Search

The utilization of lithium–sulfur battery is hindered by various challenges, including the "shuttle effect", limited sulfur utilization, and the sluggish conversion kinetics of lithium polysulfides (LiPSs). In the present work, a theoretical design for the viability of graphitic carbon nitride (g-C3N4) and phosphorus-doping graphitic carbon nitride substrates (P-g-C3N4) as promising host materials in a Li-S battery was conducted utilizing first-principles calculations. The PDOS shows that when the P atom is introduced, the 2p of the N atom is affected by the 2p orbital of the P atom, which increases the energy band of phosphorus-doping substrates. The energy bands of PC and Pi are 0.12 eV and 0.20 eV, respectively. When the lithium polysulfides are adsorbed on four substrates, the overall adsorption energy of PC is 48–77% higher than that of graphitic carbon nitride, in which the charge transfer of long-chain lithium polysulfides increase by more than 1.5-fold. It is found that there are powerful Li-N bonds between lithium polysulfides and P-g-C3N4 substrates. Compared with the graphitic carbon nitride monolayer, the anchoring effect of the LiPSs@P-g-C3N4 substrate is enhanced, which is beneficial for inhibiting the shuttle of high-order lithium polysulfides. Furthermore, the catalytic performance of the P-g-C3N4 substrate is assessed in terms of the S8 reduction pathway and the decomposition of Li2S; the decomposition energy barrier of the P-g-C3N4 substrate decrease by 10% to 18%. The calculated results show that P-g-C3N4 can promote the reduction of S8 molecules and Li-S bond cleavage within Li2S, thus improving the utilization of sulfur-active substances and the ability of rapid reaction kinetics. Therefore, the P-g-C3N4 substrates are a promising high-performance lithium-sulfur battery anchoring material. [ABSTRACT FROM AUTHOR]

Layered BaFZnP compound, characterized by a supercell structure with the stacking axis perpendicular to the [Ba2F2]2+ and [Zn2P2]2– layers, has garnered special attention in thermoelectric (TE) materials. In the current work, the crystal structure, thermal and electronic transport properties, and thermoelectric performance of the BaFZnP compound are explored through first-principles calculations and Boltzmann transport theory. The layered BaFZnP compound exhibits a direct band gap of 1.24 eV, featuring band degeneracy in the electronic band structure. Due to the weak interlayer interactions along the out-of-plane direction and correspondingly robust intralayer interactions along the in-plane direction, a low lattice thermal conductivity of 1.99 W/mK is achieved for the BaFZnP compound at 300 K under the consideration of a four-phonon scattering process. Meanwhile, excellent electronic transport performance is also observed in the BaFZnP compound, as demonstrated by the high Seebeck coefficient, the appropriate electrical conductivity, and the high power factor. Within the consideration of four-phonon scattering and multiple carrier scattering rates, a high thermoelectric dimensionless figure of merit (ZT) of 1.94 at 900 K is achieved for the BaFZnP compound along the in-plane direction, showcasing the great promising prospect for the p-type thermoelectric material. Our current work not only delves into the fundamental comprehension regarding the electronic and thermal transport properties of the layered BaFZnP compound but also contributes to a deeper understanding of the intrinsic four-phonon scattering and multiple carrier scattering processes in governing the excellent TE performance. [ABSTRACT FROM AUTHOR]

Contrastive-based clustering models usually rely on a large number of negative pairs to capture uniform representations, which requires a large batch size and high computational complexity. In contrast, some self-supervised methods perform non-contrastive learning to capture discriminative representations only with positive pairs, but suffer from the collapse of clustering. To solve these issues, a novel end-to-end self-supervised clustering model is proposed in this paper. The basic self-supervised learning network is first modified, followed by the incorporation of a Softmax layer to obtain cluster assignments as data representation. Then, adversarial learning on the cluster assignments is integrated into the methods to further enhance discrimination across different clusters and mitigate the collapse between clusters. To further encourage clustering-oriented guidance, a new cluster-level discrimination is assembled to promote clustering performance by measuring the self-correlation between the learned cluster assignments. Experimental results on real-world datasets exhibit better performance of the proposed model compared with the existing deep clustering methods. [ABSTRACT FROM AUTHOR]

Thallium (Tl) is highly toxic in the environment. In order to solve the harm of Tl pollution to the environment, thiol-polystyrene microsphere (TPM) with good adsorption properties for Tl were prepared in this paper. The GAUSSIAN software was used to calculate the adsorption performance of the TPM on Tl+, and the adsorption mechanism was discussed. The thermogravimetric analysis show that the TPM prepared with chloromethyl polystyrene microspheres (CPM) and thiourea as the main raw materials has good chemical thermal stability. In the Tl+ solution of 1mg/L, the adsorption and removal rate of the TPMs in was 99%, with a significant adsorption of Tl+ properties. When the dosage of TPM is 0.4L/g, pH is 6-10, temperature is 5-20 °C, and adsorption time reaches 640min, thallium-containing water with Tl+ concentration of 5mg/L can be treated to within the national discharge standard (5μg/L). The analytical effect of 0.5mol/L dilute sulfuric acid on TPM can reach 99.96%, and the adsorption capacity of TPM on Tl+ is reduced by only 0.1% after repeated use 4 times, which has good regeneration performance. The modified polystyrene microspheres were characterized by EDS, FT-IR, Raman spectra and XPS, and it was proved that the TPM were ligated with Tl+ through the grafted mercapto group, so as to adsorb and remove Tl+ from the solution. According to the isotherm and kinetic model of TPM adsorption Tl+, the maximum saturated adsorption amount of TPM to Tl+ can reach 3.47mg/g, mainly chemical adsorption, and the membrane diffusion stage is the main control step of TPM adsorption Tl+. The results showed that the TPM could be a promising adsorbent with good adsorption capacity and reusability for Tl+ removal from wastewater