Lithiophilic Dibenzamide Linkages to Impart Lithium Storage Capacity in Porous Polybenzamides.

Polymer-based organic cathode materials have shown immense promise for lithium storage, owing to their structural diversity and functional group tunability. However, designing appropriate high-performance cathode materials with a high-rate capability and long cycle life remains a significant challenge. It is quintessential to design polymer-based electrodes with lithiophilic linkages. Herein, we design a bifurcated dibenzamide (DBA) linkage having lithiophilic functionalities. 1H NMR has been used as an experimental tool to understand the lithiophilic nature of the DBAs. Considering the strong Li+ affinity of DBAs, a series of polybenzamides have been designed as lithium storage systems. The design of porous polybenzamides consists of amides as only redox-active functionalities, and the rest are inactive phenyl units. Porous polybenzamides, when tested as cathodes against a Li-metal anode, displayed high capacity and rate performance, demonstrating their redox activity. The most efficient polybenzamide (TAm-TA) delivered a specific capacity of 248 mA h g-1 at 1C. TAm-TA retained 63% of its specific capacity at a very high rate of 10C (157 mA h g-1). Notably, polybenzamides displayed a capacity enhancement during long cycling, tending to achieve their theoretical capacity. Long cycling stability tests over 3000 cycles at a rate of 1.3C and over 6000 cycles at elevated rates (5C to 40C) demonstrate the electrochemical robustness of dibenzamide linkages. Finally, two full-cell experiments using TAm-TA as both cathode and anode were conducted, which delivered high capacity, demonstrating that TAm-TA is a promising candidate for Li+-ion batteries (LIBs). Furthermore, the ex situ Fourier transform infrared (FT-IR), X-ray photoemission spectroscopy (XPS), and density functional theory (DFT) studies revealed the stepwise lithiation/delithiation mechanism for polybenzamides.

Luminescent Hydride-Free [Cu7(SC5H9)7(PPh3)3] Nanocluster: Facilitating Highly Selective C-C Bond Formation.

Amidst burgeoning interest, atomically precise copper nanoclusters (Cu NCs) have emerged as a remarkable class of nanomaterials distinguished by their unparalleled reactivity. Nonetheless, the synthesis of hydride-free Cu NCs and their role as stable catalysts remain infrequently explored. Here, we introduce a facile synthetic approach to fabricate a hydride-free [Cu7(SC5H9)7(PPh3)3] (Cu7) NC and delineate its photophysical properties intertwined with their structural configuration. Moreover, the utilization of its photophysical properties in a photoinduced C-C coupling reaction demonstrates remarkable specificity toward cross-coupling products with high yields. The combined experimental and theoretical investigation reveals a nonradical mechanistic pathway distinct from its counterparts, offering promising prospects for designing hydride-free Cu NC catalysts in the future and unveiling the selectivity of the hydride-free [Cu7(SC5H9)7(PPh3)3] NC in photoinduced Sonogashira C-C coupling through a polar reaction pathway.

Machine Learning-Assisted Direct RNA Sequencing with Epigenetic RNA Modification Detection via Quantum Tunneling.

RNA sequence information holds immense potential as a drug target for diagnosing various RNA-mediated diseases and viral/bacterial infections. Massively parallel complementary DNA (c-DNA) sequencing helps but results in a loss of valuable information about RNA modifications, which are often associated with cancer evolution. Herein, we report machine learning (ML)-assisted high throughput RNA sequencing with inherent RNA modification detection using a single-molecule, long-read, and label-free quantum tunneling approach. The ML tools achieve classification accuracy as high as 100% in decoding RNA and 98% for decoding both RNA and RNA modifications simultaneously. The relationships between input features and target values have been well examined through Shapley additive explanations. Furthermore, transmission and sensitivity readouts enable the recognition of RNA and its modifications with good selectivity and sensitivity. Our approach represents a starting point for ML-assisted direct RNA sequencing that can potentially decode RNA and its epigenetic modifications at the molecular level.

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.

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.

Development of an Artificially Intelligent Nanopore for High-Throughput DNA Sequencing with a Machine-Learning-Aided Quantum-Tunneling Approach.

Solid-state nanopore-based single-molecule DNA sequencing with quantum tunneling technology poses formidable challenges to achieve long-read sequencing and high-throughput analysis. Here, we propose a method for developing an artificially intelligent (AI) nanopore that does not require extraction of the signature transmission function for each nucleotide of the whole DNA strand by integrating supervised machine learning (ML) and transverse quantum transport technology with a graphene nanopore. The optimized ML model can predict the transmission function of all other nucleotides after training with data sets of all the orientations of any nucleotide inside the nanopore with a root-mean-square error (RMSE) of as low as 0.062. Further, up to 96.01% accuracy is achieved in classifying the unlabeled nucleotides with their transmission readouts. We envision that an AI nanopore can alleviate the experimental challenges of the quantum-tunneling method and pave the way for rapid and high-precision DNA sequencing by predicting their signature transmission functions.

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.

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.

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.

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.

Conductance and tunnelling current characteristics for individual identification of synthetic nucleic acids with a graphene device.

Based on combined density functional theory and non-equilibrium Green's function quantum transport studies, in the present work we have demonstrated the quantum interference (QI) effect on the transverse conductance of Hachimoji (synthetic) nucleic acids when placed between the oxygen-terminated zigzag graphene nanoribbon (O-ZGNR) nanoelectrodes. We theorize that the QI effect could be well preserved in π-π coupling between a target nucleobase molecule and the carbon-based nanoelectrodes. Our study indicates that the QI effect, such as anti-resonance or Fano-resonance, affects the variation of transverse conductance depending on the nucleobase conformation. Furthermore, a variation of up to 2-5 orders of magnitude is observed in the conductance upon rotation for all the nucleobases. The current-voltage (I-V) characteristics results suggest a distinct variation in the electronic tunnelling current across the proposed nanogap device for all five nucleobases with the applied bias voltage ranges from 0.1-1.0 V. The different rotation angles keep the distinct feature of the nucleobases in both transverse conductance and tunnelling current features. Both features could be utilized in an accurate synthetic DNA sequencing device.

Identification of DNA nucleotides by conductance and tunnelling current variation through borophene nanogaps.

Rapid and inexpensive DNA sequencing is critical to biomedical research and healthcare for the accomplishment of personalized medicine. Solid-state nanopores and nanogaps have marshalled themselves in the fascinating paradigm of nano-research since the advent of its application in DNA sequencing by analyzing the quantum conductance and electric current signals. In this study, the feasibility of the considered borophene nanogaps for DNA sequencing purposes via the electronic tunnelling current approach was investigated by utilizing combined density functional theory with non-equilibrium Green's function (DFT-NEGF) techniques. The interaction energy (Ei) and the charge density difference (CDD) plots exploit the charge modulation around the nanogap edges due to the presence of each nucleotide. Our results revealed a distinct variation in the tunnelling conductance, as a characteristic fingerprint of each nucleotide at the Fermi level. The calculated tunnelling current variation across the nanogap under an applied bias voltage was also significant due to the effective coupling of nucleotides with the electrode edges. The current was in the picoampere (pA) range, which was fairly higher than the electrical background noise and also experimentally detectable by the canning tunnelling microscopy (STM) technique. Our findings demonstrated that in the borophene nanopore vs. nanogap scenario, the nanogap has several advantages and is a more promising nanobiosensor. Moreover, we also compared our results with various previous experimental and theoretical reports on nanogaps as well as nanopores for gaining better insights.

Mechanistic exploration of CO2 conversion to dimethoxymethane (DMM) using transition metal (Co, Ru) catalysts: an energy span model.

The conversion of CO2 to DMM is an important transformation for various reasons. Co and Ru-based triphos catalysts have been investigated using density functional theory (DFT) calculations to understand the mechanistic pathways of the CO2 to DMM conversion and the role of noble/non-noble metal-based catalysts. The reaction has been investigated sequentially through methylformate (MF) and methoxymethane (MM) intermediates as they are found to be important intermediates. For the hydrogenation of CO2 and MF, the hydrogen sources such as H2 and methanol have been investigated. The calculated reaction free energy barriers for all the possible pathways suggest that both hydrogen sources are important for the Co-triphos catalyst. However, in the case of the Ru-triphos catalyst, molecular H2 is calculated to be the only hydrogen source. Various esterification and acetalization possibilities have also been explored to find the most favorable pathway for the conversion of CO2 to DMM. We find that the hydride transfer to the CO2 is the rate determining step (RDS) for the overall reaction. Our mechanistic investigation reveals that the metal center is the active part for the catalysis rather than the Brønsted acid and the redox triphos ligand plays an important role through the push-pull mechanism. The implemented microkinetic study shows that the reaction is also quite dependent on the concentration of the gaseous reactants and the rate constant increases exponentially above 363 K.

Relativistic Effects in Platinum Nanocluster Catalysis: A Statistical Ensemble-Based Analysis.

Nanoclusters are materials of paramount catalytic importance. Among various unique properties featured by nanoclusters, a pronounced relativistic effect can be a decisive parameter in governing their catalytic activity. A concise study delineating the role of relativistic effects in nanocluster catalysis is carried by investigating the oxygen reduction reaction (ORR) activity of a Pt7 subnanometer cluster. Global optimization analysis shows the critical role of spin-orbit coupling (SOC) in regulating the relative stability between structural isomers of the cluster. An overall improved ORR adsorption energetics and differently scaled adsorption-induced structural changes are identified with SOC compared to a non-SOC scenario. Ab initio atomistic thermodynamics analysis predicted nearly identical phase diagrams with significant structural differences for high coverage oxygenated clusters under realistic conditions. Though inclusion of SOC does not bring about drastic changes in the overall catalytic activity of the cluster, it is having a crucial role in governing the rate-determining step, transition-state configuration, and energetics of elementary reaction pathways. Furthermore, a statistical ensemble-based approach illustrates the strong contribution of low-energy local minimum structural isomers to the total ORR activity, which is significantly scaled up along the activity improving direction within the SOC framework. The study provides critical insights toward the importance of relativistic effects in determining various catalytic activity relevant features of nanoclusters.

Role of atomicity in the oxygen reduction reaction activity of platinum sub nanometer clusters: A global optimization study.

Metal nanoclusters are an important class of materials for catalytic applications. Sub nanometer clusters are relatively less explored for their catalytic activity on account of undercoordinated surface structure. Taking this into account, we studied platinum-based sub nanometer clusters for their catalytic activity for oxygen reduction reaction (ORR). A comprehensive analysis with global optimization is carried out for structural prediction of the platinum clusters. The energetic and electronic properties of interactions of clusters with reaction intermediates are investigated. The role of structural sensitivity in the dynamics of clusters is unraveled, and unique intermediate specific interactions are identified. ORR energetics is examined, and exceptional activity for sub nanometer clusters are observed. An inverse size versus activity relationship is identified, challenging the conventional trends followed by larger nanoclusters. The principal role of atomicity in governing the catalytic activity of nanoclusters is illustrated. The structural norms governing the sub nanometer cluster activity are shown to be markedly different from larger nanoclusters.

Solvent-Dependent Photophysical Properties of a Semiconducting One-Dimensional Silver Cluster-Assembled Material.

Unraveling the total structure of the atom-precise silver cluster-assembled materials (CAMs) is extremely significant to elucidating the structure-property correlation, but it is a very challenging task. Herein, a new silver CAM is synthesized by a facile synthetic pathway with a unique distorted elongated square-bipyramid-based Ag11 core geometry. The core is protected by two different kinds of the surface protecting ligands (adamantanethiolate and trifluoroacetate) and connected through a bidentate organic linker. The crystallographic data show that this material embraces a one-dimensional periodic structure that orchestrates by various noncovalent interactions to build a thermally stable supramolecular assembly. Further characterization confirms its n-type semiconducting property with an optical band gap of 1.98 eV. The impact of an adamantanethiol-protected silver core on the optical properties of this type of periodic framework is analyzed by the UV-vis absorbance and emission phenomena. Theoretical calculations predicted that the occupied states are majorly contributed by Ag-S. Solvent-dependent photoluminescence studies proved that a polar solvent can significantly perturb the metal thiolate and thiolate-centered frontier molecular orbitals that are involved in the electronic transitions.

Role of Ligand on Photophysical Properties of Nanoclusters with fcc Kernel: A Case Study of Ag14(SC6H4X)12(PPh3)8 (X = F, Cl, Br).

The structure-property correlation of a series of silver nanoclusters (NCs) is essential to understand the origin of photophysical properties. Here, we report a series of face-centered cubic (fcc)-based silver NCs by varying the halogen atom in the thiolate ligand to investigate the influence of the halide atoms on the electronic structure. These are {Ag14(FBT)12(PPh3)8·(solvent)x} (NC-1), Ag14(CBT)12(PPh3)8 (NC-2), and Ag14(BBT)12(PPh3)8 (NC-3), where 4-fluorothiophenol (FBT), 4-chlorothiophenol (CBT), and 4-bromothiophenol (BBT) have been utilized as thiolate ligands, respectively. Interestingly, the optical and electrochemical bandgap values of these NCs nicely correlated with the electronic effect of the halides, which is governed by the intracluster and interclusters π-π interactions. These clusters are emissive at room temperature and the luminescence intensity increases with the lowering of temperature. The short lifetime data suggest that the emission is predominantly originating due to the interband relaxation (d → sp) of the Ag cores. Femtosecond transient absorption (TA) spectra revealed similar types of decay profiles for NC-2 and NC-3 and longer decay time for NC-2. The relaxation dominates the decay profile to the surface states and most of the excited-state energy dissipates via this process. This supports the molecular-like dynamics of these series of NCs with an fcc core. This overview shed light on an in-depth understanding of ligand's role in luminescence and transient absorption spectra.

Synthesis of 1-indolyl-3,5,8-substituted γ-carbolines: one-pot solvent-free protocol and biological evaluation.

1,5-Disubstituted indole-2-carboxaldehyde derivatives 1a-h and glycine alkyl esters 2a-c are shown to undergo a novel cascade imination-heterocylization in the presence of the organic base DIPEA to provide 1-indolyl-3,5,8-substituted γ-carbolines 3aa-ea in good yields. The γ-carbolines are fluorescent and exhibit anticancer activities against cervical, lung, breast, skin, and kidney cancer cells.

Serendipitous base catalysed condensation-heteroannulation of iminoesters: a regioselective route to the synthesis of 4,6-disubstituted 5-azaindoles.

A serendipitous discovery of a novel one-pot synthesis of 4,6-disubstituted 5-azaindoles is reported herein. In the presence of Hunig's base, various N-substituted pyrrole-2-carboxaldehydes have been efficiently transformed into their corresponding 4,6-disubstituted 5-azaindoles through an imine mediated cascade condensation-heteroannulation. The synthetic value of the methodology is established by preparing a novel chemical analogue of a cannabinoid receptor type 2 (CB2) agonist.