The review, authored by Asma Nouira of the University of Évora and University of Tunis El Manar and Imene Bekri-Abbes of the CNRSM Technopole of Borj Cédria, systematically analyzes how different carbon structures transform the properties of polyaniline, known to materials scientists as PANI. The numbers are striking. A composite of polyaniline anchored covalently inside a three-dimensional porous skeleton of reduced graphene oxide and helical carbon nanotubes achieved a specific capacitance of 696.75 farads per gram, compared with 274.75 farads per gram for pure PANI. More dramatically, the composite retained 93.57 percent of its capacitance over 3,500 charge-discharge cycles, while the pristine polymer managed only 72.3 percent retention after just 2,500 cycles.

The roots of the problem lie in polyaniline’s own chemistry. The rigid conjugated backbone that makes the polymer electrically conductive also renders it mechanically brittle, prone to cracking and delamination when strained. Its highly conductive emeraldine salt form is stable only below pH 4, which severely limits biomedical and environmental uses that operate near neutral conditions. During electrochemical cycling, the polymer swells and contracts with each doping and dedoping event, generating mechanical stress that destroys films over time. And because PANI chains aggregate into densely packed granules, many potentially useful electroactive sites are simply locked away from the electrolyte.

Carbon nanomaterials attack each of these weaknesses in a different way. One-dimensional carbon nanotubes act as electron highways, allowing charge to travel through the nanotube network rather than relying solely on the polymer backbone, while simultaneously reinforcing the composite like nanoscale rebar. Two-dimensional graphene offers exceptional conductivity and mechanical strength, though its pristine hydrophobic surface must usually be functionalized, most commonly through oxidation to graphene oxide and subsequent reduction, to disperse in water and bind with aniline monomers. Zero-dimensional carbon dots and graphene quantum dots introduce quantum confinement effects and, when covalently linked to aniline molecules before polymerization, serve as multifunctional crosslinking nodes that prevent chain aggregation.

The choice of synthesis route turns out to matter as much as the choice of carbon. In situ polymerization, in which aniline is polymerized directly in the presence of dispersed carbon nanomaterials, remains the most scalable and industrially viable method, though achieving uniform dispersion at large volumes is challenging. Electrochemical polymerization offers exquisite control over film thickness and doping level by driving aniline oxidation on a conductive substrate with cyclic voltammetry, but it is fundamentally limited to thin films on conducting electrodes. Microwave-assisted synthesis, which heats polar molecules directly through dielectric heating, can be extraordinarily fast: one recent study prepared CNT/Ag/PANI composite electrodes in just 50 seconds.

More exotic techniques push performance further. Cryo-polymerization carries out oxidative polymerization at temperatures between minus 20 and minus 78 degrees Celsius, using growing ice crystals as a sacrificial template to create lightweight, three-dimensional macroporous aerogels. Composites of polyaniline with carbon nanofibers made this way reached gravimetric capacitances of 201 farads per gram, three to six times higher than carbon-fiber-free counterparts. Gamma radiation-assisted fabrication, meanwhile, generates free radicals that initiate polymerization and crosslinking without any chemical oxidant, a clean route recently used to produce flexible energy-storage electrodes from sugarcane bagasse waste.

Perhaps the strongest message of the review is that covalent bonding between the polymer and its carbon scaffold yields qualitatively better materials than simple physical mixtures. Where the two phases are chemically linked, phase separation and delamination under mechanical load largely disappear. The synergy is visible across applications: a ternary composite of polyaniline, reduced graphene oxide and single-walled carbon nanotubes raised electrochromic optical contrast from 0.38 to 0.52 and cut switching times to as fast as 0.78 seconds, enabling smart windows and low-power displays that change color on demand.

The applications extend well beyond electronics. Nitrogen-rich polyaniline binds carbon dioxide through acid-base and dipole-quadrupole interactions, and when combined with hierarchically porous carbon aerogels containing ultramicropores of 0.54 to 0.64 nanometers, it achieved a CO2 capture capacity of 6.04 millimoles per gram. In microbial fuel cells, a polyaniline coating on a covalent organic framework-carbon nanotube cathode delivered power densities 8.65 times higher than a blank cathode, using bacteria to convert wastewater organic matter into electricity. Magnetic activated carbon composites functionalized with polyaniline removed lead ions from water at 348.39 milligrams per gram, while biomass-derived activated carbons from coconut husk and date seeds are turning agricultural waste into supercapacitor electrodes with retention above 98 percent after 50,000 cycles.

The review’s authors are candid about what still stands between the laboratory and the factory. Long-term operational stability under realistic conditions, with high current densities, neutral pH and repeated mechanical deformation, remains poorly characterized, and few studies subject materials to simultaneous electrochemical and mechanical fatigue. Only in situ polymerization is currently suitable for tonne-scale production; covalent conjugation, despite its superior interfacial quality, has been demonstrated only at milligram-to-gram scale and relies on hazardous solvents and coupling reagents. The authors also point to machine learning as an underexploited accelerator: with a design space spanning carbon type, dimensionality, loading, dopant acid and processing parameters, data-driven models trained on hundreds of composite systems could predict conductivity and sensing performance far faster than trial-and-error experimentation.

What emerges from the analysis is a portrait of a mature field at an inflection point. The fundamental science, linking the dimensionality and surface chemistry of carbon nanomaterials to the electrochemical, mechanical and optical behavior of the resulting composites, is now well established. Biomass-derived porous carbons, green oxidants and continuous-flow reactors are beginning to address the sustainability deficits of conventional synthesis. If scalable manufacturing and rigorous durability testing catch up with the materials themselves, polyaniline’s century-and-a-half-long journey from an obscure blue-black precipitate to the backbone of flexible supercapacitors, electrochromic windows and carbon-capturing aerogels may finally reach its commercial destination.

Subject of Research: Polyaniline-carbon nanocomposite synthesis, properties and emerging applications

Article Title: Design and functional performance of polyaniline-carbon nanocomposites: synthesis, properties, and emerging applications

Article References: Nouira, A., & Bekri-Abbes, I. (2026). Design and functional performance of polyaniline-carbon nanocomposites: synthesis, properties, and emerging applications. Frontiers in Carbon, 5, Article 1925654. https://doi.org/10.3389/frcrb.2026.1925654

Image Credits: AI Generated

DOI: 10.3389/frcrb.2026.1925654

Keywords: polyaniline, carbon nanomaterials, supercapacitors, graphene, carbon nanotubes, electrochromic devices, CO2 capture, energy storage, nanocomposites, conducting polymers, biomass-derived carbon, electrochemical stability

The research team, led by Wojciech Jerzak of AGH University of Krakow, pyrolyzed both materials at 700, 800 and 900 degrees Celsius in a fixed-bed reactor flushed with high-purity nitrogen. Each 1.5-gram sample was held at the target temperature for one hour, after which the resulting chars were ground, sieved and subjected to a battery of analytical techniques including Fourier-transform infrared spectroscopy, X-ray diffraction, X-ray fluorescence, scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy and nitrogen sorption analysis. Carbon dioxide uptake was then measured at 20 degrees Celsius across pressures ranging from 0.5 to 110 kilopascals.

The starting materials could hardly have been more different. Chicken manure, collected from a poultry farm in southern Poland, contained just 8 percent fixed carbon but a hefty 26.4 percent ash, along with 4.1 percent nitrogen. Onion peels from a processing facility in the Kuyavian-Pomeranian Voivodeship were richer in combustible material, with 56.4 percent volatile matter, 14.9 percent fixed carbon and a lignocellulosic structure containing substantial cellulose and hemicellulose. X-ray fluorescence showed that calcium oxide dominated the ash of both feedstocks, at 48.8 percent for the manure and 40.8 percent for the peels, but the manure also carried elevated potassium, phosphorus, magnesium and sulphur, while the peels were unusually rich in silica at 33.8 percent.

As pyrolysis temperature climbed, both feedstocks lost mass, moisture and volatile components while their ash fractions concentrated in the solid residue. Manure biochar ash content soared from 26.4 percent in the raw material to 65.2 percent at 900 degrees Celsius, while onion peel biochar ash rose from 14.9 to roughly 41.8 percent. Hydrogen contents in both biochars fell below 1 percent, and nitrogen in the manure chars dropped from 4.1 to between 1.1 and 1.8 percent, reflecting the thermal cracking of volatile compounds and the release of small nitrogenous molecules. Onion peel biochars, by contrast, concentrated carbon to around 50 to 52 percent, more than the manure chars managed, thanks to their lower initial mineral burden.

Spectroscopy traced the chemical evolution in fine detail. Infrared spectra showed the progressive disappearance of hydroxyl, aliphatic and carbonyl bands with rising temperature, signalling dehydration, decarboxylation and the growth of a condensed aromatic carbon matrix. Yet phosphate and carbonate signals persisted in the manure-derived chars, underscoring the thermal stability of their inorganic constituents. X-ray diffraction revealed dramatic mineral reorganisation: at 700 degrees Celsius the manure char held quartz, portlandite and rutile, but by 800 and 900 degrees Celsius the ash had transformed into calcium oxide, whitlockite-type calcium-magnesium phosphates, magnesite, oldhamite and eventually sulfoapatite. The onion peel chars followed a different path, developing graphitic carbon alongside quartz, kalsilite, sodium carbonate and, at the highest temperature, the stable alkali aluminosilicate sanidine.

Electron microscopy captured the morphological consequences. Manure biochars remained dense, heterogeneous aggregates with no well-defined pore network, their high mineral content apparently filling or masking the developing carbon porosity. The onion peel chars told a more elegant story: at 700 degrees Celsius they retained elongated, layered fragments of the original plant tissue, and at 800 degrees Celsius they developed a striking channel-like structure the authors liken to a fish skeleton, with aligned, interconnected spaces carved out by devolatilisation. At 900 degrees Celsius, however, that ordered architecture began to fragment and partially collapse, a warning that excessive heat can destroy the very structure adsorbent designers hope to build.

Porosity measurements quantified these visual impressions. The onion peel biochar produced at 900 degrees Celsius achieved the highest specific surface area of the entire study, 109.8 square metres per gram—more than three times that of its 800-degree counterpart and nearly 6.5 times that of the 700-degree sample—with micropores contributing up to 60 percent of the internal surface in the intermediate-temperature samples. Manure biochars reached more modest areas between 14.0 and 36.2 square metres per gram, but their average pore diameter also shrank steadily with temperature, indicating progressive micropore refinement.

The carbon dioxide adsorption results upended the expectation that bigger surface area always means better capture. Among the onion peel chars, the 700-degree sample—despite its modest 17 square metres per gram—delivered the highest uptake, 26.6 cubic centimetres per gram at 100 kilopascals, while the 900-degree sample with the largest surface area actually adsorbed less. The researchers attribute this to pore widening and a shrinking population of narrow ultramicropores, those cavities below 0.7 nanometres whose dimensions closely match the kinetic diameter of CO2 and which nitrogen adsorption at cryogenic temperatures cannot fully resolve. Residual oxygen-containing surface groups may also enhance CO2-surface interactions in the cooler char.

The manure biochars behaved in almost mirror-image fashion, with CO2 uptake rising steadily as pyrolysis temperature increased, tracking the growth of microporosity and surface area. But texture alone could not explain the performance of the 900-degree manure char, which captured substantial CO2 despite a smaller surface area than its onion peel rivals. X-ray diffraction and fluorescence pointed to the missing piece: calcium oxide and calcium-rich phosphate phases that furnish basic adsorption sites with a strong affinity for acidic CO2 molecules, potentially even fixing some of the gas chemically as carbonate or bicarbonate species. In these mineral-rich chars, capture is a partnership between physical pore-filling and mineral-assisted interaction.

The practical lesson is that biochar design must be matched to feedstock chemistry. For lignocellulosic wastes like onion peels, the goal should be preserving narrow micropores rather than maximising total surface area, and avoiding the pore widening and structural collapse that come with excessive heat. For manures, engineers should exploit the inherent calcium, magnesium and potassium phases that add a chemical dimension to capture. Converting two problematic wastes into tailored carbon sorbents in a single thermal step offers a double dividend—waste valorisation and carbon management—grounded not in exotic chemistry but in a careful reading of what heat does to the organic and mineral halves of agricultural residue.

Subject of Research: Thermal conversion of chicken manure and onion peels into biochars for carbon dioxide adsorption

Article Title: Effect of thermal treatment on the structure and CO2 adsorption capacity of biochar from chicken manure and onion peels

Article References: Jerzak, W., Dutka, B., Sokołowski, K., Wilk, A., Chwiej, J., Gajek, M., Kalemba-Rec, I., Cierpińska, M., & Magdziarz, A. (2026). Effect of thermal treatment on the structure and CO2 adsorption capacity of biochar from chicken manure and onion peels. Clean Technologies and Environmental Policy, 28(10), Article 244. https://doi.org/10.1007/s10098-026-03598-2

Image Credits: AI Generated

DOI: 10.1007/s10098-026-03598-2

Keywords: biochar, pyrolysis, CO2 capture, chicken manure, onion peels, carbon adsorption, microporosity, mineral phases, waste valorisation, X-ray diffraction, Raman spectroscopy, surface area

The study, published in Results in Chemistry, was built around a modelling dataset of 1,047 observations spanning 24 input descriptors and five performance targets: maximum adsorption capacities for lead, cadmium, hexavalent chromium and trivalent arsenic in water, plus gas-phase CO₂ uptake. The descriptor set covered feedstock composition, pyrolysis temperature, heating rate, residence time, BET surface area, pore-volume fractions, elemental composition, H/C and O/C ratios, pH, and iron loading. The team fitted random forest and gradient boosting models to each target separately, then combined them into a simple arithmetic ensemble that served as a transparent surrogate for interpretation and optimization.

Predictive performance was respectable across the board. The ensemble achieved holdout R² values of 0.852 for Pb²⁺, 0.806 for Cd²⁺, 0.741 for Cr(VI), 0.710 for As(III) and 0.818 for CO₂, and repeated cross-validation over ten train/test splits confirmed the rankings with standard deviations of only about 0.02. The lower accuracy for chromium and arsenic is chemically informative rather than merely a modelling failure: these species exist in more complex aqueous forms, involving oxyanions, redox transformations and surface-bound reduction, that bulk descriptors such as total iron or pH cannot fully represent. Lead and cadmium, by contrast, are both divalent cations whose uptake is governed by shared mechanisms like cation exchange, complexation and mineral precipitation, which are better captured by the available variables.

The heart of the paper lies in how the authors interpreted their models. Rather than relying on unsigned feature importance, which reveals what matters but not in which direction, they computed signed SHAP values for each target and combined normalized magnitude with a stable direction derived from Spearman correlations between feature values and their SHAP contributions. Each descriptor was then classified as cooperative, conflicting, target-specific or negligible according to a prespecified 2 percent materiality threshold. The result was a clean cross-target taxonomy that no single-target study could have produced.

One descriptor stood out above all the rest: iron loading. Across every split and every tested threshold, iron emerged as the sole genuine conflict descriptor, showing materially positive signed effects on all four heavy-metal targets and a materially negative effect on CO₂. The chemistry is plausible. Iron oxides and hydroxides supply inner-sphere complexation sites for arsenic, promote reduction and co-precipitation of chromium species, and enhance binding of divalent metals. Yet the same deposits can occupy pore mouths and reduce the ultramicropore volume that low-pressure CO₂ adsorption depends on. Partial-dependence analysis quantified the penalty: predicted CO₂ capacity fell continuously by 0.751 mmol/g across the iron range, with the decline steepening modestly around 6 to 7 wt% iron.

The remaining descriptors sorted into chemically coherent categories. BET surface area was the only consistently cooperative descriptor, helping both objective families, while nitrogen content, micropore volume and pyrolysis temperature were CO₂-specific, and oxygen content was classified as heavy-metal-specific because its small negative CO₂ association fell below the materiality cutoff. Intriguingly, that oxygen classification proved threshold-dependent, flipping to conflict at a 1 percent cutoff in most splits, a nuance the authors flag rather than hide. The distinction between BET area and micropore volume is particularly useful for design: total accessible surface helps everything, whereas narrow-pore confinement is selectively valuable for gas adsorption.

What elevates the work beyond feature ranking is its optimization layer. Using multi-objective tree-structured Parzen estimation over 1,000 trials, with candidates constrained to stay near the empirical data cloud, the team generated a Pareto front of 27 nondominated biochar configurations that separated into three regimes. Carbon-dioxide-oriented candidates in Regime A reached 8.06 to 8.95 mmol/g of CO₂ with low metal performance; Regime B occupied a balanced middle ground; and metal-oriented Regime C candidates pushed the four-metal objective above 222 mg/g while sacrificing CO₂ uptake. No configuration maximized everything, confirming that the trade-off is structural rather than an artefact of model choice.

The authors are notably candid about limits. The dataset is a synthetic benchmark calibrated to published ranges, not raw experimental measurements, and the original generation code and category label mappings were not recoverable. Target-shuffle controls ruled out trivial implementation leakage, and feature-permutation tests showed the models depend heavily on the encoded iron, oxygen, nitrogen and textural relationships, but those relationships cannot be declared experimentally true without laboratory verification. The framework is therefore presented as a hypothesis-generating screening map, complete with a falsifiable validation matrix: matched iron-loading series around the 6 to 7 wt% transition, BET-matched activation comparisons, XPS-resolved nitrogen speciation studies, and blind testing of Pareto candidates across independent laboratories.

Even with those caveats, the framework points to something the field has needed: a transparent way to decide, before synthesis begins, which descriptor benefits every function, which serves only one, and which demands an explicit sacrifice. For water treatment, iron-modified biochar remains an excellent choice. For carbon capture, the message is that iron should be left out and porosity and nitrogen prioritized instead. For anyone hoping to have both, the balanced regime offers realistic but conditional middle ground, and the paper’s constraint flags show exactly where optimization pressure runs ahead of the evidence. In turning a well-known qualitative tension between heavy-metal adsorption and CO₂ capture into signed, stability-tested, decision-ready numbers, the study exemplifies how interpretable machine learning can convert accumulated adsorption chemistry into actionable cross-target design guidance, provided that the next word belongs to the experimentalists.

Subject of Research: Quantifying trade-offs between heavy-metal adsorption and CO₂ capture in dual-function biochar using interpretable machine learning

Article Title: Quantifying heavy-metal adsorption-CO₂ capture trade-offs in dual-function biochar using interpretable machine learning

Article References: Bhadre, A. A., & Ghongade, H. P. (2026). Quantifying heavy-metal adsorption-CO₂ capture trade-offs in dual-function biochar using interpretable machine learning. Results in Chemistry, 30, Article 103829. https://doi.org/10.1016/j.rechem.2026.103829

Image Credits: AI Generated

DOI: 10.1016/j.rechem.2026.103829

Keywords: biochar, heavy-metal adsorption, CO₂ capture, interpretable machine learning, SHAP, Pareto optimization, iron loading, partial dependence, water remediation, porous carbon, pyrolysis, materials informatics