Electronic Fingerprints Research Articles

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.

Design Principle of Molybdenum-Based Metal Nitrides for Lattice Nitrogen-Mediated Ammonia Production.

Chemical looping ammonia synthesis (CLAS) is a promising technology for reducing the high energy consumption of the conventional ammonia synthesis process. However, the comprehensive understanding of reaction mechanisms and rational design of novel nitrogen carriers has not been achieved due to the high complexity of catalyst structures and the unrevealed relationship between electronic structure and intrinsic activity. Herein, we propose a multistage strategy to establish the connection between catalyst intrinsic activity and microscopic electronic structure fingerprints using density functional theory computational energetics as bridges and apply it to the rational design of metal nitride catalysts for lattice nitrogen-mediated ammonia production. Molybdenum-based nitride catalysts with well-defined structures are employed as prototypes to elucidate the decoupled effects of electronic and geometrical features. The electron-transfer and spin polarization characteristics of the magnetic metals are constructed as descriptors to disclose the atomic-scale causes of intrinsic activity. Based on this design strategy, it is demonstrated that Ni3Mo3N catalysts possess the highest lattice nitrogen-mediated ammonia synthesis activity. This work reveals the structure-activity relationship of metal nitrides for CLAS and provides a multistage perspective on catalyst rational design.

Electronic Fingerprint of the Protonated Imidazole Dimer Probed by X-ray Absorption Spectroscopy.

Protons in low-barrier superstrong hydrogen bonds are typically delocalized between two electronegative atoms. Conventional methods to characterize such superstrong hydrogen bonds are vibrational spectroscopy and diffraction techniques. We introduce soft X-ray spectroscopy to uncover the electronic fingerprints for proton sharing in the protonated imidazole dimer, a prototypical building block enabling effective proton transport in biology and high-temperature fuel cells. Using nitrogen core excitations as a sensitive probe for the protonation status, we identify the X-ray signature of a shared proton in the solvated imidazole dimer in a combined experimental and theoretical approach. The degree of proton sharing is examined as a function of structural variations that modify the shape of the low-barrier potential in the superstrong hydrogen bond. We conclude by showing how the sensitivity to the quantum distribution of proton motion in the double-well potential is reflected in the spectral signature of the shared proton.

Electronic fingerprints for diverse interactions of methanol with various Zn-based systems

We have investigated various Zn-based catalysts for their interaction with methanol (MeOH). MeOH is one of the most critical molecules being studied extensively, and Zn-based catalysts are widely used in many industrially relevant reactions involving MeOH. We note that the same element (Zn and O, in the present study) exhibits different catalytic activity in different environments. The changing environment is captured in the underlying electronic structure of the catalysts. In the present work, we compared the electronic structure of Zn-based systems, i.e., ZnAl2O4 and ZnO along with oxygen preadsorbed Zn (O-Zn) and metallic Zn. We demonstrate the one-to-one correlation between the pDOS of the bare facet and the outcome of that facet’s interaction (i.e. either adsorption or dissociation of MeOH) with MeOH. These findings would pave the way towards the in-silico design of catalysts.

Detecting Air Pollutant Molecules Using Tube-Shaped Single Electron Transistor.

An air pollution detector is proposed based on a tube-shaped single-electron transistor (SET) sensor. By monitoring the flow control component of the detector, each air pollutant molecule can be placed at the center of a SET nanopore and is treated as an island of the SET device in the same framework. Electron transport in the SET was incoherent, and the performances of the SET were sensitive at the single molecule level. Employing first-principles calculations, electronic features of an air pollutant molecule within a tube-shaped SET environment were found to be independent of the molecule rotational orientations with respect to axis of symmetry, unlike the electronic features in a conventional SET environment. Charge stability diagrams of the island molecules were demonstrated to be distinct for each molecule, and thus they can serve as electronic fingerprints for detection. Using the same setup, quantification of the air pollutant can be realized at room temperature as well. The results presented herein may help provide guidance for the identification and quantification of various types of air pollutants at the molecular level by treating the molecule as the island of the SET component in the proposed detector.

Mixed Metal Thiophosphate Fe2-xCoxP2S6: Role of Structural Evolution and Anisotropy.

Metal chalcophosphates, M2P2Q6 (M = transition metals; Q = chalcogen), are notable among the van der Waals materials family for their potential magnetic ordering that can be tuned with an appropriate choice of the metal or chalcogen. However, there has not been a systematic investigation of the basic structural evolution in these systems with alloying of the crystal subunits due to the challenge in the diffusion process of mixing different metal cations in the octahedral sites of M2P2Q6 materials. In this work, the P2S5 flux method was used to enable the synthesis of a multilayered mixed metal thiophosphate Fe2-xCoxP2S6 (x = 0, 0.25, 1, 1.75, and 2) system. Here, we studied the structural, vibrational, and electronic fingerprints of this mixed M2P2Q6 system. Structural and elemental analyses indicate a homogeneous stoichiometry averaged through the sample over multiple layers of Fe2-xCoxP2S6 compounds. It was observed that there is a correlation between the intensity of specific phonon modes and the alloying concentration. The increasing Co alloying concentration shows direct relations to the in-plane [P2S6]4- and out-of-plane P-P dimer vibrations. Interestingly, an unusual nonlinear electronic structure dependence on the metal alloying ratio is found and confirmed by two distinct work functions within the Fe2-xCoxP2S6 system. We believe this work provides a fundamental structural framework for mixed metal thiophosphate systems, which may assist in future studies on electronic and magnetic applications of this emerging class of binary cation materials.

DNA nucleobase interaction driven electronic and optical fingerprints in gallium selenide monolayer for DNA sequencing devices

The interaction of DNA nucleobases with monolayer GaSe has been studied with in DFT framework using vdW functional. We found that nucleobases are physisorbed on the GaSe monolayer. The order of binding energy per atom is C > T > G > A. The room temperature recovery time estimated to be maximum of 113.88 µs for T + GaSe indicting reusability of the GaSe based devices. The modulation in the electronic structures of GaSe has been clearly captured within the simulated STM measurements. We also demonstrate quantum capacitance as a key parameter for sensing applications. Furthermore, in optical properties, electron energy loss (EEL) spectra show red shift in photon energy on nucleobase adsorption in UV region. The red shift is maximum of 0.92 eV for E⊥c and 0.50 eV for E||c. In nutshell, GaSe monolayer exhibit anisotropic optical response in UV-region which can be highly beneficial for developing polarized optical sensors. Our results demonstrate that GaSe monolayer can be utilized to fabricate reusable DNA sequencing devices for biotechnology and medical science.

Light-Induced Migration of Spin Defects in TiO2 Nanosystems and their Contribution to the H2 Evolution Catalysis from Water.

The photocatalytic activity for H2 production from water, without presence of hole scavengers, of thermally reduced TiO2 nanoparticles (H-500, H-700) and neat anatase were followed by in-situ continuous-wave light-induced electron paramagnetic resonance technique (CW-LEPR), in order to correlate the H2 evolution rates with the electronic fingerprints of the photoexcited systems. Under UV irradiation, photoexcited electrons moved from the deep lattice towards the superficially exposed Ti sites. These photogenerated redox sites mediated (e- +h+ ) recombination and were the crucial electronic factor affecting catalysis. In the best-performant system (H-500), a synergic combination of mobile electrons was observed, which dynamically created diverse types of Ti3+ sites, including interstitial Ti3+ , and singly ionized electrons trapped in oxygen vacancies (VO . ). The interplay of these species fed successfully surface exposed Ti4+ sites, which became a catalytically active, fast reacting Ti4+ ⇄Ti3+ state that was key for the H2 evolution process.

Microcontroller Fingerprinting Using Partially Erased NOR Flash Memory Cells

Electronic device fingerprints, unique bit vectors extracted from device's physical properties, are used to differentiate between instances of functionally identical devices. This article introduces a new technique that extracts fingerprints from unique properties of partially erased NOR flash memory cells in modern microcontrollers. NOR flash memories integrated in modern systems-on-a-chip typically hold firmware and read-only data, but they are increasingly in-system-programmable, allowing designers to erase and program them during normal operation. The proposed technique leverages partial erase operations of flash memory segments that bring them into the state that exposes physical properties of the flash memory cells through a digital interface. These properties reflect semiconductor process variations and defects that are unique to each microcontroller or a flash memory segment within a microcontroller. The article explores threshold voltage variation in NOR flash memory cells for generating fingerprints and describes an algorithm for extracting fingerprints. The experimental evaluation utilizing a family of commercial microcontrollers demonstrates that the proposed technique is cost-effective, robust, and resilient to changes in voltage and temperature as well as to aging effects.

Investigating a Fluorobenzene Based Single Electron Transistor As a Toxic Gas Sensor

A fluorobenzene based single electron transistor (SET) has been investigated for the detection of toxic gases viz. NH3, HCN, AsH3, and COCl2, within the framework of density functional theory (DFT) formalism based first-principles approach. Initially, the adsorption mechanism between the fluorobenzene quantum dot and the toxic gases (NH3, HCN, AsH3, and COCl2) has been analyzed in terms of adsorption energy, distance of adsorption, DOS profiles and the charge transfer analysis. Later, the exclusive property of charge stability diagram of SET has been utilized to provide the necessary electronic fingerprints for detection of toxic gases. The results suggest that the fluorobenzene SET can be a potential sensor for proposed toxic gases based on the wide operational temperature range and high detection ability as witnessed from the electronic fingerprints.

Novel green phosphorene sheets to detect tear gas molecules - A DFT insight

The green phosphorene (GP) nanosheet, one of the allotropes of layered phosphorene is employed to detect the existence of tear gas molecules. The tear gas molecules such as 1-bromo-2-butanone, bromoacetone, and bromobenzyl cyanide are examined with the service of the ATK-VNL package by employing density functional theory (DFT) method. The geometrical stability of the chief component is affirmed with the support of formation energy and electronic fingerprints of GP nanosheet like electron density, band structure, and projected density of states (PDOS) spectrum are estimated. In this research work, using DFT technique, for the first time, surface adsorption characteristics of the target molecules on GP nanosheet are explored with the assistance of adsorption energy, average energy gap variation, and Bader charge transfer, which further suggest the deployment of GP in sensing the presence of tear gas molecules.

Interaction properties of phenol and styrene from plastic fumes on β-Arsenene sheets: A first-principles study

The recognizing efficiency of β-Arsenene nanosheet (β-AsNS) towards the plastic fumes, such as phenol and styrene is assessed by adopting the DFT (Density Functional Theory) procedure. The cohesive formation energy of the commanding material, β-AsNS is assessed to be −1.538 eV per atom, which verifies the configurational durability of the base component. The electronic fingerprints of the isolated β-AsNS and carcinogenic toxicants’ (phenol and styrene) adsorbed β-AsNS like the electron difference density and energy band gap are ciphered. Furthermore, the interaction properties of the toxicants adsorbed β-AsNS, namely the Bader charge transfer, binding energy, and average energy gap variation are evaluated to ascertain the chemi-detecting capacity of β-AsNS towards the plastic fumes, phenol, and styrene.

DFT Outlook on Surface Adsorption Properties of Nitrobenzene on Novel Red Tricycle Arsenene Nanoring

The volatile organic compound, nitrobenzene (NB) is made to interact with the primary material, Red-Tricycle-Arsenene (red-T-As) nanoring at four global minima sites (bridge, hollow, valley and ring-sites) by employing density functional theory method. The structural sturdiness of the primary material is evidenced with the cohesive conformation energy of – 3.462 eV/atom. Furthermore, the electronic fingerprints of the pristine and NB surface-assimilated red-T-As nanoring like the energy-gap based Band-Structure and Projected Density of States (PDOS) spectrum along with electron difference density are reckoned. In addition, the adsorption features of NB on red-T-As nanoring, namely, the Bader charge transfer, binding energy, and average energy gap variation are determined. The ciphered attributes articulate the utility of red-tricycle-arsenene nanoring as an efficient chemi-resistor to detect nitrobenzene.

Silicon-Based Optoelectronic Tongue for Label-Free and Nonspecific Recognition of Vegetable Oils.

A special electronic tongue system based on photoelectric measurements on Si–Si/SiNX sensitive structures is reported. The sensing approach is based on measuring of minority carrier lifetime in silicon-based substrates using microwave-detected photoconductance decay. This inexpensive and environmentally friendly combinatorial electronic sensing platform is able to create characteristic electronic fingerprints of liquids, detect, and recognize them. In particular, an application of the optoelectronic tongue for recognition of vegetable oils and their mixtures is described.

Rapid and intelligent discrimination of Notopterygium incisum and Notopterygium franchetii by infrared spectroscopic fingerprints and electronic olfactory fingerprints.

This preliminary research evaluated mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy and electronic nose (E-nose) for the rapid identification of Notopterygium incisum and Notopterygium franchetii, which were both approved sources of Notopterygii Rhizoma et Radix (Chinese Pharmacopoeia, 2015) but possessed different chemical compositions and pharmacological activities. At the level of single variables, MIR showed quite a few discriminating peaks in the regions of 3000-2800cm-1 (the stretching bands of CH), 1770-1670cm-1 (the stretching bands of CO), and 1400-1200cm-1 (the bending bands of CH and the stretching bands of CO). Meanwhile, NIR only showed an intuitive discriminating peak near 4736cm-1 (the combination band of OH and CO stretching modes). E-nose response signals of N. incisum and N. franchetii were significant different (p<0.05) on four sensors, i.e., LY2/LG, LY2/GH, LY2/gCT and LY2/gCTI. Using the infrared spectra or E-nose sensor responses as fingerprints, support vector machine (SVM) models can provide good recognition accuracy (100% for MIR and NIR models, 92.9% for E-nose model). This research indicated the feasibility of MIR, NIR and E-nose for the accurate, rapid, cheap and green identification of N. incisum and N. franchetii, which was desirable to assure the authenticity, efficacy and safety of related herb materials and products.

Public Transport Occupancy Estimation using WLAN Probing and Mathematical Modeling

The rapid urbanization and consequent metropolization of cities are phenomena present in many countries around the World. This increment in urban population causes changes in personal relationships and in the physical structure of cities. Among the transformations caused by metropolization, the most noteworthy are the changes in urban mobility systems. In emerging countries, the problems generated by this situation are exacerbated, since the social, environmental and, mainly, economic characteristics make the solution of problems related to urban transportation very difficult. As consequences, it is common to have daily commutes happening mostly by road transport, absence of effective public policies and poor transport data acquisition. Common ways to achieve quality in public transportation systems are to estimate the public transport occupancy (PTO) rate and the origin-destination matrix for a given area. This paper presents a formulation and study for the use of a low cost and reduced computational complexity system, capable of counting in real time the amount of passengers inside a public transportation unit (bus or metro composition). This system performs passenger counting through users’ smartphones electronic fingerprints and uses a mathematical model to adjust the acquired raw values. The applicability of this approach is demonstrated through case studies carried out in 3 different bus lines in the city of Belo Horizonte, Brazil, as an alternative to collect field data for the management of public transportation. It is demonstrated that the suggested system presents good accuracy and is a reduced complexity alternative for the estimation of PTO in emerging countries.

Electronic structure and core electron fingerprints of caesium-based multi-alkali antimonides for ultra-bright electron sources

The development of novel photocathode materials for ultra-bright electron sources demands efficient and cost-effective strategies that provide insight and understanding of the intrinsic material properties given the constraints of growth and operational conditions. To address this question, we propose a viable way to establish correlations between calculated and measured data on core electronic states of Cs-K-Sb materials. To do so, we combine first-principles calculations based on all-electron density-functional theory on the three alkali antimonides Cs3Sb, Cs2KSb, and CsK2Sb with x-ray photoemission spectroscopy (XPS) on Cs-K-Sb photocathode samples. Within the GW approximation of many-body perturbation theory, we obtain quantitative predictions of the band gaps of these materials, which range from 0.57 eV in Cs2KSb to 1.62 eV in CsK2Sb and manifest direct or indirect character depending on the relative potassium content. Our theoretical electronic-structure analysis also reveals that the core states of these systems have binding energies that depend only on the atomic species and their crystallographic sites, with largest shifts of the order of 2 eV and 0.5 eV associated to K 2p and Sb 3d states, respectively. This information can be correlated to the maxima in the XPS survey spectra, where such peaks are clearly visible. In this way, core-level shifts can be used as fingerprints to identify specific compositions of Cs-K-Sb materials and their relation with the measured values of quantum efficiency. Our results represent the first step towards establishing a robust connection between the experimental preparation and characterization of photocathodes, the ab initio prediction of their electronic structure, and the modeling of emission and beam formation processes.

Origins versus fingerprints of the Jahn-Teller effect in d -electron ABX3 perovskites

The Jahn-Teller (JT) distortion that can remove electronic degeneracies in partially occupied states and results in systematic atomic displacements is a common underlying feature to many of the intriguing phenomena observed in 3d perovskites, encompassing magnetism, superconductivity, orbital ordering and colossal magnetoresistance. Although the seminal Jahn and Teller theorem has been postulated almost a century ago, the origins of this effect in perovskite materials are still debated, including propositions such as super exchange, spin-phonon coupling, sterically induced lattice distortions, and strong dynamical correlation effects. Here we analyze the driving forces behind the Jahn-Teller motions and associated electronic fingerprints in a full range of ABX3 compounds. We identify (i) compounds that are prone to an electronically-driven instabilities (i.e. a pure JT effect) such as KCrF3, KCuF3 or LaVO3 and proceed to relax the structures, finding quantitatively the JTD in excellent agreement with experiment; (ii) compounds such as LaMnO3 or LaTiO3 that do not show electronically driven JTD despite orbital degeneracies, because their strongly hybridized B, d-X, p states supply but too weak JT forces to overcome the needed atomic distortions; (iii) although LaVO3 exhibits similar B, d-X, p hybridizations as LaTiO3, the former compound exhibits a robust electronic instability while LaTiO3 has zero stabilization energy, the reason being that LaVO3 has two electrons t2g2 relative to LaTiO3 with just one t2g1. (iv) We explain the trends in "orbital ordering" whereby electrons occupy orbitals that point to orthogonal directions between all nearest-neighbor 3d atoms. We thereby provide a unified vision to explain octahedra deformations in perovskites that, at odds with common wisdom, does not require the celebrated Mott-Hubbard mechanism.

(Invited) Accelerated Materials Design and Discovery: Novel Approaches for Accelerating Synthesis, Characterization, and Screening of Materials

High-throughput computations have provided access to multiple properties of several inorganic materials. High-throughput experiments have enabled generation of materials properties under operating conditions. Both these approaches have accelerated discovery of materials. Further acceleration of materials discovery requires integration of these approaches that have different scopes and underlying assumptions. In this talk, I will present novel approaches based on network theory to predict synthesizability and hence reduce the "synthesis gap" between theory and experiments. Another significant gap between theory and experiment is the "characterization gap" which is due to the need for laborious characterization methods to capture an experimentally synthesized material's fingerprint. In this talk, I will present the use of machine learning methods to address this gap to capture structural, chemical, and electronic fingerprints of materials. High-throughput experiments have played a significant role in accessing high-dimensional chemical and screening space for materials discovery. However, practical implementations of high-throughput experimentation focuses on a specific region of the large chemical and screening space due to the exponential increase in number of experiments needed as dictated by the curse of dimensionality. I will present further acceleration of high-throughput experimentation by using machine learning approaches. Particularly, approaches that utilize information obtained from high-throughput computations will be discussed.

How Substitutional Point Defects in Two-Dimensional WS2 Induce Charge Localization, Spin–Orbit Splitting, and Strain

Control of impurity concentrations in semiconducting materials is essential to device technology. Because of their intrinsic confinement, the properties of two-dimensional semiconductors such as transition metal dichalcogenides (TMDs) are more sensitive to defects than traditional bulk materials. The technological adoption of TMDs is dependent on the mitigation of deleterious defects and guided incorporation of functional foreign atoms. The first step toward impurity control is the identification of defects and assessment of their electronic properties. Here, we present a comprehensive study of point defects in monolayer tungsten disulfide (WS2) grown by chemical vapor deposition using scanning tunneling microscopy/spectroscopy, CO-tip noncontact atomic force microscopy, Kelvin probe force spectroscopy, density functional theory, and tight-binding calculations. We observe four different substitutional defects: chromium (CrW) and molybdenum (MoW) at a tungsten site, oxygen at sulfur sites in both top and bottom layers (OS top/bottom), and two negatively charged defects (CD type I and CD type II). Their electronic fingerprints unambiguously corroborate the defect assignment and reveal the presence or absence of in-gap defect states. CrW forms three deep unoccupied defect states, two of which arise from spin-orbit splitting. The formation of such localized trap states for CrW differs from the MoW case and can be explained by their different d shell energetics and local strain, which we directly measured. Utilizing a tight-binding model the electronic spectra of the isolectronic substitutions OS and CrW are mimicked in the limit of a zero hopping term and infinite on-site energy at a S and W site, respectively. The abundant CDs are negatively charged, which leads to a significant band bending around the defect and a local increase of the contact potential difference. In addition, CD-rich domains larger than 100 nm are observed, causing a work function increase of 1.1 V. While most defects are electronically isolated, we also observed hybrid states formed between CrW dimers. The important role of charge localization, spin-orbit coupling, and strain for the formation of deep defect states observed at substitutional defects in WS2 as reported here will guide future efforts of targeted defect engineering and doping of TMDs.