CO2 removal from natural gas by moisture swing adsorption

Quaternized Graphene for High-Performance Moisture Swing Direct Air Capture of CO2

Nowadays, moisture-swing adsorption technology still relies on quaternary ammonium resins with limited CO2 capacity under ambient air conditions. In this work, a groundbreaking moisture-driven sorbent is developed starting from commercial graphene flakes and using glycidyltrimethylammonium chloride for incorporation of CO2-sensitive quaternary ammonium functional groups. Boasting an outstanding CO2 capture performance under ultra-diluted conditions (namely, 3.24 mmol g-1 at CO2 400 ppm and 20% RH), the functionalized sorbent (fGO) features clear competitive advantages over current technologies for direct air capture. Notably, fGO demonstrated unprecedented moisture-swing capacity, ease of regenerability, versatility, selectivity, and longevity. These distinctive features position the fGO as an advanced and promising solution, showcasing its potential to outperform existing methods for moisture-swing direct air capture of CO2.

Expanding the Library of Ions for Moisture-Swing Carbon Capture

Developing materials that can more efficiently and cheaply capture carbon dioxide from ambient atmospheric conditions is essential for improving negative emission technologies. This study builds on the promising moisture-swing modality for direct air capture of carbon dioxide by investigating the use of several new anions─orthosilicate, borate, pyrophosphate, tripolyphosphate, and dibasic phosphate─that when introduced into ion-exchange resins allow for the cyclable capture of CO2 under dry conditions and its release under wet conditions. These ions, as well as many others that failed to show moisture-swing performance, are tested and directly compared thermodynamically and kinetically to understand their differences. This includes the use of analytical approaches new to the carbon capture field, such as the correlation of adsorption isotherms to moisture-swing performance, the use of phase lag kinetics, the examination of the humidity-carbon capture hysteresis of the sorbents, and the precise quantification of ion loading using inductively coupled plasma-optical emission spectroscopy. Phosphate dibasic was found to have the largest mass-normalized CO2 moisture-swing capacity, whereas phosphate tribasic had the best performance when factoring in kinetics, and pyrophosphate had the highest swing capacity when normalizing on a per-ion or per-unit-charge basis. This work not only sheds light on ways to improve DAC but also provides insights pertinent to the advancement of gas separation, negative emission technologies, and sorbent materials.

Covalent organic frameworks for CO2 capture: from laboratory curiosity to industry implementation

CO2 concentration in the atmosphere has increased by about 40% since the 1960s. Among various technologies available for carbon capture, adsorption and membrane processes have been receiving tremendous attention due to their potential to capture CO2 at low costs. The kernel for such processes is the sorbent and membrane materials, and tremendous progress has been made in designing and fabricating novel porous materials for carbon capture. Covalent organic frameworks (COFs), a class of porous crystalline materials, are promising sorbents for CO2 capture due to their high surface area, low density, controllable pore size and structure, and preferable stabilities. However, the absence of synergistic developments between materials and engineering processes hinders achieving the qualitative leap for net-zero emissions. Considering the lack of a timely review on the combination of state-of-the-art COFs and engineering processes, in this Tutorial Review, we emphasize the developments of COFs for meeting the challenges of carbon capture and disclose the strategies of fabricating COFs for realizing industrial implementation. Moreover, this review presents a detailed and basic description of the engineering processes and industrial status of carbon capture. It highlights the importance of machine learning in integrating simulations of molecular and engineering levels. We aim to stimulate both academia and industry communities for joined efforts in bringing COFs to practical carbon capture.