Porous boron carbon nitride (BCN) is one of the exciting systems with unique electrochemical and adsorption properties. However, the synthesis of low-cost and porous BCN with tunable porosity is challenging, limiting its full potential in a variety of applications. Herein, the preparation of well-defined mesoporous boron carbon nitride (MBCN) with high specific surface area, tunable pores, and nitrogen contents is demonstrated through a simple integration of chemical polymerization of readily available sucrose and borane ammonia complex (BAC) through the nano-hard-templating approach. The bimodal pores are introduced in MBCN by controlling the self-organization of BAC and sucrose molecules within the nanochannels of the template. It is found that the optimized sample shows a high specific capacitance (296 F g at 0.5 A g ), large specific capacity for sodium-ion battery (349 mAg h at 50 mAh g ), and excellent CO adsorption capacity (27.14 mmol g at 30 bar). Density functional theory calculations demonstrate that different adsorption sites (BC, BN, CN, and CC) and the large specific surface area strongly support the high adsorption capacity. This finding offers an innovative breakthrough in the design and development of MBCN nanostructures for energy storage and carbon capture applications.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165510PMC
http://dx.doi.org/10.1002/advs.202105603DOI Listing

Publication Analysis

Top Keywords

boron carbon
12
mesoporous boron
8
energy storage
8
adsorption properties
8
carbon nitride
8
high specific
8
specific surface
8
surface area
8
large specific
8
adsorption capacity
8

Similar Publications

Variable relative biological effectiveness (RBE) of carbon radiotherapy may be calculated using several models, including the microdosimetric kinetic model (MKM), stochastic MKM (SMKM), repair-misrepair-fixation (RMF) model, and local effect model I (LEM), which have not been thoroughly compared. In this work, we compared how these four models handle carbon beam fragmentation, providing insight into where model differences arise. Monoenergetic and spread-out Bragg peak carbon beams incident on a water phantom were simulated using Monte Carlo.

View Article and Find Full Text PDF

This study investigated silicone composites with distributed boron nitride platelets and carbon microfibers that are oriented electrically. The process involved homogenizing and dispersing nano/microparticles in the liquid polymer, aligning the particles with DC and AC electric fields, and curing the composite with IR radiation to trap particles within chains. This innovative concept utilized two fields to align particles, improving the even distribution of carbon microfibers among BN in the chains.

View Article and Find Full Text PDF

Chitosan-Based Porous Carbon Materials with Built-In Lewis Acid Boron Sites for Enhanced CO Capture and Conversion via an Electron-Inducing Effect.

ACS Appl Mater Interfaces

January 2025

Key Laboratory of Green Chemical and Clean Energy Technology, School of Chemistry and Chemical Engineering, Guizhou University, Guiyang 550025, P. R. China.

Electron-induced effects, which are prevalent in adsorption and heterogeneous catalytic reactions, can significantly influence the state and uptake of adsorbates. Here, we demonstrate the in situ doping of electron-deficient boron into the backbone of chitosan-based porous carbon materials. Despite a reduction in specific surface area, the resulting boron-doped porous carbons (NBPCs) exhibit an enhanced CO adsorption performance, with sample NBPC-10 achieving CO adsorption capacities of 7.

View Article and Find Full Text PDF

Trace contaminants are toxic and their widespread presence in the environment potentially threatens human health. The levels of these pollutants are often difficult to determine directly using instruments owing to the complexities of environment matrices. Hence, pretreatment steps, such as sample purification and concentration, are key along with various processes that enhance the accuracy and sensitivity of the detection method.

View Article and Find Full Text PDF

Advancing efficiency in deep-blue OLEDs: Exploring a machine learning-driven multiresonance TADF molecular design.

Sci Adv

January 2025

Center for Organic Photonics and Electronics Research (OPERA), Kyushu University, 744 Motooka, Nishi, Fukuoka 819-0395, Japan.

The pursuit of boron-based organic compounds with multiresonance (MR)-induced thermally activated delayed fluorescence (TADF) is propelled by their potential as narrowband blue emitters for wide-gamut displays. Although boron-doped polycyclic aromatic hydrocarbons in MR compounds share common structural features, their molecular design traditionally involves iterative approaches with repeated attempts until success. To address this, we implemented machine learning algorithms to establish quantitative structure-property relationship models, predicting key optoelectronic characteristics, such as full width at half maximum (FWHM) and main peak wavelength, for deep-blue MR candidates.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!