Advancement of Next-Generation DNA Sequencing through Ionic Blockade and Transverse Tunneling Current Methods.

DNA sequencing is transforming the field of medical diagnostics and personalized medicine development by providing a pool of genetic information. Recent advancements have propelled solid-state material-based sequencing into the forefront as a promising next-generation sequencing (NGS) technology, offering amplification-free, cost-effective, and high-throughput DNA analysis. Consequently, a comprehensive framework for diverse sequencing methodologies and a cross-sectional understanding with meticulous documentation of the latest advancements is of timely need. This review explores a broad spectrum of progress and accomplishments in the field of DNA sequencing, focusing mainly on electrical detection methods. The review delves deep into both the theoretical and experimental demonstrations of the ionic blockade and transverse tunneling current methods across a broad range of device architectures, nanopore, nanogap, nanochannel, and hybrid/heterostructures. Additionally, various aspects of each architecture are explored along with their strengths and weaknesses, scrutinizing their potential applications for ultrafast DNA sequencing. Finally, an overview of existing challenges and future directions is provided to expedite the emergence of high-precision and ultrafast DNA sequencing with ionic and transverse current approaches.

Localized charge-induced ORR/OER activity in doped fullerenes for Li-air battery applications.

Non-aqueous Li-air batteries have garnered significant interest in recent years. The key challenge lies in the development of efficient catalysts to overcome the sluggish kinetics associated with the oxygen reduction reaction (ORR) during discharge and the oxygen evolution reaction (OER) during charging at the cathode. In this work, we conducted a comprehensive study on B/N-doped and BN co-doped fullerenes using first-principles analysis. Our results show significant changes in the geometries, electronic properties, and catalytic behaviors of doped and co-doped fullerenes. The coexistence of boron and nitrogen boosts the formation energy, enhancing stability compared to pristine and single-doped structures. C179B exhibits minimal overpotentials (0.98 V), implying superior catalyst performance for ORR and OER in LABs and significantly better performance than Pt (111) (3.48 V) and standard graphene (3.51 V). The electron-deficient nature of the B atom makes it provide its vacant 2pz orbital for conjugation with the p-electrons of nearby carbon atoms. Consequently, boron serves as a highly active site due to the localization of positive charge, which improves the adsorption of intermediates through oxygen atoms. Moreover, the higher activity of B-doped systems than N-doped systems in lithium-rich environments is opposite to the observed trend in the reported PEM fuel cells. This work introduces doped and co-doped fullerenes as LAB catalysts, offering insights into their tunable ORR/OER activity via doping with various heteroatoms and fullerene size modulation.

A thiolated copper-hydride nanocluster with chloride bridging as a catalyst for carbonylative C-N coupling of aryl amines under mild conditions: a combined experimental and theoretical study.

Atomically precise copper nanoclusters (Cu NCs), an emerging class of nanomaterials, have garnered significant attention owing to their versatile core-shell architecture and their potential applications in catalytic reactions. In this study, we present a straightforward synthesis strategy for [Cu29(StBu)12(PPh3)4Cl6H10][BF4] (Cu29) NCs and explore their catalytic activity in the carbonylative C-N coupling reaction involving aromatic amines and N-heteroarenes with dialkyl azodicarboxylates. Through a combination of experimental investigations and density functional theory studies, we elucidate the radical mechanisms at play. The crucial step in the catalytic process is identified as the decomposition of diisopropyl azodicarboxylates on the surface of Cu29 NCs, leading to the generation of oxyacyl radicals and the liberation of nitrogen gas. Subsequently, an oxyacyl radical abstracts a hydrogen atom from aniline, initiating the formation of an aminyl radical. Finally, the aminyl radical reacts with another oxyacyl radical, culminating in the synthesis of the desired carbamate product. This detailed analysis provides insights into the intricate catalytic pathways of Cu29 NCs, shedding light on their potential for catalyzing carbonylative C-N coupling reactions.

Functionality Modulation Toward Thianthrene-based Metal-Free Electrocatalysts for Water Splitting.

The development of metal-free bifunctional electrocatalysts for hydrogen and oxygen evolution reactions (HER and OER) is significant but rarely demonstrated. Porous organic polymers (POPs) with well-defined electroactive functionalities show superior performance in hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Precise control of the active sites' local environment requires careful modulation of linkers through the judicious selection of building units. Here, a systematic strategy is introduced for modulating functionality to design and synthesize a series of thianthrene-based bifunctional sp2 C═C bonded POPs with hollow spherical morphologies exhibiting superior electrocatalytic activity. This precise structural tuning allowed to gain insight into the effects of heteroatom incorporation, hydrophilicity, and variations in linker length on electrocatalytic activity. The most efficient bifunctional electrocatalyst THT-PyDAN achieves a current density of 10 mA cm─2 at an overpotential (η10) of ≈65 mV (in 0.5 m H2SO4) and ≈283 mV (in 1 m KOH) for HER and OER, respectively. THT-PyDAN exhibits superior activity to all previously reported metal-free bifunctional electrocatalysts in the literature. Furthermore, these investigations demonstrate that THT-PyDAN maintains its performance even after 36 h of chronoamperometry and 1000 CV cycling. Post-catalytic characterization using FT-IR, XPS, and microscopic imaging techniques underscores the long-term durability of THT-PyDAN.

Insights of the efficient hydrogen evolution reaction performance in bimetallic Au4Cu2 nanoclusters.

The design of efficient electrocatalysts for improving hydrogen evolution reaction (HER) performance using atomically precise metal nanoclusters (NCs) is an emerging area of research. Here, we have studied the HER electrocatalytic performance of monometallic Cu6 and Au6 nanoclusters and bimetallic Au4Cu2 nanoclusters. A bimetallic Au4Cu2/MoS2 composite exhibits excellent HER catalytic activity with an overpotential (η10) of 155 mV vs. reversible hydrogen electrode observed at 10 mA cm-2 current density. The improved HER performance in Au4Cu2 is due to the increased electrochemically active surface area (ECSA), and Au4Cu2 NCs exhibits better stability than Cu6 and Au6 systems and bare MoS2. This augmentation offers a greater number of active sites for the favorable adsorption of reaction intermediates. Furthermore, by employing X-ray photoelectron spectroscopy (XPS) and Raman analysis, the kinetics of HER in the Au4Cu2/MoS2 composite were elucidated, attributing the favorable performance to better electronic interactions occurring at the interface between Au4Cu2 NCs and the MoS2 substrate. Theoretical analysis reveals that the inherent catalytic enhancement in Au4Cu2/MoS2 is due to favorable H atom adsorption over it and the smallest ΔGH* value. The downshift in the d-band of the Au4Cu2/MoS2 composite influences the binding energy of intermediate catalytic species. This new catalyst sheds light on the structure-property relationship for improving electrocatalytic performance at the atomic level.

Unravelling CO2 Reduction Reaction Intermediates on High Entropy Alloy Catalysts: An Interpretable Machine Learning Approach to Establish Scaling Relations.

Establishment of a scaling relation among the reaction intermediates is highly important but very much challenging on complex surfaces, such as surfaces of high entropy alloys (HEAs). Herein, we designed an interpretable machine learning (ML) approach to establish a scaling relation among CO2 reduction reaction (CO2 RR) intermediates adsorbed at the same adsorption site. Local Interpretable Model-Agnostic Explanations (LIME), Accumulated Local Effects (ALE), and Permutation Feature Importance (PFI) are used for the global and local interpretation of the utilized black box models. These methods were successfully applied through an iterative way and validated on CuCoNiZnMg and CuCoNiZnSnbased HEAs data. Finally, we successfully predicted adsorption energies of *H2 CO (MAE: 0.24 eV) and *H3 CO (MAE: 0.23 eV) by using the *HCO training data. Similarly, adsorption energy of *O (MAE: 0.32 eV) is also predicted from *H training data. We believe that our proposed method can shift the paradigm of state-of-the-art ML in catalysis towards better interpretability.

Enhancing Spin-Transport Characteristics, Spin-Filtering Efficiency, and Negative Differential Resistance in Exchange-Coupled Dinuclear Co(II) Complexes for Molecular Spintronics Applications.

Single-molecule spintronics, where electron transport occurs via a paramagnetic molecule, has gained wide attention due to its potential applications in the area of memory devices to switches. While numerous organic and some inorganic complexes have been employed over the years, there are only a few attempts to employ exchange coupled dinuclear complexes at the interface, and the advantage of fabricating such a molecular spintronics device in the observation of switchable Kondo resonance was demonstrated recently in the dinuclear [Co2(L)(hfac)4] (1) complex (Wagner et al., Nat. Nanotechnol. 2013, 8, 575-579). In this work, employing an array of theoretical tools such as density functional theory (DFT), the ab initio CASSCF/NEVPT2 method, and DFT combined with nonequilibrium Green Function (NEGF) formalism, we studied in detail the role of magnetic coupling, ligand field, and magnetic anisotropy in the transport characteristics of complex 1. Particularly, our calculations not only reproduce the current-voltage (I-V) characteristics observed in experiments but also unequivocally establish that these arise from an exchange-coupled singlet state that arises due to antiferromagnetic coupling between two high-spin Co(II) centers. Further, the estimated spin Hamiltonian parameters such as J, g values, and D and E/D values are only marginally altered for the molecule at the interface. Further, the exchange-coupled state was found to have very similar transport responses, despite possessing significantly different geometries. Our transport calculations unveil a new feature of the negative differential resistance (NDR) effect on 1 at the bias voltage of 0.9 V, which agrees with the experimental I-V characteristics reported. The spin-filtering efficiency (SFE) computed for the spin-coupled states was found to be only marginal (∼25%); however, if the ligand field is fine-tuned to obtain a low-spin Co(II) center, a substantial SFE of 44% was noted. This spin-coupled state also yields a very strong NDR with a peak-to-valley ratio (PVR) of ∼56 - a record number that has not been witnessed so far in this class of compounds. Additionally, we have established further magnetostructural-transport correlations, providing valuable insights into how microscopic spin Hamiltonian parameters can be associated with SFE. Several design clues to improve the spin-transport characteristics, SFE and NDR in this class of molecule, are offered.

Unlocking the Potential of Dual-Ion Batteries: Identifying Polycyclic Aromatic Hydrocarbon Cathodes and Intercalating Salt Combinations through Machine Learning.

Dual-ion batteries (DIBs) represent a promising energy storage technology, offering a cost-effective safe solution with impressive electrochemical performance. The large combinatorial configuration space of the electrode-electrolyte leads to design challenges. We present a machine learning (ML) approach for accurately predicting the voltage and volume changes of polycyclic aromatic hydrocarbon (PAH) cathodes upon intercalation with a variety of DIB salts following different mechanisms. Gradient Boosting and XGBoost Regression models trained on the data set demonstrate exceptional performance in voltage and volume change prediction, respectively. The models are further cross-validated and utilized to predict the properties for ∼700 combinations of PAH and DIB salt intercalations, a subset of which is further validated by density functional theory. Using average voltage and volume change for all combinations of PAHs and salts, preferable combinations for high/low voltage requirements along with long-term stability are obtained. Overall, the study shows the applicability of PAHs in DIBs exhibiting good electrochemical performance with low volume change compared to graphite indicative of its potential to overcome the cycling stability issues of DIBs. This research establishes a reliable and broadly applicable ML-based workflow for efficient screening and accelerated design of advanced PAH cathodes and salts, thus driving progress in the field of DIBs.

The electrocatalytic N2 reduction activity of core-shell iron nanoalloy catalysts: a density functional theory (DFT) study.

A molecular level understanding of the property evolution in binary nanoalloy catalysts is crucial for designing novel electrocatalysts for ammonia synthesis. In this regard, designing core-shell catalyst structures has been a versatile approach to achieve the product selectivity. Herein, we investigated the activity evolution of Fe-based core-shell (M15@Fe50) (M = Co, Ni, or Cu) clusters for the nitrogen reduction reaction (NRR). Nitrogen reduction following the associative mechanistic pathway is significantly activated over the Cu15@Fe50 cluster. The d-band center from the electronic structure analysis is found to be upshifted, justifying the activity towards the NRR. The reduction reaction occurs via the surface restructuring of the catalyst, in which the *NH2 formation is found to be the lowest endergonic potential determining step compared to pristine Fe(110). Based on this, the high NRR activity of the Cu15@Fe50 cluster has been proposed, which, we envision, will provide useful insights into the position and compositional effects of core-shell structures for the discovery of efficient NRR electrocatalysts.

Photoluminescence Properties of a Chiral One-Dimensional Silver Chalcogenolate Chain.

Atom-precise metal nanoclusters, which contain a few tens to hundreds of atoms, have drawn significant interest due to their interesting physicochemical properties. Structural analysis reveals a fundamental architecture characterized by a central core or kernel linked to a staple motif with metal-ligand bonding playing a pivotal role. Ligands not only protect the surface but also exert a significant influence in determining the overall assembly of the larger superstructures. The assemblies of nanoclusters are driven by weak interaction between the ligand molecules; it also depends on the ligand type and functional group present. Here, we report an achiral ligand and Ag(I)···Ag(I) interaction-driven spontaneous resolution of silver-thiolate structure, [Ag18(C6H11S)12(CF3COO)6(DMA)2], where silver atoms and cyclohexanethiolate are connected to form a one-dimensional chain with helicity. Notably, silver atoms adopt different types of coordination modes and geometries. The photoluminescence properties of the one-dimensional (1D) chain structure were investigated, and it was found to exhibit excitation-dependent emission properties attributed to hydrogen-bonding interactions. Experimental and theoretical investigations corroborate the presence of triplet-emitting ligand-to-metal charge-transfer transitions.

Deciphering DNA nucleotide sequences and their rotation dynamics with interpretable machine learning integrated C3N nanopores.

A solid-state nanopore combined with the quantum transport method has garnered substantial attention and intrigue for DNA sequencing due to its potential for providing rapid and accurate sequencing results, which could have numerous applications in disease diagnosis and personalized medicine. However, the intricate and multifaceted nature of the experimental protocol poses a formidable challenge in attaining precise single nucleotide analysis. Here, we report a machine learning (ML) framework combined with the quantum transport method to accelerate high-throughput single nucleotide recognition with C3N nanopores. The optimized eXtreme Gradient Boosting Regression (XGBR) algorithm has predicted the fingerprint transmission of each unknown nucleotide and their rotation dynamics with root mean square error scores as low as 0.07. Interpretability of ML black box models with the game theory-based SHapley Additive exPlanation method has provided a quasi-explanation for the model working principle and the complex relationship between electrode-nucleotide coupling and transmission. Moreover, a comprehensive ML classification of nucleotides based on binary, ternary, and quaternary combinations shows maximum accuracy and F1 scores of 100%. The results suggest that ML in tandem with a nanopore device can potentially alleviate the experimental hurdles associated with quantum tunneling and facilitate fast and high-precision DNA sequencing.

Sustainable Organic Photocatalysis for Site-Selective Hydrazocoupling of Electron-Rich Arenes.

An efficient photocatalytic para- and ortho-selective amination and aminative dearomatization of phenols, naphthols, and anilines with azodicarboxylates was developed using riboflavin tetraacetate (RFTA) as an organic photocatalyst. The site selectivity was controlled using tetrabutylammonium bromide (TBAB), which also acts as a phase transfer catalyst. The reaction conditions are simple and mild, giving high regioselectivity with good to excellent yields. A broad substrate scope and nice functional group tolerance with scalability and post-functionalization make this protocol both useful and regioselective.

Quasi-Isomeric Anion-Templated Silver Nanoclusters: Effect of Bulkiness on Luminescence.

Anion-templated silver nanoclusters are fascinating to study because of their diverse structures, which are dictated by the nature of both anions and ligands. Here, we used the bulky 1-ethynyladamantane as one of the protecting ligands alongside trifluoracetate to successfully synthesize a chlorine-templated silver nanocluster─Cl@Ag19(C12H15)11(C2O2F3)7. Elucidation of its structure by single crystal X-ray diffraction revealed the structure to be a chlorine-centered Ag19 cage with protection by alkynyl and carboxylic ligands. This cluster is non-emissive at room temperature and showed green emission with a large Stokes shift at low temperature. The crystal structure was found to be quasi-isomeric with a previously reported Ag19 cluster protected by tert-butyl acetylene, which is emissive at room temperature. Detailed photoluminescence studies and structure-property correlation revealed that the arrangement of the silver skeleton which is influenced by the bulky substituent of the ligand might be responsible for the difference in emission properties.

Design of porphyrin-based frameworks for efficient visible light-promoted reduction of CO2 from dilute gas: Combined experimental and theoretical investigation.

The photocatalytic carbon dioxide reduction (CO2R) coupled with hydrogen evolution reaction (HER) constitutes a promising step for a sustainable generation of syngas (CO + H2), an essential feedstock for the preparation of several commodity chemicals. Herein, visible light/sunlight-promoted catalytic reduction of CO2 and protons to syngas using rationally designed porphyrin-based 2D porous organic frameworks, POF(Co/Zn) is demonstrated. Indeed, POF(Co) showed superior catalytic performance over the Zn counterpart with CO and H2 generation rates of 1104 and 3981 µmol g-1h-1, respectively. The excellent catalytic performance of Co-based POF is aided by the favorable transfer of photo-excited electrons from Ru-sensitizer to the CoII catalytic site, which is not feasible in the case of POF(Zn), revealed from the theoretical investigation. More importantly, the POF(Co) catalyzes the reduction of CO2 even from dilute gas (13% CO2), surpassing most reported framework-based photocatalytic systems. Significantly, the catalytic performance of POF(Co) was increased under natural sunlight conditions suggesting sunlight-promoted enhancement in syngas generation. The in-depth theoretical investigation further unveiled the comprehensive mechanistic pathway of the light-promoted concurrent CO and H2 generation. This work showcases the advantages of porphyrin-based frameworks for visible light/sunlight-promoted syngas generation by utilizing greenhouse gas (CO2) and protons under mild eco-friendly conditions.

Protein Sequencing with Artificial Intelligence: Machine Learning Integrated Phosphorene Nanoslit.

Achieving high throughput protein sequencing at single molecule resolution remains a daunting challenge. Herein, relying on a solid-state 2D phosphorene nanoslit device, an extraordinary biosensor to rapidly identify the key signatures of all twenty amino acids using an interpretable machine learning (ML) model is reported. The XGBoost regression algorithm allows the determination of the transmission function of all twenty amino acids with high accuracy. The resultant ML and DFT studies reveal that it is possible to identify individual amino acids through transmission and current signals readouts with high sensitivity and selectivity. Moreover, we thoroughly compared our results to those from graphene nanoslit and found that the phosphorene nanoslit device can be an ideal candidate for protein sequencing up to a 20-fold increase in transmission sensitivity. The present study facilitates high throughput screening of all twenty amino acids and can be further extended to other biomolecules for disease diagnosis and therapeutic decision making.

Control over product formation and thermodynamic stability of thiolate-protected gold nanoclusters through tuning of surface protecting ligands.

Surface-protecting ligands can regulate the structure of a cluster's core either through electronic or steric effects. However, the influence of the steric effect along with the electronic effect over controlling the structure during ligand exchange reactions remains elusive. To understand this, we have carried out ligand exchange on [Au23(CHT)16]- (CHT: cyclohexane thiol) using aromatic thiolates where we have tuned the bulkiness at the para position of the thiolate group on the incoming ligands. The outcome of the experiments reveals that each of the ligands in the chosen series is precisely selective towards the parent cluster transformation through specific intermediates. The ligand with more steric crowding directed the reaction pathway to have Au28 nanocluster as the major product while Au36 was the final product obtained with the gradual decrease of bulkiness over the ligand. The combined experimental and theoretical results elucidated the mechanism of the reaction pathways, product formation, and their stability. Indeed, this study with the series of ligands will add up to the ligand library, where we can decide on the ligand to obtain our desired cluster for specific applications through the ligand exchange reaction.

Diruthenium Catalyst for Hydrogen Production from Aqueous Formic Acid.

Diruthenium complexes [{(η6-arene)RuCl}2(µ-κ2:κ2-benztetraimd)]2+ containing the bridging bis-imidazole methane-based ligand {1,4-bis(bis(2-ethyl-5-methyl-1H-imidazol-4-yl)methyl)benzene} (benztetraimd) are synthesized for catalytic formic acid dehydrogenation in water at 90 °C. Catalyst [{(η6-p-cymene)RuCl}2(µ-κ2:κ2-benztetraimd)]2+ [1-Cl2] exhibited a remarkably high turnover frequency (1993 h-1 per Ru atom) and long-term stability over 60 days for formic acid dehydrogenation, while the analogous (η6-benzene)diruthenium and mononuclear catalysts displayed low activity with poor long-term stability. Notably, catalyst [1-Cl2] also displayed an appreciably high turnover number of 93 200 for the bulk-scale reaction. In addition, the in-depth mass and nuclear magnetic resonance investigations under the catalytic and control experimental conditions revealed the active involvement of several crucial catalytic intermediate species, such as Ru-aqua species [{(η6-p-cymene)Ru(H2O)}2(µ-L)]2+ [1-(OH2)2], Ru-formato species [{(η6-p-cymene)Ru(HCOO)}2(µ-L)] [1-(HCOO)2], and Ru-hydrido species [{(η6-p-cymene)Ru(H)}2(µ-L)] [1-(H)2], in the catalytic formic acid dehydrogenation reaction.

Luminescent [CO2@Ag20(SAdm)10(CF3COO)10(DMA)2] nanocluster: synthetic strategy and its implication towards white light emission.

Owing to the quantized size and associated discrete energy levels, atomically precise silver nanoclusters (Ag NCs) hold great potential for designing functional luminescent materials. However, the thermally activated non-radiative transition of Ag(I)-based NCs has faded the opportunities. To acquire the structurally rigid architecture of cluster nodes for constraining such transitions, a new synthetic approach is unveiled here that utilizes a neutral template as a cluster-directing agent to assemble twenty Ag(I) atoms that ensure the maximum number of surface-protecting ligand attachment possibilities in a particular solvent medium. The solvent polarity triggers the precise structural design to circumvent the over-reliance of the templates, which results in the formation of [CO2@Ag20(SAdm)10(CF3COO)10(DMA)2] NC (where SAdm = 1-adamantanethiolate and DMA = N,N-dimethylacetamide) exhibiting an unprecedented room-temperature photoluminescence emission. The high quantum yield of the generated blue emission ensures its candidature as an ideal donor for artificial light-harvesting system design, and it is utilized with the two-step sequential energy transfer process, which finally results in the generation of ideal white light. For implementing perfect white light emission, the required chromophores in the green and red emission regions were chosen based on their effective spectral overlap with the donor components. Due to their favorable energy-level distribution, excited state energy transfers occurred from the NC to ß-carotene at the initial step, then from the conjugate of the NC and ß-carotene to another chromophore, Nile Blue, at the second step via a sequential Förster resonance energy transfer pathway.

Energy level alignments between organic and inorganic layers in 2D layered perovskites: conjugation vs. substituent.

2D layered hybrid perovskites have attracted huge attention due to their interesting optoelectronic properties and chemical flexibility. Depending upon their electronic structures and properties, these materials can be utilised in various optoelectronic devices like photovoltaics, LEDs and so on. In this context, study of the excited energy levels of the organic spacers can help us to align the excited energy levels of the organic unit with the excitonic level of the inorganic unit according to the requirement of a particular optoelectronic device. We have explored the role of 3-phenyl-2-propenammonium on the electronic structure of a perovskite containing this cation as a spacer. Our results clearly demonstrate the active participation of conjugated ammonium spacers in the electronic structure of a perovskite. Also, we have considered a variety of amines to identify the best alignment with common inorganic units and studied the role of substituents and conjugation on the energy level alignment. Placing the triplet excited level of an organic spacer below the lowest excitonic level of the inorganic unit can induce energy transfer from the inorganic to organic unit, finally resulting in phosphorescence emission. We have shown that the triplet energy level of 3-anthracene-2-propeneamine/3-pyrene-2-propeneamine can be tuned in such a way that there can be an excitonic energy transfer from the Pb2I7/PbI4 inorganic unit-based perovskites. Therefore, perovskite material with such combinations of organic spacer cations will be very useful for light emission applications.

A luminescent Cu4 cluster film grown by electrospray deposition: a nitroaromatic vapour sensor.

We present the fabrication and use of a film of a carborane-thiol-protected tetranuclear copper cluster with characteristic orange luminescence using ambient electrospray deposition (ESD). Charged microdroplets of the clusters produced by an electrospray tip deposit the clusters at an air-water interface to form a film. Different microscopic and spectroscopic techniques characterized the porous surface structure of the film. Visible and rapid quenching of the emission of the film upon exposure to 2-nitrotoluene (2-NT) vapours under ambient conditions was observed. Density functional theory (DFT) calculations established the favourable binding sites of 2-NT with the cluster. Desorption of 2-NT upon heating recovered the original luminescence, demonstrating the reusability of the sensor. Stable emission upon exposure to different organic solvents and its quenching upon exposure to 2,4-dinitrotoluene and picric acid showed selectivity of the film to nitroaromatic species.