Effects of Inorganic Salts on the Phase Separation of Partially Miscible Solutes.

Partially miscible solutions with a lower critical solution temperature have promising applications in the field of physical chemistry. To better guide the utilization of these solutions in practice, we conduct an in-depth study about the phase separation behavior of the solution added with inorganic salts. The addition of the inorganic salts into the solution is found to consequently reduce the phase separation temperature. The variation of concentrations of inorganic salts does not notably affect the mass fraction of the separation. Moreover, the addition of inorganic salts in the solutions at lower mass fractions improves the separation mass fraction, while the addition of inorganic salts decreases the separation mass fraction at the mass fractions above 30%. It sheds light on selecting the proper mass fractions and inorganic salt concentrations. Furthermore, we explore the phase separation behavior of mixed solutions under different inorganic salt additions by means of a high-speed camera. The phase separation behavior under different inorganic salt systems shows a similar trend. However, calcium ions and Fe3+ ions in the solutions can greatly decrease the rate of droplet coalescence and result in an increase in phase separation. For better regulating the solutions with a lower critical solution temperature through inorganic salts, sodium chloride or potassium chloride is recommended with an appropriate concentration.

Phosphorylation of Oligopeptides: Design of Ultra-Hydrophilic Zwitterionic Peptides for Anti-Fouling Detection of Nucleic Acids in Saliva.

The construction of low-fouling biosensors for assaying biomarkers in complex biological samples remains a challenge, and the key limitation is the lack of effective anti-fouling materials. Inspired by the biomimetic process of protein phosphorylation, we herein designed a new phosphorylated peptide modified with the dihydrogen phosphate (-PO4H2) group, which significantly increased the hydrophilicity and anti-fouling capability of the peptide when compared with natural and normal peptides. Molecular simulation (MS) illustrated that, compared with the -COOH and -NH2 groups, the -PO4H2 group formed the most numbers of hydrogen bonds and stronger hydrogen bonds with water molecules. As a result, the PO4H2-oligopeptide was proved by MS to be able to attract the greatest number of water molecules, so as to form a compact layer of H2O to resist further adsorption of nonspecific biomolecules. The modification of electrodes with the designed PO4H2-oligopeptides, in addition to the adoption of neutral peptide nucleic acids (PNAs) as the sensing probes, ensured the fabrication of anti-fouling electrochemical biosensors capable of detecting nucleic acids in complex saliva. The constructed anti-fouling biosensor was able to detect the nucleic acid of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in undiluted saliva, with a wide linear response range (0.01 pM-0.01 µM) and a low limit of detection (LOD) of 3.4 fM (S/N = 3). The phosphorylation of oligopeptides offers an effective strategy to designing ultra-hydrophilic peptides suitable for the construction of promising anti-biofouling biosensors and bioelectronics.

Phase Equilibrium Studies in the Geothermal Energy Development: The Effect of Hydrogen Bond on the Multi-Component Fluid.

Geothermal energy has become an emerging resource with both large reserves and environmental friendliness and is playing an increasingly important role in the current energy transition progress. In this paper, a thermodynamically consistent NVT flash model is developed to consider the effect of hydrogen bond on the phase equilibrium states of multi-component fluid to resolve the challenges of the special thermodynamic characteristic of water as the main working fluid. In order to provide practical suggestions to the industry, a number of possible effects have been investigated on the phase equilibrium states, including the hydrogen bond, environmental temperature, and fluid compositions. The calculated phase stability and phase splitting results can provide thermodynamic foundations for the establishment of the multi-component multi-phase flow model and also help optimize the development process to control the phase transitions for a number of engineering purposes.

Atomistic Insights into the Effect of Functional Groups on the Adsorption of Water by Activated Carbon for Heat Energy Storage.

Adsorption heat storage holds great promise for solar energy applications. The development of new adsorbent materials is currently the research focus in this area. The present work designs several activated carbon models with different functional groups, including -OH, -NH2, -COOH, and -SO3H, and explores the influence of functional groups' categories and numbers on the water adsorption capacity of the activated carbon using the GCMC method. The adsorption mechanism between functional groups and water molecules is analyzed using density functional theory. The results show that the functional groups could significantly improve the water adsorption capacity of activated carbon due to the hydrogen bond between functional groups and water molecules. In the scope of this paper, under low pressure, the activated carbon with -SO3H exhibits the best adsorption capacity, followed by the activated carbon with -COOH. Under low and medium pressure, increasing the number of -SO3H functional groups could increase the water adsorption capacity; however, when the pressure is high, increasing the functional group numbers might decrease the water adsorption capacity. As the temperature increases, the water adsorption capacity of activated carbons decreases, and the activated carbon with -SO3H is proven to have excellent application prospects in heat energy storage.

Predicting the effective thermal conductivity of unfrozen soils with various water contents based on artificial neural network.

The effective thermal conductivity of soils is a crucial parameter for many applications such as geothermal engineering, environmental science, and agriculture and engineering. However, it is pretty challenging to accurately determine it due to soils' complex structure and components. In the present study, the influences of different parameters, including silt content (msi), sand content (msa), clay content (mcl), quartz content (mqu), porosity, and water content on the effective thermal conductivity of soils, were firstly analyzed by the Pearson correlation coefficient. Then different artificial neural network (ANN) models were developed based on the 465 groups of thermal conductivity of unfrozen soils collected from the literature to predict the effective thermal conductivity of soils. Results reveal that the parameters ofmsi,msa,mcl, andmquhave a relatively slight influence on the effective thermal conductivity of soils compared to the water content and porosity. Although the ANN model with six parameters has the highest accuracy, the ANN model with two input parameters (porosity and water content) could predict the effective thermal conductivity well with acceptable accuracy andR2= 0.940. Finally, a correlation of the effective thermal conductivity for different soils was proposed based on the large number of results predicted by the two input parameters ANN-based model. This correlation has proved to have a higher accuracy without assumptions and uncertain parameters when compared to several commonly used existing models.

Nonlocal Effects and Slip Heat Flow in Nanolayers.

Guyer-Krumhansl (G-K) equation is a promising macroscopic model to explore heat transport in nanoscale. In the present work, a new nonlocal characteristic length is proposed by considering the effects of heat carriers-boundaries interactions to modify the nonlocal term in G-K equation, and a slip heat flux boundary condition is developed based on the local mean free path of heat carriers. Then an analytical solution for heat flux across 2-D nanolayers and an in-plane thermal conductivity model are obtained based on the modified G-K equation and the slip heat flux boundary. The predictions of the present work are in good agreement with our numerical results of direct simulation Monte Carlo (DSMC) for argon gas nanolayer and the available experimental data for silicon thin layers. The results of this work may provide theoretical support for actual applications of G-K equation in predicting the thermal transport properties of nanolayers.