preparation approaches, was demonstrated to be feasible and reliable, with the advantage of detecting all different PLMVd isolates/variants assayed in a single reaction, reducing costs for routine diagnosis.

High miR-126-3p levels associated with cardiovascular events in a general population.

BACKGROUND: Endothelial dysfunction is a forerunner of atherosclerosis, leading to cardiovascular disease, and albuminuria is a marker of endothelial dysfunction. Circulating levels of microRNAs are emerging as potential biomarkers for cardiovascular disease. Here we estimate the predictive value of a plasma microRNAs signature associated with albuminuria in the incidence of cardiovascular events. METHODS: Plasma microRNAs quantified in hypertensive patients by next generation sequencing were validated in a cohort of patients and controls by real-time quantitative PCR. The microRNAs found to be associated with albuminuria were analysed for their prognostic value in predicting cardiovascular events incidence on a retrospective, population-based study (Hortega Study), using Cox proportional hazard models. RESULTS: A plasma microRNA profile was identified in the discovery cohort (n = 48) associated with albuminuria and three microRNAs (miR-126-3p, miR-1260b and miR-374a-5p) were confirmed in the validation cohort (n = 98). The microRNA signature discriminates urinary albumin excretion at baseline (n = 1025), and predicts the incidence of cardiovascular events and coronary heart disease and stroke in a general population retrospective study within a 14-year follow-up (n = 926). High miR-126-3p levels were associated with a shorter time free of both cardiovascular events (HR=1.48, (1.36-1.62), p < 0.0001), as well as coronary artery disease and stroke combined (HR=2.49, (2.19-2.83), p < 0.0001). CONCLUSIONS: An increased plasma microRNAs profile was identified in hypertensive patients with albuminuria. Increased miR-126-3p suggest it may serve as a prognostic marker for cardiovascular events in a long-term general population. Further studies will assess the potential role of miR-126-3p as a guide for the status of endothelial dysfunction.

First-principles study of interfacial features and charge dynamics between spiro-MeOTAD and photoactive lead halide perovskites.

The main stability and performance issues of perovskite solar cells arise from the interfaces between the perovskite and the hole transport material. Here we address these interface issues by means of state-of-the-art first-principles calculations, providing new insights into charge transfer times and mechanisms and how they depend on the perovskite chemical composition and local interfacial environment.

Role of Crystalline Si and SiC Species in the Performance of Reduced Hybrid C/Si Gels as Anodes for Lithium-Ion Batteries.

In recent years, the research on lithium-ion batteries (LIBs) to improve their lifetime, efficiency and energy density has led to the use of silicon-based materials as a promising anode alternative to graphite. Specifically, crystalline silicon (cSi) and silicon carbide (SiC) obtained from deposition or reduction processes (e.g., magnesiothermal reduction) stand out for their electrochemical properties. However, the synthesis routes proposed until now have limitations that make them difficult to afford or operate on a large scale. For this reason, in this work, carbon-silicon (C-Si) hybrid materials synthesized through an efficient route are evaluated as the potential precursor for the obtention of both cSi and SiC species in a single material. The feasibility and influence of the magnesiothermal reduction process were evaluated, and materials with 10 wt.% of reduced Si and 10-26 wt.% of SiC were obtained. Both species play a role in the improvement of the performance of silicon-based materials as anodes in lithium-ion batteries. In comparison with materials obtained by the reduction of silica gels and composites, the reduced C-Si hybrid gels stand out thanks to the homogeneous distribution and stability of the species developed.

Noninvasive prediction models of intra-amniotic infection in women with preterm labor.

BACKGROUND: Among women with preterm labor, those with intra-amniotic infection present the highest risk of early delivery and the most adverse outcomes. The identification of intra-amniotic infection requires amniocentesis, perceived as too invasive by women and physicians. Noninvasive methods for identifying intra-amniotic infection and/or early delivery are crucial to focus early efforts on high-risk preterm labor women while avoiding unnecessary interventions in low-risk preterm labor women. OBJECTIVE: This study modeled the best performing models, integrating biochemical data with clinical and ultrasound information to predict a composite outcome of intra-amniotic infection and/or spontaneous delivery within 7 days. STUDY DESIGN: From 2015 to 2020, data from a cohort of women, who underwent amniocentesis to rule in or rule out intra-amniotic infection or inflammation, admitted with a diagnosis of preterm labor at <34 weeks of gestation at the Hospital Clinic and Hospital Sant Joan de Déu, Barcelona, Spain, were used. At admission, transvaginal ultrasound was performed, and maternal blood and vaginal samples were collected. Using high-dimensional biology, vaginal proteins (using multiplex immunoassay), amino acids (using high-performance liquid chromatography), and bacteria (using 16S ribosomal RNA gene amplicon sequencing) were explored to predict the composite outcome. We selected ultrasound, maternal blood, and vaginal predictors that could be tested with rapid diagnostic techniques and developed prediction models employing machine learning that was applied in a validation cohort. RESULTS: A cohort of 288 women with preterm labor at <34 weeks of gestation, of which 103 (35%) had a composite outcome of intra-amniotic infection and/or spontaneous delivery within 7 days, were included in this study. The sample was divided into derivation (n=116) and validation (n=172) cohorts. Of note, 4 prediction models were proposed, including ultrasound transvaginal cervical length, maternal C-reactive protein, vaginal interleukin 6 (using an automated immunoanalyzer), vaginal pH (using a pH meter), vaginal lactic acid (using a reflectometer), and vaginal Lactobacillus genus (using quantitative polymerase chain reaction), with areas under the receiving operating characteristic curve ranging from 82.2% (95% confidence interval, ±3.1%) to 85.2% (95% confidence interval, ±3.1%), sensitivities ranging from 76.1% to 85.9%, and specificities ranging from 75.2% to 85.1%. CONCLUSION: The study results have provided proof of principle of how noninvasive methods suitable for point-of-care systems can select high-risk cases among women with preterm labor and might substantially aid in clinical management and outcomes while improving the use of resources and patient experience.

First-Principles Study of Cu-Based Inorganic Hole Transport Materials for Solar Cell Applications.

Perovskite solar cells (PSCs) and dye-sensitized solar cells (DSCs) both represent promising strategies for the sustainable conversion of sunlight into electricity and fuels. However, a few flaws of current devices hinder the large-scale establishment of such technologies. On one hand, PSCs suffer from instabilities and undesired phenomena mostly linked to the perovskite/hole transport layer (HTL) interface. Most of the currently employed organic HTL (e.g., Spiro-OMeTAD) are supposed to contribute to the perovskite decomposition and to be responsible for charge recombination processes and polarization barriers. On the other hand, power conversion efficiencies (PCEs) of DSCs are still too low to compete with other conversion technologies. Tandem cells are built by assembling p-type and n-type DSCs in a cascade architecture and, since each dye absorbs on a different portion of the solar spectrum, the harvesting window is increased and the theoretical efficiency limit for a single chromophore (i.e., the Shockley-Queisser limit) is overcome. However, such a strategy is hindered by the lack of a p-type semiconductor with optimal photocathode features. Nickel oxide has been, by far, the first-choice inorganic p-type semiconductor for both PV technologies, but its toxicity and non-optimal features (e.g., too low open circuit voltage and the presence of trap states) call for alternatives. Herein, we study of three p-type semiconductors as possible alternative to NiO, namely CuI, CuSCN and Cu2O. To this aim, we compare the structural and electronic features of the three materials by means of a unified theoretical approach based on the state-of-the art density functional theory (DFT). We focus on the calculation of their valence band edge energies and compare such values with those of two widely employed photo-absorbers, i.e., methylammonium lead iodide (MAPI) and the triple cation MAFACsPbBrI in PSCs and P1 and Y123 dyes in DSCs, given that the band alignment and the energy offset are crucial for the charge transport at the interfaces and have direct implications on the final efficiency. We dissect the effect a copper vacancy (i.e., intrinsic p-type doping) on the alignment pattern and rationalize it from both a structural and an electronic perspective. Our data show how defects can represent a crucial degree of freedom to control the driving force for hole injection in these devices.

Electronic structure and interfacial features of triphenylamine- and phenothiazine-based hole transport materials for methylammonium lead iodide perovskite solar cells.

Recently, great research efforts have been devoted to perovskite solar cells (PSCs) leading to sunlight-to-power conversion efficiencies above 25%. However, several barriers still hinder the full deployment of these devices. Critical issues are related to PCE stability and device lifetimes, which could be improved by targeted engineering of the hole transport material (HTM). Indeed, the HTM is not only responsible for transporting holes and preventing direct contact between the photo-active perovskite and the charge collector layer, but it plays important structural and protective roles too. As alternatives to the widely used yet expensive and unstable Spiro-OMeTAD, organic HTMs based on triphenylamine (TPA) and phenothiazine (PTZ) moieties have been proposed. However, their performances in PSC devices, and in particular their interfacial properties with the most popular methylammonium lead iodide perovskite (MAPI) still need investigations to be fully determined. In this framework, here we report a first-principles study on the structural and the electronic properties of a recently designed TPA and PTZ-based HTM (HTM1) and its interface with the MAPI (001) surface, considering both the PbI2- and the MAI-terminations. We also addressed already known HTM molecular systems to allow for a direct comparison with the recently proposed HTM1: we characterized the molecular parameters and the MAPI/HTM interfacial properties for Spiro-OMeTAD, PTZ1, and PTZ2. Our results suggest that good adhesion properties do not ensure effective and efficient MAPI-HTM hole injection. Despite the theoretical good alignment between HTM1 HOMO and MAPI valence band edge, our results for the mutually polarized interface point out the lack of a sufficient driving force for hole transport. While the hole mobility of HTM1 outperforms those of the other HTM molecules, for this HTM molecule, our findings suggest the application of lead halide perovskite compositions other than MAPI, with substituents that lower its valence band maximum potential value.

Unexpected Imidazole Coordination to the Dirhodium Center in a Protein Environment: Insights from X-ray Crystallography and Quantum Chemistry.

X-ray diffraction data demonstrate that the adduct formed upon the reaction of dirhodium(II,II) tetraacetate with RNase A reacts with imidazole, leading to the formation of an unexpected product with the imidazole that binds the dirhodium center at an equatorial site rather than an axial site. The origin of this result has been dissected using quantum-chemical calculations.

Challenges of modeling nanostructured materials for photocatalytic water splitting.

Understanding the water splitting mechanism in photocatalysis is a rewarding goal as it will allow producing clean fuel for a sustainable life in the future. However, identifying the photocatalytic mechanisms by modeling photoactive nanoparticles requires sophisticated computational techniques based on multiscale modeling. In this review, we will survey the strengths and drawbacks of currently available theoretical methods at different length and accuracy scales. Understanding the surface-active site through Density Functional Theory (DFT) using new, more accurate exchange-correlation functionals plays a key role for surface engineering. Larger scale dynamics of the catalyst/electrolyte interface can be treated with Molecular Dynamics albeit there is a need for more generalizations of force fields. Monte Carlo and Continuum Modeling techniques are so far not the prominent path for modeling water splitting but interest is growing due to the lower computational cost and the feasibility to compare the modeling outcome directly to experimental data. The future challenges in modeling complex nano-photocatalysts involve combining different methods in a hierarchical way so that resources are spent wisely at each length scale, as well as accounting for excited states chemistry that is important for photocatalysis, a path that will bring devices closer to the theoretical limit of photocatalytic efficiency.

Genetic variants in obesity-related genes and the risk of osteoporotic fracture. The Hortega Follow-up Study.

BACKGROUND: Osteoporosis and obesity are major public health problems that are closely correlated, as they share various features, including a genetic predisposition. A genetic correlation between obesity and osteoporosis due to the biological common pathways of bone and fat metabolism, which implies pleiotropic genes regulating has been described. The objective of our study was to analyse whether polymorphisms in obesity-related genes modify the risk of osteoporotic bone fracture. METHODS: We studied 575 subjects from the Hortega Study. The subjects were followed-up for 12-14 years. 202 subjects were overweight, 143 obese and 221 had bone fractures. The distribution of 39 genetic variants in 22 obesity-related genes were studied. RESULTS: The results showed a relationship between polymorphisms in the FTO and NEGR1 genes and the susceptibility to osteoporotic fracture. The variant genotype of the rs2568958 NEGR1 polymorphism and the rs6499649, rs3751812, and rs8044769 genetic variants in FTO were associated with susceptibility to bone fracture. In the best of our knowledge, this is the first time that these variants in NEGR1 and FTO genes have been associated with the susceptibility to osteoporotic bone fracture, supporting the hypothesis that the NEGR1 and FTO genes might be candidates for osteoporosis and bone fracture. CONCLUSIONS: In conclusion, this study associates obesity-related polymorphisms in the NEGR1 and FTO genes with osteoporotic bone fracture, reinforcing the hypothesis that obesity and bone metabolism are closely correlated genetically.

Association between genetic variants in oxidative stress-related genes and osteoporotic bone fracture. The Hortega follow-up study.

The most widely accepted etiopathogenesis hypothesis of the origin of osteoporosis and its complications is that they are a consequence of bone aging and other environmental factors, together with a genetic predisposition. Evidence suggests that oxidative stress is crucial in bone pathologies associated with aging. The aim of this study was to determine whether genetic variants in oxidative stress-related genes modified the risk of osteoporotic fracture. We analysed 221 patients and 354 controls from the HORTEGA sample after 12-14 years of follow up. We studied the genotypic and allelic distribution of 53 SNPs in 24 genes involved in oxidative stress. The results showed that being a carrier of the variant allele of the SNP rs4077561 within TXNRD1 was the principal genetic risk factor associated with osteoporotic fracture and that variant allele of the rs1805754 M6PR, rs4964779 TXNRD1, rs406113 GPX6, rs2281082 TXN2 and rs974334 GPX6 polymorphisms are important genetic risk factors for fracture. This study provides information on the genetic factors associated with oxidative stress which are involved in the risk of osteoporotic fracture and reinforces the hypothesis that genetic factors are crucial in the etiopathogenesis of osteoporosis and its complications.

d-Glucose Adsorption on the TiO2 Anatase (100) Surface: A Direct Comparison Between Cluster-Based and Periodic Approaches.

Titanium dioxide (TiO2) has been extensively studied as a suitable material for a wide range of fields including catalysis and sensing. For example, TiO2-based nanoparticles are active in the catalytic conversion of glucose into value-added chemicals, while the good biocompatibility of titania allows for its application in innovative biosensing devices for glucose detection. A key process for efficient and selective biosensors and catalysts is the interaction and binding mode between the analyte and the sensor/catalyst surface. The relevant features regard both the molecular recognition event and its effects on the nanoparticle electronic structure. In this work, we address both these features by combining two first-principles methods based on periodic boundary conditions and cluster approaches (CAs). While the former allows for the investigation of extended materials and surfaces, CAs focus only on a local region of the surface but allow for using hybrid functionals with low computational cost, leading to a highly accurate description of electronic properties. Moreover, the CA is suitable for the study of reaction mechanisms and charged systems, which can be cumbersome with PBC. Here, a direct and detailed comparison of the two computational methodologies is applied for the investigation of d-glucose on the TiO2 (100) anatase surface. As an alternative to the commonly used PBC calculations, the CA is successfully exploited to characterize the formation of surface and subsurface oxygen vacancies and to determine their decisive role in d-glucose adsorption. The results of such direct comparison allow for the selection of an efficient, finite-size structural model that is suitable for future investigations of biosensor electrocatalytic processes and biomass conversion catalysis.