How tetracycline molecules shape their own capture on biochar
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How tetracycline molecules shape their own capture on biochar

07/05/2026 TranSpread

Studying five common tetracycline congeners on rice-straw-derived biochar, the researchers found that hydrogen bonding between the antibiotics’ amide –NH2 groups and carbonyl C=O groups on biochar is the dominant adsorption mechanism. They also showed that substituent groups on the antibiotic molecules can either strengthen or weaken this interaction, producing a clear adsorption-rate order of doxycycline > minocycline > tetracycline > methacycline > oxytetracycline.

Tetracycline antibiotics are widely used in medicine, livestock production, and aquaculture, yet a substantial fraction enters the environment unmetabolized, where it can disrupt ecosystems and promote antibiotic resistance. These compounds have been detected in wastewater plants, rivers, and surface waters, and conventional filtration methods often fail to remove them effectively. Biochar has emerged as a promising low-cost adsorbent for tetracycline removal, and its performance has been widely reported. However, earlier studies largely treated tetracyclines as a single class, overlooking the fact that even small structural differences among congeners can alter charge behavior, hydrophobicity, electron distribution, and binding to biochar surfaces. This knowledge gap has limited the rational design of biochar materials for targeted pollutant capture.

A study (DOI:10.48130/bchax-0026-0007) published in Biochar X on 13 February 2026 by Jing Fang’s team, Zhejiang University of Science and Technology, offers a route to designing more selective, high-efficiency biochar adsorbents for removing antibiotic pollutants from wastewater and contaminated aquatic environments.

The team prepared BC700 by pyrolyzing rice straw at 700 °C and tested its interactions with tetracycline, oxytetracycline, minocycline, methacycline, and doxycycline. Batch adsorption experiments examined equilibrium behavior and pH effects, while FTIR and two-dimensional FTIR correlation spectroscopy tracked how nitrogen- and oxygen-containing functional groups changed before and after adsorption. These measurements showed that at low tetracycline concentration, the antibiotic’s –NH2 group preferentially bonded first to carboxyl C=O sites and then to ketone or ester C=O groups. At higher concentrations, this selectivity became less distinct, suggesting that crowding at the biochar surface reduced site preference. The experiments also confirmed that pH strongly affected adsorption, with low-concentration tetracycline being removed efficiently across pH 3–9, while higher concentrations showed more variable removal. The researchers then modeled adsorption kinetics and found that all five antibiotics followed a double-exponential model, indicating both fast and slow adsorption phases. Doxycycline and minocycline adsorbed the fastest, while oxytetracycline was slowest. To explain these differences, the team combined density functional theory calculations, literature-derived molecular descriptors, principal component analysis, and multiple linear regression. They compiled 11 structural descriptors, including orbital energies, dipole moment, polarizability, dissociation constants, and hydrophobicity. The analysis showed that electron-donating R1 substituents such as −N(CH3)2 and favorable R3 substituents enhanced BC700-induced electronic polarization, increased electron density around –NH2, and strengthened hydrogen bonding. In contrast, electron-withdrawing or unfavorable R2 substituents hindered these processes. The resulting predictive models linked structural principal components to adsorption-rate constants with very high goodness of fit, showing that molecular structure can be used to forecast adsorption behavior quantitatively.

Overall, the study shows that tetracycline removal by biochar is not controlled by a single universal mechanism, but by a structure-dependent interaction landscape in which functional groups and electronic features determine how strongly each congener binds. By revealing why some tetracyclines adsorb faster than others and by building predictive structure–adsorption models, the work provides both a mechanistic foundation and a practical framework for tailoring biochar adsorbents to remove antibiotic contaminants more efficiently from water.

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References

DOI

10.48130/bchax-0026-0007

Original Source URL

https://doi.org/10.48130/bchax-0026-0007

Funding information

This work was funded by the National Natural Science Foundation of China (Grant No. 42577019) and the Basic Operational Fund of Zhejiang University of Science and Technology (Grant No. 2025QN051).

About Biochar X

Biochar X is an open access, online-only journal aims to transcend traditional disciplinary boundaries by providing a multidisciplinary platform for the exchange of cutting-edge research in both fundamental and applied aspects of biochar. The journal is dedicated to supporting the global biochar research community by offering an innovative, efficient, and professional outlet for sharing new findings and perspectives. Its core focus lies in the discovery of novel insights and the development of emerging applications in the rapidly growing field of biochar science.

Title of original paper: Molecular structure-dependent adsorption mechanisms of tetracycline antibiotics congeners on biochar
Authors: Jiayi Yao1,2, Jihao Ji1, Jiahong Zhang1 & Jing Fang1,2
Journal: Biochar X
Original Source URL: https://doi.org/10.48130/bchax-0026-0007
DOI: 10.48130/bchax-0026-0007
Latest article publication date: 13 February 2026
Subject of research: Not applicable
COI statement: The authors declare that they have no competing interests.
Attached files
  • Figure 3. Adsorption kinetics of TCs on BC700 and the impacts of TCs dissociation species. (a) Adsorption kinetic profiles of five TCs at 60 mg·L−1 onto 4 g·L−1 BC700 at pH 7. (b), (c) Fast-stage (k1), and slow-stage (k2) adsorption rate constants fitted by DEM. (d) Dissociation functional moieties of TCs and their corresponding pKa values. (e)–(i) pH-dependent speciation distributions of TC, MTC, OTC, MNC, and DC. (j) Pearson correlation coefficients between the relative abundances of TCs neutral (α2), and monoanionic (α3) species with k1 and k2.
07/05/2026 TranSpread
Regions: North America, United States, Asia, China
Keywords: Applied science, Engineering

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