English

• Most biomolecular machines in nature derive energy from biochemical reactions to power their motion through energy release [1-3]. Inspired by natural systems, chemists have developed chemically fuelled dissipative systems [4-7]. The synthesis of artificial dissipative molecular machines not only provides deeper insights into biological systems but also demonstrates broad applications in diverse fields [8-11]. For instance, such dissipative systems have been successfully implemented in self-assembly gel materials [12-17], molecular switches and motors [18,19], and switchable catalysts [20,21]. However, the remarkable complexity of biological molecular machines necessitates more sophisticated control strategies for their artificial counterparts [22,23].

  To date, temporal control of host-guest interactions in artificial dissipative systems has been predominantly achieved through structural modifications of chemical fuels and adjustments in their concentrations [24,25]. In 2016, S. Di Stefano and co-workers reported the first example of a small-molecule chemical fuel that could trigger the oscillatory motion of a molecular machine, demonstrating further control over switching rates through fuel structure optimization [26]. While substituent effects play crucial roles in regulating supramolecular functions [27-35], the influence of guest substituents on the switching kinetics of dissipative molecular systems remains unexplored to the best of our knowledge. This study not only expands the toolkit of chemically fuelled systems but, more importantly, establishes a dual synergistic regulatory strategy, through molecular-level rational design of the functional components (guest and fuel), for constructing chemically fueled dissipative systems with programmable temporal control.

  “Texas-sized” molecular boxes (TxSBs), a class of conformationally flexible cationic hosts and self-assembly building blocks, have shown particular promise in this context [36-39]. Building upon our previous work that established an anion-recognition-based chemically fueled dissipative system with temporally programmable characteristics [40], we herein present a comprehensive study employing two distinct Texas-sized molecular boxes in combination with dual chemical fuels. This investigation systematically evaluates 17 different substituted p-terephthalic acid dianions (PTAs). The nature of guest substituents, which includes hydrogen-bond donors, electron-donating, or electron-withdrawing groups, exerts critical control over the operational rates of dissipative molecular switches. Our findings substantiate the hypothesis that strategic selection of anionic components can provide novel perspectives for designing and regulating the functional dynamics of dissipative molecular machines.

  The two tetra-cationic macrocycles (Fig. 1a), Na-TxSB (naphthalene-bridged) and An-TxSB (anthracene-bridged), were synthesized using naphthalene and anthracene as bridging units, respectively. A pyridyl-based trimeric precursor was synthesized via Ullmann-type coupling, followed by cyclization with 2,6-bis(bromomethyl)naphthalene or 9,10-bis(bromomethyl)anthracene. The resulting products were converted to their hexafluorophosphate salts by treatment with aqueous ammonium hexafluorophosphate. Both macrocycles feature multiple aromatic π-surfaces (naphthalene, anthracene, and pyridine moieties) that facilitate π-π donor-acceptor and anion-π interactions with specific guests. Their cationic nature and hydrogen-bond-donating capabilities further enhance anion recognition. Single-crystal X-ray analysis confirmed that Na-TxSB and An-TxSB adopt a chair-like and box-like conformation [36,41], respectively, with the naphthalene and anthracene bridges oriented perpendicularly to the 2,6-bis(1H-imidazol-1-yl)pyridine subunits due to steric constraints (Figs. S1–S4 in Supporting information).

  Figure 1

  

  Figure 1.  (a) The synthetic route of the target macrocycles Na-TxSB and An-TxSB. (b) Structures of the chemical fuels (ACA1 and ACA2) and dianionic PTA-derived guests G1-G17 considered in the present study. (c) Top view (left) and side view (right) of the optimized geometry of [Na-TxSB·G1]. (d) Geometries of [Na-TxSB·G1] was optimized at the B3LYP/6–31+G(d) level with Grimme's dispersion correction. (e) The frontier molecular orbitals of [Na-TxSB·G1] in excited states were performed at the PBE0/6–31G(d) level of theory.

  DownLoad: Full-Size Img PowerPoint

  Prior to investigating dissipative switching behavior, the interactions between Na-TxSB or An-TxSB and 17 guest molecules were analyzed via ¹H NMR in DMSO‑d₆ at 298 K. For example, mixing 0.5 mmol/L of the diprotonated guest G1 with 1 equiv. of Na-TxSB or An-TxSB induced no significant chemical shift changes. However, upon deprotonation of G1, distinct shifts in ¹H NMR spectra indicated strong host-guest complexation (Figs. S5–S72 in Supporting information).

  Due to the unsuccessful acquisition of suitable single crystals of the host-guest complex for XRD analysis, the binding geometry of the [Na-TxSB·G1] complex was optimized using density functional theory (DFT) calculations at the B3LYP/6–31G(d) level (Fig. 1c). DFT analysis revealed the presence of non-covalent weak interactions between Na-TxSB and G1. Multiple hydrogen bonds and C–H···π interactions were visualized using the Independent Gradient Model (IGM) based on Hirshfeld partitioning of the electron density, represented by thin, narrow green isosurfaces (sign(λ₂)ρ) in Fig. 1d. Frontier molecular orbital analysis of the [Na-TxSB·G1] complex indicates that the HOMOs are primarily localized on the guest molecule G1, whereas the LUMOs are distributed across the pyridyl-based trimeric precursor of the host (Fig. 1e). This orbital distribution suggests a host-guest charge-transfer character for the complex.

  Fluorescence titration or nuclear magnetic titration experiments further quantified the binding affinities between the macrocycles and G1, yielding association constants (K_a1 and K_a2) of (4.9 ± 0.1) × 10³ and (3.4 ± 0.6) × 10² L/mol for Na-TxSB and similar values for An-TxSB (Figs. S74 and S108 in Supporting information). Similar analyses for guests G2-G17 revealed K_a values summarized in Table S1 (Figs. S73–S140 in Supporting information).

  The operational dynamics of the dissipative molecular switch were interrogated through time-resolved UV–vis spectroscopy. As illustrated in Fig. 2c, the system was initially prepared in a DMSO/H₂O (9:1, v/v) solvent mixture containing equimolar concentrations (3 × 10^–5 mol/L) of the macrocyclic hosts and protonated guest G1, corresponding to the non-complexed "State B". The UV–vis spectrum (red dashed line) exhibited an absorbance of 0.13 at 370 nm. Subsequent addition of 5 equiv. triethylamine induced complete deprotonation of G1, triggering host-guest complexation ("State A"), which reduced the absorbance at 370 nm to 0.06 (blue dashed line).

  Figure 2

  

  Figure 2.  (a, b) Cartoon schematic representation of the cyclic dissipative operation of the molecular switches when using chemical fuels ACA1 (a) and ACA2 (b) respectively. Time-dependent UV–vis spectra recorded for the mixtures of dissipative molecular switches systems [Na-TxSB·ACA1·G1] (c), [Na-TxSB·ACA2·G1] (d), [An-TxSB·ACA1·G1] (e), and [An-TxSB·ACA2·G1] (f); host (0.03 mmol/L), G1 (0.03 mmol/L), Et₃N (0.15 mmol/L) and chemical fuel (0.75 mmol/L). According to Figs. 3c-f, the time-dependent absorbance changes at 374 nm (g), 374 nm (h), 378 nm (i), and 378 nm (j) were obtained, respectively. The corresponding half-reaction times are 1268 s, 264 s, 1212 s, and 320 s.

  DownLoad: Full-Size Img PowerPoint

  Introduction of 10 equiv. ACA1 as the chemical fuel provoked immediate protonation of the dianionic guest, reverting the system to State B, as evidenced by the rapid increase of absorbance. An appropriate chemical fuel concentration (10 equiv.) was selected to ensure that the kinetic processes fell within a clearly monitorable experimental window, allowing for reliable comparison of switching dynamics across different dissipative molecular switch systems. This study defines the half reaction time (t_1/2) as the time required for the absorbance to decrease to half of its maximum value. Time-dependent monitoring revealed a transient plateau phase (~902 s) attributable to fuel excess, followed by gradual absorbance decay (t_1/2 = 1268 s) as ACA1 underwent consumption via decarboxylation. This decay phase reflects slow guest re-deprotonation and subsequent reformation of the host-guest complex, ultimately restoring State A after a full cycle duration of ~2900 s (Fig. 2g). The decomposition of chemical fuel ACA1 drives the dissipative cycle by modulating the protonation state of the guest. Initially, triethylamine deprotonates the guest, enabling host–guest complex formation. Addition of ACA1 reprotonates the guest, dissociating the complex. ACA1 then undergoes decarboxylation, releasing CO₂ and generating a carbanion intermediate that is rapidly protonated, thereby restoring the basic triethylamine. This process gradually shifts the proton balance, allowing the guest to re‑deprotonate and reform the host–guest complex until the fuel is depleted, completing one operational cycle.

  Theoretically, such dissipative processes are described as analogous to catalytic cycles that return to the initial state after fuel consumption. In these dissipative systems, the chemical reaction can generate waste products chloroform or 2-(p-tolyl)propanenitrile that accumulate in the system, and the concentration of the chemical fuel used undergoes a dynamic depletion process that gradually decreases over time.

  Notably, replacing ACA1 with ACA2 markedly accelerated the switching kinetics. For the Na-TxSB system, ACA2 reduced the t_1/2 to 264 s, representing a 5-fold rate enhancement compared to ACA1 (Figs. 2d and h). Similarly, An-TxSB exhibited a t_1/2 of 1212 s with ACA1, corresponding to a 3.8-fold acceleration relative to ACA2 (Figs. 2e, i, f and j). These results unambiguously demonstrate that strategic selection of chemical fuels enables precise modulation of dissipative switching rates.

  To generalize our findings, we systematically investigated dissipative molecular switches incorporating PTAs bearing diverse substituents (G2-G17) (Figs. S141-S286 in Supporting information). Statistical analysis of the half reaction time (t_1/2) revealed pronounced variations in switching rates across the guest series (Fig. 3). To elucidate these differences, Mulliken charges of all guest molecules were computed using density functional theory (DFT) at the B3LYP/6–311G(d) level (Supporting information). The calculated charge distributions suggested a correlation between guest electronic properties and switching kinetics.

  Figure 3

  

  Figure 3.  Geometries of guest molecules were optimized at the B3LYP/6–31+G(d) level with the Mulliken charge analysis (the number on top of optimized guest electron structure). The blue numbers indicate the t_1/2 for different guests when the dissipative molecular switch system is [Na-TxSB·ACA1·G], while the numbers in parentheses represent the t_1/2 for different guests when the dissipative molecular switch system is [Na-TxSB·ACA2·G]. The light blue numbers indicate the t_1/2 for different guests when the dissipative molecular switch system is [An-TxSB·ACA1·G], while the numbers in parentheses represent the t_1/2 for different guests when the dissipative molecular switch system is [An-TxSB·ACA2·G].

  DownLoad: Full-Size Img PowerPoint

  For mono-substituted guests at the 2-position (G1, G2, G4–G6) and di-substituted guests at the 2,5-(G7–G12, G14) or 2,6-positions (G13, G16), a proportional relationship emerged: Higher Mulliken charges corresponded to longer t_1/2 values. For instance, for [Na-TxSB·ACA1·G] system, 2-mono-substituted G1 (Mulliken charge = 2.246) exhibited the longest t_1/2 of 1268 s. Replacing ACA1 with ACA2 yielded analogous trends, with G1 displaying a t_1/2 of 264 s. Similar proportionality was observed for 2,5-di-substituted guests: G12 (charge = 2.26) showed maximal t_1/2 values of 1500 s (ACA1) and 363 s (ACA2) (Figs. 4a and b).

  Figure 4

  

  Figure 4.  Dual-y-axis line charts illustrate the correlation trends between half-reaction times and Mulliken charges for the dissipative molecular switch systems [Na-TxSB·ACA1·G] (a) and [Na-TxSB·ACA2·G] (b).

  DownLoad: Full-Size Img PowerPoint

  The observed correlation between a higher Mulliken charge on the dianionic guest and a longer t_1/2 can be mechanistically rationalized. A higher Mulliken charge density on the guest molecule (specifically, the greater negative charge on the carboxylate oxygen atoms) signifies a higher proton affinity. Consequently, the subsequent re-deprotonation of the guest, which is necessary for regenerating the complex, becomes the rate-limiting step. This deprotonation process is slowed down because it is less favorable for a guest with a higher proton affinity, leading to a prolonged t_1/2. Furthermore, specific electronic substituent effects also influence the half-reaction time; for example, electron-withdrawing groups can lower the Mulliken charge density of the guest carboxylate, thereby accelerate the deprotonation step and shortening the t_1/2.

  Although the association constant (K_a) is essential for establishing reversible host–guest binding, its correlation with t_1/2 across the series of dissipative molecular switch systems is not straightforward. Specifically, for systems composed of the same host and the same chemical fuel paired with different guest molecules, we observed no simple monotonic correlation between K_a and t_1/2. This suggests that, in the present dissipative cycle, the rate-limiting process is not the physical re-association of the deprotonated guest with the preorganized host cavity, but is instead more closely tied to the kinetics of the guest's protonation-state interconversion, which is modulated by electronic effects. Thus, in the current dissipative molecular switch systems, the influence of the guest’s intrinsic acid–base character, reflected in its Mulliken charge, on the switching rate outweighs differences in K_a.

  Notably, the unsubstituted guest G3 (charge = 2.224) deviated from this trend, exhibiting shorter t_1/2 values (821 s with ACA1; 195 s with ACA2) compared to substituted analogs. This anomaly likely arises from the synergistic interplay of electronic and steric effects in substituted derivatives. Supporting this hypothesis, di-substituted hydroxyl derivatives (G14, G15, G16) with elevated Mulliken charges displayed extended t_1/2 values (e.g., 937 s for G14 with ACA1; 168 s with ACA2), further underscoring the critical roles of substituent electronic character and steric hindrance.

  To validate the universality of these observations, parallel experiments were conducted using An-TxSB as the host. The resulting t_1/2 trends for both ACA1 and ACA2-driven systems corroborated the above conclusions (Figs. S209-S286 in Supporting information), confirming that substituent electronic modulation combined with steric factors governs the operational dynamics of dissipative molecular switches. The different decarboxylation rates of the two chemical fuels (ACA1 and ACA2) used in this study indicate that the proton-transfer kinetics are significantly influenced by the substituents of the chemical fuel. This is due to the strong structural dependence of carbanion stability and reactivity [24,42].

  In conclusion, we have developed a versatile platform for controlling dissipative molecular switch kinetics through integrated host-guest design and fuel engineering. The combination of π-rich Texas-sized macrocycles (Na-TxSB and An-TxSB) and varied PTA derivatives enabled precise correlation of guest substituent effects with switching dynamics. Key findings include: (1) Chemical fuel structure affects temporal control, with ACA2 outperforming ACA1 by 3–6-fold in switching rates; (2) Substituent electronic character (quantified via Mulliken charges) and positional isomerism synergistically govern t_1/2 values, establishing design rules for rate modulation; (3) Host flexibility (naphthalene and anthracene bridges) preserving substituent-dependent trends. These insights bridge supramolecular design with non-equilibrium thermodynamics, enabling a strategy for rational modulation for constructing chemically fueled dissipative systems. This methodology expands the toolkit for temporally programmed molecular switch systems.

  CRediT authorship contribution statement

  Xin Zhang: Writing – original draft, Investigation, Conceptualization. Shuo Li: Investigation. Chenghao Zhu: Investigation. Xu-Lang Chen: Investigation. Lijun Mao: Writing – review & editing, Writing – original draft, Investigation. Da Ma: Writing – review & editing, Writing – original draft, Project administration, Conceptualization.

  Declaration of competing interest

  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

  Acknowledgments

  The authors want to thank Zhejiang Provincial Natural Science Foundation of China (No. LQN26B020017 to X. Zhang, No LR24B020003 to D. Ma and No LQ24B020003 to L. Mao), Key Research and Development Program of Sichuan Province of China (No. 2024YFFK0057, D. Ma), the Technology Project of Taizhou City (No. 24gyb17, X. Zhang), open Research Fund of Hubei Key Laboratory of Pollutant Analysis & Reuse Technology (No. PA210102, X.-L. Chen).

  Supplementary materials

  Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.cclet.2026.112483.

  
  
• 1. [1]

     G. Ragazzon, L.J. Prins, Nat. Nanotechnol. 13 (2018) 882–889. doi: 10.1038/s41565-018-0250-8

  2. [2]

     K. Das, L. Gabrielli, L.J. Prins, Angew. Chem. Int. Ed. 60 (2021) 20120–20143. doi: 10.1002/anie.202100274

  3. [3]

     C. Biagini, S. Di Stefano, Angew. Chem. Int. Ed. 59 (2020) 8344–8354. doi: 10.1002/anie.201912659

  4. [4]

     S.A.P. van Rossum, M. Tena-Solsona, J.H. van Esch, R. Eelkema, J. Boekhoven, Chem. Soc. Rev. 46 (2017) 5519–5535. doi: 10.1039/C7CS00246G

  5. [5]

     B. Rieß, R.K. Grörtsch, J. Boekhoven. Chem. 6 (2020) 552–578.

  6. [6]

     M. Cheng, D. Chen, L. Zhang, et al., Org. Chem. Front. 10 (2023) 1380–1385. doi: 10.1039/d2qo01888h

  7. [7]

     E. Olivieri, J.M. Gallagher, A. Betts, T.W. Mrad, D.A. Leigh, Nat. Synth. 3 (2024) 707–714. doi: 10.1038/s44160-024-00493-w

  8. [8]

     S.A.P. van Rossum, M. Tena-Solsona, J.H. van Esch, R. Eelkema, J. Boekhoven, Chem. Soc. Rev. 46 (2017) 5519–5535. doi: 10.1039/C7CS00246G

  9. [9]

     G. Fusi, D. Del Giudice, O. Skarsetz, S. Di Stefano, A. Walther, Adv. Mater. 35 (2023) 2209870. doi: 10.1002/adma.202209870

  10. [10]

      S. De, R. Klajn, Adv. Mater. 30 (2018) 1706750. doi: 10.1002/adma.201706750

  11. [11]

      S.T. Han, H.Y. Duan, T.G. Zhan, et al., Chin. Chem. Lett. 34 (2023) 107639. doi: 10.1016/j.cclet.2022.06.062

  12. [12]

      E. Olivieri, B. Gasch, G. Quintard, J.V. Naubron, A. Quintard, ACS Appl. Mater. Interfaces 14 (2022) 24720–24728. doi: 10.1021/acsami.2c01608

  13. [13]

      M. Cheng, C. Qian, Y. Ding, et al., ACS Materials Lett 2 (2020) 425–429. doi: 10.1021/acsmaterialslett.9b00509

  14. [14]

      G. Aykent, C. Zeytun, A. Marion, S. Özçubukçu, Sci. Rep. 9 (2019) 4893–4900. doi: 10.1038/s41598-019-41142-z

  15. [15]

      J. Boekhoven, W.E. Hendriksen, G.J.M. Koper, R. Eelkema, J.H. van Esch, Science 349 (2015) 1075–1079. doi: 10.1126/science.aac6103

  16. [16]

      J. Boekhoven, A.M. Brizard, K.N.K. Kowlgi, et al., Angew. Chem. Int. Ed. 49 (2010) 4825–4828. doi: 10.1002/anie.201001511

  17. [17]

      M. George, R.G. Weiss, J. Am. Chem. Soc. 123 (2001) 10393–10394. doi: 10.1021/ja016819+

  18. [18]

      D. Thomas, D.J. Tetlow, Y. Ren, et al., Nat. Nanotechnol. 17 (2022) 701–707. doi: 10.1038/s41565-022-01097-1

  19. [19]

      Q. Shi, C.F. Chen, Chem. Sci. 10 (2019) 2529–2533. doi: 10.1039/c8sc05469j

  20. [20]

      I. Valiyev, A. Ghosh, I. Paul, M. Schmittel, Chem. Commun. 58 (2022) 1728–1731. doi: 10.1039/d1cc06398g

  21. [21]

      C. Biagini, S.D.P. Fielden, D.A. Leigh, et al., Angew. Chem. Int. Ed. 58 (2019) 9876–9880. doi: 10.1002/anie.201905250

  22. [22]

      X. Mao, S. Zhang, Q. Shi, et al., Chin. Chem. Lett. 36 (2025) 110950. doi: 10.1016/j.cclet.2025.110950

  23. [23]

      M.N. Tasbas, E. Sahin, S. Erbas-Cakmak, Coord. Chem. Rev. 443 (2021) 214039. doi: 10.1016/j.ccr.2021.214039

  24. [24]

      C. Biagini, S. Albano, R. Caruso, et al., Chem. Sci. 9 (2018) 181–188. doi: 10.1039/C7SC04123C

  25. [25]

      D. Del Giudice, E. Spatola, M. Valentini, et al., Chem. Sci. 12 (2021) 7460–7466. doi: 10.1039/d1sc01196k

  26. [26]

      J.A. Berrocal, C. Biagini, L. Mandolini, S. Di Stefano, Angew. Chem. Int. Ed. 55 (2016) 6997–7001. doi: 10.1002/anie.201602594

  27. [27]

      Y. Li, N. Li, G. Li, et al., J. Am. Chem. Soc. 145 (2023) 9118–9128. doi: 10.1021/jacs.3c00800

  28. [28]

      X.L. Chen, Y.J. Shen, C. Gao, et al., J. Am. Chem. Soc. 142 (2020) 7443–7455. doi: 10.1021/jacs.9b13473

  29. [29]

      R. Lavendomme, T.K. Ronson, J.R. Nitschke, J. Am. Chem. Soc. 141 (2019) 12147–12158. doi: 10.1021/jacs.9b06182

  30. [30]

      Y.C. Chang, Y. Jiao, H.E. Symons, et al., Chem. Soc. Rev. 48 (2019) 989–1003. doi: 10.1039/c8cs00806j

  31. [31]

      S. Corra, C. de Vet, J. Groppi, et al., J. Am. Chem. Soc. 141 (2019) 9129–9133. doi: 10.1021/jacs.9b00941

  32. [32]

      X.D.C. R T Wu, T. Hirao, V.M. Lynch, J.L. Sessler, J. Am. Chem. Soc. 140 (2018) 6823–6831. doi: 10.1021/jacs.7b12957

  33. [33]

      C. Qin, Y. Li, Q. Li, C. Yan, L. Cao, Chin. Chem. Lett. 32 (2021) 3531–3534. doi: 10.1016/j.cclet.2021.05.006

  34. [34]

      P.J. Waller, Y.S. AlFaraj, C.S. Diercks, N.N. Jarenwattananon, O.M. Yaghi, J. Am. Chem. Soc. 140 (2018) 9099–9103. doi: 10.1021/jacs.8b05830

  35. [35]

      M. Li, D. Li, M. O’Keeffe, O.M. Yaghi, Chem. Rev. 114 (2014) 1343–1370. doi: 10.1021/cr400392k

  36. [36]

      X. Zhang, Z. Lu, T. Ren, et al., Chin. Chem. Lett. 36 (2025) 110946. doi: 10.1016/j.cclet.2025.110946

  37. [37]

      X. Zhang, J.L. Sessler, H.Y. Gong, Sci. China Chem. 69 (68) (2026) 300–308.

  38. [38]

      X. Zhang, Y.D. Yang, Z.H. Lu, et al., Proc. Natl. Acad. Sci. U. S. A. 118 (2021) e2112973118. doi: 10.1073/pnas.2112973118

  39. [39]

      Y.D. Yang, J.L. Sessler, H.Y. Gong, Chem. Commun. 53 (2017) 9684–9696. doi: 10.1039/C7CC04661H

  40. [40]

      X. Zhang, L. Mao, R. He, et al., Chem. Commun. 60 (2024) 1180–1183. doi: 10.1039/d3cc05912j

  41. [41]

      D. Luo, J. Tian, J. Zhou, X. Chi, Chin. Chem. Lett. 35 (2024) 109444. doi: 10.1016/j.cclet.2023.109444

  42. [42]

      D. Del Giudice, E. Spatola, R. Cacciapaglia, et al., Chem. Eur. J. 26 (2020) 14954–14962. doi: 10.1002/chem.202002574

• 

  Figure 1  (a) The synthetic route of the target macrocycles Na-TxSB and An-TxSB. (b) Structures of the chemical fuels (ACA1 and ACA2) and dianionic PTA-derived guests G1-G17 considered in the present study. (c) Top view (left) and side view (right) of the optimized geometry of [Na-TxSB·G1]. (d) Geometries of [Na-TxSB·G1] was optimized at the B3LYP/6–31+G(d) level with Grimme's dispersion correction. (e) The frontier molecular orbitals of [Na-TxSB·G1] in excited states were performed at the PBE0/6–31G(d) level of theory.

  下载: 全尺寸图片 幻灯片
  

  Figure 2  (a, b) Cartoon schematic representation of the cyclic dissipative operation of the molecular switches when using chemical fuels ACA1 (a) and ACA2 (b) respectively. Time-dependent UV–vis spectra recorded for the mixtures of dissipative molecular switches systems [Na-TxSB·ACA1·G1] (c), [Na-TxSB·ACA2·G1] (d), [An-TxSB·ACA1·G1] (e), and [An-TxSB·ACA2·G1] (f); host (0.03 mmol/L), G1 (0.03 mmol/L), Et₃N (0.15 mmol/L) and chemical fuel (0.75 mmol/L). According to Figs. 3c-f, the time-dependent absorbance changes at 374 nm (g), 374 nm (h), 378 nm (i), and 378 nm (j) were obtained, respectively. The corresponding half-reaction times are 1268 s, 264 s, 1212 s, and 320 s.

  下载: 全尺寸图片 幻灯片
  

  Figure 3  Geometries of guest molecules were optimized at the B3LYP/6–31+G(d) level with the Mulliken charge analysis (the number on top of optimized guest electron structure). The blue numbers indicate the t_1/2 for different guests when the dissipative molecular switch system is [Na-TxSB·ACA1·G], while the numbers in parentheses represent the t_1/2 for different guests when the dissipative molecular switch system is [Na-TxSB·ACA2·G]. The light blue numbers indicate the t_1/2 for different guests when the dissipative molecular switch system is [An-TxSB·ACA1·G], while the numbers in parentheses represent the t_1/2 for different guests when the dissipative molecular switch system is [An-TxSB·ACA2·G].

  下载: 全尺寸图片 幻灯片
  

  Figure 4  Dual-y-axis line charts illustrate the correlation trends between half-reaction times and Mulliken charges for the dissipative molecular switch systems [Na-TxSB·ACA1·G] (a) and [Na-TxSB·ACA2·G] (b).

  下载: 全尺寸图片 幻灯片
•