A plant-receptor-inspired cuprous complex for wearable trace-level ethylene gas sensing

Domain: neuroscience
Published: 2026-04-08
Editorial outcome: major_revision

Abstract
Ethylene (C2H4) functions both as a key phytohormone regulating plant growth and development and as an essential feedstock in organic chemical synthesis. Reliable detection of C2H4 is critical for monitoring emissions during crop cultivation and ensuring safety in industrial transportation. However, most existing C2H4 sensors rely on noble-metal catalysts and/or high-operating temperature, which significantly constrain their practical applications. Moreover, achieving high specificity in C2H4 recognition remains a major challenge. Inspired by the signal transduction mechanism of plant C2H4 receptor, this study propose a biomimetic sensing strategy based on a facilely synthesized cuprous-cystine complex (Cu2Cyt), which features a sulfur-bridged Cu+ coordination center that mimics the biological binding site for C2H4 recognition. The noble-metal-free wearable sensor was fabricated by depositing a Cu2Cyt/MXene composite onto a flexible interdigital electrode, enabling room-temperature detection of C2H4 emitted from fruits or leaked from transport pipelines of chemical industries. It exhibits a detection range (0.05-5 ppm), an ultra-low detection limit of 1.07 ppb, fast response/recovery (51/92 s), high sensitivity of 3.64%·ppm-1 in trace concentration range of 0-0.5 ppm, and good reversibility and reproducibility. Overall, this work offers a bioinspired design strategy for low-cost, high-performance, noble-metal-free, and wearable sensors, capable of trace-level C2H4 monitoring.

Introduction
Ethylene (C2H4) plays a dual role as both a pivotal plant hormone regulating growth and development, and as one of the most widely produced industrial chemicals, primarily used in the manufacture of plastics and polymers1,2. In the agricultural field, understanding C2H4 dynamics is essential for optimizing harvest timing, improving storage conditions, and enabling early detection of spoilage or stress-induced responses. Meanwhile, in industrial settings, unintended C2H4 leakage from transportation pipeline not only leads to resource loss but also poses safety risks3. Therefore, the development of a highly sensitive and selective C2H4 detection system holds significant value for postharvest quality control, plant physiological research, and safety management in chemical industries.

Traditional C2H4 detection technologies, such as gas chromatography (GC)4, fluorescence spectroscopy5, and photoacoustic spectroscopy6, offer high analytical precision. However, their reliance on bulky instrumentation, labor-intensive sample preparation, and stringent operational conditions greatly limits their feasibility for real-time and in-situ applications7,8. To overcome these limitations, various sensor-based approaches have been developed, including metal oxide semiconductor9, electrochemical10, and quartz crystal microbalance sensors11. While each exhibits specific advantages, most conventional C2H4 sensors suffer from inherent drawbacks such as mechanical rigidity, high operating temperature, and limited long-term durability. These characteristics hinder their integration into wearable platforms required for low-cost distributed deployment in smart agriculture and industrial pipeline monitoring12.

Chemiresistive sensors detect target gases by monitoring changes in the electrical resistance of sensing materials in response to varying gas concentrations13,14. Owing to their simple architecture, fast response, ease of miniaturization, and low manufacturing cost, these sensors have gained widespread use, especially in wearable and portable gas-sensing devices15,16. A wide array of sensing materials has been employed in chemiresistive platforms, including carbon-based nanomaterials (such as carbon nanotubes and graphene), conductive polymers (such as polyaniline and polypyrrole), and emerging two-dimensional materials such as MoS2 and MXenes17,18. Although the general sensing mechanisms are well understood, the specific pathways through which environmental factors (such as humidity and oxygen) interfere with sensor performance remain unclear. Moreover, high-cost noble metal catalysts (such as Pd, Pt, Ru) are commonly incorporated to enhance response and sensitivity via the Wacker-type oxidation mechanism19-21. Some low-cost catalysts, including catalytic overlayer (such as Cr2O3)22 and metal-organic complexes23 have also been explored to enhance surface oxidation and facilitate charge transfer upon C2H4 adsorption. Nevertheless, these catalytic systems involved oxidation mechanism often suffer from poor selectivity, particularly for reducing gases, thereby restricting their applicability in complex environments.

Recent studies have demonstrated the unique specificity and affinity of copper(I) compounds (such as Cu2O and Cu+-based metal-organic frameworks) toward C2H4, primarily due to the stable π-complexation between Cu+ and the C=C double bond in C2H4 24-26. These findings position Cu+ as a highly effective active center for selective C2H4 detection. This chemical specificity finds a remarkable parallels in plant biology, where C2H4 receptor proteins localized on the endoplasmic reticulum serve as evolutionarily optimized modules for C2H4 recognition27,28. The primary recognition center is widely considered to be disulfide-linked homodimers coordinated with chelating Cu+ cofactors. Such biological precision in trace C2H4 recognition offers compelling biomimetic inspiration for the development of Cu+-mediated wearable sensing technologies. In fact, a coordination compound structurally analogous to the biological recognition center has been chemically synthesized using L-Cysteine thiol and CuCl in defined stoichiometric ratios29,30. Leveraging this concept, bioinspired functional interfaces that mimic natural receptor structures represent a promising strategy for developing high-selectivity C2H4 sensors.

In this work, we present a biomimetic strategy for selective C2H4 recognition, inspired by plant receptor. As illustrated in Fig. 1, a Cu+ coordination complex (cuprous cystine, Cu2Cyt) with a peony-like morphology (Fig. 1a) was rationally designed to mimic the Cu⁺-coordinated active center of plant C2H4 receptors (Fig. 1b). To construct the sensing platform, MXene, a p-type two-dimensional semiconductor material, was employed as a conductive substrate to form a heterojunction with Cu2Cyt. Upon C2H4 binding, the formation of a Cu2Cyt(C2H4) complex induces electron transfer (ET) from the complex to MXene substrate, in which this process reduces the hole carrier density within MXene, resulting in a measurable increase in its electrical resistance. Such biomimetic recognition mechanism enables a concentration-dependent resistance response at room temperature, without the use of noble-metal catalysts. The sensing composite was integrated onto a flexible interdigital electrode (IDE) and systematically evaluated in performance. Furthermore, the sensing mechanism was elucidated through a combination of spectral analyses, theoretical calculations, and a response model that integrates Langmuir gas adsorption theory with semiconductor principles. Overall, this work demonstrates the successful translation of biological recognition principles into material design, offering a pathway for the development of low-cost, room-temperature, and wearable C2H4 sensors.

Results
The morphology and structure of sensing materials have an important effect on the performance of sensors. Scanning electron microscopy (SEM) revealed that the as-synthesized Cu2Cyt exhibits a peony flower-like architecture composed of micrometer-sized clusters (Fig. 2a, b). These clusters are assembled from nanoscale petal-like sheets containing carbon (C), nitrogen (N), copper (Cu), oxygen (O), and sulfur (S) elements (Fig. 2c). Nanosheets significantly increase the surface-to-volume ratio, while the open, petal-shaped configuration enhances the accessibility of target C2H4 molecules. To facilitate ET upon C2H4 binding, Cu2Cyt was composited with a small amount of two-dimensional MXene possessing a wrinkled morphology (Fig. S1). The resulting Cu2Cyt/MXene composite retains the characteristic flower-like morphology of Cu2Cyt (Fig. 2d), with MXene distributed around the Cu2Cyt clusters, as highlighted by the white-dotted region. The hierarchical structure is well-preserved (Fig. 2e), ensuring effective gas diffusion and adsorption. Elemental mapping of Ti (from MXene) further confirms the surface location of Cu2Cyt clusters atop the MXene background (Fig. 2f).

Low-magnification SEM images of the Cu2Cyt/MXene composites reveal the arrangement of multiple microflowers (Fig. S2a–b), indicating good structural uniformity on a larger scale. A side-view SEM image of an individual microflower is also provided to elucidate its internal composition and architecture (Fig. 2g). The structure forms a well-connected three-dimensional network composed of branched and sheet-like units with open channels, without noticeable aggregation or densely packed regions (Fig. 2h). Elemental mapping of a cross-sectional region further shows the presence of Ti within the interior of the microflowers (Fig. 2i), confirming that MXene, as a conductive component, is interwoven with Cu2Cyt nanosheets throughout the structure. This hierarchical porous architecture and cross-distributed composition create efficient pathways for gas diffusion and electron transport, thereby exposing more active sites and enhancing the sensing response.

High-magnification SEM images reveal neat petal edges with individual sheet thicknesses of ca. 50-100 nm (Fig. 2j). The smooth overlapping nanosheets form a porous network with nanoscale inter-sheet gaps, enabling gas molecules to access both external and internal surfaces. The N2 adsorption–desorption isotherms (Fig. S3) show that Cu2Cyt and Cu2Cyt/MXene composites possess BET surface area of 7.07 and 11.55 m2 •g-1 respectively. The slight increase confirms that a small amount of MXene effectively enhances the accessible surface area without disrupting the structural integrity. Notably, the characteristic of Cu2Cyt nanosheets accords with the requirement for the assumptions of Langmuir gas adsorption model, i.e., a uniform planar surface with no intermolecular interactions, dynamic equilibrium governed by partial pressure and surface coverage31,32.

High-resolution transmission electron microscope (HR-TEM) was employed to investigate the crystalline features of the petal-like Cu2Cyt structures. As shown in Fig. 2k, faint lattice fringes were observed, with interplanar spacings of 0.231, 0.282, 0.289 nm, indicating the presence of partially ordered domains within the otherwise amorphous or low-crystalline matrix. To further elucidate the crystal structure, X-ray diffraction (XRD) patterns were recorded for commercial L-Cysteine, the synthesized Cu2Cyt, and Cu2Cyt/MXene composite (Fig. 2l). The diffraction pattern of L-Cysteine matches well with the reference standard card (PDF #32-1636), confirming its phase purity. In contrast, Cu2Cyt exhibits a distinct set of diffraction peaks that differ from L-Cysteine but partially align with those of L-Cystine — the oxidized disulfide dimer of L-Cysteine — corresponding to the (100), (0018), (112) and (201) crystal planes of L-Cystine (PDF #37-1802). This suggests that Cu2Cyt adopts a structural motif analogous to L-Cystine, likely retaining the disulfide bond (S–S) as a bridging ligand in the Cu+ coordination environment. Moreover, the characteristic peaks of Cu2Cyt remain visible in the Cu2Cyt/MXene composite, with increased intensity (Fig. S4), indicating that the incorporation of a small amount of MXene enhances the crystallinity of Cu2Cyt and endows interaction between them. This also supports the conclusion that Cu2Cyt is distributed on the surface of MXene, in agreement with the SEM and elemental mapping results discussed earlier.

The Cu2Cyt complex was synthesized via the reaction between L-Cysteine and CuCl2 under alkaline conditions, as detailed in Methods section. In this system, NaOH promotes the deprotonation of the thiol group (‒SH) in L-Cysteine, generating a thiolate anion (–S⁻) with enhanced nucleophilicity for Cu2+ coordination. Due to the oxidizing nature of Cu2+, the –S⁻ simultaneously acts as a reducing agent, converting Cu2+ to Cu+ while being oxidized to form a S–S. The overall reaction is shown in Fig. 3a: 2C3H7NO2S + 4OH- + 2Cu2+ → Cu2C6H10N2O4S2 ↓ + 4H2O. The standard Gibbs free energy of this reaction was calculated to be -22.92 eV at B3LYP/def2-TZVP level of theory with Grimme’s D3 dispersion correction and Becke-Johnson damping, using Gaussian 16 program33, suggesting the process is thermodynamically favorable. The optimized structure of Cu2Cyt reveals that one Cu+ is coordinated to the carbonyl oxygens of the two carboxyl groups (‒C=O), as well as to the nitrogen atom of the amino group (‒NH2) and the sulfur atom of the cystine-derived disulfide bridge. The second Cu+ ion coordinates with the carbonyl oxygen of a single C=O and the amino nitrogen, forming a stable chelate structure resembling the C2H4-binding domain of plant C2H4 receptor.

To experimentally validate the formation mechanism of Cu2Cyt, molecular spectroscopy techniques were employed to analyze the relevant reactants and products. Raman spectra reveal the disappearance of the characteristic ‒SH stretching peak of L-Cysteine, accompanied by the appearance of a signal assigned to the S–S bond in Cu2Cyt (Fig. 3b). This confirms that L-Cysteine undergoes oxidative dimerization via S‒S linkage, forming a cystine-like molecular structure. Fourier transform infrared (FTIR) spectroscopy was further conducted to probe vibrational changes associated with functional group conversion and coordination interactions (Fig. S5). In the FTIR spectrum of L-Cysteine, bands at ~1540 cm-1 and ~1585/1395 cm-1 correspond to the bending vibration of ‒NH3+ and the asymmetric/symmetric stretching of –COO⁻, respectively34, reflecting its internal protonation of molecules. In commercial L-Cystine sample, there are similar bands at ~1621.9 cm-1 (symmetry bending vibration of ‒ NH3+ ) and ~1581.1/1406.7 cm-1 (the asymmetric/symmetric stretching of –COO⁻) due to internal protonation of molecules, as shown in Fig. 3c. Nevertheless, the spectrum of the prepared Cu2Cyt shows the disappearance of the ‒NH3+ bending band and the emergence of a signal assigned to –NH2 bending at 1619.7 cm-1, indicating that the ammonium group is deprotonated under alkaline conditions during complexation.

Notably, the majority of peaks of the prepared Cu2Cyt are consistent with those of L-Cystine sample, while several different points exist due to Cu coordination. Because transition metal atoms are relatively heavy, the related vibrations should be in the low-frequency region35, as shown in the enlarged area of Fig. 3c. Compared with L-Cystine, three peaks for Cu2Cyt newly emerge at 518.4, 502.5, and 489.9 cm⁻1, which are attributed to Cu–O, Cu–N, Cu–S coordination vibrations36,37, respectively, suggesting the formation of Cu-ligand bonds. In addition, the bending vibration of –COO⁻ in Cu2Cyt exhibits a redshift compared with that of L-Cystine, indicating that it is the heavier Cu(I) coordination in Cu2Cyt while it is the lighter ‒NH3+ coordination in L-Cystine. Furthermore, the redshift observed in the –COO⁻ bending vibration of Cu2Cyt, compared with that in L-Cystine, signifies the difference in cation coordination: the heavier Cu(I) coordinates in Cu2Cyt, whereas the lighter ‒NH3+ is involved in L-Cystine. These spectral features are consistent with the coordination structure predicted by DFT calculations, further corroborating the proposed binding mode of Cu+ with the ‒COO‒, ‒NH2, and ‒S‒S‒ in the Cu2Cyt complex.

X-ray photoelectron spectroscopy (XPS) was employed to investigate the elemental composition and chemical state of Cu2Cyt and Cu2Cyt/MXene composite. The survey spectrum of Cu2Cyt confirms the presence of C, N, O, S, and Cu elements, while an additional Ti signal is observed in the Cu2Cyt/MXene sample, originating from the MXene component. This is consistent with the elemental distribution observed in SEM-EDS mapping (Fig. S6). The high-resolution Cu 2p spectrum (Fig. 3d) displays two distinct peaks at 931.4 eV and 951.4 eV, corresponding to Cu 2p3/2 and Cu 2p1/2, respectively. The absence of satellite peaks between them suggests that the copper species predominantly exist in the +1 or 0 oxidation states—Cu(I) or Cu(0) — rather than Cu(II). Electron paramagnetic resonance (EPR) measurements were further conducted to support this conclusion (Fig. S7). As expected, no signal corresponding to paramagnetic Cu(II), which has an [Ar]3d9 electron configuration, is observed within the magnetic field range of 3000–3500 G38. In contrast, Cu(I) possesses a diamagnetic [Ar]3d10 configuration, and therefore its absence in the EPR spectrum is consistent with its electronic structure. Given the negligible binding energy difference (approximately 0.1 eV) between Cu(I) and Cu(0)39, it is difficult to unambiguously distinguish them by XPS alone. However, no characteristic metallic red color associated with Cu(0) was observed during synthesis. Instead, the as-prepared Cu2Cyt appeared as a milky yellow suspension, yielding a white precipitate after washing and centrifugation (inset of Fig. 3d). These visual observations, in agreement with prior reports30, support the assignment of Cu(I) as the dominant oxidation state in the metal complex.

The high-resolution S 2p spectrum of Cu2Cyt (Fig. 3e) shows two peaks at 163.4 eV and 164.5 eV, attributable to S 2p3/2 and S 2p1/2 of the S–S bond40, consistent with Raman results confirming oxidative dimerization of thiols. After mixing with MXene, the high-resolution C 1s spectrum of Cu2Cyt (Fig. 3f) shows no significant shift in the binding energies of the C=O, C‒O, C‒N/C‒S (Fig. S8), indicating that the chemical environment of Cu2Cyt remains unchanged. This suggests that the interaction between Cu2Cyt and MXene is primarily physical rather than covalent. To determine the semiconducting nature of MXene, Mott-Schottky analysis was performed (Fig. S9), which can reveal the relationship between the space charge layer capacitance and the applied potential (E)41. The resulting plot exhibits a negative slope (Fig. S10), confirming the p-type semiconductor behavior of MXene, which is crucial for facilitating hole modulation upon ET from the Cu2Cyt sensing layer.

The adsorption of C2H4 onto Cu2Cyt is a key factor influencing the selectivity of Cu(I)-based sensing systems. As the Cu2Cyt molecule contains two Cu+ centers capable of π-complexation with C2H4, the Gibbs free energy changes (∆Gads) for the adsorption of one and two C2H4 molecules were calculated to be -1.07 eV and -1.51 eV, respectively (Fig. 4a), indicating that dual-site adsorption is thermodynamically more favorable. In this process, the electron-rich C=C double bond of C2H4 interacts with the electron-deficient Cu+ centers, forming a π-complex through coordination. These results provide theoretical support for the high affinity of Cu2Cyt toward C2H4, confirming its potential as an effective sensing material. Detailed computational methods are provided in Section S2 of Supplementary Information. This specific binding mode mimics the C2H4 recognition mechanism found in plant receptor, wherein cysteine residues coordinate to chelated Cu+ ions to enable selective and sensitive detection.

Fig. 4b presents the charge redistribution behavior among MXene, Cu2Cyt, and C2H4 after C2H4 adsorption. A decrease in charge density is observed around 15 Å, corresponding to the spatial position of the C2H4 molecule, indicating electron donation from the C=C π-system to the Cu2Cyt complex. Concurrently, an increase in charge density in charge density near 14 Å, aligned with the Cu+ site, confirms that these electrons are partially accepted by the Cu+ center. Additionally, an increase in charge density is observed at approximately 8 Å, corresponding to the Cu2Cyt/MXene interface, suggesting that electrons are further transferred from Cu2Cyt complex to the underlying MXene substrate. These results collectively indicate a sequential ET pathway: electrons flow from C2H4 → Cu2Cyt → MXene. The total transferred charge, quantified by the charge displacement curve (Fig. S11), is estimated to be 0.43 e-.

Based on this charge redistribution, a sensing mechanism is proposed, as illustrated in Fig. 4c. In air, O (‒COO-) and H (‒NH2) of Cu2Cyt form hydrogen bond with H (Ti‒OH) and O (Ti‒O terminal), respectively. Upon exposure to C2H4, the gas molecules are specifically captured by the Cu+ active sites in Cu2Cyt, forming coordination structure of Cu(I)-C2H4 (d-π conjugation). Subsequent electron donation from C2H4 initiates cascade electron transfer by two potential pathways (marked with p1 and p2) through the Cu2Cyt complex into MXene. As a p-type semiconductor, MXene accepts these electrons into its vacant states, leading to an upward shift in the Fermi level, a reduced hole concentration, and an increase in electrical resistance. This resistance modulation serves as the measurable output signal for C2H4 detection. The hydrogen bonds can be evidenced by buleshift of Cu‒O vibriation and redshift of Cu‒N vibration (Fig. 4d). The former is caused by the increased electron density (O pulls electron from H of T‒OH), while the latter is due to the decreased electron density (N loses electron to O of Ti‒O terminal). Notably, Cu‒S vibration disappears due to the interaction between MXene and Cu2Cyt/MXene.

The interaction between MXene and Cu2Cyt can be also demonstrated by time-dependent XRD patterns after mixing for 1, 5, 10, and 30 min (Fig. 4e). The characteristic peak centered around 6.3 can be assigned to the (200) plane of MXene42, while that centered around 18.9 can be attributed to the (100) plane of Cu2Cyt. The intensities of both peaks show an increase (high crystallinity) from 1 to 5 minutes and then a decrease (low crystallinity) from 10 to 30 min. The time-dependent crystallinity variations can be attributed to interconnect caused by surface interactions, which has been illustrated in Fig. 2. Similarly, the time-dependent FTIR spectroscopies also demonstrate the interactions between MXene and Cu2Cyt (Fig. S12), because of the changing vibration modes caused by the formation of hydrogen bonds in the low frequency region along with time range of 1-30 min.

As shown in Fig. 4f, in-situ FTIR spectroscopies are further utilized to verify the dynamic recognition process of Cu2Cyt to ethylene gas described in Fig. 4c. The characteristic peaks at 1888.7 cm-1 and 1912.7 cm-1 can be assigned to the combination and double vibrations of =CH swing mode in Cu(I)-C2H4, respectively, while the characteristic peak at 949.8 cm-1 belongs to =CH swing mode43. These characteristic peaks emerged exclusively upon ethylene exposure, and their intensity increased progressively from 1 to 3 minutes. This trend illustrates the gradual capture of ethylene molecules by the active Cu(I) sites in Cu2Cyt. Notably, the peak intensity plateaued between 3 and 5 minutes, indicating that adsorption saturation was reached at approximately 3 minutes. This saturation time closely aligns with the response saturation time observed in the electrical measurements (~200 s), highlighting the effectiveness of in situ FTIR on illustrating the dynamic process of ethylene recognition.

The sensor was fabricated by drop-casting the Cu2Cyt/MXene composite onto an IDE patterned on a flexible polyimide (PI) substrate. Optical microscopy images confirm the uniform coverage of the sensing film across the electrode gaps (Fig. S13). The performance was tested on the gas sensor testing system as shown in Supplementary Fig. S14. Current-voltage (I-V) measurements at different C2H4 concentrations reveal a linear relationship in the range of 0-2 V (Fig. S15), indicating that an ohmic contact is formed between the Cu2Cyt/MXene layer and the IDEs44. To meet the low-power requirements of portable or outdoor applications, a low voltage of 0.1 V was selected for subsequent measurements. As shown in Fig. 4g, the Cu2Cyt/MXene sensor exhibits a distinct and rapid response toward C2H4, featuring a response magnitude of 3.3%, an approximate 100% recovery rate, and response/recovery times (defined by 90% signal change) of 51/92 s, respectively. The response and recovery rate are defined by equation (S1) and equation (S2), respectively, as presented in section S1 of Supplementary Information. In contrast, the pristine MXene sensor shows negligible response under the same conditions. Independent sensing tests of pure Cu2Cyt were not feasible due to its low conductivity (1.01×10-4 S•cm-1), confirming that Cu2Cyt alone cannot generate an electrical signal upon gas exposure. These results highlight the synergistic effect between Cu2Cyt and MXene, wherein Cu2Cyt serves as the selective recognition component, and MXene (3500 ± 500 S•cm-1) provides the conductive pathway for signal transduction via resistance change.

To optimize sensor performance, three parameters were systematically investigated: (i) the molar ratio of CuCl2 to L-Cysteine during Cu2Cyt synthesis, (ii) the molar ratio of Cu2Cyt to MXene, and (iii) the drop-casting volume. Optimal sensing behavior was achieved at a synthesis ratio of 2:10 (CuCl2 : L-Cysteine), a mixing ratio of 50:5 (Cu2Cyt : MXene), and a casting volume of 70 μL (Fig. S16). All subsequent measurements were conducted using electrodes prepared under these optimized conditions.

To comprehensively explore alternative sensing materials, we also evaluated other common transition-metal complexes, including those of cobalt (Co), nickel (Ni), and zinc (Zn), under the same optimized conditions. As shown in Fig. S17, these complexes exhibit detectable responses to ethylene; however, their responses are significantly weaker than that of the Cu-based complex. This contrast further underscores the unique advantage of the copper-centered design, consistent with the highly efficient ethylene-binding mechanism evolved in plants.

In open systems, C2H4 released by plants typically ranges from 0.05 to 0.5 ppm, and may even drop to ppb level45. Based on this, nine representative C2H4 concentrations within this range were selected to evaluate the concentration-dependent response behavior of the optimized Cu2Cyt/MXene sensor (Fig. 4h). In the dynamic response curves, purple-shaded regions indicate exposure to C2H4 (introduced at 180 s), while the remaining intervals correspond to ambient air flushing. The sensors exhibits a clear increase in response with rising C2H4 concentrations. However, at higher concentrations, particularly above 1 ppm, the response increment becomes less pronounced, suggesting a sublinear trend toward saturation (Fig. 4i). To quantitatively describe this behavior, a response model integrating Langmuir gas adsorption theory with semiconductor principle31,32,46, was developed, as shown in equation (1):

S(C) = (1 - β × KS ∙ C / 1 + K ∙ C) + γ (1)

where C is the C2H4 concentration, K is the adsorption equilibrium constant, β = α/P0, with α representing the hole depletion coefficient per adsorbed molecule, and P0 the intrinsic carrier concentration of the sensing material. The parameter γ = S(0) - 1, where S(0) is the baseline response. According to Langmuir theory, the response increases with concentration as more gas molecules are adsorbed, but approaches a plateau as active sites on the surface become saturated. The detailed derivation of this model is provided in Section S3 of Supplementary Information. Nonlinear regression fitting of the experimental data using equation (1) yields excellent agreement (red curve in Fig. 4i), with a determination coefficient R2 = 0.9909. The fitted parameters were: β = 0.88, K = 5.45, and S = -0.02. Notably, under the assumption that α and K remain constant, an increase in P0 (i.e., higher intrinsic hole density) would lead to a reduction in overall response amplitude, highlighting the importance of charge modulation in p-type semiconducting MXene.

At trace C2H4 concentrations, equation (1) can be simplified to a linearized equation (2) using a Taylor series expansion, as follows:

S(C) = (α ∙ K / P0) × C (2)

Remarkably, even beyond the trace-level concentration regime, this linearized model provides an excellent fit to the experimental data in the 0.05-0.5 ppm range, with a coefficient of determination R2 = 0.9928 (inset of Fig. 4i). The sensitivity (S), defined as the slope of the linear fit, is calculated to be 3.64% · ppm-¹. The limit of detection (LOD) was estimated using the standard formula LOD=3σ/S, where σ is standard deviation of the sensor tested for three times in air, yielding a remarkably low value of 1.07 ppb. This ultra-low LOD ensures reliable detection of C2H4 emissions at biologically relevant levels, such as those released by fruits and plants under postharvest or stress conditions. To comprehensively evaluate the practical viability of the Cu2Cyt/MXene sensor, further performance tests were conducted, including assessments of selectivity, repeatability, reproducibility, signal stability under mechanical deformation, and environmental robustness, as detailed below.

To investigate how the growth evolution of Cu2Cyt crystals influences sensing performance, we conducted time-series SEM characterization at key reaction intervals (5 min, 15 min, 30 min, 1 h, 2 h, and the final 3 h) and analyzed the corresponding particle-size distributions (Fig. 5). The size distributions were fitted using a Gaussian function, i.e. equation (3) below:

f(d) = A × exp[-(d - d̅)2 / 2σ2] (3)

where d is the particle diameter, f(d) is the probability density, 𝑑̅ and σ are the fitted mean diameter and standard deviation, respectively, and A is a normalization constant. The time-dependent SEM images reveal a clear morphological progression from initial aggregates to well-defined microflowers. At the early stage (5 min), small flake-like units densely stack into compact, nascent flower-like structures with an average particle size of 11.86 ± 2.28 µm (Fig. 5a). As the reaction proceeds to 15–30 min, the primary nanosheets undergo self-assembly through oriented attachment and intermolecular interactions. The petals begin to spread, the layered stacking becomes more distinct, the flower contours sharpen, and the overall structure becomes looser (Fig. 5b, c). Correspondingly, the particle size increases to 12.18 ± 2.37 µm (15 min) and 13.46 ± 3.72 µm (30 min).

Between 60 and 120 min, the petal dimensions further increase and the packing density becomes higher, yielding average particle sizes of 15.78 ± 2.98 µm (60 min) and 16.61 ± 3.84 µm (120 min) (Fig. 5d, e). By 180 min, however, the microflower structure becomes severely damaged, showing a coexistence of large agglomerates and nanofibrous fragments, with the particle size expanding to 20.76 ± 5.24 µm (Fig. 5f). The standard deviation increases from 2.28 µm to 5.24 µm, reflecting a continuous evolution from primary aggregates to mature flower-like assemblies, followed by excessive collapse (Fig. S18a-f).

The particle-size evolution is consistent with an Ostwald ripening process, in which smaller crystallites dissolve and re-deposit onto larger ones over time47, indicating that the synthesis is governed by thermodynamic control. Time-dependent XRD patterns confirm that the crystal structure remains unchanged throughout the growth process (Fig. S18g). The sensing response exhibits an initial increase followed by a decline, mirroring the morphological evolution (Fig. S18h). Because the improvement in response beyond 15 min was marginal, a reaction time of 15 min was selected for subsequent experiments.

To further elucidate how synthesis parameters steer this thermodynamic pathway, we systematically examined the effects of precursor concentration, reaction temperature, and pH (Figs. S19-S24). These results demonstrate that the morphology and particle size of the composite are strongly dictated by synthesis conditions, which in turn determine the sensing performance. Detailed analyses are provided in the Supplementary Information. Collectively, these insights offer a systematic foundation for the rational design of future multi-factor optimization strategies.

Selectivity is a vital parameter for practical gas sensors, especially in complex agricultural environments. The Cu2Cyt/MXene sensor was evaluated against six common agricultural gases, including ammonia (NH3), ethanol (EtOH), carbon dioxide (CO2), nitrogen dioxide (NO2), methane (CH4), and isoprene (C5H8) (Fig. 6a). The sensor exhibits a significant response of 3.3% to 1 ppm C2H4, whereas the responses to non-olefin gases were negligible even at a higher concentration, with specific values as follows: 0.54% to 5 ppm EtOH, 0.48% to 5 ppm CO2, 0.52% to 5 ppm NO2, 0.49% to 5 ppm CH4, and 0.51% to 50 ppm NH3. Notably, the sensor shows a moderate response of 1.3% to 1 ppm isoprene, another olefin gas (Fig. S25). However, in practical agricultural environments, interference from isoprene is negligible, as plants typically emit isoprene at ambient concentrations that are several orders of magnitude lower than those of ethylene48. This high selectivity to ethylene gas is attributed to the Cu2Cyt component, which highly mimics the biological evolved recognition mechanism of plant C2H4 receptor proteins.

The mechanical robustness of the Cu2Cyt sensor was evaluated through graded bending tests, including four levels: flat (0°), slightly bent (~45°), half-folded (~90°), and fully folded (~180°). As shown in Fig. 6b, the sensor retained over 99% of its original response under the slight bending states, and maintained approximately 80% of its performance even under 180° folding. These results confirm the excellent mechanical robustness and flexibility of the sensor, supporting its application in wearable and flexible agricultural monitoring applications. Repeatability was evaluated through six consecutive exposure–recovery cycles at 1 ppm C2H4 (Fig. 6c). The response values remained stable with a relative standard deviation (RSD) below 0.069%, indicating excellent operational repeatability. Furthermore, device-to-device reproducibility was verified across eight independently fabricated Cu2Cyt/MXene sensors. The measured responses showed minimal variation, with an RSD of 1.72% (Fig. 6d), demonstrating consistent fabrication quality and reliable sensing performance across batches.

The influence of temperature on sensor performance was investigated by exposing the Cu2Cyt/MXene sensor to 1 ppm C2H4 at five temperatures ranging from 0 ℃ to 50 ℃ (Fig. 6e). The response increased with temperature from 0 to a maximum at approximately 20 ℃, after which it gradually declined with further temperature rise. According to Equation (2), assuming a constant hole depletion coefficient α, the sensor response is directly proportional to the adsorption equilibrium constant K and inversely proportional to the intrinsic carrier concentration P0 of the MXene substrate. At lower temperatures (0-20 ℃), the increase in K dominates, likely due to enhanced gas adsorption, resulting in an overall rise in response. This suggests that adsorption-desorption kinetics play a leading role in this range. Instead, at elevated temperatures (20- 50 ℃), the thermally induced increase in P0 becomes dominant, which reduces the degree of charge modulation and thus suppresses the sensing signal. This competing relationship between adsorption affinity and semiconductor carrier dynamics results in a peak-shaped temperature–response curve, with an optimal operating temperature of approximately 20 ℃, where these effects are balanced.

The Cu2Cyt/MXene sensor was evaluated under controlled relative humidity (RH) conditions ranging from 10% to 80% to assess the influence of environmental moisture on sensing performance. As shown in Fig. 6f, the sensor response exhibits a slightly increase below 50% RH (range I), and is followed by a gradual decline above 50% RH (range II). The underlying mechanism was investigated through theoretical calculations, which were provided at the bottom of Fig. 6f. In range I, water molecules form dynamic hydrogen bonds with the exposed Cu+ of Cu2Cyt, inducing conformational expansion that exposes previously shielded Cu+ sites. This structural rearrangement enhanced the accessibility and adsorption efficiency for C2H4 49, as evidenced by a reduction in the adsorption Gibbs free energy to approximately 0.09 eV compared to the dry condition. Nevertheless, in range II, the presence of excessive water molecules leads to competitive adsorption on the Cu+ active sites of Cu2Cyt, which reduces the effective binding of C2H4 50, reflected by an increased adsorption Gibbs free energy (~0.12 eV higher than under dry conditions). In addition to humidity, molecular oxygen (O2) also influences sensing performance (Fig. 6g). After eight days of ambient exposure, O2 adsorbs onto the MXene surface and captures electrons to form superoxide radicals (O•- ), which modulate the electronic properties of the sensing layer51. This electron withdrawal effect increases the baseline carrier concentration P0, thereby diminishing the signal modulation capacity upon C2H4 exposure46. In contrast, sensors stored in an inert argon atmosphere exhibited a much slower decline in response, confirming the detrimental role of O2 adsorption. The bottom of Fig. 6g provides a diagrammatic explanation of this mechanism. To ensure long-term reliability in complex environments, it is recommended to incorporate hydrophobic surface modifications and antioxidant treatments, along with real-time environmental compensation algorithms, to maintain sensor stability and performance under fluctuating ambient conditions.

To evaluate its practical applicability, the Cu2Cyt/MXene sensing electrode was integrated with a miniaturized U-disc electrochemical workstation capable of wireless Bluetooth connection to a tablet, enabling portable, real-time C2H4 detection and data visualization in field environments (Fig. 7a). The system architecture is illustrated in Supplementary Fig. S26. The first demonstration focused on monitoring C2H4 emissions from fruits. A sealed transparent acrylic chamber was used to test apples and bananas individually and in combination (Fig. 7b). The sensor exhibited a stronger response to bananas than to apples, and the highest response when both fruits were present. These results highlight the sensor's high sensitivity and its ability to distinguish C2H4 emissions profiles from different fruit sources. This observation is consistent with the physiological characteristics of the two fruits. Bananas are classified as climacteric fruits and exhibit a positive feedback loop in C2H4 biosynthesis, leading to a rapid, a self-amplifying ripening process52,53. In contrast, C2H4 release from apples is modulated by endogenous hormonal antagonism and restricted by the fruit’s epidermal barrier, which suppresses immediate C2H4 surges to favor long-term storage54,55. To visually demonstrate the practical applicability of our sensors, the supplementary movies document the complete validation process (Supplementary Movies 1-3). These visual demonstrations, together with independent GC analysis confirming an ethylene concentration of 3.7 ppm in the fruit container (Fig. S27), provide strong scientific evidence that the Cu2Cyt/MXene sensor delivers a reliable and accurate response under practical conditions.

In addition, a wearable sensing configuration was evaluated under open-environment conditions to simulate practical, on-fruit monitoring scenarios. The Cu2Cyt/MXene electrode was affixed directly onto the surface of a mature apple, and continuous real-time monitoring of C2H4 emissions was conducted over a 24-hour period starting at 11:00 am. As shown in Fig. 7c, the C2H4 release exhibited a stepwise increase approximately every three hours. This trend is consistent with the enzymatic kinetics of C2H4 biosynthesis, where the activities of aminocyclopropane-1-carboxyllic acid (ACC) synthase and ACC oxidase peak during ripening, driving elevated C2H4 production and accelerated fruit maturation56,57. To further explore C2H4 dynamics at different physiological stages, apples at mature, senescent, and decayed stages were tested (Fig. 7d). The sensor response during the senescence was lower than that in the mature stage, whereas a slight increase was observed during decay. This pattern reflects the suppression of C2H4 production due to reduced respiration in senescence and a secondary rise during decay, likely caused by microbial activity and tissue degradation58,59. These results demonstrate the practical capability of the Cu2Cyt/MXene sensor to sensitively track fruit ripeness, freshness, and spoilage in real time, offering a non-invasive and continuous monitoring tool for postharvest management.

Beyond agricultural applications, the sensor was also tested in a simulated industrial setting to detect C2H4 leakage. The device was attached over a small aperture on a C2H4 transmission pipeline using adhesive film. Upon exposure to 5 ppm of leaked C2H4 gas, a distinct resistance response was recorded (Fig. 7e), confirming the sensor's rapid response under leakage conditions. This wearable configuration provides a practical and cost-effective solution for real-time C2H4 leakage detection in industrial environments, enhancing safety monitoring within transport and storage infrastructure.

To benchmark the performance of the Cu2Cyt/MXene sensor, a comparative analysis with previously reported C2H4 sensors was conducted, as summarized in Table 1. Unlike many reported sensors that rely on noble-metal catalysts such as Pd or Pt, the presented sensor is entirely noble-metal-free, significantly reducing material cost. In terms of detection capability, the sensor exhibits a wide linear range of 0.05-5 ppm and an ultra-low limit of detection (LOD) of 1.07 ppb, which is among the best reported for noble-metal-free sensors. Notably, the sensor operates effectively at room temperature (RT), in contrast to many oxide-based sensors (e.g., porous ZnO, LIG-SnO2) that require elevated working temperatures of 250-500 ℃ to achieve comparable performance.

The Cu2Cyt/MXene sensor also demonstrates a rapid response/recovery time (51/92 s), outperforming several flexible sensors platforms such as SWCNT/PdNPs/Polystyrene (~500 s) and PdNPs-SWCNT@Cu-MOF-74 (200/50 s). To further accelerate the response speed, future work may focus on several key rate-limiting steps: (1) increasing the specific surface area of the sensing material to maximize active site exposure; (2) engineering a more porous sensing layer to promote rapid ethylene diffusion; (3) enhancing the catalytic activity of copper sites through doping or heterojunction design; (4) optimizing operational parameters such as temperature and bias voltage; and (5) fabricating electrodes with sub-micron gaps to shorten charge-transport pathways. These strategies provide a clear roadmap toward developing ultrafast sensors capable of real-time monitoring.

Compared with other MXene-based sensors incorporating noble-metal nanoparticles (e.g., MXene@PdNP), the proposed sensor achieves superior sensitivity while maintaining excellent mechanical flexibility. It is noteworthy that the optimal bias voltage in this work — and in most reported studies-centers around 0.1 V, indicating a common operational window that effectively balances sensitivity and stability. This consistency further highlights our sensor’s strong performance within a standard low-voltage framework. These advantages underscore the promise of the Cu2Cyt/MXene sensor as a low-cost, high-performance, and wearable solution for real-time C2H4 monitoring in both agricultural and industrial applications.

Methods
Material characterization
The microstructure and element distribution of the samples were characterized by using scanning electron microscopy (QUANTA 250) with accessories of EDS and HRTEM (Tecnai G2 F20). XRD analyses were performed on a Rigaku B/Max-RB diffractometer. FTIR was measured on infrared spectrometer (Nexus 870). XPS was tested using Thermo ESCALAB 250XI. Raman spectra were conducted by Raman spectrometer with 532 nm light source (RTS Ultra). Nitrogen adsorption/desorption isotherms were tested on BET Surface Area Analyzer (Micromeritics Tristar 3000). EPR measurements were carried out on a Bruker EMX Plus spectrometer to analyze the electronic spin states of the samples. In situ FTIR spectra were recorded using a Nicolet iS50 FTIR spectrometer equipped with a custom-built in situ reaction cell to monitor the dynamic structural changes during the reaction process. Cross-sectional SEM observations were performed on the samples prepared by platinum deposition (for surface protection) followed by focused ion beam (FIB) milling with a gallium ion source (FEI Scios 2 HiVac) to precisely cut and fabricate the cross-sectional samples. GC was employed to determine the ethylene concentration in fruit boxes using an Agilent 7890A gas chromatograph.

Manufacture procedures of sensors
Synthesis of Cu2Cyt complex. NaOH (120 mg, 3 mmol) and L-Cysteine (484.64 mg, 4 mmol) were dissolved in 3 mL of deionized water and thoroughly mixed. The reaction was conducted under ambient air with the mixture maintained at 500 rpm under magnetic stirring. Subsequently, 3 mL of CuCl2 solution (107.56 mg, 0.8 mmol) was slowly added dropwise to the mixture under continuous stirring. The reaction was allowed to proceed for 15 minutes to facilitate the formation of Cu2Cyt nanosheets. Upon completion, the resulting precipitate was collected by centrifugation at 10270 x g for 10 minutes, and washed sequentially with deionized water and ethanol to remove unreacted residues. The purified Cu2Cyt product was then redispersed in 15 mL of absolute ethanol and stored at 4 °C for further use. In addition, key parameters, including precursor concentrations, reaction time, reaction temperature, pH values (controlled by NaOH dosage), and stirring conditions are summarized in Table S1.

Preparation of Cu2Cyt/MXene composite. Cu2Cyt/MXene composite was obtained by mixing 1 mL of the synthesized Cu2Cyt solution and 100 μL of Ti3C2Tx dispersion (5 mg/mL), followed by ultrasonication for 10 minutes to ensure uniform blending. Ti3C2Tx MXene monolayer dispersion (product code: XFK04-1; Concentration: 5 mg/mL) used in this study was commercially acquired from XFNANO Materials Tech Co., Ltd., Nanjing, Jiangsu, China.

Fabrication of sensors with Cu2Cyt/MXene composite. 50 μL of Cu2Cyt/MXene solution was droped onto gold interdigitated electrodes with a polyimide substrate. The electrodes were dried at 60 ℃ for 30 minutes in a drying oven to complete the sensor fabrication. The interdigitated electrodes are composed of copper and gold layers with thicknesses of 18 μm and 1 μm, respectively. The available region of interdigitated electrodes is 12 mm × 10 mm, which contains 12 pairs of interdigitated fingers with an inter-finger spacing of 200 μm.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Xu et al. explained the detection of ethylene using cuprous complex. However, the work is not so systemic and significant to be published in this journal.\nAuthors showed ethylene sensing. But, they did not clearly illustrate the selectivity of sensing.\nThere was no prominent evidence of the formation of the cuprous complex. EPR/XPS analysis is recommended.\nThe method should be compared with other existing methods.\nWhy was copper complex chosen? Authors should try other metal complexes.\nI recommend rejection of the paper.", "reviewer_2": "In this work, the authors report the synthesis of cuprous cystine microflowers incorporated into 2D p-type MXene to mimic plants’ natural capacity to capture C₂H₄ gas molecules via the formation of a π-complex with the cuprous ion center. The authors convincingly demonstrate how the experiments were conducted, supported by strong and comprehensive characterization, computational, and mathematical approaches to explain the observed outcomes in depth. Through this approach, they achieve a cost-effective, highly stable, fast-responding, and flexible ethylene gas sensor capable of detecting trace levels of C₂H₄ at room temperature. The authors also study the performance of this wearable sensor under environmentally relevant conditions, including varying temperature and humidity ranges, and explore its potential for wireless deployment. The outcomes are promising and convincing, representing significant advances for specialists in the field of chemiresistive gas sensing, aligning well with the aims of Nature Communications. After reviewing this work, I would highly recommend it for consideration for publication in Nat. Commun. after addressing the following points:\n1. Trace levels of ethylene molecules exist in river systems. Therefore, I suggest the authors slightly modify the title to be more specific, for example by adding “gas” after “ethylene.”\n2. Several typos and formatting issues need correction, including: “server” (Page 3, Line 93), “bend” in Fig. 4b, “HTEM” (Page 24, Line 506), “insect” (Page 9, Line 162, SI section), “I/V comverter” (Fig. S11), and name abbreviations in Fig. S10a,b. Additionally, spaces should be added in equations inset in Fig. 3f. A thorough spelling and formatting check is recommended to ensure consistency and integrity.\n3. The petal edges of the nanosheets are 50–100 nm thick; calling them “ultrathin” (Page 4, Line 131) may need reconsideration.\n4. To better understand the microstructure at a larger scale and show material distribution across multiple microflowers with MXenes, low-magnification SEM images and side views of the final material should be added.\n5. The assignments of the new adsorption peaks at 518.4 and 502.5 cm⁻¹ should include references or a detailed explanation.\n6. In plants, ETR1 is evolved to capture ethylene. While the cuprous complex may selectively interact with C=C bonds, the authors should verify whether the cuprous ion site specifically interacts with C=C. For instance, isoprene, a widely emitted VOC from plants under thermal stress and abundant in rubber industries, also contains C=C bonds. Testing the sensor against isoprene could evaluate potential cross-reactivity.\n7. For readability, the x-axis title in Fig. 4d could be changed to “Sensor number.”\n8. MXenes, particularly the popular Ti₃C₂Tₓ variant, are susceptible to oxidation, leading to degradation and diminished signal modulation after ~8 days of ambient exposure, as the authors note. For future work, the authors should consider exploring other p-type 2D alternatives with better stability.\n9. The authors need to explain the source of the MXenes in their experimental section.\n10. Two extended electrodes are used for signaling, but a 3-probe alligator configuration is shown in Fig. 5. The authors should clarify this discrepancy.\n11. Since this biomimetic sensor operates under an external voltage, the relevant parameters from other references should be included in the comparison table to ensure fairness.\n12. The authors may also discuss potential strategies to further increase the sensor response speed.\n13. Several abbreviations in the reference section appear to be incorrect, such as “Sensor. Actuat. B: Chem.” and “Nano-Micro Letters”, etc. The authors should carefully check and correct all reference abbreviations.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "In sum, the authors report a composite of Cu2Cyt/MXene for C2H4 sensing, however, considering the current research towards C2H4 sensing, the materials systems proposed by authors lack novelty and explanation of materials sensing mechanisms. Specific comments are listed below:\n1、Synthesis section lacks sufficient procedural details to allow reproducibility. Key parameters such as precursor concentrations, reaction temperature profiles, stirring conditions, and atmosphere control (e.g., inert gas vs. air) should be clearly described. A table summarizing synthesis parameters would help standardize the process.\n2、Mechanistic discussion is vague.To explore the interaction between MXene and Cu2Cyt during composition process, the authors should propose a more concrete reaction pathway supported by experimental evidence such as time-dependent XRD, in situ spectroscopy, or ex situ TEM. The current schematic is too conceptual and not adequately supported by current data.\n3、Characterization data provided are not sufficient to verify the claimed phase purity. Rietveld refinement of XRD data or complementary techniques such as Raman or FTIR would improve the mechanistic understanding of how the synthesis leads to the better C2H4 sensing performance.\n4、The mechanism section does not address whether the reaction is kinetically or thermodynamically controlled. The authors should discuss how temperature, time, or precursor concentration influences the product formation pathway. A time-series morphological study (0 h, 1 h, 3 h, etc.) would provide clearer evidence of growth evolution.\n5、As shown in the video, the scientificity of the testing method is uncertain, and the response of the chemical sensor is also affected by the operation methods."}, "author_response": "Response to the Reviewers’ Comments\nReviewer #1\nXu et al. explained the detection of ethylene using cuprous complex. However, the work is not\nso systemic and significant to be published in this journal. Authors showed ethylene sensing.\nBut, they did not clearly illustrate the selectivity of sensing. There was no prominent evidence\nof the formation of the cuprous complex. EPR/XPS analysis is recommended. The method\nshould be compared with other existing methods. Why was copper complex chosen? Authors\nshould try other metal complexes. I recommend rejection of the paper.\nAuthors Response: We appreciate the reviewer’s careful evaluation of our work. Following\nthe reviewer’s suggestion, we have conducted additional experiments and expanded the\ndiscussion to address the concerns raised. Specifically, we have supplemented the\ncharacterization of the cuprous complex, including adding the recommended analyses, and we\nhave strengthened the discussion on sensing selectivity. We have also compared our method\nwith existing ethylene-detection approaches and clarified the rationale for choosing the copper\ncomplex, while briefly exploring other metal complexes as suggested. We believe that these\nrevisions substantially improve the rigor and completeness of the study and adequately resolve\nthe issues highlighted by the reviewer.\nAuthors showed ethylene sensing. But, they did not clearly illustrate the selectivity of sensing.\nAuthors Response: In the original manuscript, the sensor’s selectivity was assessed through\ncomparative response tests against various potential interfering gases, as shown in Fig. 4a. In\nthe revised version, we have further clarified the sensing selectivity by presenting the\ncomparative data more clearly and expanding the related discussion. The updated results are\nsummarized as follows.\n“Selectivity is a vital parameter for practical gas sensors, especially in complex agricultural\nenvironments. The Cu Cyt/MXene sensor was evaluated against six common agricultural\n2\ngases, including ammonia (NH ), ethanol (EtOH), carbon dioxide (CO ), nitrogen dioxide\n3 2\n(NO ), methane (CH ), and isoprene (C H ) (Fig. 5a). The sensor exhibits a significant\n2 4 5 8\nresponse of 3.3% to 1 ppm C H , whereas the responses to non-olefin gases were negligible\n2 4\neven at a higher concentration, with specific values as follows: 0.54% to 5 ppm EtOH, 0.48%\nto 5 ppm CO , 0.52% to 5 ppm NO , 0.49% to 5 ppm CH , and 0.51% to 50 ppm NH .\n2 2 4 3\nHowever, in practical agricultural environments, interference from isoprene is negligible, as\nplants typically emit isoprene at ambient concentrations that are several orders of magnitude\nlower than those of ethylene48. This high selectivity to ethylene gas is attributed to the Cu Cyt\n2\ncomponent, which highly mimics the biological evolved recognition mechanism of plant C H\n2 4\nreceptor proteins.”\nThere was no prominent evidence of the formation of the cuprous complex. EPR/XPS analysis\nis recommended.\nAuthor Response: In the original manuscript, we characterized the prepared Cu-based\ncomplex using multiple spectroscopic techniques, including Raman spectroscopy (Fig. 2b),\nXPS (Fig. 2d–f), and FTIR (Fig. S7), all of which support the successful formation of the\ndesigned Cu Cyt complex. In response to the reviewer’s suggestion, we have further included\n2\nformation, as shown below.\n“The absence of satellite peaks indicates that the copper species predominantly exist in the +1\nor 0 oxidation states—Cu(I) or Cu(0)—rather than Cu(II). Electron paramagnetic resonance\n(EPR) measurements were further conducted to support this conclusion (Fig. S7). As expected,\nno signal corresponding to paramagnetic Cu(II), which has an [Ar]3d9 electron configuration,\nis observed within the magnetic field range of 3000–3500 G38. In contrast, Cu(I) possesses a\ndiamagnetic [Ar]3d10 configuration, and therefore its absence in the EPR spectrum is\nconsistent with its electronic structure.......”\nFig. S7 EPR spectra of Cu Cyt.\n2\n2\n38. Luo, Y., et al. Decoding the redox behaviour of copper in Ullmann-type coupling reactions.\nNature, 646, 1105–1113 (2025).\nThe method should be compared with other existing methods.\nAuthor Response: In the original manuscript, we provided a systematic comparison in Table\n1 between our method and recently reported approaches across several key performance\nparameters, including detection temperature, use of noble-metal catalysts, linear range,\nlimit of detection (LOD), flexibility, and response/recovery time.\nTo address the reviewer’s concern and more comprehensively evaluate the electrochemical\nsensing performance, we have now added the parameter “detection bias voltage” to the\ncomparison table in the revised manuscript. Notably, our method enables high-sensitivity\ndetection at a lower driving voltage, which is advantageous for practical applications by\nreducing power consumption, minimizing potential side reactions, and enhancing device\nsafety.\nTable 1 Comparison of key parameters of C H sensors in this work and recent reports.\n2 4\nNoble- Linear Bias Response/\nLOD Temp.\nmetal range Texture voltage recovery Refs.\nMaterial (ppb) (℃)\ncatalysis (ppm) (V) time (s)\nLIG/SnO No 0.05-100 1.65 Rigid 250 5.5* ~140/210 61\n2 5 2\nPorous ZnO No 10-2000 5000 Rigid 500 - ~8/20 9\nPd/rGO/α-Fe O Yes 0.01-1000 - - 250 - ~18/50 20\n2 3\nPd/Nitrite-4-Pyridyl\nYes 0.5-50 15 Rigid RT - ~60/240 19\n/SWCNT\n2-MoS /SCNT No 0.1-1 100 Rigid RT 0.1 ~102/215 62\nMXene@PdNPs Yes 0.5-20 84 Flexible RT - ~92/113 64\nYes 0.1-100 - Flexible RT 0.1 ~500/- 15\nlystyrene\nPdNPs-SWCNT@\nYes 0.1-100 31 Flexible RT 0.1 ~200/50 65\nCu-MOF-74\nThis\nCu Cyt/MXene No 0.05-5 1.07 Flexible RT 0.1 ~51/92 wor\n2\nk\n* The higher bias voltage is due to the fact that the sensor requires heating.\nThe updated comparison table more clearly demonstrates that our method offers distinct\nadvantages in detection bias voltage, flexibility, and the elimination of noble-metal catalysts,\nwhile still achieving high sensitivity and rapid response. These strengths highlight the strong\npotential and competitiveness of our approach for practical applications. The corresponding\ndiscussion has been incorporated into the revised manuscript and is also provided below.\n“The Cu Cyt/MXene sensor also demonstrates a rapid response/recovery time (51/92 s),\n2\noutperforming several flexible sensors platforms such as SWCNT/PdNPs/Polystyrene (~500 s)\nand PdNPs-SWCNT@Cu-MOF-74 (200/50 s). To further accelerate the response speed, future\nwork may focus on several key rate-limiting steps: (1) increasing the specific surface area of\nthe sensing material to maximize active site exposure; (2) engineering a more porous sensing\nlayer to promote rapid ethylene diffusion; (3) enhancing the catalytic activity of copper sites\nthrough doping or heterojunction design; (4) optimizing operational parameters such as\ntemperature and bias voltage; and (5) fabricating electrodes with sub-micron gaps to shorten\ncharge-transport pathways. Collectively, these strategies provide a clear roadmap toward\ndeveloping ultrafast sensors capable of real-time monitoring.\nCompared with other MXene-based sensors incorporating noble-metal nanoparticles (e.g.,\nMXene@PdNP), the proposed sensor achieves superior sensitivity while maintaining\nexcellent mechanical flexibility. It is noteworthy that the optimal bias voltage in this\nwork—and in most reported studies—centers around 0.1 V, indicating a common operational\nwindow that effectively balances sensitivity and stability. This consistency further highlights\nour sensor’s strong performance within a standard low-voltage framework. These advantages\n4\nunderscore the promise of the Cu Cyt/MXene sensor as a low-cost, high-performance, and\n2\nwearable solution for real-time C H monitoring in both agricultural and industrial\n2 4\napplications.”\nWhy was copper complex chosen? Authors should try other metal complexes.\nAuthor Response: The choice of a copper complex as the core sensing element was guided\nby a biomimetic design strategy, inspired by the ethylene-binding mechanism of plant\nethylene receptor proteins (e.g., ETR1). Moreover, compared with precious-metal catalysts\nsuch as platinum and palladium, copper is abundant, low-cost, and thus more suitable for\nscalable applications.\nIn response to the reviewer’s suggestion, we also examined several other common\ntransition-metal complexes, including those of cobalt (Co), nickel (Ni), and zinc (Zn), to\nexplore potential alternatives. As shown in Fig. S17, these complexes exhibit measurable\nresponses to ethylene under identical conditions; however, their responses are significantly\nweaker than that of the Cu-based complex. This contrast further underscores the unique\nadvantages conferred by the copper-centered design, consistent with the efficiency observed\nin natural plant receptors.\nFig. S17 Comprehensive sensing performance of L-Cysteine complexes with various metals (Co, Ni, Zn,\nand Cu) for 1 ppm C H detection at room temperature.\n2 4\nIn the revised manuscript, we have expanded the corresponding discussion as follows:\n“All subsequent measurements were conducted using electrodes prepared under these\n5\noptimized conditions. To comprehensively explore alternative sensing materials, we also\nevaluated other common transition-metal complexes, including those of cobalt (Co), nickel\n(Ni), and zinc (Zn), under the same optimized conditions. As shown in Fig. S17, these\ncomplexes exhibit detectable responses to ethylene; however, their responses are significantly\nweaker than that of the Cu-based complex. This contrast further underscores the unique\nadvantage of the copper-centered design, consistent with the highly efficient ethylene-binding\nmechanism evolved in plants....”\nIn this work, the authors report the synthesis of cuprous cystine microflowers incorporated\ninto 2D p-type MXene to mimic plants’ natural capacity to capture C H gas molecules via the\n2 4\nformation of a π-complex with the cuprous ion center. The authors convincingly demonstrate\nhow the experiments were conducted, supported by strong and comprehensive\ncharacterization, computational, and mathematical approaches to explain the observed\noutcomes in depth. Through this approach, they achieve a cost-effective, highly stable,\nfast-responding, and flexible ethylene gas sensor capable of detecting trace levels of C H at\n2 4\nroom temperature. The authors also study the performance of this wearable sensor under\nenvironmentally relevant conditions, including varying temperature and humidity ranges, and\nexplore its potential for wireless deployment. The outcomes are promising and convincing,\nrepresenting significant advances for specialists in the field of chemiresistive gas sensing,\naligning well with the aims of Nature Communications. After reviewing this work, I would\nhighly recommend it for consideration for publication in Nat. Commun. after addressing the\nfollowing points:\nAuthor Response: We sincerely appreciate the reviewer’s highly positive and encouraging\nevaluation of our work. We have carefully addressed all concerns and constructive suggestions\nin a point-by-point manner below, and the corresponding revisions have been highlighted in\nred in the revised manuscript.\n1. Trace levels of ethylene molecules exist in river systems. Therefore, I suggest the authors\nslightly modify the title to be more specific, for example by adding “gas” after\n“ethylene.”\nAuthor Response: As suggested, we have modified the title as “A Plant-receptor-inspired\nCuprous Complex for Wearable Trace-level Ethylene Gas Sensing”.\n2. Several typos and formatting issues need correction, including: “server” (Page 3, Line 93),\n“bend” in Fig. 4b, “HTEM” (Page 24, Line 506), “insect” (Page 9, Line 162, SI section),\n“I/V comverter” (Fig. S11), and name abbreviations in Fig. S10a,b. Additionally, spaces\nshould be added in equations inset in Fig. 3f. A thorough spelling and formatting check is\nrecommended to ensure consistency and integrity.\nerrors. We have corrected all of them and have thoroughly polished the manuscript once\nagain.\n3. The petal edges of the nanosheets are 50–100 nm thick; calling them “ultrathin” (Page 4,\nLine 131) may need reconsideration.\nAuthor Response: Thanks; we have removed the term in the revised manuscript.\n4. To better understand the microstructure at a larger scale and show material distribution\nacross multiple microflowers with MXenes, low-magnification SEM images and side\nviews of the final material should be added.\nAuthor Response: As suggested, we have added low-magnification SEM images (Fig. S1b)\nof the Cu Cyt/MXene composite to present its larger-scale morphology. In addition, a\n2\nside-view SEM image (Fig. 1) has been included to better illustrate the three-dimensional\narchitecture and the integration of MXene sheets throughout the structure. The\ncorresponding discussion has been added below and highlighted in red in the revised\nmanuscript.\n“Low-magnification SEM images of the Cu Cyt/MXene composites reveal the arrangement of\n2\nmultiple microflowers (Fig. S2a–b), indicating good structural uniformity on a larger scale. A\nside-view SEM image of an individual microflower is also provided to elucidate its internal\ncomposition and architecture (Fig. 1g). The structure forms a well-connected\nthree-dimensional network composed of branched and sheet-like units with open channels,\nwithout noticeable aggregation or densely packed regions (Fig. 1h). Elemental mapping of a\ncross-sectional region further shows the presence of Ti within the interior of the microflowers\n(Fig. 1i), confirming that MXene, as a conductive component, is interwoven with Cu Cyt\n2\nnanosheets throughout the structure. This hierarchical porous architecture and\ncross-distributed composition create efficient pathways for gas diffusion and electron\ntransport, thereby exposing more active sites and enhancing the sensing response.”\nFig. 1 (g-h) SEM images of the cross-sectional view of Cu Cyt/MXene; the region with dotted line\n2\ncorresponds to Pt protective layer, which serves to ensure cutting completeness; (i) Elemental mapping of N,\nCu, O, S, and Ti in the cross-sectional area;\n5. The assignments of the new adsorption peaks at 518.4 and 502.5 cm-1 should include\nreferences or a detailed explanation.\nAuthor Response: As recommended, the discussion has been expanded in detail, with\nsupporting references provided below.\n“Notably, the majority of peaks of the prepared Cu Cyt are consistent with those of L-Cystine\n2\nsample, while several different points exist due to Cu coordination. Because transition metal\natoms are relatively heavy, the related vibrations should be in the low-frequency region35, as\n9\nshown in the enlarged area of Fig. 3c. Compared with L-Cystine, three new peaks for Cu Cyt\n2\nemerge at 518.4 502.5, and 489.9 cm⁻1, which are attributed to Cu–O, Cu–N, Cu-S\ncoordination vibrations36,37, respectively, suggesting the formation of Cu-ligand bonds. In\naddition, the bending vibration of –COO⁻ in Cu Cyt exhibits a redshift compared with that of\n3\nvibration of Cu Cyt, compared with that in L-Cystine, signifies the difference in cation\n2\ncoordination: the heavier Cu(I) coordinates in Cu Cyt, whereas the lighter ‒NH+ is involved\n2 3\nin L-Cystine. These spectral features are consistent with the coordination structure predicted\nby DFT calculations, further corroborating the proposed binding mode of Cu+ with the -COO-,\n-NH , and -S-S- in the Cu Cyt complex.”\n2 2\n35. Shearer J., Neurock M. & Mavrikakis M. Scaling relationships and theory for vibrational\nfrequencies of adsorbates on transition metal surfaces. Nat. Catal. 4, 363–370 (2021).\n36. Saleem, S., et al. Enhancement in structural, morphological, and optical properties of\ncopper oxide for optoelectronic device applications. Nanotechnol. Rev. 11, 2827-2838 (2022).\n37. Yin, Z., et al. Flotation separation of molybdenite from chalcopyrite using an\nenvironmentally-efficient depressant L-cysteine and its adsoption mechanism. Miner. Eng.\n156, 106438 (2020).\n6. In plants, ETR1 is evolved to capture ethylene. While the cuprous complex may\nselectively interact with C=C bonds, the authors should verify whether the cuprous ion\nsite specifically interacts with C=C. For instance, isoprene, a widely emitted VOC from\nplants under thermal stress and abundant in rubber industries, also contains C=C bonds.\nTesting the sensor against isoprene could evaluate potential cross-reactivity.\nAuthor Response: As suggested, we have supplemented the response test to isoprene (C H )\n5 8\nin Fig. 4a. The corresponding discussion, along with relevant references, is presented below.\n“Selectivity is a vital parameter for practical gas sensors, especially in complex agricultural\nenvironments. The Cu Cyt/MXene sensor was evaluated against six common agricultural\n2\ngases, including ammonia (NH ), ethanol (EtOH), carbon dioxide (CO ), nitrogen dioxide\n3 2\n(NO ), methane (CH ), and isoprene (C H ) (Fig. 5a). The sensor exhibits a significant\n2 4 5 8\n10\nresponse of 3.3% to 1 ppm C H , whereas the responses to non-olefins gases were negligible\n2 4\neven at a higher concentration, with specific values as follows: 0.54% to 5 ppm EtOH, 0.48%\nto 5 ppm CO , 0.52% to 5 ppm NO , 0.49% to 5 ppm CH , and 0.51% to 50 ppm NH .\n2 2 4 3\nNotably, the sensor shows a moderate response of 1.3% to 1 ppm isoprene, another olefin gas\n(Fig. S25). However, in practical agricultural environments, interference from isoprene is\nnegligible, as plants typically emit isoprene at ambient concentrations that are several orders\nof magnitude lower than those of ethylene48. This high selectivity to ethylene gas is attributed\nto the Cu Cyt component, which highly mimics the biological evolved recognition mechanism\n2\nof plant C H receptor proteins.”\n2 4\n48. Jia, Y., Qiao, L., Xie, W. & Li, L. Sptial-temporal characteristics of ambient isoprene and\nmonoterpene and their ozone and secondary organic aerosol formation potential in China.\nEnviron. Rev. 32, 203-213 (2024).\nFig. 5 (a) Selectivity against common interfering gases.\n2\n7. For readability, the x-axis title in Fig. 4d could be changed to “Sensor number.”\nAuthor Response: Thanks; we updated the x-axis label of Fig. 4d to “Sensor number”.\n8. MXenes, particularly the popular Ti C T variant, are susceptible to oxidation, leading to\n3 2 x\ndegradation and diminished signal modulation after ~8 days of ambient exposure, as the\nauthors note. For future work, the authors should consider exploring other p-type 2D\nalternatives with better stability.\nAuthor Response: We have added the following statement to explicitly incorporate the\nsuggestion into our future research agenda in the Conclusion section, as follows:\n“Future studies will focus on exploring alternative p-type 2D materials—particularly stable\nreduced graphene oxide (rGO) and transition-metal dichalcogenides such as MoS and\n2\narchitecture.”\n9. The authors need to explain the source of the MXenes in their experimental section.\nAuthor Response: As recommended, we have explicitly added the source information of the\nMXene materials in section of “Preparation of Cu Cyt/MXene composite”, as below:\n2\n“Ti C T MXene monolayer dispersion (product code: XFK04-1; Concentration: 5 mg/mL)\n3 2 x\nused in this study was commercially acquired from XFNANO Materials Tech Co., Ltd.,\nNanjing, Jiangsu, China.”\n12\n10. Two extended electrodes are used for signaling, but a 3-probe alligator configuration is\nshown in Fig. 5. The authors should clarify this discrepancy.\nAuthor Response: Thanks for careful observation regarding the discrepancy between the\nschematic and the actual measurement configuration. We sincerely appreciate the\nopportunity to clarify this important technical detail. Though three alligator clips are\nvisually present in the setup (connected to a three-electrode electrochemical workstation),\nall sensing measurements were strictly performed in a two-electrode mode. This is because\nour interdigitated electrode (IDE) device inherently provides only two conductive terminals.\nTo adapt it to the workstation, the reference (Ref) and counter (CE) electrode clips were\nshort-circuited and connected together to one IDE pad, while the working electrode (WE)\nclip was connected to the other IDE pad.\nTo avoid future confusion, we have made a supplementary explanation in the caption of\nFigure 6 (previous Figure 5) in the revised manuscript to accurately depict this adapted\ntwo-terminal connection scheme through the short-circuited Ref/CE node, as follows:\n“Fig. 6 Practical demonstrations of the Cu Cyt/MXene sensor. (a) Schematic of portable\n2 4\nand counter electrode clips are short-circuited and connected to one IDE pad, while the\nworking electrode clip is connected to the other pad, enabling operation in a two-electrode\nmode;.....”\n11. Since this biomimetic sensor operates under an external voltage, the relevant parameters\nfrom other references should be included in the comparison table to ensure fairness.\nAuthor Response: In response to the concern, we have incorporated the key parameter\n“bias voltage” into Table 1 and added the relevant discussion in the revised manuscript,\nas detailed below.\nTable 1 Comparison of key parameters of C H sensors in this work and recently reports.\n2 4\nNoble- Linear Bias Response/\nLOD Temp.\nmetal range Texture voltage recovery Refs.\nMaterial (ppb) (℃)\ncatalysis (ppm) (V) time (s)\nLIG/SnO No 0.05-100 1.65 Rigid 250 5.5 * ~140/210 61\n2\n2 5 2\nPorous ZnO No 10-2000 5000 Rigid 500 - ~8/20 9\nPd/rGO/α-Fe O Yes 0.01-1000 - - 250 - ~18/50 20\n2 3\nPd/Nitrite-4-Pyridyl\nYes 0.5-50 15 Rigid RT - ~60/240 19\n/SWCNT\n2-MoS /SCNT No 0.1-1 100 Rigid RT 0.1 ~102/215 62\nMXene@PdNPs Yes 0.5-20 84 Flexible RT - ~92/113 64\nSWCNT/PdNPs/Po\nYes 0.1-100 - Flexible RT 0.1 ~500/- 15\nlystyrene\nPdNPs-SWCNT@\nYes 0.1-100 31 Flexible RT 0.1 ~200/50 65\nCu-MOF-74\nThis\nCu Cyt/MXene No 0.05-5 1.07 Flexible RT 0.1 ~51/92\n2\nwork\n* The higher bias voltage is due to the fact that the sensor requires heating.\nThe supplemented discussion in the revised manuscript: “......the proposed sensor\nachieves superior sensitivity while maintaining excellent mechanical flexibility. It is\nnoteworthy that the optimal bias voltage in this work—and in most reported\nstudies—centers around 0.1 V, indicating a common operational window that effectively\nbalances sensitivity and stability. This consistency further highlights our sensor’s strong\nperformance within a standard low-voltage framework. These advantages underscore the\npromise......”\n12. The authors may also discuss potential strategies to further increase the sensor response\nspeed.\nAuthor Response: We fully agree that discussing pathways to improve response speed\nis valuable for outlining the future potential of this sensor platform. Accordingly, we\nhave added relevant discussion after description of the response/recovery time\n14\npresented in Table 1 in the revised manuscript below:\n“The Cu Cyt/MXene sensor also demonstrates a rapid response/recovery time (51/92 s),\n2\noutperforming several flexible sensors platforms such as SWCNT/PdNPs/Polystyrene (~500 s)\nand PdNPs-SWCNT@Cu-MOF-74 (200/50 s). To further accelerate the response speed, future\nwork may focus on several key rate-limiting steps: (1) increasing the specific surface area of\nthe sensing material to maximize active site exposure; (2) engineering a more porous sensing\nlayer to promote rapid ethylene diffusion; (3) enhancing the catalytic activity of copper sites\nthrough doping or heterojunction design; (4) optimizing operational parameters such as\ntemperature and bias voltage; and (5) fabricating electrodes with sub-micron gaps to shorten\ncharge-transport pathways. These strategies provide a clear roadmap toward developing\nultrafast sensors capable of real-time monitoring.”\n13. Several abbreviations in the reference section appear to be incorrect, such as “Sensor.\nActuat. B: Chem.” and “Nano-Micro Letters”, etc. The authors should carefully check\nand correct all reference abbreviations.\nAuthor Response: Thanks. Accordingly, we have corrected the abbreviations and carefully\npolished the whole manuscript once again.\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\nAuthor Response: We sincerely appreciate the time and effort you have devoted to jointly\nreviewing our manuscript, and we also thank Nature Communications for its valuable\ninitiative of providing training on peer review for early-career researchers, which not only\nensures rigorous assessment but also promotes the growth of the academic community.\nIn sum, the authors report a composite of Cu Cyt/MXene for C H sensing, however,\n2 2 4\nconsidering the current research towards C H sensing, the materials systems proposed by\n2 4\nauthors lack novelty and explanation of materials sensing mechanisms. Specific comments are\nlisted below:\nAuthor Response: Thanks for the reviewer’s summary and for highlighting these important\nconcerns. We appreciate the assessment regarding novelty and the need for a clearer\nexplanation of the sensing mechanism. In the revised manuscript, we have substantially\nstrengthened the mechanistic discussion, provided additional experimental evidence, and\nexpanded the comparison with existing C H -sensing systems to better clarify the distinct\n2 4\nadvantages of our Cu Cyt/MXene architecture. Detailed responses to each specific comment\n2\nare provided below, and all corresponding revisions have been incorporated into the\nmanuscript.\n1. Synthesis section lacks sufficient procedural details to allow reproducibility. Key\nparameters such as precursor concentrations, reaction temperature profiles, stirring\nconditions, and atmosphere control (e.g., inert gas vs. air) should be clearly described. A\ntable summarizing synthesis parameters would help standardize the process.\nAuthor Response: Thanks for the suggestion. We have thoroughly revised the synthesis\nsection to provide clear descriptions of precursor concentrations, reaction temperature, stirring\nconditions, and atmosphere control. We have added a new Table S1 in the Supplementary\nInformation, which systematically summarizes all key synthesis parameters, including\nprecursor concentrations, reaction time, reaction temperature, pH values (different contents of\nNaOH), and stirring conditions.\nOptimaz Dosage Dosage of Stirring Stirring\nCuCl2/L-Cysti Dosage of Temperature\nation of CuCl2 L-Cystine Atmosphere speed time\nne molar ratio NaOH (mg) (℃)\ntype (mg) (mg) (rpm) (min)\n53.78 484.64 0.1 120 20 Air 500 15\nConcent\n107.56 484.64 0.2 120 20 Air 500 15\nration\n161.34 484.64 0.3 120 20 Air 500 15\n107.56 484.64 0.2 120 20 Air 500 5\n107.56 484.64 0.2 120 20 Air 500 30\nTime 107.56 484.64 0.2 120 20 Air 500 60\n107.56 484.64 0.2 120 20 Air 500 120\n107.56 484.64 0.2 120 20 Air 500 180\n107.56 484.64 0.2 120 30 Air 500 15\nTemperat\n107.56 484.64 0.2 120 60 Air 500 15\nure\n107.56 484.64 0.2 120 90 Air 500 15\n107.56 484.64 0.2 0 20 Air 500 15\n107.56 484.64 0.2 40 20 Air 500 15\npH\n107.56 484.64 0.2 80 20 Air 500 15\n107.56 484.64 0.2 160 20 Air 500 15\nThe relevant discussion added to the revised manuscript: “NaOH (120 mg, 3 mmol) and\nL-Cysteine (484.64 mg, 4 mmol) were dissolved in 3 mL of deionized water and thoroughly\nmixed. The reaction was conducted under ambient air with the mixture maintained at 500 rpm\nunder magnetic stirring. …… In addition, key parameters, including precursor concentrations,\nreaction time, reaction temperature, pH values (controlled by NaOH dosage), and stirring\nconditions are summarized in Table S1.”\n2. Mechanistic discussion is vague. To explore the interaction between MXene and Cu Cyt\n2\nduring composition process, the authors should propose a more concrete reaction pathway\nsupported by experimental evidence such as time-dependent XRD, in situ spectroscopy, or\nex situ TEM. The current schematic is too conceptual and not adequately supported by\ncurrent data.\nand Cu Cyt during compositing process, we have supplemented time-dependent XRD of\n2\nbetween pure MXene, Cu Cyt, and Cu Cyt/MXene composites. In addition, the schematic\n2 2\nillustration has also been revised with more concrete electron transfer pathway and interaction.\nThe supplemented and revised figures is placed in the updated Fig. 3 below:\nFig. 3 (a) DFT-calculated binding energy of Cu Cyt with C H at different Cu+ coordination sites. (b)\n2 2 4\nDifferential charge density distribution for C H adsorption on Cu Cyt/MXene, the red curve indicates\n2 4 2\ncharge variation along the z-axis; (c) Schematic illustration of the C H sensing mechanism based on ET\n2 4\nfrom Cu Cyt to MXene; (d) FTIR spectra of MXene, Cu Cyt and Cu Cyt/MXene; (e) Time-dependent\n2 2 2\n2\nspectra of Cu Cyt/MXene during ethylene exposure; (g) Response/recovery curves of pure MXene and\n2 2 4\nCu Cyt/MXene at 0.05-5 ppm; (i) Nonlinear fitting of the response-concentration relationship based on a\nThe relevant additions to the revised manuscript: “Based on this charge redistribution, a\nsensing mechanism is proposed, as illustrated in Fig. 3c. In air, O (-COO-) and H (-NH ) of\n2\nexposure to C H , the gas molecules are specifically captured by the Cu+ active sites in\n2 4\nCu Cyt, forming a coordination structure of Cu(I)-C H (d-π conjugation). Subsequent\n2 2 4\nelectron donation from C H initiates cascade electron transfer by two potential pathways\n2 4\n(marked with p1 and p2) through the Cu Cyt complex into MXene. As a p-type semiconductor,\nlevel, a reduced hole concentration, and an increase in electrical resistance. This resistance\nmodulation serves as the measurable output signal for C H detection. The hydrogen bonds\n2 4\ncan be evidenced by buleshift of Cu-O vibriation and redshift of Cu-N vibration (Fig. 3d). The\nformer is caused by the increased electron density (O pulls electrons from H of Ti-OH), while\nthe latter is due to the decreased electron density (N loses electrons to O of Ti-O terminals).\nNotably, Cu-S vibration disappears due to the interaction between MXene and\nCu Cyt/MXene.\naround 6.3 can be assigned to the (200) plane of MXene42, while that centered around 18.9\ncan be attributed to the (100) plane of Cu Cyt.\nThe intensities of both peaks show an increase\n2\n(high crystallinity) from 1 to 5 minutes and then a decrease (low crystallinity) from 10 to 30\nmin. The time-dependent crystallinity variations can be attributed to interconnect caused by\nsurface interactions, which has been illustrated in Fig. 1. Similarly, the time-dependent FTIR\nspectroscopies also demonstrate the interactions between MXene and Cu Cyt (Fig. S12),\n2\nbecause of the changing vibration modes caused by the formation of hydrogen bonds in the\n20\nlow frequency region along with time range of 1-30 min.\nAs shown in Fig. 3f, in-situ FTIR spectroscopies are further utilized to verify the dynamic\nrecognition process of Cu Cyt to ethylene gas described in Fig. 3c. The characteristic peaks at\n2\n1888.7 cm-1 and 1912.7 cm-1 can be assigned to the combination and double vibrations of\n=CH swing mode in Cu(I)-C H , respectively, while the characteristic peak at 949.8 cm-1\n2 2 4\nbelongs to =CH swing mode43. These characteristic peaks emerged exclusively upon ethylene\n2\nexposure, and their intensity increased progressively from 1 to 3 minutes. This trend illustrates\nthe gradual capture of ethylene molecules by the active Cu(I) sites in Cu Cyt.\nNotably, the\n2\npeak intensity plateaued between 3 and 5 minutes, indicating that adsorption saturation was\nreached at approximately 3 minutes. This saturation time closely aligns with the response\nsaturation time observed in the electrical measurements (~200 s), highlighting the\neffectiveness of in situ FTIR on illustrating the dynamic process of ethylene recognition.\nFig. S12 Time-dependent FTIR of Cu Cyt/MXene\n2\n42. Cai Y., et al. Ti₃C₂Tₓ MXene/urchin-like PANI hollow nanosphere composite for high\nperformance flexible ammonia gas sensor. Anal. Chim. Acta 1225, 340256 (2022).\n43. Huang, Y. Y. Ethylene complexes in copper (I) and silver (I) Y zeolites. J. catal. 61,\n461-476 (1980).”\n3. Characterization data provided are not sufficient to verify the claimed phase purity.\nRietveld refinement of XRD data or complementary techniques such as Raman or FTIR\nwould improve the mechanistic understanding of how the synthesis leads to the better\nC H sensing performance.\n2 4\nto verify phase purity. We acknowledge the importance of this method and must clarify a key\npoint: the full single-crystal structure of the Cu₂Cyt complex itself has not yet been reported in\nthe literature, and our attempts to grow diffraction-quality single crystals for this purpose are\nongoing. Therefore, a traditional Rietveld refinement against a known structural model is not\ncurrently feasible.\nTo address the core concern of verifying the identity of our synthesized material, we have\ninstead undertaken a comprehensive multi-technique characterization approach (e.g., the\nrevised Figs. 2 and 3), and supplemented the relevant discussion to the revised manuscript.\nFig. 2 Properties analysis of related materials. (a) Reaction equation for Cu Cyt synthesis, along with the\n2\noptimized structures of reactants and products, and the Gibbs free energy; (b) Raman spectra of L-Cysteine\nand Cu Cyt; (c) FTIR spectra of L-Cystine and Cu Cyt; High-resolution XPS spectrum of Cu 2p (d) and S\n2 2\n2p (e) for Cu Cyt; inset in (d) shows optical images of Cu Cyt before and after washing; (f) High-resolution\n2 2\nC1s XPS spectrum of Cu Cyt/MXene composite.\n2\n22\n4. The mechanism section does not address whether the reaction is kinetically or\nthermodynamically controlled. The authors should discuss how temperature, time, or\nprecursor concentration influences the product formation pathway. A time-series\nmorphological study (0 h, 1 h, 3 h, etc.) would provide clearer evidence of growth\nevolution.\nAuthor Response: We sincerely thank the reviewer for the valuable suggestion regarding the\nkinetic versus thermodynamic control and the influence of reaction parameters. In response,\nwe have conducted a systematic investigation of reaction time, temperature, precursor\nconcentration, and pH value on the morphology, crystallinity, and gas-sensing performance of\nCu Cyt nanoflowers. Detailed results, including time-resolved SEM, XRD, and gas-sensing\n2\ndata, are provided in the revised manuscript and Supplementary Information.\nThe addition to the revised manuscript: “To investigate how the growth evolution of Cu Cyt\n2\ncrystals influences sensing performance, we conducted time-series SEM characterization at\nkey reaction intervals (5 min, 15 min, 30 min, 1 h, 2 h, and the final 3 h) and analyzed the\ncorresponding particle-size distributions (Fig. 4). The time-dependent SEM images reveal a\nclear morphological progression from initial aggregates to well-defined microflowers. At the\nearly stage (5 min), small flake-like units densely stack into compact, nascent flower-like\nstructures with an average particle size of . ± 2.28 µm (Fig. 4a). As the reaction proceeds to\n15–30 min, the primary nanosheets undergo self-assembly through oriented attachment and\nintermolecular interactions. The petals begin to spread, the layered stacking becomes more\ndistinct, the flower contours sharpen, and the overall structure becomes looser (Fig. 4b,c).\nCorrespondingly, the particle size increases to 12.18 ± 2.37 µm (15 min) and 13.46 ± 3.72 µm\n(30 min).\nBetween 60 and 120 min, the petal dimensions further increase and the packing density\nbecomes higher, yielding average particle sizes of 15.78 ± 2.98 µm (60 min) and\n16.61 ± 3.84 µm (120 min) (Fig. 4d,e). By 180 min, however, the microflower structure\nbecomes severely damaged, showing a coexistence of large agglomerates and nanofibrous\nfragments, with the particle size expanding to 20.76 ± 5.24 µm (Fig. 4f). The standard\ndeviation increases from 2.28 µm to 5.24 µm, reflecting a continuous evolution from primary\naggregates to mature flower-like assemblies, followed by excessive collapse (Fig. S18a–f).\ncrystallites dissolve and re-deposit onto larger ones over time47, indicating that the synthesis is\ngoverned by thermodynamic control. Time-dependent XRD patterns confirm that the crystal\nstructure remains unchanged throughout the growth process (Fig. S18g). The sensing response\nexhibits an initial increase followed by a decline, mirroring the morphological evolution\n(Fig. S18h). Because the improvement in response beyond 15 min was marginal, a reaction\ntime of 15 min was selected for subsequent experiments.\nTo further elucidate how synthesis parameters steer this thermodynamic pathway, we\nsystematically examined the effects of precursor concentration, reaction temperature, and pH\n(Figs. S19–S24). These results demonstrate that the morphology and particle size of the\ncomposite are strongly dictated by synthesis conditions, which in turn determine the sensing\nperformance. Detailed analyses are provided in the Supplementary Information. Collectively,\nthese insights offer a systematic foundation for the rational design of future multi-factor\noptimization strategies.”\n2\nreaction times: (a) 5 min, (b) 15 min, (c) 30 min, (d) 60 min, (e) 120 min, and (f) 180 min. The bottom\npanels present the particle size distribution histograms (columns) and Gaussian fitting curves (red lines).\n2 4\nreaction time: (a-f) Enlargement SEM images of the material at 5 min, 15 min, 30 min, 60 min, 120 min,\nand 180 min; (g) XRD patterns of Cu Cyt and (h) C H sensing response curves of Cu Cyt at different\n2 2 4 2\nreaction times.\nThe addition to the revised Supplementary Information: “Temperature simultaneously\ninfluences nucleation, crystal growth, and self-assembly by altering reaction activation energy\nand molecular mobility. SEM images reveal clear temperature-dependent morphological\nevolution. At 20 °C, the structures exhibit initial flake stacking with an average particle size of\n12.18 ± 2.37 µm (Fig. 4b). At 30 °C, the flakes become more densely packed and the petal\nsizes become less uniform, yielding an average particle size of 14.28 ± 3.15 µm (Fig. S19a).\nAt 60 °C, the individual petals grow substantially larger, and the average particle size\nincreases to 20.00 ± 4.04 µm (Fig. S19b). At 90 °C, the overall particle size does not change\nsignificantly (20.16 ± 2.91 µm; Fig. S19c), but the petals become excessively thick\n(Fig. S20a–c).\nThese distinct morphological features demonstrate that reaction temperature provides an\n26\neffective handle for tailoring the architecture of flower-like materials, enabling control over\nparticle size and petal thickness for specific functional requirements. Temperature-dependent\nXRD patterns confirm that the crystal structure remains unchanged, indicating that the\ncomposition is stable throughout the growth process (Fig. S20d). The sensing response\nexhibits an initial decrease followed by an increase with rising temperature (Fig. S20e),\nconsistent with the observed structural evolution.”\nFig. S19 SEM images and corresponding particle size distribution statistics of Cu Cyt at different\n2\nreaction temperatures. Morphological evolution of Cu Cyt at (a) 30 ℃, (b) 60 ℃, and (c) 90 ℃. The\n2\nbottom panels present the particle size distribution histograms (columns) and Gaussian fitting curves (red\nlines).\n2 4\nreaction temperature: (a-c) Enlargement SEM images of the material at 30 ℃, 60 ℃, 90 ℃ (d) XRD\npatterns of Cu Cyt and (e) C H sensing response curves of Cu Cyt at different reaction temperatures.\n2 2 4 2\nPrecursor concentration directly regulates the balance between nucleation and growth by\naltering the supersaturation of the reaction system. SEM images show that at a low precursor\nmolar ratio (n = 0.1), the supersaturation is insufficient to generate abundant nucleation sites,\nleading to large nanoflowers (20.75 ± 5.40 µm) with uneven morphology and disordered petal\nstacking (Fig. S21a). At n = 0.2, the nanosheets become densely packed, the layered stacking\nis well developed, and the particle size becomes uniform (12.18 ± 2.37 µm) (Fig. S21b). When\nthe concentration increases to n = 0.3, the flower-like architecture collapses entirely, yielding\namorphous, fluffy particle aggregates with smaller size (10.81 ± 3.60 µm) (Fig. S21c) and\nlosing the characteristic flower-like features (Fig. 22a–c).\n2\nreaction concentrations. Morphological evolution of Cu Cyt at (a) n=0.1, (b) n=0.2, and (c) n=0.3, while\n2\nthe bottom panels present the particle size distribution histograms (columns) and Gaussian fitting curves\n(red lines).\nXRD patterns show that at n = 0.3, the excessively high precursor concentration disrupts the\ncoordination-kinetic equilibrium, leading to kinetic reconstruction of the product, the\nformation of alternative coordination phases or amorphous/metastable phases, and noticeable\ndeviations from the characteristic diffraction peaks of Cu₂Cyt (Fig. S22d). At n = 0.1, the\npetals are large and irregularly stacked, limiting the exposure of active sites and hindering gas\ndiffusion, which results in a low sensing response. At n = 0.2, the flower-like structures are\ndense and uniform, with a high specific surface area and well-ordered stacking that preserves\nefficient gas-diffusion channels, yielding the optimal sensing performance. At n = 0.3,\nstructural collapse, phase transitions, reduced surface area, and decreased crystallinity\ncollectively cause a pronounced decline in sensing response. Therefore, n = 0.2 represents the\noptimal precursor concentration, achieving the best balance among morphology, phase\nstability, and mass-transfer-active sites under kinetic regulation (Fig. S22e).\n2 4\nreaction concentration. (a-c) Enlargement SEM images of the material at n=0.1, n=0.2, and n=0.3; (d)\nXRD patterns of Cu Cyt and (e) C H sensing response curves of Cu Cyt at different reaction\n2 2 4 2\nconcentrations.\npH regulates the coordination mode and reaction rate between L-cystine ligands and Cu2+ by\naltering the protonation state of the ligand. SEM images show that in a strongly acidic\nenvironment (0–1 mM NaOH, pH 2.4–2.8), the coordination groups are highly protonated,\nsignificantly weakening their binding ability and resulting only in amorphous, fluffy particle\naggregates (Fig. S23a, b). Under weakly acidic conditions (2 mM NaOH, pH 6.8), partial\ndeprotonation restores the coordination capability, producing a limited number of flake-like\nstructures, though with noticeable disorder and agglomeration (Fig. S23c). In a weakly\nalkaline environment (3–4 mM NaOH, pH 8–8.6), the coordination groups become fully\ndeprotonated, enabling a balanced kinetic interplay between nucleation and crystal-plane\ngrowth. This leads to the formation of well-defined flower-like architectures with uniform size\nand abundant layered features (Fig. S23d, e), yielding nanoflowers with an average size of\n20.92 ± 4.40 µm (Fig. S23f). Overall, pH-dependent protonation of L-cystine governs its\ncoordination with Cu2+ and modulates the reaction kinetics, providing a straightforward and\neffective strategy for tailoring the formation of Cu Cyt complexes (Fig. S24a–e).\n2\n2 4\nperformance of Cu Cyt at different reaction pH values. Morphological evolution of Cu Cyt at different\n2 2\npH values: (a) 0 mM NaOH (pH = 2.4), (b) 1 mM NaOH (pH = 2.8), (c) 2 mM NaOH (pH = 6.8), (d) 3\nmM NaOH (pH = 8.0), and (e) 4 mM NaOH (pH = 8.6). The right figure of (f) shows the particle size\ndistribution histograms (columns) and Gaussian fitting curves (red lines).\nXRD patterns show that under strongly acidic conditions, the product exhibits an amorphous\nstructure with very low crystallinity. Although the diffraction-peak intensity increases slightly\nunder weakly acidic conditions, the crystallinity remains poor. In contrast, under weakly\nalkaline conditions, the diffraction peaks become significantly stronger and sharper, indicating\nthe formation of a highly crystalline and well-defined Cu Cyt phase (Fig. S24g). The\n2\ngas-sensing performance correlates closely with these structural features. In the acidic range,\nthe response is extremely low because the amorphous, low-crystallinity particles provide\ninsufficient active sites and hinder electron transport. Under weakly acidic conditions, the\nresponse improves slightly, but disordered agglomeration restricts gas diffusion. In weakly\nalkaline conditions, the flower-like structures obtained at 3 mM NaOH achieve an optimal\nbalance of high specific surface area, moderate crystallinity, and ordered stacking, resulting in\nthe highest sensing response. At 4 mM NaOH, the flower size increases and the specific\nsurface area decreases slightly, but the improved crystallinity maintains a high response level\n(Fig. S24f).\n2 4\npH values: (a-e) Enlargement SEM images of the material at different amounts of NaOH ranging from 0 to\n4 mm; (d) XRD patterns of Cu Cyt and (e) C H sensing response curves of Cu Cyt at different reaction pH\n2 2 4 2\nvalues.\n5. As shown in the video, the scientificity of the testing method is uncertain, and the\nresponse of the chemical sensor is also affected by the operation methods.\nAuthor Response: Thank you for raising this critical point regarding the scientific rigor of\nour sensing tests. We fully agree that the reliability of a sensor’s response is paramount and\ncan be affected by operational factors such as manual handling and environmental fluctuations.\nTo address these concerns comprehensively and eliminate potential artifacts, we have\nredesigned our experimental protocol and performed three key control and validation\nexperiments. All updates have been incorporated into the revised manuscript, including new\nsupplementary movies and supporting information.\n32\n(1) Independent quantitative validation of ethylene concentration:\nTo verify that the sensor responds to ethylene at biologically relevant levels, we independently\nsampled the headspace gas from the same fruit container and analyzed it using gas\nchromatography (GC). The GC results quantified the ethylene concentration at 3.72 ppm\n(Fig. S28), which lies well within the quantitative detection range of our sensor. This provides\nindependent and objective confirmation that the fruit emits ethylene at concentrations that our\nsensor is specifically designed to detect.\n(2) Revised testing protocol to eliminate operational influence:\nWe have completely replaced the previous manual operation (Supplementary Movie S2). In\nthe updated protocol, the sensor remains fixed in position while the target gas is delivered\nusing a precise micro air pump. Specifically, the headspace gas from the fruit container is\nactively drawn and directed across the sensor surface at a controlled flow rate (Fig. S28). This\napproach eliminates mechanical disturbances and temperature fluctuations associated with\nmoving the sensor, ensuring that the recorded signal originates solely from the chemical\ninteraction with the target gas.\n(3) Critical blank control experiments:\nTo rigorously exclude the possibility that the sensor response originates from environmental\nfluctuations (such as temperature or humidity) or from the act of placing the sensor into a\ncontainer, we conducted a blank control experiment. The sensor was placed in an identical\nempty container (without fruit) and tested using the same air-pump-driven gas-delivery setup.\nAs shown in the new supplementary movie (Supplementary Movie S3), the sensor exhibits\nno measurable response under these conditions. This result confirms that the signals observed\nin the presence of fruit are not artifacts of the testing procedure or environmental factors, but\narise solely from the target gas.\nThe addition to the revised manuscript: “To visually demonstrate the practical applicability of\nour sensors, the supplementary movies document the complete validation process\n(Supplementary Movies S1–S3). These visual demonstrations, together with independent GC\nanalysis confirming an ethylene concentration of 3.7 ppm in the fruit container (Fig. S27),\nprovide strong scientific evidence that the Cu₂Cyt/MXene sensor delivers a reliable and\naccurate response under practical conditions.”\nFig. S27 GC of the gas extracted from the fruit box.\nFig. S28 Schematic diagram of gas acquisition and detection system corresponding to the experiment in\nMovie S2.\nReviewer #1:\nI am fine with the revised version. I recommend acceptance.\nAuthor Response: We sincerely thank the reviewer for their positive feedback and for\nendorsing the publication of our manuscript.\nReviewer #2:\nThe authors have addressed the concerns raised in the initial review. The synthesis is\nnow described in sufficient detail to ensure reproducibility, supported by a clear\nsummary of key experimental parameters. The mechanistic interpretation has been\nnotably strengthened through the addition of time-dependent XRD, in situ/ex situ\nFTIR, and DFT analysis, which together provide convincing evidence for the\nproposed Cu Cyt–MXene interaction and ethylene sensing mechanism.\nconcentration, and pH clarifies the roles of kinetic and thermodynamic control in\nmaterial formation and performance. The sensing methodology has also been\nimproved through more rigors testing protocols and independent GC validation. The\nrevisions substantially improve the scientific rigor of the study, and the manuscript is\nsuitable for publication in its revised form.\nAuthor Response: We acknowledge the reviewer's recognition of our additional\nexperiments and discussions. We also appreciate their recommendation for\npublication.\nReviewer #3:\nI co-reviewed this manuscript with one of the reviewers who provided the listed\nreports. This is part of the Nature Communications initiative to facilitate training in\npeer review and to provide appropriate recognition for Early Career Researchers who\nco-review manuscripts.\nAuthor Response: We appreciate the time and expertise contributed by all reviewers\nto the evaluation of our work and thank Nature Communications for facilitating this\ninitiative."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I am fine with the revised version. I recommend acceptance.", "reviewer_2": "The authors have addressed the concerns raised in the initial review. The synthesis is now described in sufficient detail to ensure reproducibility, supported by a clear summary of key experimental parameters. The mechanistic interpretation has been notably strengthened through the addition of time-dependent XRD, in situ/ex situ FTIR, and DFT analysis, which together provide convincing evidence for the proposed Cu₂Cyt–MXene interaction and ethylene sensing mechanism.\nIn addition, the systematic investigation of reaction time, temperature, precursor concentration, and pH clarifies the roles of kinetic and thermodynamic control in material formation and performance. The sensing methodology has also been improved through more rigors testing protocols and independent GC validation. The revisions substantially improve the scientific rigor of the study, and the manuscript is suitable for publication in its revised form.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Author Response: We acknowledge the reviewer's recognition of our additional experiments and discussions. We also appreciate their recommendation for publication.\nAuthor Response: We appreciate the time and expertise contributed by all reviewers to the evaluation of our work and thank Nature Communications for facilitating this initiative."}]

Decision letter