Graphene nanodevices for DNA sequencing

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.

Precision Basecalling of Single DNA Nucleotide from Overlapped Transmission Readouts with Machine Learning Aided Solid-State Nanogap

DNA sequencing with the quantum tunneling technique heralds a paradigm shift in genetic analysis, promising rapid and accurate identification for diverging applications ranging from personalized medicine to security issues. However, the widespread distribution of molecular conductance, conduction orbital alignment for resonant transport, and decoding crisscrossing conductance signals of isomorphic nucleotides have been persistent experimental hurdles for swift and precise identification. Herein, we have reported a machine learning (ML)-driven quantum tunneling study with solid-state model nanogap to determine nucleotides at single-base resolution. The optimized ML basecaller has demonstrated a high predictive basecalling accuracy of all four nucleotides from seven distinct data pools, each containing complex transmission readouts of their different dynamic conformations. ML classification of quaternary, ternary, and binary nucleotide combinations is also performed with high precision, sensitivity, and F1 score. ML explainability unravels the evidence of how extracted normalized features within overlapped nucleotide signals contribute to classification improvement. Moreover, electronic fingerprints, conductance sensitivity, and current readout analysis of nucleotides have promised practical applicability with significant sensitivity and distinguishability. Through this ML approach, our study pushes the boundaries of quantum sequencing by highlighting the effectiveness of single nucleotide basecalling with promising implications for advancing genomics and molecular diagnostics.

Determination of Acetylamantadine by γ-Cyclodextrin-Assisted α-HL Nanopore for Potential Cancer Prediagnosis

The high expression of Spermidine/spermine N1-acetyltransferase (SSAT-1) is an important indicator in early cancer diagnosis. Here, we developed a nanopore-based methodology with γ-cyclodextrin as an adaptor to detect and quantify acetylamantadine, the specific SSAT-1-catalyzed product from amantadine, to accordingly reflect the activity of SSAT-1. We employ γ-cyclodextrin and report that amantadine cannot cause any secondary signals in γ-cyclodextrin-assisted α-HL nanopore, while its acetylation product, acetylamantadine, does. This allows γ-cyclodextrin to practically detect acetylamantadine in the interference of excessive amantadine, superior to the previously reported β-cyclodextrin. The quantification of acetylamantadine was not interfered with even a 50-fold amantadine and displayed no interference in artificial urine sample analysis, which indicates the good feasibility of this nanopore-based methodology in painless cancer prediagnosis. In addition, the discrimination mechanism is also explored by 2-D nuclear magnetic resonance (NMR) and nanopore experiments with a series of adamantane derivatives with different hydrophilic and hydrophobic groups. We found that both the hydrophobic region matching effect and hydrophilic interactions play a synergistic effect in forming a host-guest complex to further generate the characteristic signals, which may provide insights for the subsequent design and study of drug-cyclodextrin complexes.

High-Resolution and Low-Noise Single-Molecule Sensing with Bio-Inspired Solid-State Nanopores

Solid-state nanopores have been extensively explored as single-molecule sensors, bearing the potential for the sequencing of DNA. Although they offer advantages in terms of high mechanical robustness, tunable geometry, and compatibility with existing semiconductor fabrication techniques in comparison with their biological counterparts, efforts to sequence DNA with these nanopores have been hampered by insufficient spatial resolution and high noise in the measured ionic current signal. Here we show that these limitations can be overcome by the use of solid-state nanopores featuring a thin, narrow constriction as the sensing region, inspired by biological protein nanopores that have achieved notable success in DNA sequencing. Our extensive molecular dynamics simulations show that these bio-inspired nanopores can provide high spatial resolution equivalent to 2D material nanopores and, meanwhile, significantly inhibit noise levels. A theoretical model is also provided to assess the performance of the bio-inspired nanopore, which could guide its design and optimization.

Degree of disorder-regulated ion transport through amorphous monolayer carbon

Nanopore technology, re-fueled by two-dimensional (2D) materials such as graphene and MoS2, controls mass transport by allowing certain species while denying others at the nanoscale and has a wide application range in DNA sequencing, nano-power generation, and others. With their low transmembrane transport resistance and high permeability stemming from their ultrathin nature, crystalline 2D materials do not possess nanoscale holes naturally, thus requiring additional fabrication to create nanopores. Herein, we demonstrate that nanopores exist in amorphous monolayer carbon (AMC) grown at low temperatures. The size and density of nanopores can be tuned by the growth temperature, which was experimentally verified by atomic images and further corroborated by kinetic Monte Carlo simulation. Furthermore, AMC films with varied degrees of disorder (DOD) exhibit tunable transmembrane ionic conductance over two orders of magnitude when serving as nanopore membranes. This work demonstrates the DOD-tuned property in amorphous monolayer carbon and provides a new candidate for modern membrane science and technology.

Detecting Hachimoji DNA: An Eight-Building-Block Genetic System with MoS2 and Janus MoSSe Monolayers

In the pursuit of personalized medicine, the development of efficient, cost-effective, and reliable DNA sequencing technology is crucial. Nanotechnology, particularly the exploration of two-dimensional materials, has opened different avenues for DNA nucleobase detection, owing to their impressive surface-to-volume ratio. This study employs density functional theory with van der Waals corrections to methodically scrutinize the adsorption behavior and electronic band structure properties of a DNA system composed of eight hachimoji nucleotide letters adsorbed on both MoS2 and MoSSe monolayers. Through a comprehensive conformational search, we pinpoint the most favorable adsorption sites, quantifying their adsorption energies and charge transfer properties. The analysis of electronic band structure unveils the emergence of flat bands in close proximity to the Fermi level post-adsorption, a departure from the pristine MoS2 and MoSSe monolayers. Furthermore, leveraging the nonequilibrium Green's function approach, we compute the current-voltage characteristics, providing valuable insights into the electronic transport properties of the system. All hachimoji bases exhibit physisorption with a horizontal orientation on both monolayers. Notably, base G demonstrates high sensitivity on both substrates. The obtained current-voltage (I-V) characteristics, both without and with base adsorption on MoS2 and the Se side of MoSSe, affirm excellent sensing performance. This research significantly advances our understanding of potential DNA sensing platforms and their electronic characteristics, thereby propelling the endeavor for personalized medicine through enhanced DNA sequencing technologies.

Next-Generation Sequencing and Emerging Technologies

Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.

Thermoelectric Limitations of Graphene Nanodevices at Ultrahigh Current Densities

Graphene is atomically thin, possesses excellent thermal conductivity, and is able to withstand high current densities, making it attractive for many nanoscale applications such as field-effect transistors, interconnects, and thermal management layers. Enabling integration of graphene into such devices requires nanostructuring, which can have a drastic impact on the self-heating properties, in particular at high current densities. Here, we use a combination of scanning thermal microscopy, finite element thermal analysis, and operando scanning transmission electron microscopy techniques to observe prototype graphene devices in operation and gain a deeper understanding of the role of geometry and interfaces during high current density operation. We find that Peltier effects significantly influence the operational limit due to local electrical and thermal interfacial effects, causing asymmetric temperature distribution in the device. Thus, our results indicate that a proper understanding and design of graphene devices must include consideration of the surrounding materials, interfaces, and geometry. Leveraging these aspects provides opportunities for engineered extreme operation devices.

Metal-Graphene Hybrid Terahertz Metasurfaces for Circulating Tumor DNA Detection Based on Dual Signal Amplification

Terahertz (THz) spectroscopy has impressive capability for label-free biosensing, but its utility in clinical laboratories is rarely reported due to often unsatisfactory detection performances. Here, we fabricated metal-graphene hybrid THz metasurfaces (MSs) for the sensitive and enzyme-free detection of circulating tumor DNA (ctDNA) in pancreatic cancer plasma samples. The feasibility and mechanism of the enhanced effects of a graphene bridge across the MS and amplified by gold nanoparticles (AuNPs) were investigated experimentally and theoretically. The AuNPs serve to boost charge injection in the graphene film and result in producing a remarkable change in the graded transmissivity index to THz radiation of the MS resonators. Assay design utilizes this feature and a cascade hybridization chain reaction initiated on magnetic beads in the presence of target ctDNA to achieve dual signal amplification (chemical and optical). In addition to demonstrating subfemtomolar detection sensitivity and single-nucleotide mismatch selectivity, the proposed method showed remarkable capability to discriminate between pancreatic cancer patients and healthy individuals by recognizing and quantifying targeted ctDNAs. The introduction of graphene to the metasurface produces an improved sensitivity of 2 orders of magnitude for ctDNA detection. This is the first study to report the combined application of graphene and AuNPs in biosensing by THz spectroscopic resonators and provides a combined identification scheme to detect and discriminate different biological analytes, including nucleic acids, proteins, and various biomarkers.

The Role of MXene Surface Terminations on Peptide Transportation in Nanopore Sensing

Nanopores with two-dimensional materials have various advantages in sensing, but the fast translocation of molecules hinders their scale-up applications. In this work, we investigate the influence of -F, -O, and -OH surface terminations on the translocation of peptides through MXene nanopores. We find that the longest dwell time always occurs when peptides pass through the Ti3C2O2 nanopores. This elongated dwell time is induced by the strongest interaction between peptides and the Ti3C2O2 membrane, in which the van der Waals interactions dominate. Compared to the other two MXene nanopores, the braking effect is indicated during the whole translocation process, which evidence the advantage of Ti3C2O2 in nanopore sensing. Our work demonstrates that membrane surface chemistry has a great influence on the translocation of peptides, which can be introduced in the design of nanopores for a better performance.

Interplay of graphene-DNA interactions: Unveiling sensing potential of graphene materials

Graphene-based materials and DNA probes/nanostructures have emerged as building blocks for constructing powerful biosensors. Graphene-based materials possess exceptional properties, including two-dimensional atomically flat basal planes for biomolecule binding. DNA probes serve as excellent selective probes, exhibiting specific recognition capabilities toward diverse target analytes. Meanwhile, DNA nanostructures function as placement scaffolds, enabling the precise organization of molecular species at nanoscale and the positioning of complex biomolecular assays. The interplay of DNA probes/nanostructures and graphene-based materials has fostered the creation of intricate hybrid materials with user-defined architectures. This advancement has resulted in significant progress in developing novel biosensors for detecting DNA, RNA, small molecules, and proteins, as well as for DNA sequencing. Consequently, a profound understanding of the interactions between DNA and graphene-based materials is key to developing these biological devices. In this review, we systematically discussed the current comprehension of the interaction between DNA probes and graphene-based materials, and elucidated the latest advancements in DNA probe-graphene-based biosensors. Additionally, we concisely summarized recent research endeavors involving the deposition of DNA nanostructures on graphene-based materials and explored imminent biosensing applications by seamlessly integrating DNA nanostructures with graphene-based materials. Finally, we delineated the primary challenges and provided prospective insights into this rapidly developing field. We envision that this review will aid researchers in understanding the interactions between DNA and graphene-based materials, gaining deeper insight into the biosensing mechanisms of DNA-graphene-based biosensors, and designing novel biosensors for desired applications.

Label-Free Imaging of DNA Interactions with 2D Materials

Two-dimensional (2D) materials offer potential as substrates for biosensing devices, as their properties can be engineered to tune interactions between the surface and biomolecules. Yet, not many methods can measure these interactions in a liquid environment without introducing labeling agents such as fluorophores. In this work, we harness interferometric scattering (iSCAT) microscopy, a label-free imaging technique, to investigate the interactions of single molecules of long dsDNA with 2D materials. The millisecond temporal resolution of iSCAT allows us to capture the transient interactions and to observe the dynamics of unlabeled DNA binding to a hexagonal boron nitride (hBN) surface in solution for extended periods (including a fraction of 10%, of trajectories lasting longer than 110 ms). Using a focused ion beam technique to engineer defects, we find that DNA binding affinity is enhanced at defects; when exposed to long lanes, DNA binds preferentially at the lane edges. Overall, we demonstrate that iSCAT imaging is a useful tool to study how biomolecules interact with 2D materials, a key component in engineering future biosensors.

Effect of surface functionalization on DNA sequencing using MXene-based nanopores

As one of the most promising types of label-free nanopores has great potential for DNA sequencing via fast detection of different DNA bases. As one of the most promising types of label-free nanopores, two-dimensional nanopore materials have been developed over the past two decades. However, how to detect different DNA bases efficiently and accurately is still a challenging problem. In the present work, the translocation of four homogeneous DNA strands (i.e., poly(A)20, poly(C)20, poly(G)20, and poly(T)20) through two-dimensional transition-metal carbide (MXene) membrane nanopores with different surface terminal groups is investigated via all-atom molecular dynamics simulations. Interestingly, it is found that the four types of bases can be distinguished by different ion currents and dwell times when they are transported through the Ti3C2(OH)2 nanopore. This is mainly attributed to the different orientation and position distributions of the bases, the hydrogen bonding inside the MXene nanopore, and the interaction of the ssDNA with the nanopore. The present study enhances the understanding of the interaction between DNA strands and MXene nanopores with different functional groups, which may provide useful guidelines for the design of MXene-based devices for DNA sequencing in the future.

How to make DNA data storage more applicable

The storage of digital data is becoming a worldwide problem. DNA has been recognized as a biological solution due to its ability to store genetic information without alteration over long periods. The first demonstrations of high-capacity long-lasting DNA digital data storage have been shown. However, high storage costs and slow retrieval of the data must be overcome to make DNA data storage more applicable and marketable. Herein, we discuss the issues and recent advances in DNA data storage methods and highlight pathways to make this technology more applicable to real-world digital data storage. We envision that a combination of molecular biology, nanotechnology, novel polymers, electronics, and automation with systematic development will allow DNA data storage sufficient for everyday use.

Non-equilibrium molecular dynamics of steady-state fluid transport through a 2D membrane driven by a concentration gradient

We use a novel non-equilibrium algorithm to simulate steady-state fluid transport through a two-dimensional (2D) membrane due to a concentration gradient by molecular dynamics (MD) for the first time. We confirm that, as required by the Onsager reciprocal relations in the linear-response regime, the solution flux obtained using this algorithm agrees with the excess solute flux obtained from an established non-equilibrium MD algorithm for pressure-driven flow. In addition, we show that the concentration-gradient-driven solution flux in this regime is quantified far more efficiently by explicitly applying a transmembrane concentration difference using our algorithm than by applying Onsager reciprocity to pressure-driven flow. The simulated fluid fluxes are captured with reasonable quantitative accuracy by our previously derived continuum theory of concentration-gradient-driven fluid transport through a 2D membrane [D. J. Rankin, L. Bocquet, and D. M. Huang, J. Chem. Phys. 151, 044705 (2019)] for a wide range of solution and membrane parameters, even though the simulated pore sizes are only several times the size of the fluid particles. The simulations deviate from the theory for strong solute-membrane interactions relative to thermal energy, for which the theoretical approximations breakdown. Our findings will be beneficial for a molecular-level understanding of fluid transport driven by concentration gradients through membranes made from 2D materials, which have diverse applications in energy harvesting, molecular separations, and biosensing.

Unveiling DNA Translocation in Pristine Graphene Nanopores: Understanding Pore Clogging via Polarizable Simulations

Graphene has garnered remarkable attention in recent years as an attractive nanopore membrane for rapid and accurate sequencing of DNA. The inherent characteristics of graphene offer exquisite experimental control over pore dimensions, encompassing both the width (pore diameter) and height. Despite these promising prospects, the practical deployment of pristine graphene nanopores for DNA sequencing has encountered a formidable challenge in the form of pore clogging, which is primarily attributed to hydrophobic interactions. However, a comprehensive understanding of the atomistic origins underpinning this clogging phenomenon and the nuanced impact of individual nucleobase identities on clogging dynamics remain an underexplored domain. Elucidating the atomistic intricacies governing pore clogging is pivotal to devising strategies for its mitigation and advancing our understanding of graphene nanopore behavior. We harness Drude polarizable simulations to systematically dissect the nucleobase-dependent mechanisms that play a pivotal role in nanopore clogging. We unveil nucleobase-specific interactions that illuminate the multifaceted roles played by both hydrophobic and electrostatic forces in driving nanopore clogging events. Notably, the Drude simulations also unveil the bias-dependent translocation dynamics and its pivotal role in alleviating pore clogging─a facet that remains significantly underestimated in conventional additive (nonpolarizable) simulations. Our findings underscore the indispensability of incorporating polarizability to faithfully capture the intricate dynamics governing graphene nanopore translocation phenomena, thus deepening our insights into this crucial field.

Solid-State Nanopore Distinguishes Ferritin and Apo-Ferritin with Identical Exteriors through Amplified Flexibility at Single-Molecule Level

Protein identification and discrimination at the single-molecule level are big challenges. Solid-state nanopores as a sensitive biosensor have been used for protein analysis, although it is difficult to discriminate proteins with similar structures in the traditional discrimination method based on the current blockage fraction. Here, we select ferritin and apo-ferritin as the model proteins that exhibit identical exterior and different interior structures and verify the practicability of their discrimination with flexibility features by the strategy of gradually decreasing the nanopore size. We show that the larger nanopore (relative to the protein size) has no obvious effect on discriminating two proteins. Then, the comparable-sized nanopore plays a key role in discriminating two proteins based on the dwell time and fraction distribution, and the conformational changes of both proteins are also studied with this nanopore. Finally, in the smaller nanopore, the protein molecules are trapped rather than translocated, where two proteins are obviously discriminated through the current fluctuation caused by the vibration of proteins. This strategy has potential in the discrimination of other important similar proteins.

Theoretical aspects of the adsorption of normal and modified base pairs of DNA on graphene models toward DNA sequencing

A theoretical understanding of the adsorption of DNA base pairs (GC, AT, CAF-T and CAF-C) on the graphene models (Gr, SiGr and SiGr-COOH) is investigated. Among the complexes, SiGr-COOH_AT is found to have the highest adsorption energies of -202.83 kcal/mol. The strong adsorption between DNA base pairs and the SiGr-COOH model leads to concomitant charge transfer responsible for the stability of the corresponding models and is verified with NBO analysis. AIM analysis discloses the high orbital overlap that signifies the strong interaction. Closed-shell interactions are observed through the positive values of total electron density, and it is also observed that Si-O(N) interaction has both covalent and electrostatic characteristics. This is the first theoretical attempt to investigate the adsorption of DNA base pairs on SiGr-COOH, which is more favourable than other models and may call for further experimental studies, which is crucial in developing new bio-sensors.Communicated by Ramaswamy H. Sarma.

Exploring the non-monotonic DNA capture behavior in a charged graphene nanopore

Nanopore-based biomolecule detection has emerged as a promising and sought-after innovation, offering high throughput, rapidity, label-free analysis, and cost-effectiveness, with potential applications in personalized medicine. However, achieving efficient and tunable biomolecule capture into the nanopore remains a significant challenge. In this study, we employ all-atom molecular dynamics simulations to investigate the capture of double-stranded DNA (dsDNA) molecules into graphene nanopores with varying positive charges. We discover a non-monotonic relationship between the DNA capture rate and the charge of the graphene nanopore. Specifically, the capture rate initially decreases and then increases with an increase in nanopore charge. This behavior is primarily attributed to differences in the electrophoretic force, rather than the influence of electroosmosis or counterions. Furthermore, we also observe this non-monotonic trend in various ionic solutions, but not in ionless solutions. Our findings shed light on the design of novel DNA sequencing devices, offering valuable insights into enhancing biomolecule capture rates in nanopore-based sensing platforms.

Recent development of piezoelectric biosensors for physiological signal detection and machine learning assisted cardiovascular disease diagnosis

As cardiovascular disease stands as a global primary cause of mortality, there has been an urgent need for continuous and real-time heart monitoring to effectively identify irregular heart rhythms and to offer timely patient alerts. However, conventional cardiac monitoring systems encounter challenges due to inflexible interfaces and discomfort during prolonged monitoring. In this review article, we address these issues by emphasizing the recent development of the flexible, wearable, and comfortable piezoelectric passive sensor assisted by machine learning technology for diagnosis. This innovative device not only harmonizes with the dynamic mechanical properties of human skin but also facilitates continuous and real-time collection of physiological signals. Addressing identified challenges and constraints, this review provides insights into recent advances in piezoelectric cardiac sensors, from devices to circuit systems. Furthermore, this review delves into the integration of machine learning technologies, showcasing their pivotal role in facilitating continuous and real-time assessment of cardiac status. The synergistic combination of flexible piezoelectric sensor design and machine learning holds substantial potential in automating the detection of cardiac irregularities with minimal human intervention. This transformative approach has the power to revolutionize patient care paradigms.

Curvature induced structural changes of the chicken villin headpiece subdomain by single walled carbon nanotubes

Carbon nanotubes (CNTs) are identified as potential candidates for drug and biomolecular loading and delivery. CNTs of different chiralities have different diameters, which may significantly affect their abilities to interact with different types of biomolecules. Herein, we employ classical molecular dynamics simulation to provide insight into the curvature-dependent interactions between a model protein, chicken villin headpiece subdomain (HP36), with CNTs having chiralities (8,8), (12,12), and (20,20). It is revealed that, with increasing radii, the protein encounters more aromatic carbon atoms on the surface of the CNT, leading to its increasing strength of adsorption. However, the extent of adsorption has a limiting magnitude, after which an increase in the radius of the nanotube has practically no effect on the extent of adsorption. Spontaneous encapsulation of the protein was demonstrated using a (28,28) CNT, where the protein is found to undergo insignificant structural perturbation. Finally, steered molecular dynamics simulations have been performed to mimic the force-induced release of the protein from within the nanotube cavity. It has been identified that a minimum force of ∼300 pN and a minimum velocity of 4 Å ns-1 are required to release the protein from the CNT at 300 K. Any external force below the critical magnitude and inducing velocity less than 4 Å ns-1 allows the translocation of the protein through the inner surface of the CNT; however, before being released, the protein undergoes unfolding, thereby losing the secondary structure and biological activity.

Charge transport through DNA with energy-dependent decoherence

Modeling charge transport in DNA is essential to understand and control the electrical properties and develop DNA-based nanoelectronics. DNA is a fluctuating molecule that exists in a solvent environment, which makes the electron susceptible to decoherence. While knowledge of the Hamiltonian responsible for decoherence will provide a microscopic description, the interactions are complex and methods to calculate decoherence are unclear. One prominent phenomenological model to include decoherence is through fictitious probes that depend on spatially variant scattering rates. However, the built-in energy independence of the decoherence (E-indep) model overestimates the transmission in the bandgap and washes out distinct features inside the valence or conduction bands. In this study, we introduce a related model where the decoherence rate is energy-dependent (E-dep). This decoherence rate is maximum at energy levels and decays away from these energies. Our results show that the E-dep model allows for exponential transmission decay with the DNA length and maintains features within the bands' transmission spectra. We further demonstrate that we can obtain DNA conductance values within the experimental range. Our model can help study and design nanoelectronics devices that utilize weakly coupled molecular structures such as DNA.

Advances in field-effect biosensors towards point-of-use

The future of medical diagnostics calls for portable biosensors at the point of care, aiming to improve healthcare by reducing costs, improving access, and increasing quality-what is called the 'triple aim'. Developing point-of-care sensors that provide high sensitivity, detect multiple analytes, and provide real time measurements can expand access to medical diagnostics for all. Field-effect transistor (FET)-based biosensors have several advantages, including ultrahigh sensitivity, label-free and amplification-free detection, reduced cost and complexity, portability, and large-scale multiplexing. They can also be integrated into wearable or implantable devices and provide continuous, real-time monitoring of analytesin vivo, enabling early detection of biomarkers for disease diagnosis and management. This review analyzes advances in the sensitivity, parallelization, and reusability of FET biosensors, benchmarks the limit of detection of the state of the art, and discusses the challenges and opportunities of FET biosensors for future healthcare applications.

First-Principles Investigation of Nucleobase Detection by Tetranitrogen Coordinated Transition Metal Doped Graphene Nanoribbons

Detection of nucleobases is of great significance in DNA sequencing, which is one of the main goals of the Human Genome Project. By employing the nonequilibrium Green function method combined with density functional theory, we proposed a biosensor based on the TMN4 (TM = Ni, Cu) embedded graphene nanoribbons for nucleobase detection. The adsorption energy calculations show that all five nucleobases are physisorbed on the TMN4-doped graphene nanoribbons. Utilizing the distinction of current, the bases T, C, and U can be gradually detected at the biases of 0.4, 0.6, and 0.8 V by NiN4-doped graphene nanoribbons, respectively. The bases A and G can be finally distinguished by CuN4-doped graphene nanoribbons under an external bias of not less than 0.8 V. The identification of individual nucleobases at specific biases could provide a novel mechanism for the further development of biosensors in rapid genome sequencing applications.

Ion transport based structural description for in situ synthesized SBA-15 nanochannels in a sub-micropipette

Construction of nanoporous arrays can greatly facilitate their development in the fields of sensing, energy conversion, and nanofluidic devices. It is important to characterize the structure and understand the ion transport behaviour of a nanoporous array, especially those prepared by in situ synthesis, which are difficult to be characterized by conventional methods. Herein, an inorganic and non-crystalline mesoporous silica SBA-15 is selected as a template, where a combination (GP-SBA-15) of a sub-micropipette and SBA-15 is constructed by in situ synthesis, and the multichannel array structure of GP-SBA-15 is illustrated by its ion transport properties from current-voltage responses. Experiments of linear scan voltammetry and chronoamperometry show a rapid accumulation and slow redistribution of ions in the surface-charged nanochannels, and the high/low currents originate from the accumulation/depletion of ions in the channels. The finite element simulation is introduced to calculate the effects of surface charge and pore size on ion rectification and ion concentration distribution. In addition, the short straight channels and long bending channels present in GP-SBA-15 are demonstrated by the voltage-independent resistance pulse signals in the translocation of BSA. This study shows that electrochemical means effectively provide insight into ion transport, achieve structural description and reveal the sensing potential of GP-SBA-15.

Adsorption of DNA nucleobases on single-layer Ti3C2 MXene and graphene: vdW-corrected DFT and NEGF studies

We investigated the interaction of DNA nucleobases [adenine (A), guanine (G), thymine (T), and cytosine (C)] with single-layer Ti3C2 MXene using Van der Waals (vdW)-corrected density functional theory and non-equilibrium Green's function methods. All calculations were benchmarked against graphene. We showed that depending on the initial vertical height of a nucleobase above the Ti3C2 surface, two interaction mechanisms are possible, namely, physisorption and chemisorption. For graphene, DNA nucleobases always physisorbed onto the graphene surface irrespective of the initial vertical height of the nucleobase above the graphene sheet. The PBE+vdW binding energies for graphene are high (0.55-0.74 eV) and follow the order G > A > T > C, with adsorption heights in the range of 3.16-3.22 Å, indicating strong physisorption. For Ti3C2, the PBE+vdW binding energies are relatively weaker (0.16-0.20 eV) and follow the order A > G = T > C, with adsorption heights in the range of 5.51-5.60 Å, indicating weak physisorption. The binding energies for chemisorption follow the order G > A > T > C, which is the same order for physisorption. The binding energy values (5.3-7.5 eV) indicate very strong chemisorption (∼40 times larger than the physisorption binding energies). Furthermore, our band structure and electronic transport analysis showed that for physisorption, there is neither significant variation in the band structure nor modulation in the transmission function and device density of states. The relatively weak physisorption and strong chemisorption show that Ti3C2 might not be capable of identifying DNA nucleobases using the physisorption method.

Roboethics of tourism and hospitality industry: A systematic review

This study aims to give a comprehensive analysis of customers' acceptance and use of AI gadgets and its relevant ethical issues in the tourism and hospitality business in the era of the Internet of Things. Adopting a PRISMA methodology for Systematic Reviews and Meta-Analyses, the present research reviews how tourism and hospitality scholars have conducted research on AI technology in the field of tourism and the hospitality industry. Most of the journal articles related to AI issues published in Web of Science, ScienceDirect.com and the journal websites were considered in this review. The results of this research offer a better understanding of AI implementation with roboethics to investigate AI-related issues in the tourism and hospitality industry. In addition, it provides decision-makers in the hotel industry with practical references on service innovation, participation in the design of AI devices and AI device applications, meeting customer needs, and optimising customer experience. The theoretical implications and practical interpretations are further identified.

Ion transport in two-dimensional flexible nanoporous membranes

Ion transport is a fundamental mechanism in living systems that plays a role in cell proliferation, energy conversion, and maintaining homeostasis. This has inspired various nanofluidic applications such as electricity harvesting, molecular sensors, and molecular separation. Two dimensional (2D) nanoporous membranes are particularly promising for these applications due to their ultralow transport barriers. We investigated ion conduction across flexible 2D membranes via extensive molecular dynamics simulations. We found that the microscopic fluctuations of these membranes can significantly increase ion conductance, for example, by 320% in Cu-HAB with 0.5 M KCl. Our analysis of ion dynamics near the flexible membranes revealed that ion hydration is destabilized when the membrane fluctuated within a specific frequency range leading to improved ion conduction. Our results show that the dynamic coupling between the fluctuating membrane and ions can play a crucial role in ion conduction across 2D nanoporous membranes.

Highly Sensitive and Selective DNA Sequencing Device Using Metal Adatom Adsorption on 2D Phosphorene

Two-dimensional (2D) material revolutionarily extends the technique capability of traditional nanopore/nanogap-based DNA sequencing devices. However, challenges associated with DNA sequencing on nanopores still remained in improving the sensitivity and specificity. Herein, by first-principles calculation, we theoretically studied the potential of transition-metal elements (Cr, Fe, Co, Ni, and Au) anchored on monolayer black phosphorene (BP) to act as all-electronic DNA sequencing devices. The spin-polarized band structures appeared in Cr-, Fe-, Co-, and Au-doped BP. Remarkably, the adsorption energy of nucleobases can be significantly enhanced on BP with Co, Fe, and Cr doping, which contribute to the enlarged current signal and lower noise levels. Furthermore, the order of nucleobases in terms of their adsorption energies onto the Cr@BP is C > A > G > T, which exhibits more distinct adsorption energies than Fe@BP or Co@BP. Therefore, Cr-doped BP is more effective to avoid ambiguity in recognizing various bases. We thus envisaged a possibility of a highly sensitive and selective DNA sequencing device based on phosphorene.

DNA sequencing via molecular dynamics simulation with functionalized graphene nanopore

Through this research, functionalized graphene nanopores are used to verify how effective such an apparatus for DNA sequencing is. The circular symmetric pores are functionalized with hydrogen and a hydroxyl group bonded with carbon atoms of the pore rim. Plus, two adenine bases are also put at the rim perimeter to verify whether such a combination would lead to base detection. A homopolymer of single-stranded DNA (ssDNA) is pulled through a nanopore using steered molecular dynamics (SMD) simulation. Pulling force profile, moving fashion of ssDNA in irreversible DNA pulling as well as the base orientation during translocation relative to the graphene plane, called beta angle, are assessed. Based on the studied parameters, SMD force, and base orientation, the hydrogenated and hydroxylated pores do not show a clear distinction between bases, while the adenine-functionalized pore can distinguish between adenine and cytosine. Therefore, there may be some hope for achieving single-base sequencing, while further research is needed.

Ordered Assembly of DNA on Topological Insulator Bi2Se3 and Octadecylamine for a Sensitive Biosensor

Controlling the assembly of DNA in order on a suitable electrode surface is of great significance for biosensors and disease diagnosis, but it is full of challenges. In this work, we creatively assembled DNA on the surface of octadecylamine (ODA)-modified topological insulator (Tls) Bi₂Se₃ and developed an electrochemical biosensor to detect biomarker DNA of coronavirus disease 2019 (COVID-19). A high-quality Bi₂Se₃ sheet was obtained from a single crystal synthesized in our lab. A uniform ODA layer was coated in argon by chemical vapor deposition (CVD). We observed and analyzed the assembly and mechanism of single-strand DNA (ssDNA) and double-strand DNA (dsDNA) on the Bi₂Se₃ surface through atomic force microscopy (AFM) and molecular dynamics (MD) simulations. The electrochemical signal revealed that the biosensor based on the DNA/ODA/Bi₂Se₃ electrode has a wide linear detection range from 1.0 × 10^-12 to 1.0 × 10^-8 M, with the limit of detection as low as 5 × 10^-13 M. Bi₂Se₃ has robust surface states and improves the electrochemical signal-to-noise ratio, while the uniform ODA layer guides high-density ordered DNA, enhancing the sensitivity of the biosensor. Our work demonstrates that the ordered DNA/ODA/Bi₂Se₃ electrode surface has great application potential in the field of biosensing and disease diagnosis.

Scaled-Up Synthesis of Freestanding Molybdenum Disulfide Membranes for Nanopore Sensing

2D materials are ideal for nanopores with optimal detection sensitivity and resolution. Among these, molybdenum disulfide (MoS₂ ) has gained traction as a less hydrophobic material than graphene. However, experiments using 2D nanopores remain challenging due to the lack of scalable methods for high-quality freestanding membranes. Herein, a site-directed, scaled-up synthesis of MoS₂ membranes on predrilled nanoapertures on 4-inch wafer substrates with 75% yields is reported. Chemical vapor deposition (CVD), which introduces sulfur and molybdenum dioxide vapors across the sub-100 nm nanoapertures results in exclusive formation of freestanding membranes that seal the apertures. Nucleation and growth near the nanoaperture edges is followed by nanoaperture decoration with MoS₂ , which proceeds until a critical flake curvature is achieved, after which fully spanning freestanding membranes form. Intentional blocking of reagent flow through the apertures inhibits MoS₂ nucleation around the nanoapertures, promoting the formation of large-crystal monolayer MoS₂ membranes. The in situ grown membranes along with facile membrane wetting and nanopore formation using dielectric breakdown enables the recording of dsDNA translocation events at an unprecedentedly high 1 MHz bandwidth. The methods presented here are important steps toward the development of scalable single-layer membrane manufacture for 2D nanofluidics and nanopore applications.

Cation-controlled permeation of charged polymers through nanocapillaries

Molecular dynamics simulations are used to study the effects of different cations on the permeation of charged polymers through flat capillaries with heights below 2 nm. Interestingly, we found that, despite being monovalent, Li^{+}, Na^{+}, and K^{+} cations have different effects on polymer permeation, which consequently affects their transmission speed throughout those capillaries. We attribute this phenomenon to the interplay of the cations' hydration free energies and the hydrodynamic drag in front of the polymer when it enters the capillary. Different alkali cations exhibit different surface versus bulk preferences in small clusters of water under the influence of an external electric field. This paper presents a tool to control the speed of charged polymers in confined spaces using cations.

An Introduction to Nanopore Sequencing: Past, Present, and Future Considerations

There has been significant progress made in the field of nanopore biosensor development and sequencing applications, which address previous limitations that restricted widespread nanopore use. These innovations, paired with the large-scale commercialization of biological nanopore sequencing by Oxford Nanopore Technologies, are making the platforms a mainstay in contemporary research laboratories. Equipped with the ability to provide long- and short read sequencing information, with quick turn-around times and simple sample preparation, nanopore sequencers are rapidly improving our understanding of unsolved genetic, transcriptomic, and epigenetic problems. However, there remain some key obstacles that have yet to be improved. In this review, we provide a general introduction to nanopore sequencing principles, discussing biological and solid-state nanopore developments, obstacles to single-base detection, and library preparation considerations. We present examples of important clinical applications to give perspective on the potential future of nanopore sequencing in the field of molecular diagnostics.

From nanohole to ultralong straight nanochannel fabrication in graphene oxide with swift heavy ions

Porous architectures based on graphene oxide with precisely tailored nm-sized pores are attractive for biofluidic applications such as molecular sieving, DNA sequencing, and recognition-based sensing. However, the existing pore fabrication methods are complex, suffer from insufficient control over the pore density and uniformity, or are not scalable to large areas. Notably, creating vertical pores in multilayer films appears to be particularly difficult. Here, we show that uniform 6-7 nm-sized holes and straight, vertical nanochannels can be formed by simply irradiating graphene oxide (GO) films with high-energy heavy ions. Long penetration depths of energetic ions in combination with localized energy deposition and effective self-etching processes enable the creation of through pores even in 10 µm-thick GO films. This fully scalable fabrication provides a promising possibility for obtaining innovative GO track membranes.

Enumerating Stable Nanopores in Graphene and Their Geometrical Properties Using the Combinatorics of Hexagonal Lattices

Nanopores in two-dimensional (2D) materials, including graphene, can be used for a variety of applications, such as gas separations, water desalination, and DNA sequencing. So far, however, all plausible isomeric shapes of graphene nanopores have not been enumerated. Instead, a probabilistic approach has been followed to predict nanopore shapes in 2D materials, due to the exponential increase in the number of nanopores as the size of the vacancy increases. For example, there are 12 possible isomers when N = 6 atoms are removed, a number that theoretically increases to 11.7 million when N = 20 atoms are removed from the graphene lattice. In this regard, the development of a smaller, exhaustive data set of stable nanopore shapes can help future experimental and theoretical studies focused on using nanoporous 2D materials in various applications. In this work, we use the theory of 2D triangular "lattice animals" to create a library of all stable graphene nanopore shapes based on a modification of a well-known algorithm in the mathematical combinatorics of polyforms known as Redelmeier's algorithm. We show that there exists a correspondence between graphene nanopores and triangular polyforms (called polyiamonds) as well as hexagonal polyforms (called polyhexes). We develop the concept of a polyiamond ID to identify unique nanopore isomers. We also use concepts from polyiamond and polyhex geometries to eliminate unstable nanopores containing dangling atoms, bonds, and moieties. We verify using density functional theory calculations that such pores are indeed unstable. The exclusion of these unstable nanopores leads to a remarkable reduction in the possible nanopores from 11.7 million for N = 20 to only 0.184 million nanopores, thereby indicating that the number of stable nanopores is almost 2 orders of magnitude lower and is much more tractable. Not only that, by extracting the polyhex outline, our algorithm allows searching for nanopores with dimensions and shape factors in a specified range, thus aiding the design of the geometrical properties of nanopores for specific applications. We also provide the coordinate files of the stable nanopores as a library to facilitate future theoretical studies of these nanopores.

Integrating FTIR 2D correlation analyses, regular and omics analyses studies on the interaction and algal toxicity mechanisms between graphene oxide and cadmium

Graphene oxide (GO, a popular 2D graphene-based nanomaterial) has developed quickly and has received considerable attention for its applications in environmental protection and pollutant removal. However, significant knowledge gaps still exist about the interaction characteristic and joint toxicity mechanism of GO and cadmium (Cd) on aquatic organisms. In this study, GO showed a high adsorption capacity (120. 6 mg/g) and strong adsorption affinity (K_L = 0.85 L/mg) for Cd²⁺. Integrating multiple analytical methods (e.g., electron microscopy, Raman spectra, and 2D correlation spectroscopy) revealed that Cd²⁺ is uniformly adsorbed on the GO surface and edge mainly through cation-π interactions. The combined ecological effects of GO and Cd²⁺ on Chlorella vulgaris were observed. Cd²⁺ induced more severe growth inhibition, photosynthesis toxicity, ultrastructure damage and plasmolysis than GO. Interestingly, we found that GO nanosheets could augment the algal toxicity of Cd²⁺ (e.g., chlorophyll b, mitochondrial membrane damage, and uptake). Transcriptomics and metabolomics further explained the underlying mechanism. The results indicated that the regulation of PSI-, PSII-, and metal transport-related genes (e.g., ABCG37 and ZIP4) and the inhibition of metabolic pathways (e.g., amino acid, fatty acid, and carbohydrate metabolism) were responsible for the persistent phytotoxicity. The present work provides mechanistic insights into the roles of coexisting inorganic pollutants on the environmental fate and risk of GO in aquatic ecosystems.

A Step toward Amino Acid-Labeled DNA Sequencing: Boosting Transmission Sensitivity of Graphene Nanogap

Existing obstacles in next-generation DNA sequencing techniques, for instance, high noise, high translocation speed, and configurational fluctuations, call for approaches capable of reaching the goal and accelerating the process of personalized medicine development. The labeling nucleotide approach has the potential to overcome these barriers and boost the recognition sensitivity of a solid-state nanodevice. In this theoretical report, the first-principles density functional theory calculations have been employed to study the role of three different labels, tyrosine (Tyr), aspartic acid (Asp), and arginine (Arg), for labeling DNA nucleotides and study their effect in rapid and controlled DNA sequencing at atomic resolution. Remarkable differences in interaction energy values are noticed in all three cases of differently labeled nucleotides. The zero-bias transmission spectra confirm that proposed labels have the ability to detect the individual nucleotide, amplifying the tunneling current sensitivity by several orders of magnitude. The current-voltage characteristics of Arg-labeled nucleotides are found to be promising for single nucleotide recognition even at a very low bias voltage of 0.1 V.

Towards a graphene semi/hybrid-nanogap: a new architecture for ultrafast DNA sequencing

The tremendous upsurge in the research of next-generation sequencing (NGS) methods has broadly been driven by the rise of the wonder material graphene and continues to dominate the futuristic approaches for fast and accurate DNA sequencing. The success of graphene has also triggered the search for many new potential NGS methods capable of ultrafast, reliable, and controlled DNA sequencing. The present study delves into the potential of a new NGS architecture utilizing graphene, namely, a 'semi/hybrid-nanogap' for the identification of DNA nucleobases with single-base resolution. In the framework of first-principles density functional theory methods, we have calculated the transmission function and current-voltage (I-V) characteristics which are of particular significance for DNA sequencing applications. It is noted that the interaction energy values are significantly reduced compared to the previously reported graphene nanodevices, which can lead to a controlled translocation during experimental measurements. Based on the transmission function, each nucleobase can be identified with pertinent sensitivity. It is noticed that the use of highly conductive nucleobase analogs can facilitate improved single nucleobase sensing by increasing the transmission sensitivity. Therefore, we believe that the present study opens up promising frontiers for sequencing applications.

Machine Learning Aided Interpretable Approach for Single Nucleotide-Based DNA Sequencing using a Model Nanopore

Solid-state nanopore-based electrical detection of DNA nucleotides with the quantum tunneling technique has emerged as a powerful strategy to be the next-generation sequencing technology. However, experimental complexity has been a foremost obstacle in achieving a more accurate high-throughput analysis with industrial scalability. Here, with one of the nucleotide training data sets of a model monolayer gold nanopore, we have predicted the transmission function for all other nucleotides with root-mean-square error scores as low as 0.12 using the optimized eXtreme Gradient Boosting Regression (XGBR) model. Further, the SHapley Additive exPlanations (SHAP) analysis helped in exploring the interpretability of the XGBR model prediction and revealed the complex relationship between the molecular properties of nucleotides and their transmission functions by both global and local interpretable explanations. Hence, experimental integration of our proposed machine-learning-assisted transmission function prediction method can offer a new direction for the realization of cheap, accurate, and ultrafast DNA sequencing.

Graphene nano-sieves by femtosecond laser irradiation

The formation of nano-pores in graphene crystal structure is alternative way to engineer its electronic properties, chemical reactivity, and surface interactions, enabling applications in technological fields such as sensing, energy and separation. The past few years, nano-perforation of graphene sheets has been accomplished by a variety of different methods suffering mainly from poor scalability and cost efficiency issues. In this work, we introduce an experimental protocol to engineer nanometer scale pores in CVD graphene membranes under ambient conditions, using low power ultra-short laser pulses and overcoming the drawbacks of other perforation techniques. Using Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM) we visualized and quantified the nanopore network while Raman spectroscopy is utilized to correlate the nano-perforated area with the nanotopographic imaging. We suggest that Raman imaging provides the identification of nanoporous area and, in combination with AFM, we provide solid evidence for the reproducibility of the method, since under these experimental conditions, nanopores of a certain size distribution are formed.

Inner Wall and Outer Surface Distinguished Solid-State Nanopores for Sensing

Solid-state nanopores, inspired by biological nanopores, have the advantages of good mechanical properties, stability, and easy modification. They have attracted wide attention in the fields of sequencing, sensing, molecular sieving, nanofluidic devices, nanoelectrochemistry, and energy conversion. Because of the ion/molecule transport characteristic of the pore, the research on solid-state nanopores mainly focuses on the functional modification of its inner wall. In recent years, the outer surface of nanopores has also attracted the attention of researchers, and the functional elements on the outer surface have the functions of anti-interference and ionic signal enhancement. In this perspective, we review research progress of inner wall and outer surface distinguished solid-state nanopores, highlight their processing and advantages, summarize their functions and applications in sensing, and give insight into further research.

Machine Learning Prediction of the Transmission Function for Protein Sequencing with Graphene Nanoslit

Protein sequencing has rapidly changed the landscape of healthcare and life science by accelerating the growth of diagnostics and personalized medicines for a variety of fatal diseases. Next-generation nanopore/nanoslit sequencing is promising to achieve single-molecule resolution with chromosome-size-long readability. However, due to inherent complexity, high-throughput sequencing of all 20 amino acids demands different approaches. Aiming to accelerate the detection of amino acids, a general machine learning (ML) method has been developed for quick and accurate prediction of the transmission function for amino acid sequencing. Among the utilized ML models, the XGBoost regression model is found to be the most effective algorithm for fast prediction of the transmission function with a very low test root-mean-square error (RMSE ∼0.05). In addition, using the random forest ML classification technique, we are able to classify the neutral amino acids with a prediction accuracy of 100%. Therefore, our approach is an initiative for the prediction of the transmission function through ML and can provide a platform for the quick identification of amino acids with high accuracy.

Sodium Dodecyl Sulfate-Mediated Graphene Sensor for Electrochemical Detection of the Antibiotic Drug: Ciprofloxacin

The present study involves detecting and determining CIP by a new electrochemical sensor based on graphene (Gr) in the presence of sodium dodecyl sulfate (SDS) employing voltammetric techniques. Surface morphology studies of the sensing material were analyzed using a scanning electron microscope (SEM) and atomic force microscope (AFM). In the electroanalysis of CIP at the developed electrode, an enhanced anodic peak response was recorded, suggesting the electro-oxidation of CIP at the electrode surface. Furthermore, we evaluated the impact of the electrolytic solution, scan rate, accumulation time, and concentration variation on the electrochemical behavior of CIP. The possible electrode mechanism was proposed based on the acquired experimental information. A concentration variation study was performed using differential pulse voltammetry (DPV) in the lower concentration range, and the fabricated electrode achieved a detection limit of 2.9 × 10^-8 M. The proposed sensor detected CIP in pharmaceutical and biological samples. The findings displayed good recovery, with 93.8% for tablet analysis and 93.3% to 98.7% for urine analysis. The stability of a developed electrode was tested by inter- and intraday analysis.

High-Throughput Nanopore Fabrication and Classification Using Xe-Ion Irradiation and Automated Pore-Edge Analysis

Large-area nanopore drilling is a major bottleneck in state-of-the-art nanoporous 2D membrane fabrication protocols. In addition, high-quality structural and statistical descriptions of as-fabricated porous membranes are key to predicting the corresponding membrane-wide permeation properties. In this work, we investigate Xe-ion focused ion beam as a tool for scalable, large-area nanopore fabrication on atomically thin, free-standing molybdenum disulfide. The presented irradiation protocol enables designing ultrathin membranes with tunable porosity and pore dimensions, along with spatial uniformity across large-area substrates. Fabricated nanoporous membranes are then characterized using scanning transmission electron microscopy imaging, and the observed nanopore geometries are analyzed through a pore-edge detection and analysis script. We further demonstrate that the obtained structural and statistical data can be readily passed on to computational and analytical tools to predict the permeation properties at both individual pore and membrane-wide scales. As an example, membranes featuring angstrom-scale pores are investigated in terms of their emerging water and ion flow properties through extensive all-atom molecular dynamics simulations. We believe that the combination of experimental and analytical approaches presented here will yield accurate physics-based property estimates and thus potentially enable a true function-by-design approach to fabrication for applications such as osmotic power generation and desalination/filtration.

Which 2D Material is Better for DNA Detection: Graphene, MoS2, or MXene?

Despite much research on characterizing 2D materials for DNA detection with nanopore technology, a thorough comparison between the performance of different 2D materials is currently lacking. In this work, using extensive molecular dynamics simulations, we compare nanoporous graphene, MoS₂ and titanium carbide MXene (Ti₃C₂) for their DNA detection performance and sensitivity. The ionic current and residence time of DNA are characterized in each nanoporous materials by performing hundreds of simulations. We devised two statistical measures including the Kolmogorov-Smirnov test and the absolute pairwise difference to compare the performance of nanopores. We found that graphene nanopore is the most sensitive membrane for distinguishing DNA bases. The MoS₂ is capable of distinguishing the A and T bases from the C and G bases better than graphene and MXene. Physisorption and the orientation of DNA in nanopores are further investigated to provide molecular insight into the performance characteristics of different nanopores.