Polymer self-assembly and thin film deposition in supercritical fluids

Patterning of flexible electronic devices using large-area printing techniques is the focus of intense research due to their promise of producing low-cost, light-weight, and flexible devices. The successful integration of advanced materials like semiconductor nanocrystals, carbon nanotubes and polymer semiconductors into microscale electronic devices requires deposition techniques that are robust, scalable, and enable fine patterning. To this end, we have established a deposition technique that leverages the unique solubility properties of supercritical fluids. The technique is the solution-phase analog of physical vapour deposition and allows thin films of a semiconducting polymer to be grown without the need for in-situ chemical reactions. To demonstrate the flexibility of the technique, we demonstrated precise control over the location of material deposition using a combination of photolithography and resistive heating. The versatility of the technique is demonstrated by creating a patterned film on the concave interior of a silicone hemisphere, a substrate that cannot be patterned via any other technique. More generally, the ability to control the deposition of solution processed materials with lithographic accuracy provides the long sought-after bridge between top-down and bottom-up self-assembly. In addition, we investigated the self-assembly of polymers in supercritical fluids by depositing thin films and studying their morphology using polarized optical microscopy and grazing incidence wide angle x-ray scattering. We summarized our observations with a two-step model for film formation. The first step is pre-aggregation in solution whereby the local crystalline order is established, and the solution turbulence can easily disrupt the solution-phase self-assembly. The second step to film formation is the longer length scale organization that is influenced by the chain mobility on the surface. We identified pressure and solvent additive as two powerful tools to facilitate the local crystalline order and longer length scale organization. The work demonstrated key insights necessary to optimizing thin-film morphologies and principles for understanding self-assembly in supercritical fluids that could be applied to self-assembly of materials in other contexts. Finally, we developed a simple empirical model based on classical thermodynamics that highlights the interplay of intermolecular interactions and solvent entropy and describes both the temperature and pressure dependence of polymer solubility in supercritical fluids

Gamma-Radiolysis Kinetics of Liquid, Vapour and Supercritical Water

Inadequate understanding of radiation-induced water chemistry under supercritical conditions has been identified as one of the important obstacles in the development of a supercritical water-cooled reactor. Radiolysis of supercritical water generates a variety of redox reactive species, but their persistence in supercritical water is not well understood. This thesis describes the work performed towards addressing this deficiency: (1) the development of a reliable experimental method to determine the concentrations of water radiolysis products, primarily H2, O2 and H2O2, formed under g-irradiation of sub- and supercritical water (SCW), (2) the expansion of the application ranges of the existing g-radiolysis kinetic models for liquid water and water vapour to high temperatures and pressures, and (3) the development of the first versions of the supercritical water radiolysis models based on these two models. With each model calculations were performed as a function of temperature and the computational results were analysed to identify the key reactions and reaction parameters that are important in determining the effect of temperature on the net radiolytic production of H2, O2 and H2O2. The results indicate that the model approach that has been taken is promising and worthy of further development

The Relationship between Social Capital and Self-Efficacy in Women with Gestational Diabetes Mellitus: A Cross Sectional Study

BACKGROUND: Self-efficacy is one of the most likely determinants of glucose self-management and self-monitoring by diabetic patients. Also, social capital is one of the effective social factors that may affect health behaviors. The aim of this study was to evaluate the relationship between social capital and selfefficacy in women with gestational diabetes mellitus (GDM).METHODS: This descriptive- analytical cross-sectional study was conducted on 212 women with GDM in two diabetes center in Mazandaran, north of Iran, from April to July 2019. Patients' social capital and self-efficacy levels were measured using the Social Capital Questionnaire (SCQ) and Confidence in Diabetes Self-Care Scale questionnaire, respectively.RESULTS: Among eight dimensions of social capital, the highest and the lowest mean scores were related to proactivity (21.3) and tolerance of diversity (5) dimensions. The mean (standard deviation=SD) of self-efficacy total score was 40.7(18.2), indicating moderate self-efficacy. Pearson correlation coefficient indicated that there was significant positive relationship between all dimensions of social capital and self-efficacy (p˂0.05). In addition, the results of multiple regression analysis indicated that community participation, neighborhood connections, family and friends' connections, tolerance of diversity and work connections, explained 55% of the variance in self-efficacy in women with GDM (p˂0.05).CONCLUSION: The results highlighted a significant positive relationship between social capital and self-efficacy in women with GDM. Improving women’s social capital may enhance their self-efficacy in controlling GDM

Fabrication of an autonomously self-healing flexible thin-film capacitor by slot-die coating

Flexible pressure sensors with self-healing abilities for wearable electronics are being developed, but generally either lack autonomous self-healing properties or require sophisticated material processing methods. To address this challenge, we developed flexible, low-cost and autonomously self-healing capacitive sensors using a crosslinked poly(dimethylsiloxane) through metal-ligand interactions processed into thin films via slot-die coating. These films have excellent self-healing properties, approximately 1.34 × 105 μm3 per hour at room temperature and 2.87 × 105 μm3 per hour at body temperature (37 °C). Similarly, no significant change in capacitance under bending strain was observed on these flexible thin-films when assembled on poly(ethyleneterephthalate) (PET) substrates; capacitors showed good sensitivity at low pressure regimes. More importantly, the devices fully recovered their sensitivity after being damaged and healed, which is directly attributed to the rapid and autonomous self-healing of the dielectric materials

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Polyethylene and Semiconducting Polymer Blends for the Fabrication of Organic Field-Effect Transistors: Balancing Charge Transport and Stretchability

Polyethylene is amongst the most used polymers, finding a plethora of applications in our lives owing to its high impact resistance, non-corrosive nature, light weight, cost effectiveness, and easy processing into various shapes from different sizes. Despite these outstanding features, the commodity polymer has been underexplored in the field of organic electronics. This work focuses on the development of new polymer blends based on a low molecular weight linear polyethylene (LPE) derivative with a high-performance diketopyrrolopyrrole-based semiconducting polymer. Physical blending of the polyethylene with semiconducting polymers was performed at ratios varying from 0 to 75 wt.%, and the resulting blends were carefully characterized to reveal their electronic and solid-state properties. The new polymer blends were also characterized to reveal the influence of polyethylene on the mechanical robustness and stretchability of the semiconducting polymer. Overall, the introduction of LPE was shown to have little to no effect on the solid-state properties of the materials, despite some influence on solid-state morphology through phase separation. Organic field-effect transistors prepared from the new blends showed good device characteristics, even at higher ratios of polyethylene, with an average mobility of 0.151 cm2 V−1 s−1 at a 25 wt.% blend ratio. The addition of polyethylene was shown to have a plasticizing effect on the semiconducting polymers, helping to reduce crack width upon strain and contributing to devices accommodating more strain without suffering from decreased performance. The new blends presented in this work provide a novel platform from which to access more mechanically robust organic electronics and show promising features for the utilization of polyethylene for the solution processing of advanced semiconducting materials toward novel soft electronics and sensors

Polyethylene and Semiconducting Polymer Blends for the Fabrication of Organic Field-Effect Transistors: Balancing Charge Transport and Stretchability

Polyethylene is amongst the most used polymers, finding a plethora of applications in our lives owing to its high impact resistance, non-corrosive nature, light weight, cost effectiveness, and easy processing into various shapes from different sizes. Despite these outstanding features, the commodity polymer has been underexplored in the field of organic electronics. This work focuses on the development of new polymer blends based on a low molecular weight linear polyethylene (LPE) derivative with a high-performance diketopyrrolopyrrole-based semiconducting polymer. Physical blending of the polyethylene with semiconducting polymers was performed at ratios varying from 0 to 75 wt.%, and the resulting blends were carefully characterized to reveal their electronic and solid-state properties. The new polymer blends were also characterized to reveal the influence of polyethylene on the mechanical robustness and stretchability of the semiconducting polymer. Overall, the introduction of LPE was shown to have little to no effect on the solid-state properties of the materials, despite some influence on solid-state morphology through phase separation. Organic field-effect transistors prepared from the new blends showed good device characteristics, even at higher ratios of polyethylene, with an average mobility of 0.151 cm2 V−1 s−1 at a 25 wt.% blend ratio. The addition of polyethylene was shown to have a plasticizing effect on the semiconducting polymers, helping to reduce crack width upon strain and contributing to devices accommodating more strain without suffering from decreased performance. The new blends presented in this work provide a novel platform from which to access more mechanically robust organic electronics and show promising features for the utilization of polyethylene for the solution processing of advanced semiconducting materials toward novel soft electronics and sensors

Visual Saliency and Image Reconstruction from EEG Signals via an Effective Geometric Deep Network-Based Generative Adversarial Network

Reaching out the function of the brain in perceiving input data from the outside world is one of the great targets of neuroscience. Neural decoding helps us to model the connection between brain activities and the visual stimulation. The reconstruction of images from brain activity can be achieved through this modelling. Recent studies have shown that brain activity is impressed by visual saliency, the important parts of an image stimuli. In this paper, a deep model is proposed to reconstruct the image stimuli from electroencephalogram (EEG) recordings via visual saliency. To this end, the proposed geometric deep network-based generative adversarial network (GDN-GAN) is trained to map the EEG signals to the visual saliency maps corresponding to each image. The first part of the proposed GDN-GAN consists of Chebyshev graph convolutional layers. The input of the GDN part of the proposed network is the functional connectivity-based graph representation of the EEG channels. The output of the GDN is imposed to the GAN part of the proposed network to reconstruct the image saliency. The proposed GDN-GAN is trained using the Google Colaboratory Pro platform. The saliency metrics validate the viability and efficiency of the proposed saliency reconstruction network. The weights of the trained network are used as initial weights to reconstruct the grayscale image stimuli. The proposed network realizes the image reconstruction from EEG signals

Epidemiology of psychiatric disorders in children and adolescents 6 -18 yearsold in Kurdistan province in 2016

Background and Aim: Psychiatric disorders in children and adolescents impose high costs on individuals, families and society, and are associated with significant problems in the future. The purpose of this study was to conduct the epidemiological study on psychiatric disorders in children between 6 and 18 years of age in Kurdistan Province in 2016. Material and Method: This cross-sectional study was conducted in Kurdistan Province in 2016. Using random cluster sampling and systematic method, 1016 people were selected and examined for psychiatric disorders by using a digital version of the K-SADS. Result: The results showed that the prevalence of psychiatric disorders in the children and adolescents in Kurdistan Province in 2016 was 33.8% (34.4% of the boys and 33.1% of the girls). Anxiety disorders (21.9%) and behavioral disorders (16.3%) had the highest prevalence rates. Abuse disorders (0.7%) and psychotic disorders (0.9%) had the lowest prevalence rates respectively. The highest prevalence rates belonged to attention deficit hyperactivity disorder (11.6%), oppositional defiant disorder (8.9%) and specific phobia (8.8%) respectively. Autism disorders (0.1%), substance use disorders (0.1%) and incopresis (0.1%) had the lowest prevalence rates. Conclusion: At least 33% of the children and adolescents in Kurdistan Province needed psychiatric outpatient and inpatient services. Awareness of this issue is essential to develop policies on prevention of mental illness, promotion of general health and provision of mental health services to people in Kurdistan Province. We should consider mental disorders of childhood and adolescence as a key risk factor for the future psychiatric problems

Epidemiology of psychiatric disorders in children and adolescents 6 -18 yearsold in Kurdistan province in 2016

Background and Aim: Psychiatric disorders in children and adolescents impose high costs on individuals, families and society, and are associated with significant problems in the future. The purpose of this study was to conduct the epidemiological study on psychiatric disorders in children between 6 and 18 years of age in Kurdistan Province in 2016. Material and Method: This cross-sectional study was conducted in Kurdistan Province in 2016. Using random cluster sampling and systematic method, 1016 people were selected and examined for psychiatric disorders by using a digital version of the K-SADS. Result: The results showed that the prevalence of psychiatric disorders in the children and adolescents in Kurdistan Province in 2016 was 33.8% (34.4% of the boys and 33.1% of the girls). Anxiety disorders (21.9%) and behavioral disorders (16.3%) had the highest prevalence rates. Abuse disorders (0.7%) and psychotic disorders (0.9%) had the lowest prevalence rates respectively. The highest prevalence rates belonged to attention deficit hyperactivity disorder (11.6%), oppositional defiant disorder (8.9%) and specific phobia (8.8%) respectively. Autism disorders (0.1%), substance use disorders (0.1%) and incopresis (0.1%) had the lowest prevalence rates. Conclusion: At least 33% of the children and adolescents in Kurdistan Province needed psychiatric outpatient and inpatient services. Awareness of this issue is essential to develop policies on prevention of mental illness, promotion of general health and provision of mental health services to people in Kurdistan Province. We should consider mental disorders of childhood and adolescence as a key risk factor for the future psychiatric problems