Transient Changes in Cerebral Tissue Oxygen, Glucose, and Temperature by Microstrokes: A Computational Study.

OBJECTIVE: This study focuses on evaluating the disruptions in key physiological parameters during microstroke events to assess their severity. METHODS: A mathematical model was developed to simulate the changes in cerebral tissue pO2, glucose concentration, and temperature due to blood flow interruptions. The model considers variations in baseline cerebral blood flow (CBF), capillary density, and blood oxygen/glucose levels, as well as ambient temperature changes. RESULTS: Simulations indicate that complete blood flow obstruction still allows for limited glucose availability, supporting nonoxidative metabolism and potentially exacerbating lactate buildup and acidosis. Partial obstructions decrease tissue pO2, with minimal impact on glucose level, which can remain almost unchanged or even slightly increase. Reduced CBF, capillary density, or blood oxygen due to aging or disease enhances hypoxia risk at lower obstruction levels, with capillary density having a significant effect on stroke severity by influencing both pO2 and glucose levels. Conditions could lead to co-occurrence of hypoxia/hypoglycemia or hypoxia/hyperglycemia, each worsening outcomes. Temperature effects were minimal in deep brain regions but varied near the skull by 0.2-0.8°C depending on ambient temperature. CONCLUSIONS: The model provides insights into the conditions driving severe stroke outcomes based on estimated levels of hypoxia, hypoglycemia, hyperglycemia, and temperature changes.

The association between health literacy and pedestrian safety behavior among adults: a cross-sectional study.

INTRODUCTION: Pedestrians are considered the most vulnerable and complex road users as human behavior constitutes one of the fundamental reasons for traffic-related incidents involving pedestrians. However, the role of health literacy as a predictor of Pedestrian safety behavior remains underexplored. Therefore, the current study was designed to examine the level of health literacy and its association with the safety behavior of adult pedestrians in the city of Tabriz. METHODS: This cross-sectional analytical study was conducted among individuals aged 18 to 65 years in the metropolitan area of Tabriz from January to April 2023. Data were collected using the HELIA standard questionnaire (Health Literacy Instrument for adults), comprising 33 items across 5 domains (access, reading, understanding, appraisal, decision-making and behavior), as well as the Pedestrian Behavior Questionnaire (PBQ) consisting of 29 items. Data were analyzed using descriptive and analytical statistics (independent t-tests, ANOVA, and Pearson correlation coefficient) via SPSS-22 software. RESULTS: Based on the results, 94% (376 individuals) had excellent health literacy levels, and their safety behavior scores were at a good level. Health literacy and safety behavior were higher among the age group of 31 to 45 years, women, married individuals, those who read books, and individuals with higher education. However, safety behavior showed no significant association with education level (P > 0.05). There was a significant and positive relationship between health literacy and all its domains and pedestrian safety behavior (r = 0.369, P < 0.001). CONCLUSION: This study underscores the significant impact of health literacy on pedestrians' safety behavior. The findings reveal that higher levels of health literacy are associated with better safety behavior among individuals aged 18 to 63. Demographic factors such as age, gender, marital status, and education level also play a role in shaping both health literacy and safety behavior. By recognizing these relationships, interventions can be tailored to improve health literacy levels and promote safer pedestrian practices, ultimately contributing to a healthier and safer community in Tabriz city.

Nanoparticles and nanofiltration for wastewater treatment: From polluted to fresh water.

Water pollution poses significant threats to both ecosystems and human health. Mitigating this issue requires effective treatment of domestic wastewater to convert waste into bio-fertilizers and gas. Neglecting liquid waste treatment carries severe consequences for health and the environment. This review focuses on intelligent technologies for water and wastewater treatment, targeting waterborne diseases. It covers pollution prevention and purification methods, including hydrotherapy, membrane filtration, mechanical filters, reverse osmosis, ion exchange, and copper-zinc cleaning. The article also highlights domestic purification, field techniques, heavy metal removal, and emerging technologies like nanochips, graphene, nanofiltration, atmospheric water generation, and wastewater treatment plants (WWTPs)-based cleaning. Emphasizing water cleaning's significance for ecosystem protection and human health, the review discusses pollution challenges and explores the integration of wastewater treatment, coagulant processes, and nanoparticle utilization in management. It advocates collaborative efforts and innovative research for freshwater preservation and pollution mitigation. Innovative biological systems, combined with filtration, disinfection, and membranes, can elevate recovery rates by up to 90%, surpassing individual primary (<10%) or biological methods (≤50%). Advanced treatment methods can achieve up to 95% water recovery, exceeding UN goals for clean water and sanitation (Goal 6). This progress aligns with climate action objectives and safeguards vital water-rich habitats (Goal 13). The future holds promise with advanced purification techniques enhancing water quality and availability, underscoring the need for responsible water conservation and management for a sustainable future.

Screen-printed Sn-doped TiO2 nanoparticles for photocatalytic dye removal from wastewater: A technological perspective.

TiO2 is widely used as a photocatalyst with a wide band gap, which limited its application. Ion doping and formulating a high-quality screen-printing paste enhance its features. However, the printability of objects for advanced application seems essential nowadays. In this research, the Sn-doped TiO2 nanoparticles were prepared through a sol-gel method followed by calcination at various temperatures of 450 °C, 550 °C, 650 °C, 750 °C, and 850 °C. Screen-printing pastes were prepared with 18 wt% of the synthesized Sn-doped TiO2 nanoparticles to evaluate photocatalytic activity. Finally, the prepared paste with optimum nanoparticle concentration was screen printed onto the microscope glass slides at various printing times (1, 3, and 5 runs) and annealed at 500 °C temperature to investigate the thickness of printed Sn-doped TiO2 nanoparticles effect. The photocatalytic activity and crystal structure of nano Sn-doped-TiO2 were characterized using photoluminescence (PL) spectroscopy and X-ray diffraction (XRD). Transmission electron microscopy (TEM) and scanning electron microscope (SEM) analyses were conducted to investigate the size and morphology of the prepared nanoparticles, respectively. The highest photocatalytic activity for the degradation of methylene blue was obtained at the calcination temperature of 450 °C.

Wastewater reuse in agriculture: Prospects and challenges.

Sustainable water recycling and wastewater reuse are urgent nowadays considering water scarcity and increased water consumption through human activities. In 2015, United Nations Sustainable Development Goal 6 (UN SDG6) highlighted the necessity of recycling wastewater to guarantee water availability for individuals. Currently, wastewater irrigation (WWI) of crops and agricultural land appears essential. The present work overviews the quality of treated wastewater in terms of soil microbial activities, and discusses challenges and benefits of WWI in line with wastewater reuse in agriculture and aquaculture irrigation. Combined conventional-advanced wastewater treatment processes are specifically deliberated, considering the harmful impacts on human health arising from WWI originating from reuse of contaminated water (salts, organic pollutants, toxic metals, and microbial pathogens i.e., viruses and bacteria). The comprehensive literature survey revealed that, in addition to the increased levels of pathogen and microbial threats to human wellbeing, poorly-treated wastewater results in plant and soil contamination with toxic organic/inorganic chemicals, and microbial pathogens. The impact of long-term emerging pollutants like plastic nanoparticles should also be established in further studies, with the development of standardized analytical techniques for such hazardous chemicals. Likewise, the reliable, long-term and extensive judgment on heavy metals threat to human beings's health should be explored in future investigations.

Hydrochar-nanoparticle integration for arsenic removal from wastewater: Challenges, possible solutions, and future horizon.

Arsenic (As) contamination poses a significant threat to human health, ecosystems, and agriculture, with levels ranging from 12 to 75% attributed to mine waste and stream sediments. This naturally element is abundant in Earth's crust and gets released into the environment through mining and rock processing, causing ≈363 million people to depend on As-contaminated groundwater. To combat this issue, introducing a sustainable hydrochar system has achieved a remarkable removal efficiency of over 92% for arsenic through adsorption. This comprehensive review presents an overview of As contamination in the environment, with a specific focus on its impact on drinking water and wastewater. It delves into the far-reaching effects of As on human health, ecosystems, aquatic systems, and agriculture, while also exploring the effectiveness of existing As treatment systems. Additionally, the study examines the potential of hydrochar as an efficient adsorbent for As removal from water/wastewater, along with other relevant adsorbents and biomass-based preparations of hydrochar. Notably, the fusion of hydrochar with nanoparticle-centric approaches presents a highly promising and environmentally friendly solution for achieving the removal of As from wastewater, exceeding >99% efficiency. This innovative approach holds immense potential for advancing the realms of green chemistry and environmental restoration. Various challenges associated with As contamination and treatment are highlighted, and proposed solutions are discussed. The review emphasizes the urgent need to advance treatment technologies, improve monitoring methods, and enhance regulatory frameworks. Looking outlook, the article underscores the importance of fostering research efforts, raising public awareness, and fostering interdisciplinary collaboration to address this critical environmental issue. Such efforts are vital for UN Sustainable Development Goals, especially clean water and sanitation (Goal 6) and climate action (Goal 13), crucial for global sustainability.

Theoretical Encapsulation of Fluorouracil (5-FU) Anti-Cancer Chemotherapy Drug into Carbon Nanotubes (CNT) and Boron Nitride Nanotubes (BNNT).

INTRODUCTION: Chemotherapy with anti-cancer drugs is considered the most common approach for killing cancer cells in the human body. However, some barriers such as toxicity and side effects would limit its usage. In this regard, nano-based drug delivery systems have emerged as cost-effective and efficient for sustained and targeted drug delivery. Nanotubes such as carbon nanotubes (CNT) and boron nitride nanotubes (BNNT) are promising nanocarriers that provide the cargo with a large inner volume for encapsulation. However, understanding the insertion process of the anti-cancer drugs into the nanotubes and demonstrating drug-nanotube interactions starts with theoretical analysis. METHODS: First, interactions parameters of the atoms of 5-FU were quantified from the DREIDING force field. Second, the storage capacity of BNNT (8,8) was simulated to count the number of drugs 5-FU encapsulated inside the cavity of the nanotubes. In terms of the encapsulation process of the one drug 5-FU into nanotubes, it was clarified that the drug 5-FU was more rapidly adsorbed into the cavity of the BNNT compared with the CNT due to the higher van der Waals (vdW) interaction energy between the drug and the BNNT. RESULTS: The obtained values of free energy confirmed that the encapsulation process of the drug inside the CNT and BNNT occurred spontaneously with the free energies of -14 and -25 kcal·mol-1, respectively. DISCUSSION: However, the lower value of the free energy in the system containing the BNNT unraveled more stability of the encapsulated drug inside the cavity of the BNNT comparing the system having CNT. The encapsulation of Fluorouracil (5-FU) anti-cancer chemotherapy drug (commercial name: Adrucil®) into CNT (8,8) and BNNT (8,8) with the length of 20 Å in an aqueous solution was discussed herein applying molecular dynamics (MD) simulation.

Connectionist technique estimates of hydrogen storage capacity on metal hydrides using hybrid GAPSO-LSSVM approach.

The AB2 metal hydrides are one of the preferred choices for hydrogen storage. Meanwhile, the estimation of hydrogen storage capacity will accelerate their development procedure. Machine learning algorithms can predict the correlation between the metal hydride chemical composition and its hydrogen storage capacity. With this purpose, a total number of 244 pairs of AB2 alloys including the elements and their respective hydrogen storage capacity were collected from the literature. In the present study, three machine learning algorithms including GA-LSSVM, PSO-LSSVM, and HGAPSO-LSSVM were employed. These models were able to appropriately predict the hydrogen storage capacity in the AB2 metal hydrides. So the HGAPSO-LSSVM model had the highest accuracy. In this model, the statistical factors of R2, STD, MSE, RMSE, and MRE were 0.980, 0.043, 0.0020, 0.045, and 0.972%, respectively. The sensitivity analysis of the input variables also illustrated that the Sn, Co, and Ni elements had the highest effect on the amount of hydrogen storage capacity in AB2 metal hydrides.

2D Ni2P/N-doped graphene heterostructure as a Novel electrocatalyst for hydrogen evolution reaction: A computational study.

The main prerequisite for designing electrocatalysts with favorable performance is to examine the links between electronic structural features and catalytic activity. In this work, Ni2P as a model electrocatalyst and one of the most potent catalysts for hydrogen evolution reaction (HER) was utilized to develop various Ni2P and carbon-based (graphene and N-doped graphene) heterostructures. The characteristics of such structures (Ni2P, graphene, N-doped graphene, Ni2P/graphene, and Ni2P/N-doped graphene), including binding energies, the projected density of states (PDOS), band structure, charge density difference, charge transfer, Hirshfeld charge analysis, and minimum-energy path (MEP) towards HER were calculated and analyzed by density functional theory (DFT) approach. The coupling energy values of hybrid systems were correlated with the magnitude of charge transfer. The main factors driving a promising water-splitting reaction were explained by the data of PDOS, band structures, and charge analysis, including the inherent electronegativity of the N species alongside shifting the Fermi level toward the conductive band. It was also shown that a significant drop occurs in the HER energy barrier on Ni2P/graphene compared to the pristine Ni2P due to N doping on the graphene layer in the Ni2P/N-doped graphene heterostructure.

Microplastics in water resources: Global pollution circle, possible technological solutions, legislations, and future horizon.

Beneath the surface of our ecosystems, microplastics (MPs) silently loom as a significant threat. These minuscule pollutants, invisible to the naked eye, wreak havoc on living organisms and disrupt the delicate balance of our environment. As we delve into a trove of data and reports, a troubling narrative unfolds: MPs pose a grave risk to both health and food chains with their diverse compositions and chemical characteristics. Nevertheless, the peril extends further. MPs infiltrate the environment and intertwine with other pollutants. Worldwide, microplastic levels fluctuate dramatically, ranging from 0.001 to 140 particles.m-3 in water and 0.2 to 8766 particles.g-1 in sediment, painting a stark picture of pervasive pollution. Coastal and marine ecosystems bear the brunt, with each organism laden with thousands of microplastic particles. MPs possess a remarkable ability to absorb a plethora of contaminants, and their environmental behavior is influenced by factors such as molecular weight and pH. Reported adsorption capacities of MPs vary greatly, spanning from 0.001 to 12,700 µg·g-1. These distressing figures serve as a clarion call, demanding immediate action and heightened environmental consciousness. Legislation, innovation, and sustainable practices stand as indispensable defenses against this encroaching menace. Grasping the intricate interplay between microplastics and pollutants is paramount, guiding us toward effective mitigation strategies and preserving our health ecosystems.

The role of the current waveform in mitigating passivation and enhancing electrocoagulation performance: A critical review.

Electrocoagulation (EC) can be an efficient alternative to existing water and wastewater treatment methods due to its eco-friendly nature, low footprint, and facile operation. However, the electrodes applied in the EC process suffer from passivation or fouling, an issue resulting from the buildup of poorly conducting materials on the electrode surface. Indeed, such passivation gives rise to various operational problems and restricts the practical implementation of EC on a large scale. Therefore, it has been suggested that using pulsed direct current (PDC), alternating pulse current (APC), and sinusoidal alternating current (AC) waveforms in EC as alternatives to conventional direct current (DC) can help mitigate passivation and alleviate its associated detrimental effects. This paper presents a critical review of the impact of the current waveform on the EC process towards the capabilities of the PDC, APC, and AC waveforms in de-passivation and performance enhancement while comparing them to the conventional DC. Additionally, current waveform parameters influencing the surface passivation of electrodes and process efficiency are elaborately discussed. Meanwhile, the performance of the EC process is evaluated under different current waveforms based on pollutant removal efficiency, energy consumption, electrode usage, sludge production, and operating cost. The proper current waveforms for treating various water and wastewater matrices are also explained. Finally, concluding remarks and outlooks for future research are provided.

New insights into the hydrogen evolution reaction using Ni-ZIF8/67-derived electrocatalysts.

One of the present great challenges is finding nonprecious materials characterized by efficient electrocatalytic behavior in order to substitute the expensive platinum-based materials for the purpose of hydrogen evolution reactions (HERs). In this study, ZIF-67 and ZIF-67 were used as precursors in order to fabricate metallic-doped N-enriched carbon successfully through a simple process of pyrolysis for applying the hydrogen evolution reaction. In addition, nickel was added to these structures in the course of the synthesis procedure. While under high-temperature treatment, Nickel doped ZIF-67 was transformed into metallic NiCo doped N enriched carbon (NiCo/NC), under high-temperature treatments, Ni-doped ZIF-8 changed into metallic NiZn doped N enriched carbon (NiZn/NC). By combining metallic precursors, the following five structures were synthesized: NiCo/NC, Co/NC, NiZn/NC, NiCoZn/NC, as well as CoZn/NC. It is noteworthy that the produced Co/NC shows optimum hydrogen evolution reaction activity along with superior overpotential of 97 mV and the minimum Tafel slope of 60 mV/dec at 10 mA cm. In addition, the superb behavior of hydrogen evolution reaction can be attributable to the numerous active sites, the superior electrical conductivity of carbon, and the firm structure. As a result, the present paper suggests a novel strategy in order to produce nonprecious materials characterized by superb HER efficiency for future scholars.

Fabrication of the PES Membrane Embedded with Plasma-Modified Zeolite at Different O2 Pressures.

In this research, the non-thermal glow discharge plasma process was implemented to modify the surface of natural clinoptilolite zeolite before incorporation into the polyethersulfone (PES) membrane. The influence of plasma gas pressure variation on the fouling resistance and separation performance of the prepared membranes was studied. Fourier transform infrared, field emission scanning electron microscopy, and X-ray diffraction analyses of the unmodified and modified clinoptilolites revealed the Si-OH-Al bond's development during plasma treatment and the change in surface characteristics. In terms of performance, increasing the plasma gas pressure during clinoptilolite treatment resulted in the twofold enhancement of water flux from 91.2 L/m2 h of bare PES to 188 L/m2 h of the membrane containing plasma-treated clinoptilolite at 1.0 Torr pressure. Meanwhile, the antifouling behavior of membranes was improved by introducing more hydrophilic functional groups derived from the plasma treatment process. Additionally, the enhanced dye separation of membranes was indicated by the separation of 99 and 94% of reactive green 19 and reactive red 195, respectively.

Nickel sulfide and phosphide electrocatalysts for hydrogen evolution reaction: challenges and future perspectives.

The search for environmentally friendly and sustainable energy sources has become necessary to alleviate the issues associated with the consumption of fossil fuel such as air pollution and global warming. Furthermore, this is significant considering the exhaustible resources and burgeoning energy demand globally. In this regard, hydrogen, a clean fuel with high energy density, is considered a reliable alternative energy source. The hydrogen evolution reaction (HER) is one of the most promising methods to produce green hydrogen from water on a large scale. However, the HER needs effective electrocatalysts to address the concerns of energy consumption; thus, finding active materials has recently been the main focus of researchers. Among the various electrocatalysts, nickel sulfides and phosphides and their derivatives with low cost, high abundance, and relatively straightforward preparation have shown high HER activity. In this review, we compare the diverse methods in the synthesis of nickel sulfides and phosphides together with effective synthesis parameters. Also, the optimum conditions for the preparation of the desired active materials and their properties are provided. Then, the performance of nickel sulfide and phosphide electrocatalysts in the HER is addressed. The HER activity of the various crystalline phases is compared, and their most active crystalline phases are introduced. Finally, the present challenges and perspectives for future HER electrocatalysts are presented.

Hydrogenation of pyrolysis gasoline by novel Ni-doped MOF derived catalysts from ZIF-8 and ZIF-67.

Pyrolysis gasoline is the valuable byproduct of the thermal breakdown of heavier oil fractions in an olefin unit with high aromatic content. To separate such aromatic components, firstly, this product should be hydrogenated. In this contribution, new nanostructure catalysts derived from the zeolitic metal-organic framework, namely ZIF-8 and ZIF-67, were used to investigate their hydrogenation capability. Owing to its great hydrogenation capability of Nickle, the structures of the ZIF-8 and ZIF-67 were improved by Nickle through in situ synthesis. Moreover, to enhance the pore size of catalysts and their electronic properties, the synthesized catalysts were pyrolyzed under nitrogen media at 450 °C, and five catalysts, namely Co/NC, ZnCo/NC, ZnNi/NC, CoNi/NC, and ZnCoNi/NC were created. Results indicated that the CoNi/NC showed a superior hydrogenation performance (69.5% conversion of total olefins) to others. In addition, the synthesized catalysts without the carbonization process had no conversion in the hydrogenation process because there is no active site in these structures. The current synthesized catalysts can compete with the costly Pt or Pd-based hydrogenation catalysts due to their high surface area and great electronic properties.

An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique.

Tetracyclines (TCs) have been extensively used for humans and animal diseases treatment and livestock growth promotion. The consumption of such antibiotics has been ever-growing nowadays due to various bacterial infections and other pathologic conditions, resulting in more discharge into the aquatic environments. This brings threats to ecosystems and human bodies. Up to now, several attempts have been made to reduce TC amounts in the wastewater, among which photocatalysis, an advanced oxidation process, is known as an eco-friendly and efficient technology. In this regard, metal organic frameworks (MOFs) have been known as the promising materials as photocatalysts. Thus, studying TC photocatalytic degradation by MOFs would help scientists and engineers optimize the process in terms of effective parameters. Nevertheless, the costly and time-consuming experimental methods, having instrumental errors, encouraged the authors to use the computational method for a more comprehensive assessment. In doing so, a wide-ranging databank including 374 experimental data points was gathered from the literature. A powerful machine learning method of Gaussian process regression (GPR) model with four kernel functions was proposed to estimate the TC degradation in terms of MOFs features (surface area and pore volume) and operational parameters (illumination time, catalyst dosage, TC concentration, pH). The GPR models performed quite well, among which GPR-Matern model shows the most accurate performance with R2, MRE, MSE, RMSE, and STD of 0.981, 12.29, 18.03, 4.25, and 3.33, respectively. In addition, an analysis of sensitivity was carried out to assess the effect of the inputs on the TC photodegradation by MOFs. It revealed that the illumination time and the surface area play a significant role in the decomposition activity.

Intelligent route to design efficient CO2 reduction electrocatalysts using ANFIS optimized by GA and PSO.

Recently, electrochemical reduction of CO2 into value-added fuels has been noticed as a promising process to decrease CO2 emissions. The development of such technology is strongly depended upon tuning the surface properties of the applied electrocatalysts. Considering the high cost and time-consuming experimental investigations, computational methods, particularly machine learning algorithms, can be the appropriate approach for efficiently screening the metal alloys as the electrocatalysts. In doing so, to represent the surface properties of the electrocatalysts numerically, d-band theory-based electronic features and intrinsic properties obtained from density functional theory (DFT) calculations were used as descriptors. Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. The developed ANFIS-PSO and ANFIS-GA showed excellent performance with RMSE of 0.0411 and 0.0383, respectively, the minimum errors reported so far in this field. Additionally, the sensitivity analysis showed that the center and the filling of the d-band are the most determining parameters for the electrocatalyst surface reactivity. The present study conveniently indicates the potential and value of machine learning in directing the experimental efforts in alloy system electrocatalysts for CO2 reduction.

Estimating hydrogen absorption energy on different metal hydrides using Gaussian process regression approach.

Hydrogen is a promising alternative energy source due to its significantly high energy density. Also, hydrogen can be transformed into electricity in energy systems such as fuel cells. The transition toward hydrogen-consuming applications requires a hydrogen storage method that comes with pack hydrogen with high density. Among diverse methods, absorbing hydrogen on host metal is applicable at room temperature and pressure, which does not provide any safety concerns. In this regard, AB2 metal hydride with potentially high hydrogen density is selected as an appropriate host. Machine learning techniques have been applied to establish a relationship on the effect of the chemical composition of these hosts on hydrogen storage. For this purpose, a data bank of 314 data point pairs was used. In this assessment, the different A-site and B-site elements were used as the input variables, while the hydrogen absorption energy resulted in the output. A robust Gaussian process regression (GPR) approach with four kernel functions is proposed to predict the hydrogen absorption energy based on the inputs. All the GPR models' performance was quite excellent; notably, GPR with Exponential kernel function showed the highest preciseness with R2, MRE, MSE, RMSE, and STD of 0.969, 2.291%, 3.909, 2.501, and 1.878, respectively. Additionally, the sensitivity of analysis indicated that ZR, Ti, and Cr are the most demining elements in this system.

Heat transfer through hydrogenated graphene superlattice nanoribbons: a computational study.

Optimization of thermal conductivity of nanomaterials enables the fabrication of tailor-made nanodevices for thermoelectric applications. Superlattice nanostructures are correspondingly introduced to minimize the thermal conductivity of nanomaterials. Herein we computationally estimate the effect of total length and superlattice period ([Formula: see text]) on the thermal conductivity of graphene/graphane superlattice nanoribbons using molecular dynamics simulation. The intrinsic thermal conductivity ([Formula: see text]) is demonstrated to be dependent on [Formula: see text]. The [Formula: see text] of the superlattice, nanoribbons decreased by approximately 96% and 88% compared to that of pristine graphene and graphane, respectively. By modifying the overall length of the developed structure, we identified the ballistic-diffusive transition regime at 120 nm. Further study of the superlattice periods yielded a minimal thermal conductivity value of 144 W m-1 k-1 at [Formula: see text] = 3.4 nm. This superlattice characteristic is connected to the phonon coherent length, specifically, the length of the turning point at which the wave-like behavior of phonons starts to dominate the particle-like behavior. Our results highlight a roadmap for thermal conductivity value control via appropriate adjustments of the superlattice period.

Crystalline polysaccharides: A review.

The biodegradability and mechanical properties of polysaccharides are dependent on their architecture (linear or branched) as well as their crystallinity (size of crystals and crystallinity percent). The amount of crystalline zones in the polysaccharide significantly governs their ultimate properties and applications (from packaging to biomedicine). Although synthesis, characterization, and properties of polysaccharides have been the subject of several review papers, the effects of crystallization kinetics and crystalline domains on the properties and application have not been comprehensively addressed. This review places focus on different aspects of crystallization of polysaccharides as well as applications of crystalline polysaccharides. Crystallization of cellulose, chitin, chitosan, and starch, as the main members of this family, were discussed. Then, application of the aforementioned crystalline polysaccharides and nano-polysaccharides as well as their physical and chemical interactions were overviewed. This review attempts to provide a complete picture of crystallization-property relationship in polysaccharides.