Yeast cells as macropore bio-templates enhancing transport properties and conversions in coated catalyst layers for exhaust gas oxidation

Microbial Surface Confined Growth Strategy for the Synthesis of Highly Loaded NiCoP Nanoparticles with Hollow Derived Carbon Shells for Sodium Ion Capture

NiCoP is considered to be a very promising material for sodium ion (Na+) capturing, however, the volume expansion and poor cyclic stability of NiCoP during the storage limit its application. In response to these limitations, Finite element simulations are used to help in the rational design of the NiCoP structure. A novel microbial surface confined growth strategy is employed to synthesize highly loaded NiCoP nanoparticles (NiCoP NPs) supported on hollow derived carbon shells (NPC), constructing a stable composite structure known as NiCoP@NPC. The highly loaded and uniformly dispersed NiCoP NPs are anchored in-situ and fully exposed, enabling enhanced electron and ion transport efficiency and thereby boosting pseudocapacitance. The NPC from yeast played a crucial role in mitigating the volume expansion of NiCoP NPs, thereby enhancing the structural stability of the electrode. Consequently, NiCoP@NPC demonstrated a high Na+ storage capacity of 59.70 ± 1.51 mg g-1 at 1.6 V and maintained good cycling stability, retaining over 73.3% of its capacity after 80 cycles at 1.6 V. Scanning transmission X-ray microscopy (STXM) analysis confirmed the reversible conversion reaction mechanism and the robust structure of NiCoP@NPC before and after the reaction; Density function theory (DFT) and electrochemical quartz crystal microbalance (EQCM-D) further confirmed that the structural design of NiCoP@NPC promoted electron transport, Na+ adsorption as well as improved cycling stability. This study is intended to provide a new idea for the in-situ confined synthesis of metal phosphides electrodes with stable performance and structure.

Modeling and analysis of transport and reaction in washcoated monoliths: Cu-SSZ-13 SCR and dual-layer Cu-SSZ-13 + Pt/Al2O3 ASC

Modeling and analysis of washcoated single- and dual-layer monolith catalysts is presented for selective catalytic reduction (SCR) on Cu-SSZ-13 and ammonia oxidation on Cu-SSZ-13 + Pt/Al₂O₃ ammonia slip catalyst (ASC).

Correlation between physicochemical properties of modified clinoptilolite and its performance in the removal of ammonia-nitrogen

The physicochemical properties of the 24 modified clinoptilolite samples and their ammonia-nitrogen removal rates were measured to investigate the correlation between them. The modified clinoptilolites obtained by acid modification, alkali modification, salt modification, and thermal modification were used to adsorb ammonia-nitrogen. The surface area, average pore width, macropore volume, mecropore volume, micropore volume, cation exchange capacity (CEC), zeta potential, silicon-aluminum ratios, and ammonia-nitrogen removal rate of the 24 modified clinoptilolite samples were measured. Subsequently, the linear regression analysis method was used to research the correlation between the physicochemical property of the different modified clinoptilolite samples and the ammonia-nitrogen removal rate. Results showed that the CEC was the major physicochemical property affecting the ammonia-nitrogen removal performance. According to the impacts from strong to weak, the order was CEC > silicon-aluminum ratios > mesopore volume > micropore volume > surface area. On the contrary, the macropore volume, average pore width, and zeta potential had a negligible effect on the ammonia-nitrogen removal rate. The relational model of physicochemical property and ammonia-nitrogen removal rate of the modified clinoptilolite was established, which was ammonia-nitrogen removal rate = 1.415[CEC] + 173.533 [macropore volume] + 0.683 [surface area] + 4.789[Si/Al] - 201.248. The correlation coefficient of this model was 0.982, which passed the validation of regression equation and regression coefficients. The results of the significance test showed a good fit to the correlation model.