Thermomechanically Resilient Polyionic Elastomers with Enhanced Anti-Icing Performances.

Anti-icing gels inhibit ice formation and accretion; however, current iterations face prevalent drawbacks such as poor strength, weak substrate adhesion, and limited anti-icing properties. Herein, we propose a novel approach to address these challenges by developing a thermomechanical robust polyionic elastomer (PIE) with enhanced anti-icing properties. The PIE surface exhibits an icing delay time up to 5400 s and remains frost-free after exposure to -10 °C for 3.5 h, attributed to the inhibitory effect on ice formation by ions from ILs and the polyelectrolyte network. Moreover, the PIE exhibits remarkable anti-icing durability, with ice adhesion strengths below 35 kPa after undergoing 30 icing/deicing cycle tests at -20 °C. Following sandpaper abrasion (300 cycles), scratching, and heat treatment (100 °C, 16 h), the adhesion strength remains ca. 20 kPa, highlighting its resilience under various thermal and mechanical conditions. This exceptional durability is attributed to the low volatility of the IL and the robust ionic interactions within the PIE network. Furthermore, the PIE demonstrates favorable self-healing properties and strong substrate adhesion in both low-temperature and ambient environments, facilitated by the abundance of hydrogen bonds and electrostatic forces within PIE. This work presents an innovative approach to developing high-performance, durable, and robust anti-icing materials with potential implications across various fields.

Insights into the mechanical stability of tetrahydrofuran hydrates from experimental, machine learning, and molecular dynamics perspectives.

Natural gas hydrates (NGHs) hold immense potential as a future energy resource and for sustainable applications such as gas capture and storage. Due to the challenging formation conditions, however, their mechanical properties remain poorly understood. Herein, the mechanical characteristics of tetrahydrofuran (THF) hydrates, a proxy for methane hydrates, were investigated at different ice contents, strain rates, and temperatures using uniaxial compressive experiments. The results unveil a distinct behavior in the peak strength of THF hydrates with a varying ice content, strain rate and temperature, exhibiting an increase as the strain rate and temperature decrease, in contrast to the peak strength-strain rate relationship observed in polycrystalline ice. Based on the experimental data, four machine learning (ML) models including extreme gradient boosting (XGboost), multilayer perceptron (MLP), gradient boosting decision tree (GBDT) and decision tree (DT) were developed to predict the peak strength. The XGboost model demonstrates superior predictive performance, emphasizing the significant influence of ice content and temperature on the peak strength of hydrates. Furthermore, molecular dynamics (MD) simulations were employed to gain insights into the dissociation and formation processes of clathrate cages, as well as phase transitions and amorphization occurring at grain boundaries (GBs) involving diverse unconventional clathrate cages, including 51265, 4151062, 4151064, 425861 and 425862, with 425861 and 425862 cages being predominant. This study enhances our understanding of the mechanical properties and deformation mechanisms of hydrates and provides a ML-based predictive framework for estimating the compressive strength of hydrates under diverse coupling conditions. The findings have significant implications for stability assessments of NGHs and the exploitation of NGH resources.

Multifunctional Anti-Icing Gel Surface with Enhanced Durability.

Materials with low ice adhesion and long-lasting anti-icing properties remain an ongoing challenge in ultralow temperature environments (≤-30 °C). This study presents a gel material consisting of a polymer matrix (copolymer of polyurethane and acrylamide) and an anti-icing agent, ethylene glycol (EG), designed for anti-icing applications at ultralow temperatures. The surface shows a prolonged droplet freezing delay of ca. 322 s at -30 °C and frost resistance properties. It also exhibits an ice adhesion strength of 1.1 kPa at -10 °C and 39.8 kPa at -50 °C, resulting from the interaction between EG and water molecules that hinders the crystallization of ice as well as the significant mismatch between elastic gel and ice. In addition, the gel surface exhibits favorable anti-icing durability, with an ice adhesion strength below 20.0 kPa after 25 icing/deicing cycles and mechanical scratch tests. The gel demonstrates remarkable thermal durability, achieved through the H-bonds between the EG and polymer matrix. The H-bonds further enhance the anti-icing performance, thereby remarkably decreasing EG depletion and improving anti-icing durability. Overall, these properties suggest the potential application of this gel material in harsh environments including polar regions.

Thermal conductivity of fivefold twinned silicon-germanium heteronanowires.

The thermal transport properties of five-fold twinned (5FT) germanium-silicon (Ge-Si) heteronanowires (h-NWs) with varying cross-sectional areas, germanium (Ge) domain ratios and heterostructural patterns are investigated using homogeneous nonequilibrium molecular dynamics (HNEMD) simulations. The results demonstrate a distinctive behavior in the thermal conductivity (κ) of 5FT-NWs, characterized by a "flipped" trend at a critical cross-sectional area. This behavior is attributed to the hydrodynamic phonon flow, arising from the normal three-phonon scattering process in the low-frequency region. In addition, the composition ratio of 5FT-NWs has a significant impact on reducing the κ of 5FT-NWs and suppressing the hydrodynamic effect. Intriguingly, as the homogeneous element domains are separated, stronger phonon hydrodynamic flows are observed in comparison to the adjacent homogeneous element domains. By analyzing various phonon properties, including phonon dispersion, three-phonon scattering rate, and phonon mean free path, critical insights into the origin of the differential κ in different 5FT-NW structures are provided. The findings deepen the understanding of the thermal transport properties of nanomaterials and hold implications for the design and development of nanoelectronics and thermoelectric devices.

Predicting mechanical properties of CO2hydrates: machine learning insights from molecular dynamics simulations.

Understanding the mechanical properties of CO2hydrate is crucial for its diverse sustainable applications such as CO2geostorage and natural gas hydrate mining. In this work, classic molecular dynamics (MD) simulations are employed to explore the mechanical characteristics of CO2hydrate with varying occupancy rates and occupancy distributions of guest molecules. It is revealed that the mechanical properties, including maximum stress, critical strain, and Young's modulus, are not only affected by the cage occupancy rate in both large 51262and small 512cages, but also by the distribution of guest molecules within the cages. Specifically, the presence of vacancies in the 51262large cages significantly impacts the overall mechanical stability compared to 512small cages. Furthermore, four distinct machine learning (ML) models trained using MD results are developed to predict the mechanical properties of CO2hydrate with different cage occupancy rates and cage occupancy distributions. Through analyzing ML results, as-developed ML models highlight the importance of the distribution of guest molecules within the cages, as crucial contributor to the overall mechanical stability of CO2hydrate. This study contributes new knowledge to the field by providing insights into the mechanical properties of CO2hydrates and their dependence on cage occupancy rates and cage occupancy distributions. The findings have implications for the sustainable applications of CO2hydrate, and as-developed ML models offer a practical framework for predicting the mechanical properties of CO2hydrate in different scenarios.

Positioning System of Infrared Sensors Based on ZnO Thin Film.

Infrared sensors incorporating suspended zinc oxide (ZnO) pyroelectric films and thermally insulated silicon substrates are fabricated using conventional MEMS-based thin-film deposition, photolithography, and etching techniques. The responsivity of the pyroelectric film is improved via annealing at 500 °C for 4 h. The voltage response of the fabricated sensors is evaluated experimentally for a substrate thickness of 1 µm over a sensing range of 30 cm. The results show that the voltage signal varies as an inverse exponential function of the distance. A positioning system based on three infrared sensors is implemented in LabVIEW. It is shown that the position estimates obtained using the proposed system are in excellent agreement with the actual locations. In general, the results presented in this study provide a useful source of reference for the further development of MEMS-based pyroelectric infrared sensors.

Aripiprazole combined with nerve growth factor improves cognitive function in mice with schizophrenia model.

The pathogenesis and treatment of cognitive dysfunction in patients with schizophrenia (SCZ) remains a challenge. Exploring new effective treatment strategies is relevant for the improvement of cognitive function. Aripiprazole (ARI) is an atypical antipsychotic that improves some cognitive functions. Nerve growth factor (NGF) has been shown to improve cognitive function in certain neurological impairments and partial neurological deficits, but its mechanism of action in cognitive dysfunction in SCZ is unclear. In this study, we established schizophrenia mouse model with dizocilpine (MK-801); treated mice with ARI alone or in combination with NGF; assessed spontaneous activity and cognitive function using open field test and Morris water maze test; and measured brain-derived neurotrophic factor (BDNF) protein and mRNA expression levels using immunohistochemistry and molecular biology assays. The results showed that ARI alone or in combination with NGF can improve increased spontaneous activity and spatial learning memory deficits in model mice by elevating BDNF expression levels in prefrontal cortex (PFC) and hippocampus (HIP). The results suggest that ARI combined with NGF can improve cognitive function in SCZ, which provides new ideas and directions for the clinical treatment of cognitive dysfunction in SCZ.

Study on correlations of BDNF, PI3K, AKT and CREB levels with depressive emotion and impulsive behaviors in drug-naïve patients with first-episode schizophrenia.

BACKGROUND: The pathogenesis of schizophrenia is still unknown. Nearly a half of schizophrenic patients have depressive symptoms and even some impulsive behaviors. The definite diagnosis of schizophrenia is an immense challenge. Molecular biology plays an essential role in the research on the pathogenesis of schizophrenia. OBJECTIVE: This study aims to analyze the correlations of serum protein factor levels with depressive emotion and impulsive behaviors in drug-naïve patients with first-episode schizophrenia. METHODS: Seventy drug-naïve patients with first-episode schizophrenia and sixty-nine healthy volunteers from the health check center in the same period participated in this study. In both the patient group and control group, brain-derived neurotrophic factor (BDNF), phosphatidylin-ositol-3-kinase (PI3K), protein kinase B (AKT), and cAMP-response element binding protein (CREB) levels in the peripheral blood were tested by enzyme-linked immunosorbent assay (ELISA). The depressive emotion and impulsive behaviors were evaluated with Chinese versions of the Calgary Depression Scale for Schizophrenia (CDSS) and Short UPPS-P Impulsive Behavior Scale (S-UPPS-P), respectively. RESULTS: The serum levels of BDNF, PI3K, and CREB in the patient group were lower than those in the control group, while AKT level, total CDSS score and total S-UPPS-P score were all higher. In the patient group, total CDSS score, and total S-UPPS-P score were both correlated negatively with BDNF, PI3K, and CREB levels but positively with AKT level, and the lack-of-premeditation (PR) sub-scale score was not significantly correlated with BDNF, PI3K, AKT, and CREB levels. CONCLUSION: Our study results showed that the peripheral blood levels of BDNF, PI3K, AKT, and CREB in drug-naïve patients with first-episode schizophrenia were significantly different from those in the control group. The levels of these serum protein factors are promising biomarkers to predict schizophrenic depression and impulsive behaviors.

Telotristat Etiprate alleviates rheumatoid arthritis by targeting LGALS3 and affecting MAPK signaling.

Rheumatoid arthritis (RA) is one of the most widespread chronic immune-mediated inflammatory diseases characterized by continuous erosion of bone and cartilage by synovial hyperplasia. Telotristat Etiprate is an inhibitor of tryptophan hydroxylase, a rate-limiting enzyme in the biosynthesis of serotonin. Telotristat Etiprate can be used in the treatment of carcinoid syndrome. The purpose of this study was to explore the effect of Telotristat Etiprate on RA and its mechanism. We investigated Telotristat Etiprate in collagen-induced arthritis (CIA) model mice and in rheumatoid arthritis synovial fibroblasts (RASFs). Results showed that Telotristat Etiprate had anti-inflammatory effects both in vitro and in vivo, can inhibit the invasion and migration of cells, inhibit the formation of pannus, and induce cell apoptosis. Transcriptome sequencing (RNA-seq) and mass spectrometry analysis showed that Galectins-3 (LGALS3) could be a newly identified target of Telotristat Etiprate, affecting the phosphorylation of the MAPK signaling pathway through UBE2L6, thereby improving RA.

Interfacial mechanical properties of tetrahydrofuran hydrate-solid surfaces: Implications for hydrate management.

Understanding the interfacial mechanical properties between hydrate and solids is vital to designing and fabricating surfaces for hydrate management. Herein, the role of the surface wettability, the type of solid substrate and temperature on the interfacial adhesion properties of tetrahydrofuran (THF) hydrate and ice were examined by force analysis based shearing measurements and molecular dynamics (MD) simulations. The results showed that the adhesion strength of THF hydrate and ice on silica varies with the compositions of coating, and the adhesion strength of ice is larger than that of THF hydrate for all investigated solid substrates. Particularly, in contrast to a linear relationship between 1 + cosθr and hydrate adhesion on organic silanes/thiols/polymer surfaces, the hydrate adhesion on the coated inorganic glass surfaces is enhanced as a function of 1 + cosθr, in which θr is the receding contact angle. MD simulations uncovered that the adhesion strength of ice on solid substrates is dominated by the quasi-liquid water layer, however, that of hydrate is governed not only by the quasi-liquid layer but also newly formed unconventional clathrate cages. This study provides new insights and perspectives into the hydrate adhesion on solid surfaces, which is of help to develop hydrate-phobic coatings for advanced hydrate management.

Isotope doping-induced crossover shift in the thermal conductivity of thin silicon nanowires.

Here, using homogeneous nonequilibrium molecular dynamics simulations, we report the thermal transport characteristics of thin Si nanowires (NWs) with varying size and isotope doping ratio. It is identified that crossover in the thermal conductivity (κ) of both isotope doping-free and isotope doped Si-NWs appears at critical sizes, below whichκis enlarged with decreasing size because the hydrodynamic phonon flow predominates, above which, due to the dominant phonon boundary scattering, opposite behavior is observed. With increasing isotope doping, however, the critical size in minimizing theκis moved to small values because the phonon impurity scattering caused by isotope doping is critically involved. Moreover, there is a critical isotope doping (<50%) in the critical size motion, originating from that, above which, the critical size no longer moves due to the persistence of hydrodynamic phonon flow. This study provides new insights into the thermal transport behaviors of quasi-1D structures.

Size-dependent melting of onion-like fullerenic carbons: a molecular dynamics and machine learning study.

The melting thermodynamic characteristics of 2- to 20-layered onion-like fullerenes (OLFn) (C60@C240to C60@···@C6000···@C24000) are comprehensively explored using first-principles-based ReaxFF atomistic simulations and random forest machine learning (RF ML). It is revealed that OLFnshows lower thermal stability than the counterparts of single-walled fullerenes (SWFn). The melting point of SWFnincreases monotonically with increasing size, whereas for OLFn, an unusual size-dependent melting point is observed; OLFnwith intermediate size shows the highest melting point. For small OLFn, the melting occurs from the inner to the outer, whereas for large OLFn, it nucleates from the inner to the outer and to intermediate fullerenes. The melting and erosion behaviors of both SWFnand OLFnare mainly characterized by the nucleation of non-hexagons, nanovoids, carbon chains and emission of C2. RF ML model is developed to predict the melting points of both SWFnand OLFn. Moreover, the analysis of the feature importance reveals that the Stone-Wales transformation is a critical pathway in the melting of SWFnand OLFn. This study provides new insights and perspectives into the thermodynamics and pyrolysis chemistry of fullerenic carbons, and also may shed some lights onto the understanding of thermally-induced erosion of carbon-based resources and spacecraft materials.

Role of mechanical deformation in the thermal transport of sI-type methane hydrate.

Natural gas hydrates (NGHs) are rising as an unconventional energy resource. The fundamental thermal characteristics of NGHs are of importance for natural gas exploitation from permafrost and oceanic sediments that are geomechanically deformed. Here, utilizing classic molecular dynamics simulations with all-atom (AA) and coarse-grained (CG) models of the methane guest molecule, the effects of mechanical strain on the thermal conductivity of sI-type methane hydrate are for the first time examined. Upon triaxial tension and compression, methane hydrate exhibits strong asymmetry in the stress responses. As the triaxial loads go from compression to tension, a reduction trend in the thermal conductivity is revealed for methane hydrate with both AA and CG models of methane, within a maximum reduction of over 44%. This reduction is because triaxial strain from compression to tension softens the phonon modes. Interestingly, there is a sudden rise in thermal conductivity at critical triaxial strain of 0.06, originating from that, at which, the phonon modes are hardened and the peaks of radial distribution functions are shifted back. This study provides important information on the thermal conductivity of methane hydrate, which is helpful for the practical production of natural gas from geo-deformed NGH-bearing sediments via a heating technique as well as evaluating their stability.

Mechanical ductile detwinning in CH3NH3PbI3 perovskite.

Twin boundaries (TBs) were identified to show conflicting positive/negative effects on the physical properties of CH3NH3PbI3 perovskites, but their effects on the mechanical properties are still unclear. Herein, the tensile characteristics of a variety of TB-dominated bicrystalline CH3NH3PbI3 perovskites are explored using molecular simulations. The results show that TB-containing CH3NH3PbI3 perovskites can be classified into four types based on their tensile ductile detwinning characteristics. Type I is characterized by smooth loading flow stress-strain responses, originating from relatively uniform stress distribution induced gradual amorphization in the TB region. Types II and III are represented by a sudden drop in loading stresses but then distinct ductile flow stress-strain curves, resulting from limited and large-area amorphizations of TB-involved structures, respectively. However, Type IV is highlighted by double apparent peaks in the loading curve, followed by a ductile flow response, originating from the stress-concentration of localization-to-globalization in the TB region, as well as amorphization. This study provides critical insights into the mechanical characteristics of CH3NH3PbI3 perovskites and indicates that TB engineering is a promising strategy to design mechanically robust hybrid organic-inorganic perovskite-based device systems.

Binding-Induced Molecular Amplifier as a Universal Detection Platform for Biomolecules and Biomolecular Interaction.

Techniques that detect multiple classes of biomolecules and biomolecular interactions from biological or patient samples are highly desirable for applications ranging from accurate disease diagnosis to deciphering comprehensive biological processes. Because of the large variations in target recognition, signal transduction, and instrumentation, it is technically challenging to generalize a single detection method to a diverse range of analytical targets. Herein, we introduce a binding-induced molecular amplifier (BIMA) strategy that translates a variety of biomolecules and biomolecular interactions into unified predesigned DNA barcode in homogeneous solutions. On the basis of a three-dimensional DNA-walking mechanism, BIMA not only translates various targets into a unified barcode but also amplifies the translation by generating multiple barcode molecules in response to a single input target molecule. Using this strategy, we have successfully expanded the uses of a simple toehold-mediated strand displacement beacon for the sensitive detection of multiple classes of targets, including nucleic acids, proteins, and protein-protein interactions.

Universal strategy to engineer catalytic DNA hairpin assemblies for protein analysis.

Nucleic acids can be programmed into enzyme-free catalytic DNA circuits (CDCs) to carry out various functions ranging from DNA computing to signal amplifications for biosensing. Catalytic hairpin assembly (CHA), the accelerated hybridization between two DNA hairpins catalyzed by a DNA input, is one of the most widely studied and used CDCs for amplified detection of nucleic acids and small molecules. So far, it is still challenging to expand CHAs to proteins largely due to the lack of a universal strategy to construct protein-responsive CHAs. To address this challenge, we demonstrate that a rationally designed protein-DNA binding complex can be used as an effective catalyst to accelerate CHA reactions. On the basis of this principle, we developed specific CHAs for a number of important protein biomarkers, including human α-thrombin, human prostate specific antigen, and human epidermal growth factor receptor 2. Upon establishing this panel of protein-responsive CHAs, we further explore their potential applications to the detection of specific protein biomarkers from human serum samples and cancer cells.

Aptamer binding assays for proteins: the thrombin example--a review.

Experimentally selected single-stranded DNA and RNA aptamers are able to bind to specific target molecules with high affinity and specificity. Many analytical methods make use of affinity binding between the specific targets and their aptamers. In the development of these methods, thrombin is the most frequently used target molecule to demonstrate the proof-of-principle. This paper critically reviews more than one hundred assays that are based on aptamer binding to thrombin. This review focuses on homogeneous binding assays, electrochemical aptasensors, and affinity separation techniques. The emphasis of this review is placed on understanding the principles and unique features of the assays. The principles of most assays for thrombin are applicable to the determination of other molecular targets.

Sequential strand displacement beacon for detection of DNA coverage on functionalized gold nanoparticles.

Functionalizing nanomaterials for diverse analytical, biomedical, and therapeutic applications requires determination of surface coverage (or density) of DNA on nanomaterials. We describe a sequential strand displacement beacon assay that is able to quantify specific DNA sequences conjugated or coconjugated onto gold nanoparticles (AuNPs). Unlike the conventional fluorescence assay that requires the target DNA to be fluorescently labeled, the sequential strand displacement beacon method is able to quantify multiple unlabeled DNA oligonucleotides using a single (universal) strand displacement beacon. This unique feature is achieved by introducing two short unlabeled DNA probes for each specific DNA sequence and by performing sequential DNA strand displacement reactions. Varying the relative amounts of the specific DNA sequences and spacing DNA sequences during their coconjugation onto AuNPs results in different densities of the specific DNA on AuNP, ranging from 90 to 230 DNA molecules per AuNP. Results obtained from our sequential strand displacement beacon assay are consistent with those obtained from the conventional fluorescence assays. However, labeling of DNA with some fluorescent dyes, e.g., tetramethylrhodamine, alters DNA density on AuNP. The strand displacement strategy overcomes this problem by obviating direct labeling of the target DNA. This method has broad potential to facilitate more efficient design and characterization of novel multifunctional materials for diverse applications.

Binding-induced formation of DNA three-way junctions and its application to protein detection and DNA strand displacement.

DNA three-way junctions (DNA TWJs) are important building blocks to construct DNA architectures and dynamic assemblies. We describe here a binding-induced DNA TWJ strategy that is able to convert protein bindings to the formation of DNA TWJ. The binding-induced DNA TWJ makes use of two DNA motifs each conjugated to an affinity ligand. The binding of two affinity ligands to the target molecule triggers assembly of the DNA motifs and initiates the subsequent DNA strand displacement, resulting in a binding-induced TWJ. Real-time fluorescence monitoring of the binding-induced TWJ enables detection of the specific protein targets. A detection limit of 2.8 ng/mL was achieved for prostate-specific antigen. The binding-induced TWJ approach compares favorably with the toehold-mediated DNA strand-displacement, the associative (combinative) toehold-mediated DNA strand-displacement, and the binding-induced DNA strand-displacement. Importantly, the binding-induced TWJ broadens the scope of dynamic DNA assemblies and provides a new strategy to design protein-responsive DNA devices and assemblies.

Preparation and characterization of TiO2-regenerated cellulose inorganic-polymer hybrid membranes for dehydration of caprolactam.

Novel membrane of inorganic-polymer hybrid membrane was prepared by incorporation of the nano-TiO2 into regenerated cellulose (RC). The resulting membrane was characterized by AFM, SEM, and XRD. TiO2 particles formed on the surface and in the interior of the hybrid membrane due to the TiO2 conglomeration, and the surface roughness of the hybrid membrane increased linearly with increasing TiO2 content. The membrane was tested for their ability to separate caprolactam-water mixtures by pervaporation. Among all the prepared membranes, RC-TiO2 inorganic-polymer hybrid membrane containing 5wt.% TiO2 exhibited the good pervaporation performance with a flux of 1787.3gm-2h-1 and separation factor of 55091.7 at 328K for 50wt.% caprolactam. Besides, the normalized permeation fluxes in terms of water permeance, caprolactam permeance and selectivity were also introduced to evaluate the membranes performance. The activation energies were calculated using Arrhenius equation.