Structure Identification for Force-Induced Reaction Using Single-Molecule Conductance Measurement
2022; Chinese Chemical Society; Volume: 5; Issue: 8 Linguagem: Inglês
10.31635/ccschem.022.202202297
ISSN2096-5745
AutoresJueting Zheng, Wenli Gao, Taige Lu, Lijue Chen, Luchun Lin, Ruiyun Huang, Yongxiang Tang, Gang Dong, Junyang Liu, Yifei Pan, Wengui Weng, Wenjing Hong,
Tópico(s)Molecular Junctions and Nanostructures
ResumoOpen AccessCCS ChemistryRESEARCH ARTICLES22 Oct 2022Structure Identification for Force-Induced Reaction Using Single-Molecule Conductance Measurement Jueting Zheng†, Wenli Gao†, Taige Lu, Lijue Chen, Luchun Lin, Ruiyun Huang, Yongxiang Tang, Gang Dong, Junyang Liu, Yifei Pan, Wengui Weng and Wenjing Hong Jueting Zheng† State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 †J. Zheng and W. Gao contributed equally to this work.Google Scholar More articles by this author , Wenli Gao† Department of Chemistry, College of Chemistry and Engineering, Xiamen University, Xiamen 361005 †J. Zheng and W. Gao contributed equally to this work.Google Scholar More articles by this author , Taige Lu State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Lijue Chen State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Luchun Lin State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Ruiyun Huang State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Yongxiang Tang State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Gang Dong State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Junyang Liu State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Yifei Pan Department of Chemistry, College of Chemistry and Engineering, Xiamen University, Xiamen 361005 Google Scholar More articles by this author , Wengui Weng *Corresponding authors: E-mail Address: [email protected] E-mail Address: [email protected] Department of Chemistry, College of Chemistry and Engineering, Xiamen University, Xiamen 361005 Google Scholar More articles by this author and Wenjing Hong *Corresponding authors: E-mail Address: [email protected] E-mail Address: [email protected] State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering and Institute of Artificial Intelligence and Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen 361005 Google Scholar More articles by this author https://doi.org/10.31635/ccschem.022.202202297 SectionsSupplemental MaterialAboutAbstractPDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinked InEmail Spiropyran derivatives are prototype mechanophores with a promising application as molecular sensors because of their changeable structure under external force stimuli. However, the chemical structure evolution under external stimuli remains unclear due to the uncertainty and difficulty in distinguishing the structures of different ring-opened merocyanine isomers generated in the force-induced reaction. Here we identify the structure of isomers produced by the force-induced reaction of spiropyran derivatives using a single-molecule conductance measurement and an unsupervised clustering algorithm. We found that the original data from the single-molecule conductance measurement can be divided into four clusters through unsupervised clustering. By introducing a photoinduced reaction and theoretical calculation, we identified and attributed the four clusters of data to the multiple states of the molecular junctions. Our work demonstrates that a single-molecule break junction measurement can distinguish the isomers in the force-induced reaction, suggesting the great potential of single-molecule conductance measurement and unsupervised clustering approaches for structural analysis. Download figure Download PowerPoint Introduction Mechanochemistry offers a unique strategy for the study of mechanical transformations of bonds in mechanophores.1–6 Among these mechanophores, spiropyran-cored (SP) compounds can not only be mechanically activated but also stimulated by other cues to display color changes due to the spiro C–O bond breaking into merocyanine (MC) isomers. Therefore, spiropyran derivatives have been extensively studied, especially for the incorporation into polymers and the corresponding polymer mechanochemistry.7–10 Investigation of the evolution of MC isomers under external stimuli is critical to understanding the structure–property relationships of MC and the application of SP mechanophores.11–13 However, since there are several product isomers generated in the force-induced reaction, the exact chemical structure of spiropyran derivatives formed under external stimuli remains unclear.14 The in situ characterization of the structural changes in spiropyran derivatives under external stimuli has the potential to reveal the structural evolution in the forced-induced reaction process.15 Single-molecule techniques16–18 hold great potential to reveal the structural evolution of mechanophores in the force-induced reaction process. Atomic force microscopy (AFM)-based single-molecule force spectroscopy has been adopted to study SP-containing polymers.19,20 However, the structure of the MC isomers13 generated in the force-induced reaction cannot be well distinguished due to the presence of multiple isomers in the polymers. Single-molecule break junction techniques, including mechanically controllable break junction,21–23 scanning tunneling microscopy break junction (STM-BJ),16,17,24–28 and atomic force microscopy break junction,29,30 can also analyze the structure evolution in a reaction at the single-molecule level,31–33 which offers a unique chance for investigating the structural changes during the reaction of mechanically sensitive compounds by monitoring the single-molecule conductance changes under applied tension force. In this study, we synthesized a novel thioether-functionalized spiropyran-cored compound ( SSP) and measured its single-molecule conductance using the STM-BJ technique with repetitive force applied to the junction. We divided over 4000 individual curves into four types via a lab-developed unsupervised spectral clustering algorithm according to the Calinski–Harabasz (CH) index.34–37 The change of conductance along with the stretching distance indicates that the Au/ SSP/Au junction experienced structural changes during the break junction processes. STM-BJ measurements on the merocyanine compound ( SMC-UV), formed from ultraviolet irradiation of SSP,38 and a reference molecule SIN-Ref further suggest that the highest conductance value among the four types originated from a shorter configuration. We attributed the other three types to the ring-closed form of SSP and possible merocyanine ( SMC) products based on the experimental observations and clustering algorithm combined with density functional theory (DFT) calculations. Our results demonstrate the potential of single-molecule break junction measurement and clustering algorithm for structural analysis of the chemical reactions. Experimental Methods Materials synthesis 4-Iodophenylhydrazinium hydrochloride, iodomethane, 6-ethynyl-4,4-dimethyl 2,3-dihydrothiochromene, 2-hydroxy-3-nitrobenzaldehyde, PdCl2(PPh3)2, and CuI were purchased from Aldrich (Shanghai, China). 3-Iodo-4-nitrophenol and methyl isopropyl ketone were purchased from Meryer (Shanghai, China). All the other chemical reagents were purchased from Sinopharm (Shanghai, China) and used without further purification. The detailed synthesis procedures and characterization data (1H NMR, 13C NMR, and mass spectrometry) of SSP and SIN-Ref compounds are listed in the Supporting Information Figures S1–S3. Data analysis details Conductance histograms were constructed from the conductance traces with a bin size of 1000 (bin width = 0.01 log(G/G0)). Two-dimensional conductance-distance histograms were constructed with a bin size of 1000 × 500 (log(G/G0) × nm). The conductance-distance traces were aligned by taking Δz = 0 for the conductance value equal to 10−0.3G0. The spectral clustering algorithm was adopted from the previous report.37 The data analysis was processed in our open-source code pace XME-data analysis (Xiamen Electronics, https://github.com/Pilab-XMU/XMe_DataAnalysis). Here, each conductance trace was constructed into the conductance histogram. By choosing conductance as the feature, spectral clustering with a CH index was applied to assign similar conductance histograms, thus dividing the original conductance traces into clusters. Theoretical calculation details DFT calculation was performed with the B3LYP/6-31G* in Gaussian 16 package.39 The transmission spectra were performed using the QuantumATK 2018.6 package based on the DFT-nonequilibrium Green’s function (NEGF) method.40 Results and Discussion Single-molecule conductance measurements We fabricated single-molecule junctions via a lab-built STM-BJ setup,41 as shown in Figure 1a (for experimental details, please refer to Supporting Information Section 2 and Figures S14–S15). Since the force between the Au and S atom can transmit to the core of the target structure, the break junction process formed a ring-opened isomer of SSP compound ( SMC). This mechanochemistry reaction has several possible SMC isomer products (Figure 1b),13 thus the measuring results of SSP junction might contain multiple types of conductance traces. To classify the different states of the junction, we utilized an unsupervised spectral clustering algorithm to separate all curves of Au/ SSP/Au junction tests.37 As shown in Figure 1c, the original conductance histogram did not show a noticeable conductance feature, and the conductance traces exhibited a variety of the plateau position before clustering (inset). After analyzing the original data with a spectral clustering algorithm, the CH index42 presented the highest value at four clusters, indicating that the data is most likely separated into four types, as demonstrated in Figure 1d. The original data (4580 traces) can be divided into four kinds of typical conductance traces with distinct plateau features at certain conductance ranges after clustering, as shown in Figure 1e inset. The clustered traces were statistically analyzed into conductance histograms, which are illustrated in Figure 1e. The trace amounts from clusters 1, 2, 3, and 4 are 868, 1073, 1209, and 1430, respectively. Figure 1 | (a) Schematic of STM-BJ technique. (b) Left panel: the chemical structures of SSP and its ring-opened form SMC. Right panel: possible structures of the isomers of SMC. (c) The conductance histogram of the SSP junction without data selection. Inset: typical conductance traces before clustering. (d) Calinski–Harabasz (CH) index of the clustering results for the SSP junction and schematic of spectral clustering. (e) The conductance histograms constructed from the traces according to the clustering algorithm. Inset: clustered conductance traces. Download figure Download PowerPoint 2D conductance-distance analysis After clustering, we found an abnormal “jumping” feature in many of the conductance traces in clusters 2–4, as shown in Figure 2a. That is, when the distance of electrodes increases, the conductance value of the junction is enhanced. However, the transmission probability should be lower when the electrode distances are larger. Walkey et al.15 observed the in situ junction conductance change for spiropyran derivatives with Au–C bond connection in the individual conductance-distance traces, whereas the direct cause of the in situ changed conductance state remains unknown. Our results also indicate a structural change to a more conductive form during the break junction process. To further investigate the correlation between conductance and the structure of single-molecule junctions, we applied a 2D conductance-distance histogram43 to obtain the conductance evolution during the stretching process. As shown in Figure 2b, we selected those curves with this anomalous “jumping” feature and constructed them into another conductance-distance histogram containing 995 curves (out of 4580 curves).44 This phenomenon indicated that the structures of the single-molecule SSP junctions changed during the stretching process, leading to the conductance increase rather than decrease over a long distance. To investigate the new structure generated in the stretching process, we constructed the 2D conductance-distance histograms of the four clusters in Figure 2c–f. The corresponding 2D conductance-distance histograms constructed from the curves with the “jumping” feature are shown in Supporting Information Figure S16. Clear plateaus demonstrate the formation of molecular junctions with various conductance features and their corresponding distances. Among these four clusters, Cluster 1 has the shortest plateau, indicating that the junction length of cluster 1 is smaller than the other three. In all, 2D conductance-distance histogram analysis further confirmed the structural changes in the SSP junction, and the break junction process contained multiple configurations with different lengths. Figure 2 | (a) Typical conductance-distance traces with “jumping” feature. These traces were treated with offsets in the x direction for better view. (b) 2D conductance-distance histogram constructed from the curves with conductance enhancement with the stretching. The traces were realigned at the point where the conductance value changed abruptly. For the realignment, we chose the middle of the x-axis scale (Δz = 1.5 nm) for better vision. (c–f) 2D conductance-distance histograms constructed from the four clusters. Insets: length distributions of the molecular junction for the corresponding clusters. Download figure Download PowerPoint Structure identification To reveal the structure of the shorter junction configuration in the measurements of SSP junctions, we applied 365 nm UV-light irradiation to form the ring-opened merocyanine compound SMC-UV ( Supporting Information Figures S17 and S18). We also designed and synthesized the reference molecule, SIN-Ref, which contains the indoline structure but is half the length of the SSP and SMC molecules, as shown in Figure 3a. We measured SMC-UV and SIN-Ref junctions with the same methodology and observed an apparent plateau in conductance traces. There is also a multi-conductance feature for the SMC-UV junctions, shown as the purple line in Figure 3b. The high conductance is located around 10−3G0, and the low conductance is around 10−4.7G0. The high conductance value of spiropyran derivatives has been reported and attributed to the force or UV light-activated ring-opened configurations.15,45 However, such attribution cannot explain the origin of the low conductance feature in our experiments. The high conductance feature of the SMC-UV junction is similar to that of Cluster 1 in SSP and SIN-Ref. The 2D conductance-distance histograms of SMC-UV (Figure 3c) and SIN-Ref (Figure 3d) show similar features in the region around 10−3G0. The corresponding distance distribution (insets) demonstrate that the junction length is consistent, indicating a similar configuration in three individual measurements. The broad conductance peak constructed from the SSP-Cluster 1 indicates that a configuration of this type of junction is unstable, resulting in the decentralized distribution of conductance.32 The comparison demonstrates that the higher conductance value for the SSP and SMC-UV junction originates from the junctions with a similar configuration to SIN-Ref rather than the fully-stretched, higher conductance merocyanine form. Figure 3 | (a) The chemical structures of SMC-UV and SIN-Ref. (b) Conductance histograms of SSP-Cluster 1, SMC-UV, and SIN-Ref. (c) 2D conductance-distance histograms of SMC-UV. Insets: the corresponding distance distributions. (d) 2D conductance-distance histograms of SIN-Ref. Insets: the corresponding distance distributions. (e) The configuration demonstrations of high and low conductance. (f) Conductance histograms of the clustered results in the low conductance region of SSP and SMC-UV junctions. Download figure Download PowerPoint According to the above analysis, the junction formation configuration of the SSP and SMC-UV junction can be divided into two processes: First, when the gold electrodes separate and the distance increases, half of the SSP/SMC-UV molecule is captured through a Au–N connection,46 resulting in a high conductance with similar short plateau length distributions to the SIN-Ref junction; second, the distance between the gold electrodes increases gradually, the short junction is ruptured, and the complete molecule can be determined in the low conductance region. The possible molecular configuration evolution is shown in Figure 3e. Besides Cluster 1, there are three other types of curves extracted from the original data of the SSP junction in the low conductance region of 10−3.5 to 10−5.0G0 from the clustering, suggesting that the different structures in the isomers could be distinguished using the single-molecule break junction techniques. To further understand the origin of the conductance values, we performed spectral clustering of SMC-UV and compared the results with SSP, as shown in Figure 3f. The multi-conductance feature from the clustered SMC-UV junction agrees with the SSP junction in the low-conductance region, indicating similar structures of the molecules in these two junctions. We found that the inapparent lower conductance peak of the SMC-UV junction was composed of three different types of conductance traces. This phenomenon was probably caused by the part of the SSP molecule that did not transform into the merocyanine form after UV irradiation due to the spiropyran-merocyanine equilibrium.38,47 By comparison, molecular junction configurations with notably different lengths in the SSP junctions were distinguished, whereas the origin of the three clusters in the lower conductance regions with similar lengths remained unclear. Because the energy barriers for the conversion between the possible isomers of spiropyran derivatives are low,48,49 complex products appear in the ring-opening processes. Therefore, there are multiple compounds in the break junction processes of both SSP and SMC-UV junctions so that the molecular structure of the configurations needs further identification. DFT-NEGF calculations To reveal the possible structures corresponding to the different conductance values, we conducted theoretical calculation to get transmission spectra of the SSP compound and its four SMC isomers of ring-opening reaction, TTT, TTC, CTT, CTC, using DFT combined with the NEGF.40 According to the previous reports, the product SMC has several isomers, as shown in Figure 4a.13,50 Our calculation revealed that the ring-closed SSP compound is less planar than the ring-opened SMC, as shown in Figure 4b ( Supporting Information Figure S19), which also agrees with the previous reports.51,52 The conjugation was enhanced as the planarity changed from SSP to SMC, indicating that the ring-closed SSP junction is less conductive than SMC. As shown in Figure 4c, the transmission order of these isomers from low to high is SSP< CTC≈ CTT< TTC≈ TTT. From the transmission spectra, the ring-closed SSP has the lowest conductance among the different structures, and when it becomes more conjugated from ring-opening, the charge transport will be enhanced.53 This is also the origin of the “jumping” feature for the SSP junction shown in Figure 2b. Figure 4 | (a) The chemical structures calculated by DFT-NEGF. (b) The configurations of the SSP, CTC, and TTC isomer junctions (c) Transmission spectra of the closed and the ring-opened isomers. Download figure Download PowerPoint Combining the results of single-molecule conductance and DFT calculation, we can infer that the conductance values of the SSP junctions, which locate at 10−4.5 and 10−4.2G0, are originated from the ring-opened isomers. We attribute the three types of conductance traces with the low-conductance value from the SSP junctions into TTC/ TTT (cluster 2), CTC/ CTT (cluster 3), and closed-form SSP (cluster 4), from high to low, according to the results of conductance measurement and DFT calculations. According to the small energy barriers of isomerization of CTC/CTT and TTC/ TTT,13,48 we could not further classify the two structures in the two groups due to the interconversion between the two structures at room temperature. The proportion of isomers can also be estimated from the calculated free energy of each isomer. TTC was reported to be the most stable configuration among MC forms under thermal54 and UV-light55 stimuli, indicating that it should be the most common form. Interestingly, in our results, the number of curves from TTC/TTT junctions (cluster 2 containing 1073 curves) is close to that of CTC/CTT junctions (cluster 3 containing 1209 curves), suggesting that the structure distribution of the different isomers in a force-induced reaction could change from the equilibrium state in the confined nanogap of the single-molecule conductance measurement. Conclusion We investigated the in situ force-induced structure transition for thioether-functionalized spiropyran ( SSP) derivative at the single-molecule scale via charge-transport characterization using the STM-BJ technique. We utilized an unsupervised clustering algorithm to classify the several types of traces in the complicated processes during stretching and reforming the SSP junction. Among the clustered four types of conductance traces according to the CH index, one cluster displayed a short plateau feature, whereas the other three presented longer plateaus. By introducing UV irradiated form ( SMC-UV) and a reference molecule SIN-Ref, we revealed that the cluster with a short plateau with the highest conductance originated from an incompletely stretched configuration. In addition, the other clusters with longer plateaus can be attributed to SSP and the ring-opened isomers compound ( SMC) according to DFT-NEGF calculations. Our results revealed the origin of different conductance features at the single-molecule scale, suggesting that the structure of different isomers generated in the force-induced reaction can be extracted, demonstrating the great potential of the single-molecule junction technique in the structural analysis of chemical reactions. Supporting Information Supporting Information is available and includes synthesis and characterization, conductance measurement details, and theoretical calculation details. Conflict of Interest There is no conflict of interest to report. Funding Information This work was supported by the National Natural Science Foundation of China (grant nos. 22173075, 21933012, 61901402, 31871877, and 21774106), the National Key R&D Program of China (grant no. 2017YFA0204902), the Fundamental Research Funds for the Central Universities (grant nos. 20720200068 and 20720190002), and the Natural Science Foundation of Fujian Province (grant no. 2018J06004). References 1. Chen Y.; Mellot G.; van Luijk D.; Creton C.; Sijbesma R. P.Mechanochemical Tools for Polymer Materials.Chem. Soc. Rev.2021, 50, 4100–4140. Google Scholar 2. O’Neill R. T.; Boulatov R.The Many Flavours of Mechanochemistry and Its Plausible Conceptual Underpinnings.Nat. Rev. Chem.2021, 5, 148–167. Google Scholar 3. Diesendruck C. E.; Steinberg B. D.; Sugai N.; Silberstein M. N.; Sottos N. R.; White S. R.; Braun P. V.; Moore J. S.Proton-Coupled Mechanochemical Transduction: A Mechanogenerated Acid.J. Am. Chem. Soc.2012, 134, 12446–12449. Google Scholar 4. Davis D. A.; Hamilton A.; Yang J.; Cremar L. D.; Van Gough D.; Potisek S. L.; Ong M. T.; Braun P. V.; Martínez T. J.; White S. R.; Moore J. S.; Sottos N. R.Force-Induced Activation of Covalent Bonds in Mechanoresponsive Polymeric Materials.Nature2009, 459, 68–72. Google Scholar 5. Zhang H.; Li X.; Lin Y.; Gao F.; Tang Z.; Su P.; Zhang W.; Xu Y.; Weng W.; Boulatov R.Multi-Modal Mechanophores Based on Cinnamate Dimers.Nat. Commun.2017, 8, 1147. Google Scholar 6. Baumann C.; Stratigaki M.; Centeno S. P.; Göstl R.Multicolor Mechanofluorophores for the Quantitative Detection of Covalent Bond Scission in Polymers.Angew. Chem. Int. Ed.2021, 60, 13287–13293. Google Scholar 7. Li J.; Nagamani C.; Moore J. S.Polymer Mechanochemistry: From Destructive to Productive.Acc. Chem. Res.2015, 48, 2181–2190. Google Scholar 8. Larsen M. B.; Boydston A. J.“Flex-Activated” Mechanophores: Using Polymer Mechanochemistry to Direct Bond Bending Activation.J. Am. Chem. Soc.2013, 135, 8189–8192. Google Scholar 9. Potisek S. L.; Davis D. A.; Sottos N. R.; White S. R.; Moore J. S.Mechanophore-Linked Addition Polymers.J. Am. Chem. Soc.2007, 129, 13808–13809. Google Scholar 10. Vidavsky Y.; Yang S. J.; Abel B. A.; Agami I.; Diesendruck C. E.; Coates G. W.; Silberstein M. N.Enabling Room-Temperature Mechanochromic Activation in a Glassy Polymer: Synthesis and Characterization of Spiropyran Polycarbonate.J. Am. Chem. Soc.2019, 141, 10060–10067. Google Scholar 11. Fang X.; Zhang H.; Chen Y.; Lin Y.; Xu Y.; Weng W.Biomimetic Modular Polymer with Tough and Stress Sensing Properties.Macromolecules2013, 46, 6566–6574. Google Scholar 12. Hong G.; Zhang H.; Lin Y.; Chen Y.; Xu Y.; Weng W.; Xia H.Mechanoresponsive Healable Metallosupramolecular Polymers.Macromolecules2013, 46, 8649–8656. Google Scholar 13. Gossweiler G. R.; Kouznetsova T. B.; Craig S. L.Force-Rate Characterization of Two Spiropyran-Based Molecular Force Probes.J. Am. Chem. Soc.2015, 137, 6148–6151. Google Scholar 14. Gossweiler G. R.; Hewage G. B.; Soriano G.; Wang Q.; Welshofer G. W.; Zhao X.; Craig S. L.Mechanochemical Activation of Covalent Bonds in Polymers with Full and Repeatable Macroscopic Shape Recovery.ACS Macro Lett.2014, 3, 216–219. Google Scholar 15. Walkey M. C.; Peiris C. R.; Ciampi S.; Aragonès A. C.; Domínguez-Espíndola R. B.; Jago D.; Pulbrook T.; Skelton B. W.; Sobolev A. N.; Díez Pérez I.; Piggott M. J.; Koutsantonis G. A.; Darwish N.Chemically and Mechanically Controlled Single-Molecule Switches Using Spiropyrans.ACS Appl. Mat.Interfaces2019, 11, 36886–36894. Google Scholar 16. Xu B.; Tao N. J.Measurement of Single-Molecule Resistance by Repeated Formation of Molecular Junctions.Science2003, 301, 1221–1223. Google Scholar 17. Aragonès A. C.; Haworth N. L.; Darwish N.; Ciampi S.; Bloomfield N. J.; Wallace G. G.; Diez-Perez I.; Coote M. L.Electrostatic Catalysis of a Diels-Alder Reaction.Nature2016, 531, 88–91. Google Scholar 18. Chen Y.; Shu Z.; Zhang S.; Zeng P.; Liang H.; Zheng M.; Duan H.Sub-10 nm Fabrication: Methods and Applications.Int. J. Extreme Manuf.2021, 3, 032002. Google Scholar 19. Barbee M. H.; Kouznetsova T.; Barrett S. L.; Gossweiler G. R.; Lin Y.; Rastogi S. K.; Brittain W. J.; Craig S. L.Substituent Effects and Mechanism in a Mechanochemical Reaction.J. Am. Chem. Soc.2018, 140, 12746–12750. Google Scholar 20. Yao R.; Li X.; Xiao N.; Weng W.; Zhang W.Single-Molecule Observation of Mechanical Isomerization of Spirothiopyran and Subsequent Click Addition.Nano Res.2021, 14, 2654–2658. Google Scholar 21. Reed M. A.; Zhou C.; Muller C. J.; Burgin T. P.; Tour J. M.Conductance of a Molecular Junction.Science1997, 278, 252–254. Google Scholar 22. Kim Y.; Pietsch T.; Erbe A.; Belzig W.; Scheer E.Benzenedithiol: A Broad-Range Single-Channel Molecular Conductor.Nano Lett.2011, 11, 3734–3738. Google Scholar 23. Liu J.; Zhao X.; Zheng J.; Huang X.; Tang Y.; Wang F.; Li R.; Pi J.; Huang C.; Wang L.; Yang Y.; Shi J.; Mao B.-W.; Tian Z.-Q.; Bryce M. R.; Hong W.Transition from Tunneling Leakage Current to Molecular Tunneling in Single-Molecule Junctions.Chem2019, 5, 390–401. Google Scholar 24. Venkataraman L.; Klare J. E.; Nuckolls C.; Hybertsen M. S.; Steigerwald M. L.Dependence of Single-Molecule Junction Conductance on Molecular Conformation.Nature2006, 442, 904–907. Google Scholar 25. Li Y.; Wang H.; Wang Z.; Qiao Y.; Ulstrup J.; Chen H.-Y.; Zhou G.; Tao N.Transition from Stochastic Events to Deterministic Ensemble Average in Electron Transfer Reactions Revealed by Single-Molecule Conductance Measurement.Proc. Nat. Acad. Sci. U. S. A.2019, 116, 3407. Google Scholar 26. Li H. B.; Tebikachew B. E.; Wiberg C.; Moth-Poulsen K.; Hihath J.A Memristive Element Based on an Electrically Controlled Single-Molecule Reaction.Angew. Chem. Int. Ed.2020, 59, 11641–11646. Google Scholar 27. Tan Z.; Jiang W.; Tang C.; Chen L.-C.; Chen L.; Liu J.; Liu Z.; Zhang H.-L.; Zhang D.; Hong W.The Control of Intramolecular Through-Bond and Through-Space Coupling in Single-Molecule Junctions.CCS Chem.2021, 4, 713–721. Google Scholar 28. Wei C.; Ye J.; Su Y.; Zheng J.; Xiao S.; Chen J.; Yuan S.; Zhang C.; Bai J.; Xu H.; Shi J.; Huang J.; Hong W.Halide Anchors for Single-Cluster Electronics.CCS Chem.2022. DOI: https://doi.org/10.31635/ccschem.022.202202180 Link, Google Scholar 29. Xu B.; Xiao X.; Tao N. J.Measurements of Single-Molecule Electromechanical Properties.J. Am. Chem. Soc.2003, 125, 16164–16165. Google Scholar 30. Aradhya S. V.; Nielsen A.; Hybertsen M. S.; Venkataraman L.Quantitative Bond Energetics in Atomic-Scale Junctions.ACS Nano2014, 8, 7522–7530. Google Scholar 31. Stefani D.; Weiland K. J.; Skripnik M.; Hsu C.; Perrin M. L.; Mayor M.; Pauly F.; van der Zant H. S. J.Large Conductance Variations in a Mechanosensitive Single-Molecule Junction.Nano Lett.2018, 18, 5981–5988. Google Scholar 32. Camarasa-Gómez M.; Hernangómez-Pérez D.; Inkpen M. S.; Lovat G.; Fung E. D.; Roy X.; Venkataraman L.; Evers F.Mechanically Tunable Quantum Interference in Ferrocene-Based Single-Molecule Junctions.Nano Lett.2020, 20, 6381–6386. Google Scholar 33. Li J.; Wu Q.; Xu W.; Wang H.-C.; Zhang H.; Chen Y.; Tang Y.; Hou S.; Lambert Colin J.; Hong W.Room-Temperature Single-Molecule Conductance Switch via Confined Coordination-Induced Spin-State Manipulation.CCS Chem.2021, 4, 1357–1365. Google Scholar 34. Lemmer M.; Inkpen M. S.; Kornysheva K.; Long N. J.; Albrecht T.Unsupervised Vector-Based Classification of Single-Molecule Charge Transport Data.Nat. Commun.2016, 7, 12922. Google Scholar 35. Fu T.; Zang Y.; Zou Q.; Nuckolls C.; Venkataraman L.Using Deep Learning to Identify Molecular Junction Characteristics.Nano Lett.2020, 20, 3320–3325. Google Scholar 36. Huang F.; Li R.; Wang G.; Zheng J.; Tang Y.; Liu J.; Yang Y.; Yao Y.; Shi J.; Hong W.Automatic Classification of Single-Molecule Charge Transport Data with an Unsupervised Machine-Learning Algorithm.Phys. Chem. Chem. Phys.2020, 22, 1674–1681. Google Scholar 37. Lin L.; Tang C.; Dong G.; Chen Z.; Pan Z.; Liu J.; Yang Y.; Shi J.; Ji R.; Hong W.Spectral Clustering to Analyze the Hidden Events in Single-Molecule Break Junctions.J. Phys. Chem. C2021, 125, 3623–3630. Google Scholar 38. Wojtyk J. T. C.; Wasey A.; Xiao N.-N.; Kazmaier P. M.; Hoz S.; Yu C.; Lemieux R. P.; Buncel E.Elucidating the Mechanisms of Acidochromic Spiropyran-Merocyanine Interconversion.J. Phys. Chem. A2007, 111, 2511–2516. Google Scholar 39. Ehara M.; Toyota K.; Fukuda R.; Hasegawa J.; Ishida M.; Nakajima T.; Honda Y.; Kitao O.; Nakai H.; Vreven T.Gaussian 16, Revision A. 03; Gaussian, Inc.: Wallingford, CT, 2016. Google Scholar 40. Brandbyge M.; Mozos J.-L.; Ordejón P.; Taylor J.; Stokbro K.Density-Functional Method for Nonequilibrium Electron Transport.Phys. Rev. B2002, 65, 165401. Google Scholar 41. Hong W.; Manrique D. Z.; Moreno-García P.; Gulcur M.; Mishchenko A.; Lambert C. J.; Bryce M. R.; Wandlowski T.Single Molecular Conductance of Tolanes: Experimental and Theoretical Study on the Junction Evolution Dependent on the Anchoring Group.J. Am. Chem. Soc.2012, 134, 2292–2304. Google Scholar 42. Calinski T.; Harabasz J.A Dendrite Method for Cluster Analysis.Commun. Stat.-Theory Methods1974, 3, 1–27. Google Scholar 43. Martin C. A.; Ding D.; Sørensen J. K.; Bjørnholm T.; van Ruitenbeek J. M.; van der Zant H. S. J.Fullerene-Based Anchoring Groups for Molecular Electronics.J. Am. Chem. Soc.2008, 130, 13198–13199. Google Scholar 44. Tang C.; Tang Y.; Ye Y.; Yan Z.; Chen Z.; Chen L.; Zhang L.; Liu J.; Shi J.; Xia H.Identifying the Conformational Isomers of Single-Molecule Cyclohexane at Room Temperature.Chem2020, 6, 2770–2781. Google Scholar 45. Tamaki T.; Minode K.; Numai Y.; Ohto T.; Yamada R.; Masai H.; Tada H.; Terao J.Mechanical Switching of Current–Voltage Characteristics in Spiropyran Single-Molecule Junctions.Nanoscale2020, 12, 7527–7531. Google Scholar 46. Zang Y.; Pinkard A.; Liu Z.-F.; Neaton J. B.; Steigerwald M. L.; Roy X.; Venkataraman L.Electronically Transparent Au–N Bonds for Molecular Junctions.J. Am. Chem. Soc.2017, 139, 14845–14848. Google Scholar 47. Sommer M.Substituent Effects Control Spiropyran–Merocyanine Equilibria and Mechanochromic Utility.Macromol. Rapid Commun.2021, 42, 2000597. Google Scholar 48. Wohl C. J.; Kuciauskas D.Excited-State Dynamics of Spiropyran-Derived Merocyanine Isomers.J. Phys. Chem. B2005, 109, 22186–22191. Google Scholar 49. Roessler A. G.; Zimmerman P. M.Examining the Ways to Bend and Break Reaction Pathways Using Mechanochemistry.J. Phys. Chem. C2018, 122, 6996–7004. Google Scholar 50. Kim D.; Zhang Z.; Xu K.Spectrally Resolved Super-Resolution Microscopy Unveils Multipath Reaction Pathways of Single Spiropyran Molecules.J. Am. Chem. Soc.2017, 139, 9447–9450. Google Scholar 51. Berkovic G.; Krongauz V.; Weiss V.Spiropyrans and Spirooxazines for Memories and Switches.Chem. Rev.2000, 100, 1741–1754. Google Scholar 52. Kortekaas L.; Browne W. R.The Evolution of Spiropyran: Fundamentals and Progress of an Extraordinarily Versatile Photochrome.Chem. Soc. Rev.2019, 48, 3406–3424. Google Scholar 53. Darwish N.; Aragones A. C.; Darwish T.; Ciampi S.; Diez-Perez I.Multi-Responsive Photo- and Chemo-Electrical Single-Molecule Switches.Nano Lett.2014, 14, 7064–7070. Google Scholar 54. Cottone G.; Noto R.; La Manna G.Theoretical Study of Spiropyran–Merocyanine Thermal Isomerization.Chem. Phys. Lett.2004, 388, 218–222. Google Scholar 55. Qiu W.; Gurr P. A.; da Silva G.; Qiao G. G.Insights into the Mechanochromism of Spiropyran Elastomers.Polym. Chem.2019, 10, 1650–1659. Google Scholar Previous articleNext article FiguresReferencesRelatedDetails Issue AssignmentVolume 0Issue 0Page: 1-8Supporting Information Copyright & Permissions© 2022 Chinese Chemical SocietyKeywordssingle-molecule conductance measurementsunsupervised clusteringforce-induced reactionstructure identification Downloaded 352 times PDF downloadLoading ...
Referência(s)