Structural, Mechanical, Electronic and Thermodynamic Analysis of Calcium Aluminum Silicate Crystalline Phases in Stone Wool Insulation Materials: A first-principles study

Stone wool materials have gained considerable attention due to their effectiveness as thermal and acoustic insulation solutions. The comprehension of crystal structure properties is pivotal in determining the overall performance of these materials, as it enables us to optimize their composition for enhanced insulating capabilities. Crucial factors such as structural, mechanical, and thermodynamic characteristics of crystalline phases within stone wool are vital for evaluating its thermal and acoustic insulation properties. This study investigates the properties of calcium aluminum silicate crystal phases commonly present in stone wool, including anorthite, svyatoslavite, scolecite, and dehydrated scolecite using density functional theory (DFT) calculations. In comparison to previous works, this study provides a more comprehensive analysis using advanced DFT calculations. Our analysis reveals the complex interplay between the crystal structures and mechanical behavior of these phases. The calculated bulk modulus of the phases varies significantly, ranging from 38 to 83 GPa. We have compared the calculated elastic properties with available experimental data and found excellent agreement, confirming the accuracy of the computational approach. Moreover, we find that polymorphism has a significant impact on the mechanical strength, with anorthite exhibiting higher strength compared to svyatoslavite. Furthermore, dehydration is found to cause a reduction in unit volume and mechanical strength. The thermodynamic properties of dehydrated scolecite, including entropy and heat capacity, are significantly lower due to the absence of water molecules. These findings highlight the importance of understanding the structural and mechanical characteristics of calcium aluminum silicate phases in stone wool materials. Additionally, our findings have broader implications in various industries requiring effective insulation solutions such as to develop new materials or to enhance the energy efficiency of existing insulating products. © 2023 The Author(s)publishedVersio

Elastic and thermodynamic properties of the major clinker phases of Portland cement: Insights from first principles calculations

Portland based cement is one of the most popular materials used in the civil and construction applications. Reliable computational methods to provide an insight into the underlying mechanics of the major phases of this material are of great interest for cement design. The present work investigated the performance of density functional theory (DFT) calculations using the PBE-D2 method to predict the mechanical, thermodynamic properties of four major phases namely Alite C3S, Belite C2S, tricalcium aluminate C3A and tetracalcium aluminoferrite C4AF. The calculated elastic properties were in a good agreement with available experimental data. In addition, a deeper insight into the electron density of state, spin-polarization, atomic charge, as well as free energy and entropy properties were also presented. Further development is necessary to improve the established DFT models for predicting the mechanical properties of the ferrite phase of Portland clinker.publishedVersio

Synthesis and Optical Characterization of Building-Block Plasmonic Gold Nanostructures

Plasmonics, the field involves manipulating light at the nanoscale, has been being an emergent research field worldwide. Synthesizing the plasmonic gold nanostructures with controlled morphology and desired optical properties is of special importance towards specific applications in the field. Here, we report the chemical synthesis and the optical properties of various plasmonic Au nanostructures, namely Au nanoparticles (AuNPs), Au nanorods (AuNRs) and random Au nano-islands (AuNI) that are the building blocks for plasmonic research. The results show that the AuNPs exhibited a single plasmonic resonance, the AuNRs displayed two identical and separated modes of the resonance, and the random Au nano-islands presented a very broad resonance. Specifically, tailoring the anisotropy of the Au nanorods enabled extending their resonant frequencies from the visible to the near infrared ones, which is in accordance with the finite different time domain simulations

Farming systems in the sandy area of the Thua Thien Hue Province, Central Vietnam, survey of socio-economic situation and constraints identified by farmers

peer reviewe

A framework for practically effective creation of postprocessors for 5-axis CNC machines with all possible configurations and working mechanisms

The 5-axis CNC (Computer Numerical Control) machining plays an important role in manufacturing, especially in making parts of complex shapes such as turbine or propeller blades. However, there are always challenges of generating 5-axis CNC machining programs when working with different 5-axis CNC machines of various structures; and 5-axis CNC programs must be automatically generated by CNC postprocessors which calculate the inverse kinematics and convert the Cutter Location data to the CNC programs that are used for operating 5-axis CNC machines. Since the family of 5-axis CNC machines has a wide spectrum of machine configurations, with hundreds of mechanisms of 5 degrees of freedom, it is therefore practically challenging for engineers and CNC machine operators to create CNC postprocessors for specific 5-axis CNC machines. It is more challenging to create CNC postprocessors if engineers or CNC operators do not have strong backgrounds and professional skills in mathematical modeling and kinematics of machines. This paper presents a universal and intuitive framework and practical guidance to create CNC postprocessors for all 5-axis CNC machines, with the focus on a novel mathematical formulation of inverse kinematics of three main groups of 5-axis CNC machines. The case studies of creating CNC postprocessors with the commercially available 5-axis CNC machines were successfully demonstrated, in which the simulation scenarios and experiments were implemented to verify the created CNC postprocessors. The proposed frameworks and guides for generating CNC postprocessors can be conveniently and effectively applied in industrial practices, without the required strong backgrounds and skills for engineers or CNC operators in mathematical modeling and kinematics of machines, especially mathematical modeling of multibody systems

Состояние провоспалительного цитокинового звена у больных с нестабильной стенокарадией и сахарным диабетом 2-го типа в зависимости от функционального класса хронической сердечной недостаточности

Проанализировано состояние провоспалительного звена цитокинов у больных с нестабильной стенокардией (НС) и сопутствующим сахарным диабетом (СД) 2−го типа в зависимости от функционального класса хронической сердечной недостаточности (ХСН). Нарастание проявлений сердечной декомпенсации у больных с НС и СД 2−го типа ассоциируется с высокой активностью провоспалительного цитокинового звена, представленного фактором некроза опухолей−α и интерлейкином−6. Повышение функционального класса ХСН характеризуется увеличением инсулинорезистентности у больных с НС и СД 2−го типа.Проаналізовано стан прозапальної ланки цитокінів у хворих із нестабільною стенокардією (НС) та супутнім цукровим діабетом (ЦД) 2−го типу залежно від функціонального класу хронічної серцевої недостатності (ХСН). Наростання проявів серцевої декомпенсації у хворих із НС та СД 2−го типу асоціюється з високою активністю прозапальної цитокінової ланки, представленої фактором некрозу пухлин−α та інтерлейкіном−6. Підвищення функціонального класу ХСН характеризується зростанням інсулінорезистентності у хворих із НС та ЦД 2−го типу.The state of pro−inflammatory cytokines in patients with unstable angina (UA) and associated type 2 diabetes mellitus (DM) was analyzed depending on the functional class of chronic heart failure (CHF). The increase in manifestations of cardiac decompensation in patients with UA and type 2 DM is associated with high activity of pro−inflammatory cytokine level represented by tumor necrosis factor−β and interleukin−6. Increase of functional class of CHF is characterized by increased insulin resistance in patients with UA and type 2 DM

Long short-term memory (LSTM) neural networks for short-term water level prediction in Mekong river estuaries

This study firstly adopts a state-of-the-art deep learning approach based on a Long Short-Term Memory (LSTM) neural network for predicting the hourly water level of Mekong estuaries in Vietnam. The LSTM models were developed from around 8,760 hourly data points within 2018 and were evaluated using the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error (MAE), and root mean square error (RMSE). The results showed that the NSE values for the training and testing steps were both above 0.98, which can be regarded as very good performance. Furthermore, the RMSE were between 0.09 and 0.11 m for the training and between 0.10 and 0.12 m for the testing, while MAE for the training ranged from 0.07 to 0.08 m and varied from 0.08 to 0.10 m for the testing. The LSTM networks appear to enable high precision and robustness in water level time series prediction. The outcomes of this research have crucial implications in river water level predictions, especially from the viewpoint of employing deep learning algorithms

Current advances in seagrass research: A review from Viet Nam

Seagrass meadows provide valuable ecosystem services but are fragile and threatened ecosystems all over the world. This review highlights the current advances in seagrass research from Viet Nam. One goal is to support decision makers in developing science-based conservation strategies. In recent years, several techniques were applied to estimate the size of seagrass meadows. Independent from the method used, there is an alarming decline in the seagrass area in almost all parts of Viet Nam. Since 1990, a decline of 46.5% or 13,549 ha was found. Only in a few protected and difficult-to-reach areas was an increase observed. Conditions at those sites could be investigated in more detail to make suggestions for conservation and recovery of seagrass meadows. Due to their lifestyle and morphology, seagrasses take up compounds from their environment easily. Phytoremediation processes of Thalassia hemprichii and Enhalus acoroides are described exemplarily. High accumulation of heavy metals dependent on their concentration in the environment in different organs can be observed. On the one hand, seagrasses play a role in phytoremediation processes in polluted areas; on the other hand, they might suffer at high concentrations, and pollution will contribute to their overall decline. Compared with the neighboring countries, the total Corg stock from seagrass beds in Viet Nam was much lower than in the Philippines and Indonesia but higher than that of Malaysia and Myanmar. Due to an exceptionally long latitudinal coastline of 3,260 km covering cool to warm water environments, the seagrass species composition in Viet Nam shows a high diversity and a high plasticity within species boundaries. This leads to challenges in taxonomic issues, especially with the Halophila genus, which can be better deduced from genetic diversity/population structures of members of Hydrocharitaceae. Finally, the current seagrass conservation and management efforts in Viet Nam are presented and discussed. Only decisions based on the interdisciplinary cooperation of scientists from all disciplines mentioned will finally lead to conserve this valuable ecosystem for mankind and biodiversity

Aquilaria yunnanensis S.C. Huang (Thymelaeaceae), A New Record for the Flora of Vietnam

Aquilaria yunnanensis S.C. Huang (Thymelaeaceae), known to be endemic to Yunnan, is recorded for the first time from Dong Son Ky Thuong Nature Reserve, Quang Ninh Province, Vietnam. A taxonomic description and DNA analysis based on our Vietnamese collections are presented, together with information on its distribution, habitat and colour photographs