Surface States Research Articles

Polaronic transport and magnetic field dependence of conduction parameters in rGO-CFO nanocomposites

Abstract In this paper we report the AC conductivity σ and magnetoconductivity Δσ of a series of reduced graphene oxide-cobalt ferrite (rGO-CFO) composites in which the mass ratio of rGO:CFO has been systematically varied over six compositions. The conductivity measured in the frequency range of 20 Hz to 3 MHz showed an anomalous increase with CFO content in the composite, even though the conductivity of CFO is at least three orders of magnitude smaller than that of rGO. Magnetoconductivity measured in fields upto 2000 Oe displayed both negative and positive values depending on the rGO:CFO ratio. Maximum magnetoconductivity of ∼ +14% was obtained at room temperature in a magnetic field of only 750 Oe. Samples having the largest σ and Δσ values also showed significant softening/hardening of the Raman active modes of CFO, indicating polaronic transport in these composites. Fits of σ(f) data to a power law σ(f) = σ o + Afn showed that parameters A and n depend strongly on the applied magnetic field. This dependence is qualitatively and quantitatively different for samples that display positive or negative magnetoconductivity. Although the temperature dependence of these conduction parameters has been extensively studied, we have not come across any reports of their magnetic field dependence. Based on these observations we present a surface polaron model in which hybridization of π-orbitals of graphene with surface states of CFO nanoparticles provides for a polaron conduction mechanism through a grid of CFO nanoparticles intercalated with rGO sheets.

Facile One-Pot Microwave-Assisted Synthesis and Ultrafast Spectroscopic Characterization of Nitrogen-Sulfur-Codoped Carbon Quantum Dots.

We report an eco-friendly, cost-effective, one-pot microwave-assisted synthesis of nitrogen and sulfur co-doped carbon quantum dots (N,S-CQDs) using citric acid and thiourea in formamide without surface passivation. The N,S-CQDs were characterized by HRTEM, FE-SEM, XRD, EDX, FTIR, Raman, and XPS, confirming monodispersed spherical particles of 4.8 nm with an amorphous carbon phase containing oxygen, nitrogen, and sulfur. The comprehensive photophysical studies of N,S-CQD employed by steady state and different time-resolved spectroscopic techniques (TCSPC, Ultrafast Time-Resolved Fluorescence Up-Conversion and Femtosecond Transient Absorption techniques). These N,S-CQDs show broad UV-visible to near-infrared absorption with peaks near 300 and 400 nm and emit strong blue photoluminescence at 360 nm excitation, with a quantum yield of ~8.4%. Time-resolved spectroscopy (TCSPC, fluorescence up-conversion, transient absorption) reveals multiexponential carrier relaxation with time constants from 0.5 ps to > 500 ps, including a 360 ps rise component and three distinct decay components, indicating complex fluorescence driven by surface defects. Ultrafast decay components correspond to thermal cooling of hot excitons, while later decays relate to carrier trapping at surface states. The tunable optical properties and carrier dynamics make N,S-CQDs promising for optoelectronic applications such as LEDs, sensors, and photodetectors, with further enhancement possible through surface engineering and defect control.

Enhancement of the photoelectrochemical performance of hematite by modulation of the surface states through the introduction of a ZnMgO functional layer

Enhancement of the photoelectrochemical performance of hematite by modulation of the surface states through the introduction of a ZnMgO functional layer

Optimizing surface states to elevate xylene gas sensing characteristics in ZnCo2O4 microspheres

Optimizing surface states to elevate xylene gas sensing characteristics in ZnCo2O4 microspheres

Magnetotransport and activation energy of the surface states in Cd3As2 thin films

Magnetotransport and activation energy of the surface states in Cd3As2 thin films

Heusler-based topological quantum catalyst Fe2VAl with obstructed surface states for the hydrogen-evolution reaction

Topological materials are widely esteemed for their surface metallic states and remarkable carrier mobility, making them effective catalysts for heterogeneous processes. This study showcases the outstanding properties of Fe2VAl, an experimentally prepared compound that enjoys a Cu2MnAl-type Heusler structure. It specifically highlights the presence of robust obstructed surface states on the (001) surface and the outstanding catalytic effectiveness of the compound in electrochemical hydrogen evolution processes (HER). The band structure calculation in this work shows that it is an obstructed atomic semimetal with a pseudo-gap of -0.088 eV (nearly -0.1 eV). These findings align with the previous optical conductivity measurements conducted at low temperatures, which also showed a similar pseudo-gap. This work suggests that the easily prepared Fe2VAl compound may be an excellent topological quantum material for topological catalysis.

Boosting CO2 Hydrogenation by Synergistic Incorporation of Pure Silica Silicalite‐1 Zeolite and CeO2 into Cu Catalysts

AbstractChemical conversion of CO2 is providing an opportunity to mitigate the global warming induced by the overconsumption of fossil fuel. Cu has been regarded as one of the most powerful contenders in catalyzing CO2 conversion, yet the precise manipulation of its surface state and the nearby chemical environment continues to pose a formidable challenge. In this work, we report a high‐efficiency catalyst by utilizing CeO2 and pure silicon zeolite (S1) to co‐activate Cu species. In CO2‐to‐methanol (CTM) conversion, the space‐time yield of methanol (STYMeOH) of the obtained CuCe/S1 catalysts reaches 87.23 g kgCu−1 h−1, which represents a fivefold increase compared to that of the Cu/CeO2 catalysts. The following mechanistic investigations reveal that S1 serves as a pivotal stabilizer for the small‐sized CeO2 particles, thereby significantly enhancing the synergistic interaction between Cu species and CeO2. The crafted interaface possesses abundant oxygen vacancies and a high content of Cu+, significantly enhancing the adsorption of CO2 and inhibiting the formation of CO. Our discovery presents a promising new direction for catalyst upgrading and performance enhancement for CTM processes in the foreseeable future.

Nonlinear Optical Bistability in a Bragg Reflector Multilayered Structure with MoS2

The special band structure of bilayer MoS2 makes it show strong nonlinear optical characteristics in the visible band, which provides a new way to develop visible nonlinear devices. In this paper, we present a theoretical analysis of the optical bistability (OB) in a silver–Bragg reflector structure by embedding bilayer MoS2 at the visible band. The nonlinear OB phenomenon is achieved due to the nonlinear conductivity of the bilayer MoS2 and the excitation of the optical Tamm state at the interface between the silver and the Bragg reflector. It is found that the hysteresis behavior and the threshold width of the OB can be effectively tuned by varying the incident light wavelength. In addition, the optical bistable behavior of the structure can be adjusted by varying the position of the MoS2 inset in the defect layer, the incident angle, and the structural parameters of the spacer layer. We believe the above results can provide a new paradigm for the construction of controllable bistable devices.

Polarization-Sensitive Solar-Blind Ultraviolet Photodetectors Based on Semipolar (112̅2) AlGaN Film.

Wide bandgap semiconductor AlGaN alloys have been identified as key materials to fabricate solar-blind ultraviolet photodetectors (SBUV PDs). Herein, a self-driven SBUV polarization-sensitive PD (PSPD) based on semipolar (112̅2)-oriented AlGaN films is reported. Using the flow-rate modulation epitaxy method, the full widths at half maximum (FWHMs) for the obtained (112̅2) AlGaN along [112̅3̅] and [11̅00] rocking curves are 0.205° and 0.262°, respectively, representing the best results for heteroepitaxial semipolar AlGaN so far. Density functional theory calculations and experimental results reveal that semipolar AlGaN possesses in-plane anisotropy. The self-driven (112̅2) AlGaN PSPDs exhibit strong polarization-sensitive photoresponse with a polarization ratio of 1.54 at 266 nm and rapid response of 450/450 ms compared to other low-dimensional semiconductor materials. More interestingly, we observe positive and negative photoresponse behaviors under UV light illumination due to surface states and charge transfer. Our results may enable potential applications in multifunctional SBUV optoelectronic devices.

Fermi arcs of topological surface states and Lifshitz transitions in multi-Weyl semimetals

Fermi arcs of topological surface states and Lifshitz transitions in multi-Weyl semimetals

Benchmarking passive-microwave-satellite-derived freeze–thaw datasets

Abstract. Satellite-derived soil surface state has been identified to be of added value for a wide range of applications. Frozen versus unfrozen conditions are operationally mostly derived using passive microwave (PMW) measurements from various sensors and different frequencies. Products differ thematically, as well as in terms of spatial and temporal characteristics. All of them offer only comparably coarse spatial resolutions on the order of several kilometers to tens of kilometers, which limits their applicability. Quality assessment is usually limited to comparisons with in situ point records, but a regional benchmarking dataset is, thus far, missing. Synthetic aperture radar (SAR) offers high spatial detail and, thus, is potentially suitable for assessment of the operational products. Specifically, dual-polarized C-band data acquired by Sentinel-1, operating in interferometric wide (IW) swath mode with a ground resolution of 5 m×20 m in range and azimuth, provide dense time series in some regions and are therefore a suitable basis for benchmarking. We developed a robust freeze–thaw (FT) detection approach that is suitable for tundra regions, applying a constant threshold to the combined C-band VV (vertically sent and received) and VH (vertically sent and horizontally received) polarization ratios. The achieved performance (91.8 %) is similar to previous methods which apply an empirical local threshold to single-polarized VV backscatter data. All global products, tested with the resulting benchmarking dataset, are of value for freeze–thaw retrieval, although differences were found depending on the season, particularly during the spring and autumn transition. Fusion can improve the representation of thaw and freeze-up, but a multi-purpose applicability cannot be obtained since the transition periods are not fully captured by any of the operational coarse-resolution products.

Disorder-induced instability of a Weyl nodal loop semimetal towards a diffusive topological metal with protected multifractal surface states

Disorder-induced instability of a Weyl nodal loop semimetal towards a diffusive topological metal with protected multifractal surface states

Insight into Charge Transport Behaviors in Hematite Photoanodes via Potential-Dependent Impedance Spectroscopy and Machine Learning.

We employed machine learning (ML) techniques combined with potential-dependent photoelectrochemical impedance spectroscopy (pot-PEIS) to gain deeper insights into the charge transport mechanisms of hematite (α-Fe2O3) photoanodes. By the Shapley Additive exPlanations (SHAP) analysis from the ML model constructed from a small data set (dozens of samples) of electrical parameters obtained from pot-PEIS and the PEC performance, we identified the dominant factors influencing the electron transport to the back contact in the bulk and hole transfer to a solution at the hematite/electrolyte interface. The results revealed that shallow defect states significantly enhance electron transport, while deep defect states impede it, and also one of the surface states enhances the hole transfer to the electrolyte solution. The incorporation of a titanium dioxide underlayer had an effect to increase shallow defect states to promote electron transport and induce a new surface state to promote hole transfer. Cobalt phosphate cocatalyst improved charge separation, leading to enhance electron transport in the bulk, and the cocatalyst surface state promotes the hole transfer at the interface. The understanding of the band diagram based on the selected dominant descriptors provided critical insights into the electronic structure, elucidating the role of defect states and surface states in influencing the overall photoanode performance. This study showcases the potential of combining ML and pot-PEIS for material optimization.

Exploring Surface State and Exciplex Dominated Aggregation Induced Electrochemiluminescence of Graphene Quantum Dots Prepared Via Electrochemical Exfoliation.

Graphene quantum dots (GQDs) have emerged as promising materials for electrochemiluminescence (ECL) applications due to their unique optical and electronic properties. In this study, GQDs were synthesized via electrochemical exfoliation of graphite in a constant current density mode, enabling scalable production with controlled size and surface functionalization. GQDs-4 and GQDs-20, synthesized at applied current densities of 4 mA/cm2 and 20 mA/cm2 to the graphite electrode, respectively, were investigated on roles of surface states and exciplex dominated aggregation-induced emission (AIE) in their ECL performance. GQDs-4 revealed an absolute ECL quantum efficiency of up to 0.0012%. GQDs-20, with a smaller particle size, achieved an absolute ECL quantum efficiency of up to 0.03%, demonstrating high efficiency in converting electrons into photons. While GQDs-4 exhibited minor intensity in PL and ECL, they displayed a similar emission spectrum to GQDs-20 in the ECL process. This finding highlights the significant role of surface states and AIE in influencing the emission properties of GQDs, independent from core-state transitions. These results provide critical insights into the mechanisms governing GQD-based ECL and offer pathways for optimizing these materials for use in biosensing, optoelectronics, and imaging applications.

Normal-incidence mid-infrared photodetection via intraband transitions in InGaAs/InP multiple quantum well nanowire arrays

Recently, InGaAs/InP multiple quantum well nanowires grown by selective area epitaxy have been demonstrated with uniform morphology and high optical quality. The InGaAs quantum wells wrapping around the nanowire core are formed with both axial and radial components. As such the radial quantum well configuration presents a unique advantage for the realization of intraband absorption of normal-incidence light in the nanowires, which cannot be achieved in conventional planar quantum well structures due to polarization selection rules. We report here mid-infrared intraband transitions within the atmospheric window (3–5 μm) in InP nanowire arrays embedded with five InGaAs quantum wells under normal-incidence light. The light absorption coefficient of the quantum wells is modeled, and the absorption peak indicates a bound-to-continuum transition. The intraband photocurrent shows a linear dependence on the incident power, while the interband photoresponse is sublinear due to the surface states of the nanowires. These nanowires with radial quantum wells open up great opportunities for developing next-generation mid- to long-wavelength infrared photodetectors and focal plane arrays.

Cryogenic in-memory computing using magnetic topological insulators.

Machine learning algorithms have proven to be effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementation of these algorithms at cryogenic temperatures is essential. Here we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a cryogenic in-memory computing scheme based on the coexistence of a chiral edge state and a topological surface state. The memristive switching and reading of the giant anomalous Hall effect exhibit high energy efficiency, high stability and low stochasticity. We achieve high accuracy in a proof-of-concept classification task using four magnetic topological memristors. Furthermore, our algorithm-level and circuit-level simulations of large-scale neural networks demonstrate software-level accuracy and lower energy consumption for image recognition and quantum state preparation compared with existing magnetic memristor and complementary metal-oxide-semiconductor technologies. Our results not only showcase a new application of chiral edge states but also may inspire further topological quantum-physics-based novel computing schemes.

Epitaxial Growth of Bi2Se3 Thin Films by Thermal Evaporation for the Application of Electrochemical Biosensors

Bi2Se3 is a typical topological material with the gapless surface state, which has many potential applications. In this work, high‐quality Bi2Se3 thin films are prepared by co‐evaporating bismuth and selenium on (100) silicon substrate, followed by in‐situ annealing process. The key parameters are optimized, including growth temperature and the flux ratio of Bi and Se. The crystal orientation and quality of the thin films are characterized by X‐ray diffraction, Raman spectroscopy, X‐ray photoelectron spectroscopy, and atomic force microscopy. Furthermore, Bi2Se3 thin films are employed as the working electrode of the biosensor, and their sensitive detection of SARS‐CoV‐2 characteristic gene fragments in the COVID‐19 epidemic is investigated. The cyclic voltammetry, square wave voltammetry, and electrochemical impedance spectroscopy demonstrate that the DNA biosensor is successfully constructed based on Bi2Se3 thin films. This study develops a method of the large‐scale homogeneous Bi2Se3 thin films growth by thermal evaporation technology, which has great application potential in electrochemical biosensors.

Enhancement Mechanism of Photo-Induced Artificial Boundary on Ultrastable Hybrid Solid-electrolyte Interphase of Si Anodes.

Unstable solid-electrolyte interphase (SEI) film resulting from chemically active surface state and huge volume fluctuation limits the development of Si-based anode materials in lithium-ion batteries. Herein, a photo-initiated polypyrrole (PPy) coating is manufactured on Si nanoparticles to guide the in situ generation of PPy-integrated hybrid SEI film (hSEI). The hSEI film shows excellent structure stability and optimized component composition for lithium storage. More promisingly, the photo-initiated hSEI precursor with more uniform thickness, stronger interaction with inner particles, and higher mechanical strength further enables the structural integrity of the hSEI film. The highly ordered interchain structure of photo-initiated hSEI precursor can maintain effective Li+ transport during the electrochemical cycling. Consequently, SiNPs@hSEI-L anode maintains a reversible capacity of 1044.7 mAh g-1 after 500 cycles at 2 A g-1, manifesting superior electrochemical lithium storage. This work proposes a novel polymer-integrated hSEI formation and provides an effective reference for the optimization of semiconductor materials.

Improved streamflow simulations in hydrologically diverse basins using physically informed deep learning models

Physically informed deep learning models, especially Long Short-Term Memory (LSTM) networks, have shown promise in large-scale streamflow simulations. However, an in-depth understanding of the relative contribution of physical information in deep learning models has been missing. Using a large-sample testbed of 220 catchments in hydrologically diverse regions of the Indian subcontinent, we quantify the impact of incremental addition of physical information on model performance using multiple variants of the LSTM model based on various combinations of static catchment attributes and simulated land surface states. We found that LSTM models trained with catchment geophysics as additional input outperformed the base LSTM model in terms of the nationwide median Kling-Gupta Efficiency (KGE) of in-sample catchments, increasing KGE from 0.32 to 0.60. Additionally, the model retained significant prediction skill in out-of-sample catchments, demonstrating that a pre-trained LSTM model can be a powerful tool to predict streamflow in data-scarce regions.

Boosting CO2 Hydrogenation by Synergistic Incorporation of Pure Silica Silicalite-1 Zeolite and CeO2 into Cu Catalysts.

Chemical conversion of CO2 is providing an opportunity to mitigate the global warming induced by the overconsumption of fossil fuel. Cu has been regarded as one of the most powerful contenders in catalyzing CO2 conversion, yet the precise manipulation of its surface state and the nearby chemical environment continues to pose a formidable challenge. In this work, we report a high-efficiency catalyst by utilizing CeO2 and pure silicon zeolite (S1) to co-activate Cu species. In CO2-to-methanol (CTM) conversion, the space-time yield of methanol (STYMeOH) of the obtained CuCe/S1 catalysts reaches 87.23 g kgCu -1 h-1, which represents a fivefold increase compared to that of the Cu/CeO2 catalysts. The following mechanistic investigations reveal that S1 serves as a pivotal stabilizer for the small-sized CeO2 particles, thereby significantly enhancing the synergistic interaction between Cu species and CeO2. The crafted interaface possesses abundant oxygen vacancies and a high content of Cu+, significantly enhancing the adsorption of CO2 and inhibiting the formation of CO. Our discovery presents a promising new direction for catalyst upgrading and performance enhancement for CTM processes in the foreseeable future.