Density Analysis Research Articles

Application of Modulated Vibration to Restore Driver Alertness

Since driving while drowsy is a significant cause of vehicle accidents, road safety could be improved if more effective methods were available for improving driver alertness. The present paper investigated whether it is possible to improve alertness via a wearable device that applied somatosensory vibration to the driver's wrist. The vibration used modulation frequencies ranging from 12 Hz to 50 Hz and a carrier frequency of 250 Hz. Random on-and-off intervals and variable vibration amplitudes were used to minimise sensory adaptation. Fifteen participants undertook a sixty-minute simulated driving task that caused drowsiness. Karolinska Sleepiness Scale (KSS), Power Spectral Density (PSD) and Higuchi's Fractal Dimension (HFD) analyses of brainwave signals were used to identify variations in driver alertness. The vibration stimulus was found to significantly improve alertness when compared to a no-vibration condition. Participants experienced an immediate improvement in alertness that reached significance within 9 minutes and was then sustained at the level seen at the beginning of the experiment, indicating a full restoration of alertness. This result demonstrates that wearable vibration devices have the potential to improve alertness in drivers.

Geographic clustering of cannabis stores in Canadian cities: A spatial analysis of the legal cannabis market 4 years post-legalisation.

Following the legalisation of non-medical cannabis in 2018, the number of cannabis stores in Canada has rapidly expanded with limited regulation on their geographic placement. This study characterised the clustering of cannabis stores in Canadian cities and evaluated the association of clustering with provincial policy and sociodemographic variables. Cross-sectional spatial analysis of cannabis store density in dissemination areas ('neighbourhoods', n = 39,226) in Canadian cities in September 2022. Cannabis store density was defined as the count of stores within 1000 m of a neighbourhood centre. Clusters of high-density cannabis retail were identified using Local Indicators of Spatial Autocorrelation. Associations between provincial policy (privatised vs. public market), sociodemographic variables and cannabis store density were evaluated using multivariable regression. Clusters of high-density cannabis retail were identified in 86% of Canadian cities, and neighbourhoods in clusters had a median of 5 stores within 1000 m. Toronto, Canada's most populous city, had the most extreme clustering where neighbourhoods in clusters had a median of 10 stores (and a maximum of 25 stores) within 1000 m. Neighbourhoods in private versus public retail markets had a significantly higher neighbourhood-level density of cannabis stores (adjusted rate ratio [aRR] 63.37, 95% confidence interval [CI] 25.66-156.33). Lower neighbourhood income quintile was also associated with a higher neighbourhood-level density of cannabis stores (Q5 vs. Q1, aRR 1.28, 95% CI 1.17-1.40). Since cannabis was legalised, clusters of high-density cannabis retail have emerged in most Canadian cities and were more likely to form lower income neighbourhoods and in private retail markets.

Green silver nanoparticles: Prospective nanotools against neurodegenerative cell line model

AbstractNeurodegenerative diseases represent an increasingly burdensome challenge of the past decade, primarily driven by the global aging of the population. Ongoing efforts focus on implementing diverse strategies to mitigate the adverse effects of neurodegeneration, with the goal of decelerating the pathology progression. Notably, in recent years, it has emerged that the use of nanoparticles (NPs), particularly those obtained through green chemical processes, could constitute a promising therapeutic approach. Green NPs, exclusively sourced from phytochemicals, are deemed safer compared to NPs synthetized through conventional chemical route. In this study, the effects of green chemistry‐derived silver NPs (AgNPs) were assessed in neuroblastoma cells, SHSY‐5Y, which are considered a pivotal model for investigating neurodegenerative diseases. Specifically, we used two different concentrations (0.5 and 1 µM) of AgNPs and two time points (24 and 48 h) to evaluate the impact on neuroblastoma cells by observing viability reduction and intracellular calcium production, especially using 1 µM at 48 h. Furthermore, investigation using atomic force microscopy (AFM) unveiled an alteration in Young's modulus due to the reorganization of cortical actin following exposure to green AgNPs. This evidence was further corroborated by confocal microscopy acquisitions as well as coherency and density analyses on actin fibers. Our in vitro findings suggest the potential efficacy of green AgNPs against neurodegeneration; therefore, further in vivo studies are imperative to optimize possible therapeutic protocols.

Stiffness calibration of qPlus sensors at low temperature through thermal noise measurements

Non-contact atomic force microscopy (nc-AFM) offers a unique experimental framework for topographical imaging of surfaces with atomic and/or sub-molecular resolution. The technique also permits to perform frequency shift spectroscopy to quantitatively evaluate the tip–sample interaction forces and potentials above individual atoms or molecules. The stiffness of the probe, k, is then required to perform the frequency shift-to-force conversion. However, this quantity is generally known with little precision. An accurate stiffness calibration is therefore mandatory if accurate force measurements are targeted. In nc-AFM, the probe may either be a silicon cantilever, a quartz tuning fork (QTF), or a length extensional resonator (LER). When used in ultrahigh vacuum (UHV) and at low temperature, the technique mostly employs QTFs, based on the so-called qPlus design, which actually covers different types of sensors in terms of size and design of the electrodes. They all have in common a QTF featuring a metallic tip glued at the free end of one of its prongs. In this study, we report the stiffness calibration of a particular type of qPlus sensor in UHV and at 9.8 K by means of thermal noise measurements. The stiffness calibration of such high-k sensors, featuring high quality factors (Q) as well, requires to master both the acquisition parameters and the data post-processing. Our approach relies both on numerical simulations and experimental results. A thorough analysis of the thermal noise power spectral density of the qPlus fluctuations leads to an estimated stiffness of the first flexural eigenmode of ≃2000 N/m, with a maximum uncertainty of 10%, whereas the static stiffness of the sensor without tip is expected to be ≃3300 N/m. The former value must not be considered as being representative of a generic value for any qPlus, as our study stresses the influence of the tip on the estimated stiffness and points towards the need for the individual calibration of these probes. Although the framework focuses on a particular kind of sensor, it may be adapted to any high-k, high-Q nc-AFM probe used under similar conditions, such as silicon cantilevers and LERs.

Distribution patterns of breeding nests in the colonial-breeding Azure-winged Magpie Cyanopica cyanus

ABSTRACT Capsule Distribution patterns of the breeding nests of the Azure-winged Magpie can help to understand spatial and temporal changes in core use areas throughout the breeding range. Aims We investigated the spatial and temporal patterns of nest locations in the breeding colony, to determine the effect of breeding experience and timing on the nest location of Azure-winged Magpies. Methods We collected data on the nest locations of Azure-winged Magpies in a breeding colony and analysed them to identify patterns in nest location. We estimated the nest distribution range through a kernel density analysis, using a geographic information system. Results The size and location of the core use area of the breeding population changed in the following breeding season when the previous year's reproductive success rate was low. We also observed changes in the size and location of the core-use area in relation to the timing of breeding. Conclusion Inter-annual change of the core use area was associated with the timing of breeding and the population's breeding experience.

Assessment of mechanical, physical, and thermal characterization of jujube seed shell briquettes

The escalating challenges of energy scarcity and environmental concerns stemming from fossil fuel usage have intensified the exploration of renewable energy sources, including municipal waste and agricultural residues. Despite their availability, indigenous nature, and environmental friendliness, certain residues necessitate conversion through processes such as briquetting because of the high relative humidity and low specific heat. This study delves into the examination of the mechanical, thermophysical, and physical properties of Jujube seed shell-based briquettes without the use of binders. Three distinct particle sizes; fine particles (<0.6 mm), medium particles (<2.36 mm), and coarse particles (<3.35 mm) were respectively experimented. The produced briquettes underwent analysis for density, durability, shatter resistance index, relaxation ratio, compressive strength, volatile matter (VM), and specific heat of combustion. Results unveiled a density range of 1909 kg/m3 to 2158 kg/m3, with fine particles exhibiting the highest density at 2158 kg/m3. Calorific values varied between 26,430 kJ/kg and 27,175 kJ/kg. Moisture content ranged from 3.0 % to 7 %, ash content from 1.51 % to 1.68 %, volatile matter from 73.1 % to 77.2 %, and fixed carbon from 17.29 % to 18.39 %. This comprehensive exploration provides valuable insights into the potential of Jujube seed shell briquettes as a sustainable and efficient alternative energy source, contributing to the ongoing discourse on renewable energy utilization.

Microvascular Density Analysis of Patients with Inactive Systemic Lupus Erythematosus-A Two-Year Follow-Up Optical Coherence Tomography Angiography Study.

Background/Objectives: This study aims to investigate the long-term effect of inactive systemic lupus erythematosus (SLE) on the retinal microcirculation measured via optical coherence tomography angiography (OCT-A). Methods: Twenty-four eyes of 24 patients with inactive SLE under hydroxychloroquine (HCQ) therapy were included. The OCT-A data (mainly vessel density (VD) and foveal avascular zone (FAZ) data of the superficial and of the deep capillary plexus (SCP, DCP) and the choriocapillaris (CC)) were analyzed and compared between the baseline examination (t0) and 2 years later (t1). Results: At t1, VD in the whole en face SCP and in the CC was notably reduced compared to t0 (SCP: p = 0.001, CC: p = 0.013). VD in the DCP, CRT and FAZ area showed no difference at t1 compared to t0 (DCP: p = 0.128, FAZ: p = 0.332, CRT fovea: p = 0.296). Correlation analysis between the increase in cumulative doses of HCQ between t0 and t1 and the VD of the whole en face SCP did not show any correlation (Spearman r = 0.062 (95% CI -0.367; 0.477). Conclusions: SLE patients demonstrated a decrease in the retinal VD of the SCP and CC over a 2-year period. There was no correlation with the change in cumulative doses of HCQ. These results suggest an ongoing effect of the disease on the retinal and choriocapillary microcirculation.

CRIME PREVENTION AND WORK MONITORING IN CROWD USING CCTV NETWORK

In an era where surveillance technology is becoming increasingly sophisticated, leveraging Closed-Circuit Television (CCTV) networks for crime prevention and crowd monitoring has gained significant attention. This research aims to explore the potential of CCTV systems in deterring criminal activities and ensuring public safety in crowded environments. By integrating advanced video analytics and machine learning algorithms, the CCTV network can detect suspicious behavior patterns, identify potential threats, and alert law enforcement in real-time. Moreover, by employing work monitoring features, such as crowd density analysis and traffic flow optimization, the system can enhance operational efficiency and mitigate safety risks in various public spaces, including transportation hubs, shopping malls, and urban centers. Ultimately, this study seeks to contribute to the development of proactive security measures and intelligent surveillance solutions for safer communities. Keywords— Artificial Intelligence, CCTV Network, Crime Prevention, Crowd Monitoring, Surveillance.

Value of peripheral blood rare cell EGFR gene amplification detection in the evaluation of benign and malignant pulmonary nodules

Objective: To explore the value of detection of epidermal growth factor receptor (EGFR) gene amplification in peripheral blood rare cells in the assessment of benign and malignant pulmonary nodules. Methods: A total of 262 patients with pulmonary nodules were selected as the retrospectively study subjects from the Second Affiliated Hospital of Army Military Medical University and Peking Union Medical College Hospital from July 2022 to August 2023. There were 98 males and 164 females, with the age range from 16 to 79 (52.1±12.1) years. The EGFR gene amplification testing was performed on the rare cells enriched from patients' peripheral blood, and the clinical manifestations, CT imaging features, histopathological and/or pathological cytological confirmed results of patients were collected. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value of the method of detection of EGFR gene amplification in peripheral blood rare cells, and its diagnostic efficacy was evaluated. Results: Among the 262 patients, 143 were malignant pulmonary nodules and 119 were benign pulmonary nodules. The differences between malignant pulmonary nodules and benign pulmonary nodules in nodule diameter and nodule density were statistically significant (both P<0.001), while the differences in age, gender and nodule number were not statistically significant (all P>0.05). The number [M (Q1, Q3)] of EGFR gene amplification positive rare cells in patients with malignant pulmonary nodule was 8 (6, 11), which was higher than that in patients with benign pulmonary nodule [2 (1, 4), P<0.001]. The ROC curve results showed that when the optimal cut-off value was 5 (that was, the number of EGFR gene amplification positive rare cells was>5), the area under the curve (AUC) of the detection of EGFR gene amplification in peripheral blood rare cells for discrimination of benign and malignant pulmonary lesions was 0.816 (95%CI: 0.761-0.870), with a sensitivity of 83.2%, a specificity of 80.7%, and an accuracy of 82.1%. Based on the analysis of the diameter of the nodules, the AUC for distinguishing between benign and malignant pulmonary nodules with diameter 5-9 mm and 10-30 mm was 0.797 (95%CI: 0.707-0.887) and 0.809 (95%CI: 0.669-0.949), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule density, the AUC for distinguishing between benign and malignant solid nodule and subsolid nodule was 0.845 (95%CI: 0.751-0.939) and 0.790 (95%CI: 0.701-0.880), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule number, the AUC for distinguishing between benign and malignant solitary pulmonary nodule and multiple pulmonary nodule was 0.830 (95%CI: 0.696-0.965) and 0.817 (95%CI: 0.758-0.877), respectively, with sensitivity, specificity and accuracy reached 80% or above. Conclusion: The detection of EGFR gene amplification in peripheral blood rare cells contributes to the evaluation of benign and malignant pulmonary nodules, and can be used in the auxiliary diagnosis of benign and malignant pulmonary nodules.

A Quantitative and Qualitative Exploration of Futuristic Narratives on TVTropes.org

This paper embarks on a methodical exploration of TVTropes.org, a comprehensive crowd-sourced wiki that documents storytelling conventions across various forms of media, with a special focus on representations of artificial intelligence and future scenarios. The study delineates the multifaceted nature of the platform, asserting that its offerings extend beyond mere television tropes, and explores its potent applicability for futurists and scholars. Through the strategic application of web scraping and data analysis, this research quantifies diverse aspects of science fiction media and the embedded tropes therein. The paper underscores the pivotal role of tropes in shaping societal perceptions and influencing discourse, particularly in the realm of futuristic thinking, using instances such as the impact of “The Terminator” franchise on military strategic thinking as a case study. Furthermore, the research engages in a quantitative analysis of trope density and frequency within science fiction works, offering a nuanced understanding and uncovering patterns in storytelling conventions. This study thus offers a foundational framework for understanding, categorizing, and analyzing the influential images of the future that permeate today’s media environment, thereby providing a valuable resource for futurists, researchers, and media scholars in their respective endeavors.

Comparative assessment and policy analysis of forecasting quarterly renewable energy demand: Fresh evidence from an innovative seasonal approach with superior matching algorithms

In the pursuit of sustainable development, accurate renewable energy demand forecasting holds great significance for climate change mitigation and promoting sustainability. However, renewable energy forecasting has been consistently challenged by seasonality and nonlinearity. Identifying the periodic and nonlinear characteristics concealed within renewable energy sources accurately is still an unexplored problem. Consequently, an innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting, which incorporates seasonal dummy variables and a power exponent term for handling the seasonality and nonlinear patterns in time series. Furthermore, an intelligent algorithm matching framework is proposed to augment the flexibility of the newly developed model. For practical purposes, the new methodology is contrasted against a range of benchmarks encompassing statistical, machine-learning, and traditional grey models in forecasting the quarterly total renewable energy consumption in the United States. The proposed model exhibits over 27% improvement rates over its counterparts, achieving the most superior predictive accuracies of 1.45%, 39.27, and 0.79 in MAPEP, RMSEP, and MASEP metrics, respectively. Furthermore, the probability density and sample size analyses are conducted to validate the robustness of the new model, confirming its adaptability and stability towards algorithm randomness and historical information volume. Consequently, the novel model is employed to forecast the short-to-long-terms renewable energy consumption in the U.S., showcasing an upward trend and seasonal fluctuations of the consumption for the forthcoming 24 quarters from 2023Q4 to 2029Q3. These insights can offer valuable implications to the stakeholders such as energy suppliers, utility managers, and policy advocates, highlighting actionable strategies for optimizing renewable energy consumption forecasting and aiding sustainable development initiatives.

Potentially functional lactose-free ice cream with Lacticaseibacillus casei CSL3, ginger, and honey.

To develop and characterize a functional lactose-free ice cream with added ginger and honey, evaluate the survival of Lacticaseibacillus casei CSL3 under frozen storage and the simulated gastrointestinal tract (GIT), as well as antioxidant activity and product acceptability. The survival of Lacticaseibacillus casei CSL3 was evaluated for 180 days, under frozen storage, and GIT at 60 days. At 15 days of storage, proximal composition, antioxidant activity, color, pH, acidity, fusion, density, overrun, and sensory analysis were performed. Ice cream was an effective food matrix for maintaining the viability of CSL3, with concentrations > 7 log CFU g- 1 during storage and GIT. In addition, the analysis showed overrun and prebiotic characteristics through high values of antioxidant activity and phenolic compounds, good acceptability, and purchase intention. The product has satisfactory market potential (acceptance rate of 95.19% and purchase intention rate > 96%), and it could become another means of inserting probiotics in food.

Impact of Urban Expansion on Carbon Emissions in the Urban Agglomerations of Yellow River Basin, China

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin.

Quantum computational, charge density, optical, molecular reactivity and thermodynamical analysis of Di-Halogen substituted nicotinic acid derivatives

6-Chloro-3-fluoro-2-(trifluoromethyl) isonicotinic acid (6C3F2TINA) and 6-Chloro-5-fluoronicotinic acid (6C5FNA) are currently being studied using the DFT method for the detailed examination of structural and molecular character alterationsin gas as well as in several organic solvent media. Implementing electrostatic potential maps and Fukui functions analyses the reactive environment of compounds. The occurrence of the transfer of electrons and holes within the molecule is reported by a charge transfer study along with the heat maps. The orbital study investigates the electronic density and interactions within themolecules. Optical examination of compounds revealed an enhancement with the solvents. Thebonding typefound in molecules isdetermined by topographical investigation, which examines the concentration and localisationof electrons present in them. The UV–Vis spectra exhibit the absorption characteristics of these compounds. The thermodynamic investigation reveals the compound’s stability at various temperatures at 1 atm pressure.

Determination of the temporal–spatial distribution patterns of ancient heritage sites in China and their influencing factors via GIS

In this paper, we analysed the temporal and spatial distributions of ancient archaeological sites in China as well as their influencing factors. Our aim was to reveal the developmental trajectory of Chinese civilisation and to explore the natural and cultural factors affecting human distribution, with the goal of providing insights for the conservation and development of ancient relics. We employed spatial analysis methods using ArcGIS 10.8 software, such as kernel density analysis and trend surface analysis, to analyse 1194 historical ancient sites listed in the National Cultural Relics Protection Units of China. The research findings are as follows: (1) the distribution of ancient sites demonstrates an agglomerative spatial pattern. The nearest neighbour index (R < 1) for sites from various historical periods indicates an agglomerative spatial distribution of ancient sites across historical periods, with the clustering degree being relatively poor for sites from the Wei-Jin, Northern and Southern Dynasties and in the Ming and Qing periods. The regions with a concentration of ancient sites are the middle and lower reaches of the Yangtze River and Yellow River Basins. Furthermore, there is a higher abundance of ancient sites in the southeastern region than in the northwestern region. (2) The distribution of ancient sites in different historical periods also exhibits an imbalance, with an overall decreasing trend in the number of ancient sites in China. Notably, more ancient sites were found for the prehistoric and pre-Qin periods. The temporal trend of ancient sites during historical periods follows a trajectory from northeast to northwest, northeast to southwest, etc. (3) The temporal and spatial distributions of ancient sites are influenced by multiple factors, including social development, the natural environment, geographical elements, and socioeconomic and political factors. Finally, based on an understanding of the spatiotemporal distribution pattern of ancient sites and the factors that influence this pattern, recommendations for conservation and development can be proposed and supported by modern technological methods, with the aim of offering insights for the protection and sustainable development of heritage sites.

One Stone Two Birds: Anomalously Enhancing the Cross‐Plane and In‐Plane Heat Transfer in 2D/3D Heterostructures by Defects Engineering

AbstractThis study addresses a crucial challenge in two‐dimensional (2D) material‐based electronic devices—inefficient heat dissipation across the van der Waals (vdW) interface connecting the 2D material to its three‐dimensional (3D) substrate. The objective is to enhance the interfacial thermal conductance (ITC) of 2D/3D heterostructures without compromising the intrinsic thermal conductivities (κ) of 2D materials. Using 2D‐MoS2/3D‐GaN as an example, a novel strategy to enhance both the ITC across 2D/3D interface and κ of 2D material is proposed by introducing a controlled concentration (ρ) of vacancy defects to substrate's bottom surface. Molecular dynamics simulations demonstrate a notable 2.1‐fold higher ITC of MoS2/GaN at ρ = 4% compared to the no‐defective counterpart, along with an impressive 56% enhancement in κ of MoS2 compared to the conventional upper surface modification approaches. Phonon dynamics analysis attributes the ITC enhancement to increased phonon coupling between MoS2 and GaN, resulting from polarization conversion and hybridization of phonons at the defective surface. Spectral energy density analysis affirms that the improved κ of MoS2 directly results from the proposed strategy, effectively reducing phonon scattering at the interface. This work provides an effective approach for enhancing heat transfer in 2D/3D vdW heterostructures, promisingly advancing electronics’ heat dissipation.

Molecular Hydrogen Acts as a Hydrogen Bond Proton Acceptor: From Protonated Betaine Tagging to the Weakest Hydrogen Bond.

In an attempt to gain further insights into the intermolecular interactions implied by Rizzo's group's cautionary tale related to molecular tagging in infrared multiple photon dissociation (IRMPD) spectroscopy with molecular messengers [Masson, A. . J. Chem. Phys. 2015, 143, 104313], in the present study, we provide an in-depth analysis of the noncovalent interaction between the molecular hydrogen and protonated betaine molecule in the gas phase. We aim to shed some new light on the fundamental issues concerning the wide diapason of hydrogen-bonding-type intermolecular interactions, with a wide variety of proton acceptors. We demonstrate that in the course of tagging the protonated betaine with molecular hydrogen from the OH group side, it is the σ bond of molecular hydrogen that plays the role of hydrogen-bonding proton acceptor. The tagging thus induces a small yet significant red shift of the protonated betaine O-H stretching mode. We investigate the performance of a wide range of density functional theory (DFT) functionals for the calculation of anharmonic vibrational frequency shifts of the studied system, which are essential for the correct interpretation of the experimental IRMPD data. For an accurate prediction of the OH stretching frequency shifts, specifically designed functionals such as Handy's group HCTH/407 should be applied. The empirical dispersion correction enhances the systematic overestimation of the anharmonic frequency shift, characteristic of the most widely used DFT functionals. Combining the full-wave function approach with the charge field perturbation and natural bond orbital (NBO) deletion analyses, we demonstrate that the frequency shift in the OH-tagged structure is governed by the σHH → σ*OH intermolecular charge transfer. This interaction stabilizes the OH-tagged dimer as well, in contrast to the dipole-quadrupole electrostatic interaction energy term. Topological analysis of the electron density reveals the presence of an intermolecular bond critical point with a positive value of the density Laplacian very close to the lower limit for hydrogen bonds. NCI analyses demonstrate that the OH···H2 interaction is weaker than the intramolecular CH···O one within the protonated betaine molecule, with the through of reduced density gradient appearing at less negative sign(λ2)·ρ values. Analyzing the O-H stretching vibrational potential with the second-generation absolutely localized molecular orbitals energy decomposition analysis (ALMO-EDA 2) revealed that in the case of betaineH(+) tagged from the OH group side, the permanent electrostatics (ΔEelec), polarization (ΔEpol), and charge-transfer (ΔEct) contributions to the total intermolecular interaction energy contribute favorably to the weak hydrogen bond formation and to the red shift of the fundamental O-H stretching frequency, the ΔEct contribution being the most significant in the last context. The Pauli repulsion term, on the other hand, favors an O-H stretching frequency blue shift as a consequence of the vibrational confinement effects.

Investigation on the hydrogen storage properties, electronic, mechanical properties, debye temperature of H24AlXO20S2 (X=Na, Rb, Cs, K) hydrides

The stability and lattice vibration of H24AlXO20S2 (X = Na, Rb, Cs, K) hydrides are predicted by calculating the crystal structure and energy. The formation enthalpy proves the structural stability and the dynamic stability of the hydride is predicted by the phonon dispersion diagram. Meanwhile, the optical and mechanical properties are analyzed by using the quasi-Debye model. The elastic constants and modulus prove H24AlXO20S2 (X = Na, Rb, Cs, K) mechanical stability. By the value of B/G and Poisson's ratio, it inferred that H24AlNaO20S2, H24AlRbO20S2 and H24AlKO20S2 are brittle. Only H24AlCsO20S2 is ductile and has the lowest hardness. H24AlRbO20S2 has the largest shear modulus and Young's modulus, so it has the highest hardness. In addition, by calculating the anisotropy index of the hydrides, it is proved that they are anisotropic. H24AlKO20S2 has the strongest anisotropy and the value of AU is 0.2477. The anisotropy of the hydride is further studied by calculating the Debye temperature and sound velocity of H24AlXO20S2 (X = Na, Rb, Cs, K) hydrides. The energy band and state density analysis reveal their electronic transitions and bonding.

Chemical bonding and electronic properties along Group 13 metal oxides

ContextThe present work provides a systematic theoretical analysis of the nature of the chemical bond in Al2O3, Ga2O3, and In2O3 group 13 cubic crystal structure metal oxides. The influence of the functional in the resulting band gap is assessed. The topological analysis of the electron density provides unambiguous information about the degree of ionicity along the group which is linearly correlated with the band gap values and with the cost of forming a single oxygen vacancy. Overall, this study offers a comprehensive insight into the electronic structure of metal oxides and their interrelations. This will help researchers to harness information effectively, boosting the development of novel metal oxide catalysts or innovative methodologies for their preparation.MethodsPeriodic density functional theory was used to predict the atomic structure of the materials of interest. Structure optimization was carried out using the PBE functional, using a plane wave basis set and the PAW representation of the atomic cores, using the VASP code. Next, the electronic properties were computed by carrying out single point calculations employing PBE, PBE + U functionals using VASP and also with PBE and the hybrid HSE06 functionals using the FHI-AIMS software. For the hybrid HSE06, the impact of the screening parameter, ω, and mixing parameter, α, on the calculated band gap has also been assessed.

Density and Viscosity Analysis of 3-Methyl-3-pentanol and C3–C6 1-Alkanols: Employing Free Volume Theory for Viscosity Insights

Density and Viscosity Analysis of 3-Methyl-3-pentanol and C3–C6 1-Alkanols: Employing Free Volume Theory for Viscosity Insights