Pervaporation Membranes Based on Polyelectrolyte Complex of Sodium Alginate/Polyethyleneimine Modified with Graphene Oxide for Ethanol Dehydration.

Pervaporation is considered the most promising technology for dehydration of bioalcohols, attracting increasing attention as a renewable energy source. In this regard, the development of stable and effective membranes is required. In this study, highly efficient membranes for the enhanced pervaporation dehydration of ethanol were developed by modification of sodium alginate (SA) with a polyethylenimine (PEI) forming polyelectrolyte complex (PEC) and graphene oxide (GO). The effect of modifications with GO or/and PEI on the structure, physicochemical, and transport characteristics of dense membranes was studied. The formation of a PEC by ionic cross-linking and its interaction with GO led to changes in membrane structure, confirmed by spectroscopic and microscopic methods. The physicochemical properties of membranes were investigated by a thermogravimetric analysis, a differential scanning calorimetry, and measurements of contact angles. The theoretical consideration using computational methods showed favorable hydrogen bonding interactions between GO, PEI, and water, which caused improved membrane performance. To increase permeability, supported membranes without treatment and cross-linked were developed by the deposition of a thin dense layer from the optimal PEC/GO (2.5%) composite onto a developed porous substrate from polyacrylonitrile. The cross-linked supported membrane demonstrated more than two times increased permeation flux, higher selectivity (above 99.7 wt.% water in the permeate) and stability for separating diluted mixtures compared to the dense pristine SA membrane.

Machine Learning Meets Cancer.

The role of machine learning (a part of artificial intelligence-AI) in the diagnosis and treatment of various types of oncology is steadily increasing. It is expected that the use of AI in oncology will speed up both diagnostic and treatment planning processes. This review describes recent applications of machine learning in oncology, including medical image analysis, treatment planning, patient survival prognosis, and the synthesis of drugs at the point of care. The fast and reliable analysis of medical images is of great importance in the case of fast-flowing forms of cancer. The introduction of ML for the analysis of constantly growing volumes of big data makes it possible to improve the quality of prescribed treatment and patient care. Thus, ML is expected to become an essential technology for medical specialists. The ML model has already improved prognostic prediction for patients compared to traditional staging algorithms. The direct synthesis of the necessary medical substances (small molecule mixtures) at the point of care could also seriously benefit from the application of ML. We further review the main trends in the use of artificial intelligence-based technologies in modern oncology. This review demonstrates the future prospects of using ML tools to make progress in cancer research, as well as in other areas of medicine. Despite growing interest in the use of modern computer technologies in medical practice, a number of unresolved ethical and legal problems remain. In this review, we also discuss the most relevant issues among them.

Unraveling the effect of Cu doping on the structural and morphological properties and photocatalytic activity of ZrO2.

Pristine ZrO2 and doped with different concentrations of Copper (0-7 %) were synthesized using a sol-gel combustion route. Several advanced techniques like XRD, EDX, TEM, XPS, P.L., and UV-vis spectrophotometer have characterized the compositions. The XRD proved that all peaks matched with a tetragonal phase of ZrO2 without any impurities of other phases. An average crystallite size rises from 20 to 55 nm by increasing the concentrations of Copper. The elemental analysis was examined by EDX and confirmed the presence of Cooper, Zirconium, and Oxygen. The red shift was observed due to a decrease in the bandgap (5.5-4.01 eV) with increasing the Cu concentrations. From the analysis of photocatalysis of pure ZrO2 and different concentrations of Cu-doped ZrO2 for M.B., RHB, and mix of them. The increase in doping of Cu led to enhancing the performance of the removing MB from 35 to 80 %, however, the RHB degradation was from 42 to 81 % while the mix of M.B. and RHB reached 85 % with 7 % Cu-doping ZrO2.

Structural transition and migration of incoherent twin boundary in diamond.

Grain boundaries (GBs), with their diversity in both structure and structural transitions, play an essential role in tailoring the properties of polycrystalline materials1-5. As a unique GB subset, {112} incoherent twin boundaries (ITBs) are ubiquitous in nanotwinned, face-centred cubic materials6-9. Although multiple ITB configurations and transitions have been reported7,10, their transition mechanisms and impacts on mechanical properties remain largely unexplored, especially in regard to covalent materials. Here we report atomic observations of six ITB configurations and structural transitions in diamond at room temperature, showing a dislocation-mediated mechanism different from metallic systems11,12. The dominant ITBs are asymmetric and less mobile, contributing strongly to continuous hardening in nanotwinned diamond13. The potential driving forces of ITB activities are discussed. Our findings shed new light on GB behaviour in diamond and covalent materials, pointing to a new strategy for development of high-performance, nanotwinned materials.

Nanomaterials and biochar mediated remediation of emerging contaminants.

The unrestricted release of various toxic substances into the environment is a critical global issue, gaining increased attention in modern society. Many of these substances are pristine to various environmental compartments known as contaminants/emerging contaminants (ECs). Nanoparticles and emerging sorbents enhanced remediation is a compelling methodology exhibiting great potential in addressing EC-related issues and facilitating their elimination from the environment, particularly those compounds that demonstrate eco-toxicity and pose considerable challenges in terms of removal. It provides a novel technique enabling the secure and sustainable removal of various ECs, including persistent organic compounds, microplastics, phthalate, etc. This extensive review presents a critical perspective on the current advancements and potential outcomes of nano-enhanced remediation techniques such as photocatalysis, nano-sensing, nano-enhanced sorbents, bio/phyto-remediation, which are applied to clean-up the natural environment. In addition, when dealing with residual contaminants, special attention is paid to both health and environmental implications; therefore, an evaluation of the long-term sustainability of nano-enhanced remediation methods has been considered. The integrated mechanical approaches were thoroughly discussed and presented in graphical forms. Thus, the critical evaluation of the integrated use of most emerging remediation technologies will open a new dimension in environmental safety and clean-up program.

Machine Learning for Quantitative Structural Information from Infrared Spectra: The Case of Palladium Hydride.

Infrared spectroscopy (IR) is a widely used technique enabling to identify specific functional groups in the molecule of interest based on their characteristic vibrational modes or the presence of a specific adsorption site based on the characteristic vibrational mode of an adsorbed probe molecule. The interpretation of an IR spectrum is generally carried out within a fingerprint paradigm by comparing the observed spectral features with the features of known references or theoretical calculations. This work demonstrates a method for extracting quantitative structural information beyond this approach by application of machine learning (ML) algorithms. Taking palladium hydride formation as an example, Pd-H pressure-composition isotherms are reconstructed using IR data collected in situ in diffuse reflectance using CO molecule as a probe. To the best of the knowledge, this is the first example of the determination of continuous structural descriptors (such as interatomic distance and stoichiometric coefficient) from the fine structure of vibrational spectra, which opens new possibilities of using IR spectra for structural analysis.

Single-Stage Microfluidic Synthesis Route for BaGdF5:Tb3+-Based Nanocomposite Materials: Synthesis, Characterization and Biodistribution.

Rare-earth-doped nanoscaled BaGdF5 is known as an efficient contrasting agent for X-ray micro-CT and NMR as well as a promising candidate for X-ray photodynamic therapy, thereby opening an opportunity for theragnostic applications. Conventional synthesis of Ln-doped BaGdF5 consider a long-lasting batch procedure, while a conjugation with photosensitizer usually implies a separate stage requiring active mixing. To the best of our knowledge, in this work, we for the first time obtain BaGdF5:Tb3+ nanophosphors in a microfluidic route at temperatures as low as 100 °C while decreasing the time of thermal treatment down to 6 min. The proposed synthesis route allows for the obtaining of single-phase and monodisperse BaGd1-xF5:Tbx3+ nanoparticles with an averaged particle size of ca. 7-9 nm and hydrodynamic radius around 22 nm, as estimated from TEM and DLS, respectively. In addition, X-ray-excited optical luminescence has been recorded in situ for the series of nanophosphors synthesis with varied flow rates of Tb3+ and Gd3+ stock solutions, thereby anticipating a possible application of microfluidics for screening a wide range of possible co-dopants and reaction conditions and its effect on the optical properties of the synthesized materials. Moreover, we demonstrated that BaGd1-xF5:Tbx3+@RoseBengal conjugates might be obtained in a single-stage route by implementing an additional mixer at the synthesis outcome, namely, by mixing the resulting reaction mixture containing nanoparticles with an equivalent flow of photosensitizer aqueous solution. In vitro cytotoxicity test declares moderate toxicity effect on different cell lines, while the results of flow cytometry indirectly confirm cellular uptake. Finally, we report long-term biodistribution monitoring of the synthesized nanocomposites assessed by X-ray micro-CT in the in vivo experiments on balb/c mice, which depicts an unusual character of agents' accumulation.

A heterostructural MoS2QDs@UiO-66 nanocomposite for the highly efficient photocatalytic degradation of methylene blue under visible light and simulated sunlight.

The development of recyclable photocatalysts with high activity and stability has piqued the interest of researchers in the field of wastewater treatment. In this study, an ultrasonic probe approach was used to immerse a sequence of heterojunctions formed by metal-organic frameworks (UiO-66) and different amounts of molybdenum disulfide quantum dots (MoS2QDs), resulting in a highly recyclable MoS2QDs@UiO-66 photocatalyst. Multiple advanced techniques, such as XPS, XRD, TEM, XRF, and UV-vis spectrophotometry, were used to characterize and confirm the successful preparation of UIO-66 impregnated with MoS2QDs. The results indicated that the best heterostructure catalyst exhibited superior efficiency in the photocatalytic degradation of methylene blue (MB) in water, achieving approximately 99% removal within 30 minutes under simulated sunlight, while approximately 97% removal under visible light. The outstanding photocatalytic performance is predominantly attributed to the photoinduced separation of carriers in this heterostructure system. This study proposes a unique, simple, and low-cost method for improving the degradation performance of organic contaminants in water.

Aldolase of Mytilus galloprovincialis, Lamarck, 1819: Gene structure, tissue specificity of expression level and activity.

In the present study, the structure of the fructose-1,6-bisphosphataldolase (FBA) gene in Mytilus galloprovincialis (Lamarck, 1819) was analyzed and its tissue specificity of expression level and activity was determined. A 1092 base pairs (bps) complete coding sequence of the FBA gene was assembled from M. galloprovincialis transcriptome. Only one gene encoding FBA (MgFBA) was identified in the M. galloprovincialis genome. The length of MgFBA was 363 amino acids with a molecular mass of 39.7 kDa. According to the amino acid residues, the detected MgFBA gene is a type I aldolase. The FBA gene in M. galloprovincialis had 7 exons; the maximum intron length was about 2.5 kbps. Intraspecific nucleotide diversity (15 mutations) between MgFBAs from the Mediterranean mussels and the Black Sea mussels (present study) was detected. All mutations were synonymous. Tissue specificity in FBA expression level and activity was established. No direct correlation between these functions was found. The highest level of FBA gene expression is found in muscle tissue. According to the phylogenetic analyses, FBA gene in invertebrates could be considered the ancestral gene of muscle type aldolase, which may explain the character of tissue-specific expression.

Nanomaterials in biochar: Review of their effectiveness in remediating heavy metal-contaminated soils.

Biochar can be used for soil remediation in environmentally beneficial manner, especially when combined with nanomaterials. After a decade of research, still, no comprehensive review was conducted on the effectiveness of biochar-based nanocomposites in controlling heavy metal immobilization at soil interfaces. In this paper, the recent progress in immobilizing heavy metals using biochar-based nanocomposite materials were reviewed and compared their efficacy against that of biochar alone. In details, an overview of results on the immobilization of Pb, Cd, Cu, Zn, Cr, and As was presented by different nanocomposites made by various biochars derived from kenaf bar, green tea, residual bark, cornstalk, wheat straw, sawdust, palm fiber, and bagasse. Biochar nanocomposite was found to be most effective when combined with metallic nanoparticles (Fe3O4 and FeS) and carbonaceous nanomaterials (graphene oxide and chitosan). This study also devoted special consideration to different remediation mechanisms by which the nanomaterials affect the effectiveness of the immobilization process. The effects of nanocomposites on soil characteristics related to pollution migration, phytotoxicity, and soil microbial composition were assessed. A future perspective on nanocomposites' use in contaminated soils was presented.

Synchrotron-based operando X-ray diffraction and X-ray absorption spectroscopy study of LiCo0.5Fe0.5PO4 mixed d-metal olivine cathode.

Lithium-ion batteries based on high-voltage cathode materials, such as LiCoPO4, despite being promising in terms of specific power, still suffer from poor cycle life due to the lower stability of common non-aqueous electrolytes at higher voltages. One way to overcome this issue might be decreasing the working potential of the battery by doping LiCoPO4 by Fe, thus reducing electrolyte degradation upon cycling. However, such modification requires a deep understanding of the structural behavior of cathode material upon lithiation/delithiation. Here we used a combination of operando synchrotron-based XRD and XAS to investigate the dynamics of d-metal local atomic structure and charge state upon cycling of LiCo0.5Fe0.5PO4 mixed d-metal olivine cathode material. Principal components analysis (PCA) of XAS data allowed the extraction of spectra of individual phases in the material and their concentrations. For both Co and Fe two components were extracted, they correspond to fully lithiated and delithiated phases of LixMPO4 (where M = Fe, Co). Thus, we were able to track the phase transitions in the material upon charge and discharge and quantitatively analyze the M2+/M3+ electrochemical conversion rate for both Fe and Co. Rietveld's refinement of XRD data allowed us to analyze the changes in the lattice of cathode material and their reversibility upon (de)lithiation during cycling. The calculation of DFT and Bader charge analysis expects the oxygen redox procedure combined with d-metals redox, which supplements iron charge variations and dominates at high voltages when x < 0.75 in LixCoFePO4.

Ultrastrong conductive in situ composite composed of nanodiamond incoherently embedded in disordered multilayer graphene.

Traditional ceramics or metals cannot simultaneously achieve ultrahigh strength and high electrical conductivity. The elemental carbon can form a variety of allotropes with entirely different physical properties, providing versatility for tuning mechanical and electrical properties in a wide range. Here, by precisely controlling the extent of transformation of amorphous carbon into diamond within a narrow temperature-pressure range, we synthesize an in situ composite consisting of ultrafine nanodiamond homogeneously dispersed in disordered multilayer graphene with incoherent interfaces, which demonstrates a Knoop hardness of up to ~53 GPa, a compressive strength of up to ~54 GPa and an electrical conductivity of 670-1,240 S m-1 at room temperature. With atomically resolving interface structures and molecular dynamics simulations, we reveal that amorphous carbon transforms into diamond through a nucleation process via a local rearrangement of carbon atoms and diffusion-driven growth, different from the transformation of graphite into diamond. The complex bonding between the diamond-like and graphite-like components greatly improves the mechanical properties of the composite. This superhard, ultrastrong, conductive elemental carbon composite has comprehensive properties that are superior to those of the known conductive ceramics and C/C composites. The intermediate hybridization state at the interfaces also provides insights into the amorphous-to-crystalline phase transition of carbon.

Application of Artificial Intelligence at All Stages of Bone Tissue Engineering.

The development of artificial intelligence (AI) has revolutionized medical care in recent years and plays a vital role in a number of areas, such as diagnostics and forecasting. In this review, we discuss the most promising areas of AI application to the field of bone tissue engineering and prosthetics, which can drastically benefit from AI-assisted optimization and patient personalization of implants and scaffolds in ways ranging from visualization and real-time monitoring to the implantation cases prediction, thereby leveraging the compromise between specific architecture decisions, material choice, and synthesis procedure. With the emphasized crucial role of accuracy and robustness of developed AI algorithms, especially in bone tissue engineering, it was shown that rigorous validation and testing, demanding large datasets and extensive clinical trials, are essential, and we discuss how through developing multidisciplinary cooperation among biology, chemistry with materials science, and AI, these challenges can be addressed.

Synthesis Optimization of BaGdF5:x%Tb3+ Nanophosphors for Tunable Particle Size.

X-ray photodynamic therapy (XPDT) is aimed at the treatment of deep-located malignant tumors thanks to the high penetration depth of X-rays. In XPDT therapy, it is necessary to use materials that effectively absorb X-rays and convert them into visible radiation-nanophosphors. Rare-earth elements, fluorides, in particular, doped BaGdF5, are known to serve as efficient nanophosphor. On the other hand, the particle size of nanophosphors has a crucial impact on biodistribution, cell uptake, and cytotoxicity. In this work, we investigated various Tb:Gd ratios in the range from 0.1 to 0.5 and optimized the terbium content to achieve the maximum luminescence under X-ray excitation. The effect of temperature, composition of the ethylene glycol/water solvent, and the synthesis technique (solvothermal and microwave) on the size of the nanophosphors was explored. It was found that the synthesis techniques and the solvent composition had the greatest influence on the averaged particle size. By varying these two parameters, it is possible to tune the size of the nanophosphor particles, which make them suitable for biomedical applications.

Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System.

In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. In this research, an approach to intelligent decision making based on a data integration strategy to raise awareness of a controlled object is used. In the following article, this approach is considered in the context of reasonable decisions when detecting defects on the surface of welds that arise after the metal pipe welding processes. The main data types were RGB, RGB-D images, and acoustic emission signals. The fusion of such multimodality data, which mimics the eyes and ears of an experienced person through computer vision and digital signal processing, provides more concrete and meaningful information for intelligent decision making. The main results of this study include an overview of the architecture of the system with a detailed description of its parts, methods for acquiring data from various sensors, pseudocodes for data processing algorithms, and an approach to data fusion meant to improve the efficiency of decision making in detecting defects on the surface of various materials.

Glycopolymer-Based Materials: Synthesis, Properties, and Biosensing Applications.

Glycopolymer materials have emerged as a significant biopolymer class that has piqued the scientific community's attention due to their potential applications. Recently, they have been found to be a unique synthetic biomaterial; glycopolymer materials have also been used for various applications, including direct therapeutic methods, medical adhesives, drug/gene delivery systems, and biosensor applications. Therefore, for the next stage of biomaterial research, it is essential to understand current breakthroughs in glycopolymer-based materials research. This review discusses the most widely utilized synthetic methodologies for glycopolymer-based materials, their properties based on structure-function interactions, and the significance of these materials in biosensing applications, among other topics. When creating glycopolymer materials, contemporary polymerization methods allow precise control over molecular weight, molecular weight distribution, chemical activity, and polymer architecture. This review concludes with a discussion of the challenges and complexities of glycopolymer-based biosensors, in addition to their potential applications in the future.

Structural, Electronic, Reactivity, and Conformational Features of 2,5,5-Trimethyl-1,3,2-diheterophosphinane-2-sulfide, and Its Derivatives: DFT, MEP, and NBO Calculations.

In this study, we used density functional theory (DFT) and natural bond orbital (NBO) analysis to determine the structural, electronic, reactivity, and conformational features of 2,5,5-trimethyl-1,3,2-di-heteroatom (X) phosphinane-2-sulfide derivatives (X = O (compound 1), S (compound 2), and Se (compound 3)). We discovered that the features improve dramatically at 6-31G** and B3LYP/6-311+G** levels. The level of theory for the molecular structure was optimized first, followed by the frontier molecular orbital theory development to assess molecular stability and reactivity. Molecular orbital calculations, such as the HOMO-LUMO energy gap and the mapping of molecular electrostatic potential surfaces (MEP), were performed similarly to DFT calculations. In addition, the electrostatic potential of the molecule was used to map the electron density on a surface. In addition to revealing molecules' size and shape distribution, this study also shows the sites on the surface where molecules are most chemically reactive.

Spin transitions in ferric catecholate complexes mediated by outer-sphere counteranions.

A family of ionic ferric catecholate complexes 1-4 bearing a disubstituted 3,6-di-tert-butyl-catecholate ligand (3,6-DBCatH2) and tetradentate tris(2-pyridylmethyl)amine (TPA) was prepared and its spin transitions were investigated. Variation of the outer-sphere counteranions (PF6, BPh4, ClO4, BF4) is accompanied by changes in the magnetic behavior of the compounds under consideration. The crystal structures of complexes 1, 3 and 4 were determined by single crystal X-ray diffraction analysis at 100 K and 293 K. The complexes were characterized by the occurrence of a thermally induced spin-crossover process in the solid state with different degrees of completeness, which was confirmed by the comprehensive spectroscopic investigation (EPR, magnetic susceptibility, Mössbauer, and XAS) of the isolated compounds. Complex 4 containing BF4 anions was found to demonstrate valence tautomeric transition along with spin-crossover. This finding makes compound 4 the first salt-like mononuclear ferric catecholate complex exhibiting valence tautomerism.

Operando Photo-Electrochemical Catalysts Synchrotron Studies.

The attempts to develop efficient methods of solar energy conversion into chemical fuel are ongoing amid climate changes associated with global warming. Photo-electrocatalytic (PEC) water splitting and CO2 reduction reactions show high potential to tackle this challenge. However, the development of economically feasible solutions of PEC solar energy conversion requires novel efficient and stable earth-abundant nanostructured materials. The latter are hardly available without detailed understanding of the local atomic and electronic structure dynamics and mechanisms of the processes occurring during chemical reactions on the catalyst-electrolyte interface. This review considers recent efforts to study photo-electrocatalytic reactions using in situ and operando synchrotron spectroscopies. Particular attention is paid to the operando reaction mechanisms, which were established using X-ray Absorption (XAS) and X-ray Photoelectron (XPS) Spectroscopies. Operando cells that are needed to perform such experiments on synchrotron are covered. Classical and modern theoretical approaches to extract structural information from X-ray Absorption Near-Edge Structure (XANES) spectra are discussed.

Visible-Light-Driven Reduced Graphite Oxide as a Metal-Free Catalyst for Degradation of Colored Wastewater.

Reduced graphite oxide (rGO)-based materials have demonstrated promising potential for advanced oxidation processes. Along with its distinctive 2D characteristics, rGO offers the prospect of catalytic degradation of various kinds of organic pollutants from aqueous environments. The practical application of rGO as a metal-free catalyst material to promote the Fenton reaction depends on the degree of rGO reduction. In this regard, the rGO was prepared according to oxidation by modified Hummers' method and two-step reduction via hydrothermal and calcination in the N2 atmosphere. The as-prepared rGO was characterized in terms of X-ray diffraction, Fourier-transform infrared spectroscopy, thermal gravimetric analysis, scanning electron microscopy, UV-vis absorption spectroscopy, and transmission electron microscopy. The effectiveness of as-prepared rGO as a photocatalyst and the metal-free catalyst to decolorize different textile dyes, including basic red 46, basic red 18, and methylene blue, was investigated in visible/rGO and visible/rGO/H2O2 systems. The impact of operational factors such as catalyst dose, pH, and initial dye concentration was examined. The dye degradation process was investigated by the pseudo-first-order kinetic model. In addition, the recyclability of rGO in the visible/rGO/H2O2 system was examined.