Quantum-mechanical LSERs for the concentration-dependent adsorption of aromatic organic compounds by activated carbon: Applications and comparison with carbon nanotubes

Carbon nanotubes (CNTs) have taken precedence over activated carbon in various applications where adsorption is the primary process. The adsorption of chemical compounds by CNTs and activated carbon is most often predicted through linear free energy/solvation energy relationships (LFERs/LSERs). This work proposes quantum-mechanical LSER models based on a combination of quantum-mechanical descriptors and solvatochromic descriptors of LSERs for predicting the adsorption of aromatic organic compounds by activated carbon at varying adsorbate concentrations. The models are validated using state-of-the-art procedures employing an external prediction set of compounds. This work reveals the hydrogen bond donating and accepting ability of compounds to be the most influencing – but a negative – factor in the adsorption process of activated carbon. The quantum-mechanical LSERs proposed in this work are analysed and found to be equally reliable as the existing LSERs. These were further used to predict the adsorption of nucleobases, steroid hormones, agrochemicals, endocrine disruptors and pharmaceutical drugs. Notably, agrochemicals and endocrine disruptors are predicted to be adsorbed more strongly by activated carbon when compared with their adsorption by CNTs. However, quantum-mechanical LSERs predict the adsorption strength of biomolecules on activated carbon to be similar to that on the CNTs, which can be used to assess the risk associated with using carbon materials.

碳纳米管（CNTs）在以吸附为核心工艺的各类应用中，已逐步取代活性炭成为主流材料。针对碳纳米管与活性炭对化学化合物的吸附性能，当前最常用的预测方法为线性自由能/溶剂化能关系（LFERs/LSERs）。本研究提出了结合量子力学描述符与LSER溶剂化显色描述符的量子力学型LSER模型，用于预测不同吸附质浓度下活性炭对芳香族有机化合物的吸附行为。该模型通过采用外部化合物预测集的当前最先进流程完成验证。本研究发现，化合物的氢键给体与受体能力是影响活性炭吸附过程的最关键因素，但该因素对吸附表现为负面作用。经分析，本研究提出的量子力学型LSER模型与现有LSER模型具有同等可靠性。该模型被进一步用于预测核碱基、类固醇激素、农用化学品、内分泌干扰物以及药物的吸附性能。值得注意的是，相较于碳纳米管，农用化学品与内分泌干扰物更易被活性炭吸附；而量子力学型LSER模型预测得出，生物分子在活性炭与碳纳米管上的吸附强度相近，这一结论可用于评估碳基材料应用相关的风险。