Band Parameters Research Articles

Electronic properties of MAPbxSn1−xI3 hybrid perovskite alloys: k.p modeling for tetragonal crystal symmetry with C4v point group

MAPb x Sn 1 − x I 3 alloys are highly promising for photovoltaic, optoelectronic, and spintronics applications. Using k.p calculations, we derived the fundamental band parameters of these tetragonal hybrid halide perovskites as a function of Pb content (x). Our study focuses on the experimentally confirmed C4v point group structures: P4mm for Sn-rich alloys and I4cm for Pb-rich alloys. Our theoretical model successfully reproduces the non-monotonic behavior of the bandgap and provides detailed insights into the electron, hole, and reduced exciton masses (me, mh, and μ). We find that hole masses are slightly larger than electron masses, with both increasing linearly as x rises. At the structural transition (x=0.5) between P4mm and I4cm, we observe a discontinuity in hole masses and a steeper linear increase in Pb-rich structures. The calculated exciton masses show excellent agreement with experimental data across a wide range of alloy compositions. Additionally, we predict the Landé g-factors for charge carriers (ge, gh) and excitons (gX). For Pb-rich alloys, ge increases with decreasing bandgap energy, while for Sn-rich alloys, ge decreases. Exciton g-factors gX are predominantly governed by the large positive ge values, as the smaller negative gh values provide minimal compensation. Consequently, gX is not constant but varies with the bandgap, ranging from 2.4 and 4.8 for Pb-rich alloys and from 4.8 and 3.7 for Sn-rich alloys. These results highlight the tunable electronic and spin properties of MAPbxSn1−xI3 alloys, positioning them as versatile candidates for next-generation device applications.

Enhancement of High-Temperature Thermoelectric Properties in Pd-decorated Bi-Sb-Te System

Bismuth antimony telluride (Bi-Sb-Te)-based alloys remain the dominant choice for near-roomtemperature thermoelectric cooling applications. One of the most studied approaches to improve the thermoelectric performance of Bi-Sb-Te alloys has been a nanostructuring strategy, to suppress the lattice thermal conductivity. This study investigates the impact of incorporating reduced pyrolyzed Pd acetate within a Bi0.5Sb1.5Te3 matrix, building upon recent advancements in nanostructured Bi-Sb-Te alloys. While Pd acetate addition lowers the thermoelectric figure-of-merit (zT) at low temperatures, due to a corresponding increase in carrier concentration, it significantly enhances zT at higher temperatures. Notably, at 473 K, the addition of 0.02 wt.% Pd acetate increased zT by 32% (from 0.41 to 0.54) compared to the pristine sample. Above 423 K, the average zT improved by approximately 21% (from 0.44 to 0.53) in the 0.02 wt.% Pd acetate sample, primarily due to reduced bipolar conduction. Effective Mass (EM) modeling was employed to analyze band parameters. With the addition of Pd acetate, the density-of-states effective mass (md*) generally increased, while non-degenerate mobility (µ0) decreased. At 473 K, the thermoelectric quality factor increased by 42% (from 0.125 to 0.177) with 0.02 wt.% Pd acetate addition, indicating an improved theoretical maximum zT. These findings demonstrate the potential of incorporating Pd acetate for enhancing high-temperature thermoelectric performance in Bi0.5Sb1.5Te3.

A CNN-based Fault Diagnosis Method of Multi-function Integrated RF System using Frequency Domain Scanning with Lasso Regression

Multi-function Integrated RF System (MIRFS) is a key unit for improving the reliability and safety of advanced aircraft. Single-frequency point data are easily affected by various interferences and noises resulting in unreliable and insufficient information. To reduce the low fault diagnosis rate caused by this effect, a novel fault diagnosis method is proposed based on frequency domain scanning and Lasso regression in this paper. Firstly, performance parameter sequences under each fault condition are extracted using frequency domain scanning. By extracting the performance parameters of a specific frequency band as raw fault data, the reliability of the data is greatly increased. Secondly, Lasso regression prioritizes the performance parameter sequences according to their correlation with faults. This approach selects the optimal performance parameter sequences as the data source for fault diagnosis, resolving the issue of excessively high dimensions in fault data. Finally, convolutional neural networks (CNNs) achieve precise fault diagnosis for both soft and hard faults. The results confirm that the proposed method overcomes the low distinguishability of fault states for both single frequency point data and sequence feature data. Compared with diagnostic models using sequence feature data as datasets, the diagnostic accuracy for hard faults increased by 7.92%, and for soft faults by 5.34%.

Improve unsupervised Learning-based landslides detection by band ratio processing of RGB optical images: a case study on rainfall-induced landslide clusters

Automatic detection of the heavy rainfall-induced landslide clusters based on optical remote sensing images had low accuracy due to the interference of many features. This work proposes a method to improve the accuracy of landslide identification based on change detection of pre- and post-disaster satellite images. Firstly, by band ratio preprocessing, the interference features on landslide detection are eliminated. Then, by further optimizing the relevant parameters, the threshold-based Image Difference and Principal Component Analysis-based K-means unsupervised learning classification methods are used to perform change detection and landslide cluster identification. Finally, the causes of missing and errors in landslide detection by using the two methods are analyzed and discussed. The results show that band preprocessing of remote sensing images can significantly weaken the interference features of human activities on landslide detection. The verification metrics of the two methods for detecting landslides, except for a slight decrease in precision, recall, F1-score and Kappa values have all increased significantly. After band ratio preprocessing and parameters optimization, both change detection methods have significantly improved the performance of the rainfall-induced landslide clusters detection, with effects close to those of deep learning methods. These findings can provide a reference for landslide detection using optical remote-sensing images.

To the Theory of Intraband Single-Photon Absorption of Light in Semiconductors with Zinc-Blende Structure

A theoretical analysis of the frequency-temperature dependence of the coefficient of single-photon absorption of polarized radiation in narrow- and wide-bandgap semiconductors has been conducted, considering intraband optical transitions and the temperature dependence of band parameters. It has been shown that with a fixed frequency, the single-photon absorption coefficient initially increases with temperature, reaches a maximum, and then decreases. The maximum value shifts towards lower frequencies for both narrow- and wide-bandgap semiconductors when considering the temperature dependence of the bandgap width and the effective mass of holes. It was determined that in semiconductors with a zinc-blende lattice structure, the consideration of the temperature dependence of the band parameters leads to a decrease in the amplitude value of the frequency and temperature dependence of the single-photon absorption coefficient. As the temperature increases, the absorption threshold decreases, which is noticeably observed when taking into account the Passler formula. Each type of optical transition contributes differently to the frequency, temperature, and polarization dependencies of K(1)SO,lh(ω,T).

Enhanced Thermoelectric Properties of Fe1-xCoxSe2: Impact of Phase Transition and Point Defects

This study investigates the thermoelectric properties of Fe1-xCoxSe2 (x = 0, 0.25, 0.5, 0.75, and 1) alloys using theoretical modeling approaches. The Single Parabolic Band (SPB) model was employed to calculate band parameters such as density-of-states effective mass (md*), non-degenerate mobility (μ0), weighted mobility (μw), and B-factor. As the alloying content (x) increased, the B-factor improved, leading to higher predicted maximum zT values. For CoSe2 (x = 1), optimizing the carrier concentration to ~1.3 × 1019 cm-3 can potentially enhance zT to ~0.64, a 21-fold increase over the experimental value (~0.03). The Callaway-von Baeyer (CvB) model was used to analyze thermal transport properties, revealing that the increased x strengthens phonon scattering by point defects, resulting in a continuous decrease in lattice thermal conductivity (k1). Specifically, a phase transition from orthorhombic to cubic structure occurs as x increases, with a mixed phase observed at x = 0.75 and a complete transition to cubic at x = 1. This structural change significantly impacts both electronic and phonon band structures, leading to a dramatic increase in the B-factor and a substantial reduction in k1 for x > 0.75. These findings suggest that CoSe2 alloying, coupled with the induced phase transition, can significantly improve the thermoelectric performance of FeSe2-CoSe2 alloys.

Numerical analysis and optimization of photovoltaic performance of Sb2Se3 based photocathode

Antimony selenide (Sb2Se3) based heterojunction photocathodes have recently received an increased attention, largely due to their outstanding performances for hydrogen production through photoelectrochemistry (PEC) water splitting. The PEC water splitting process encompasses both physical and electrochemical processes. The physical process is capable of generating a photo-voltage, which can drive the photo-generated electrons transport to the electrode/electrolyte interface through the p-n junction. However, unlike traditional photovoltaic device, the protective layer and co-catalyst will also affect the electrical performance of device, resulting in a decrease in PEC performances and stability. How to optimize the electrical properties of the photoelectrode is a concern. In this work, devoted to Sb2Se3/TiO2 photocathode structures, the photovoltaic performances of a photocathode were modeled and analyzed from three aspects: p-n junction, back contact, and transition layer between TiO2 and co-catalyst, using the SCAPS-1D software and a realistic set of material parameters. Based on reported optimization strategy, tthe interface electrical characteristics of photocathode were studied by adjusting energy band, donor/acceptor density, defect density, electron affinity, and other parameters. A low-cost and easy to implement optimization strategy was proposed, which used Cd1-xZnxS as the buffer layer between p-n junctions, W-doped TiO2 as the transition between TiO2/co-catalyst, and Sn-doped Sb2Se3 as the back surface layer to suppress the carrier recombination. The optimized photocathode can theoretically obtain photoelectric conversion efficiency of 17.01%–17.14% and a maximum Jsc of 38.79 mA/cm2, exhibiting the potential to obtain a large photocurrent in the photoelectrochemical water splitting process.

Unveiling Frequency-Specific Microstate Correlates of Anxiety and Depression Symptoms.

Electroencephalography (EEG) microstates are canonical voltage topographies that reflect the temporal dynamics of brain networks on a millisecond time scale. Abnormalities in broadband microstate parameters have been observed in subjects with psychiatric symptoms, indicating their potential as clinical biomarkers. Considering distinct information provided by specific frequency bands of EEG, we hypothesized that microstates in decomposed frequency bands could provide a more detailed depiction of the underlying neuropathological mechanism. In this study, with a large open access resting-state dataset (n = 203), we examined the properties of frequency-specific microstates and their relationship with anxiety and depression symptoms. We conducted clustering on EEG topographies in decomposed frequency bands (delta, theta, alpha and beta), and determined the number of clusters with a meta-criterion. Microstate parameters, including global explained variance (GEV), duration, coverage, occurrence and transition probability, were calculated for eyes-open and eyes-closed states, respectively. Their ability to predict the severity of depression and anxiety symptoms were systematically identified by correlation, regression and classification analyses. Distinct microstate patterns were observed across different frequency bands. Microstate parameters in the alpha band held the best predictive power for emotional symptoms. Microstates B (GEV, coverage) and parieto-central maximum microstate E (coverage, occurrence, transitions from B to E) in the alpha band exhibited significant correlations with depression and anxiety, respectively. Microstate parameters of the alpha band achieved predictive R-square of 0.100 for anxiety scores, which is much higher than those of broadband (R-square = -0.026, p < 0.01). Similar results were found in classification of participants with high and low anxiety symptom scores (68% accuracy in alpha vs. 52% in broadband). These results suggested the value of frequency-specific microstates in predicting emotional symptoms.

Grain Size Effects on Visible and Near-infrared (0.35–2.5 μm) Laboratory Spectra of Rare Meteorite Classes

Linking near-Earth asteroids to associated meteorites can be a challenging process for many reasons, one being grain size differences. To address this issue for rarer meteorites, we studied visible and near-infrared (0.35–2.5 μm) reflectance spectra of 11 rare meteorite classes over five different grain size bins (45–90 μm, 90–150 μm, 150–300 μm, 300–500 μm, and 500–1000 μm). We analyzed the reflectance properties, diagnostic spectral band parameters (band centers and band area ratios), spectral slope, and taxonomic classification. The spectra were analyzed using principal component analysis to detect trends in principal component (PC) space and the impact on asteroid taxonomic classification in the Bus–DeMeo system. We found that the absolute reflectance (visual albedo) at 0.55 μm (photometric V band) typically decreases with increasing grain size, although there are some variations such as sharp increases for the slabs. Our EH4 and aubrite show a trend of increasing spectral slope with decreasing grain size. Our ureilite, angrite, winonaite, acapculoite, and mesosiderite show a general trend of a decrease in Band I (∼0.9 μm) depth with increasing grain size up to 500–1000 μm. Taxonomic classification of spectra of all grain sizes shows that classification tools generally struggle to differentiate grain size effects from mineralogical variations. This research demonstrates the need for a more robust taxonomic classification system that accounts for grain size and one that accurately classifies small near-Earth asteroids with regolith-free surfaces.

Effect of the electronic properties of the side charges of neutral solvent molecules on the charges of the N and H atoms of the carbazole molecule: IR experiment and DFT calculations

The IR spectral parameters of the absorption band of the valence vibration of the NH bond of the carbazole molecule in several neutral solvents (n-hexane C6H14, carbon tetrachloride CCl4, chloroform CHCl3, benzene C6H6) have been measured. It has been experimentally established that the position of the maximum of the NH vibrational band of the carbazole molecule in solvents undergoes a low-frequency shift relative to the gas phase. This shift increases in the series C6H14, CCl4, CHCl3, C6H6. The change in the magnitude of the linear shift is well described by the Kirkwood-Bauer-Magat KBM ratio in C6H14, CCl4, CHCl3. The presence of a linear shift may indicate that only universal interactions take place. The deviation of this ratio of shift magnitude for carbazole in benzene is interpreted as a manifestation of intermolecular complexation. Quantum-chemical calculations of the position of the absorption band position of the valence vibration of the NH bond of the carbazole molecule in these solvents, carried out by the electron density functional method B3LYP/6-311++G (d,r) using the Gaussian 09W program package, also showed a low-frequency shift relative to the gas phase.It was found that for the carbazole molecule in the condensed phase relative to the gas phase the following effects of changing the magnitude of charges on atoms N13 and H14 take place: 1 – increase in the positive sign of the charge on both atoms; 2 – the change in charge magnitude is larger on the nitrogen atom than on the hydrogen atom for both solvents (whose molecules have a dipole moment ∼0: C6H14, CCl4); 3 – the chlorine containing environment has a greater effect on the charge change in the carbazole molecule than the proton containing environment (whose molecules have a dipole moment ∼0: C6H14, CCl4).The correlation between the change of charges on atoms N13 and H14 with the value of electronegativity ξ of the side solvent atoms was established.Thus, it is shown that the charges on the 13N and 14H atoms of the carbazole molecule undergo changes in the presence of universal interactions, and the magnitude of the charge change depends on the electronic properties of the side atoms of the nearest solvent molecules. A hypothesis is proposed to explain the different frequency shift of the NH vibrational frequency of the molecule for chlorine-containing and hydrogen-containing side atoms of neutral solvent molecules, which takes into account different values of ξ for nitrogen and hydrogen atoms.

Machine learning for locally periodic structure transmission modelling

This research aims to obtain an analytical transmission model for locally periodic structures with the approach of data-driven physics. So far, this task has been done mainly numerically for non-trivial geometries. From a dataset of Bloch phases generated for given frequency band and structure geometry parameters, it is possible to learn equations relating dispersion relation to axis-symmetric geometry. The dataset is transformed into a lower-dimensional space by applying Principal Component Analysis (PCA) to reduce the complexity of the problem. In the newly obtained coordinate system, the lower-dimensional patterns are extracted via symbolic regression. The resulting model is interpretable in terms of underlying physics and can be used, e.g., to propose an optimized design for a desired band gap width. Note that this has been so far possible only with numerical optimization repeatedly going back and forth from geometry to the dispersion relation, and hence, it significantly contributes to the overall readability of the system features.

Calculation of Curie Temperature and Carriers Effective Masses of (Ga, Mn)As Diluted Magnetic Semiconductor from the Eight-Band k.p Model

An important step toward the development of spintronic information processing, transfer, and storage devices is the discovery of a dilute magnetic semiconductor (DMS) that demonstrates carrier-mediated ferromagnetism and maintains its magnetic properties above room temperature. Despite considerable progress made in recent decades, the maximum Curie temperature (∼200 K) remains well below room temperature. Mndoped GaAs are among the various diluted magnetic semiconductor materials that have been studied and have emerged as one of the most promising contenders for technological usage. The key characteristic of GaMnAs is its ferromagnetic properties, which are critical for spintronic devices. The primary goal of this work is to compute two critical properties of GaMnAs: the effective masses and the Curie temperature. The 8-band k.p model put forth by Kane was utilized to compile the GaMnAs band parameters using a MATLAB program. Our calculations are based on Lowdin perturbation theory, where spin-orbit, sp-d exchange interaction, and biaxial strain are taken into account. We calculated the Curie temperature of the GaMnAs alloy, within the mean-field approach based on the Zener model. Our findings demonstrated a direct proportionality relationship between the Curie temperature and the hole concentration (p) in GaMnAs. Moreover, we looked into how the Mn content and strain affected the effective masses of electrons, heavy, and light holes that were calculated for various crystallographic directions in GaMnAs. The effective masses that were calculated were highly dependent on the Mn content, which ranged from 1% to 5%, and the strain, which varied from −2% (tensile strain) to 2% (compressive strain).

Excavating oxygen vacancies in BaZrO3 to boost photocatalysis via screening vantage crystal planes

Investigations into the design and advancement of oxygen vacancies (OVs) are at the forefront of high-efficiency catalyst research. However, the lack of experimental evidence and a comprehensive mechanistic understanding regarding the promotion of OVs poses challenges. Herein, we investigate the role of crystal planes in elucidating the mechanism of OVs formation and their impact on photocatalytic hydrogen evolution. Initially, the Vienna ab-initio simulation package was utilized to calculate the key characteristics and band parameters of BaZrO3, subsequently, the screening crystal planes of (110) was synthesized. Experimental findings indicated that the (110) crystal plane increased the OVs rate from 32 % to 56 %, consequently improving photocatalytic hydrogen evolution performance from 13.1 to 20.5 mmol·g−1·h−1. Furthermore, theoretical calculations were employed to delve into both OVs formation mechanisms and catalytic activity. This study presents an innovative approach for strategically modifying catalyst OVs for efficient and high-performance photocatalytic applications.

Optimizing the moving average trade rule for cryptocurrencies: implications of band size and transaction costs

ABSTRACT In this paper, we apply an adjustable-band moving average algorithm to study technical analysis profitability in cryptocurrency markets. We find three main results. First, adjustable band trade rules act like a leveraged bet: they outperform fixed band rules in years when technical analysis is profitable and under-perform in other years. Second, our algorithm suggests significantly higher than standard 0% and 1% optimal band parameter values. Third, by comparing adjustable band rules with higher fixed band rules, we show that adjustable band rules have value beyond finding high optimal bands. Technical traders should consider higher and adjustable-band rules, especially with above-zero transaction costs.

Creep damage assessment of HR3C austenitic steel by using misorientation parameters derived from EBSD technique

The evaluation ability of misorientation parameters and Kikuchi band parameters on creep damage of HR3C austenitic steel is reported in this paper. HR3C steel samples were subjected to the creep process for 475, 756, 1240, and 1300 h, respectively. During the creep process, the average kernel average misorientation (KAM) and grain reference orientation deviation (GROD) increased significantly overall as the creep time increased, while the average mean angle deviation (MAD) and band contrast (BC) did not show significant changes. When comparing GROD and KAM, it was found that the variation range of GROD is larger and the variation trend is monotonous, making GROD more suitable for evaluating the creep damage of HR3C steel. Subsequently, the physical mechanism of GROD is derived and studied.

Estimation of Maximum &lt;i&gt;zT&lt;/i&gt; in Cu&lt;sub&gt;3&lt;/sub&gt;SbSe&lt;sub&gt;4&lt;/sub&gt; for Different Starting Materials Content

Cu&lt;sub&gt;3&lt;/sub&gt;SbSe&lt;sub&gt;4&lt;/sub&gt; is considered a promising thermoelectric material because of its large effective mass and low thermal conductivity, originating from its unique lattice structure. However, Cu&lt;sub&gt;3&lt;/sub&gt;SbSe&lt;sub&gt;4&lt;/sub&gt; has intrinsically low carrier concentration and relatively high electric resistance which limit performance. Recently, a &lt;i&gt;zT&lt;/i&gt; improvement in Cu&lt;sub&gt;3&lt;/sub&gt;SbSe&lt;sub&gt;4&lt;/sub&gt; was reported where doping/precipitation is controlled by changing the content of the starting materials. However, the effect of these changes in starting content on electronic band structures has not been studied. Here, we investigate how the change in starting materials content (&lt;i&gt;x&lt;/i&gt; varying from 6 to 20) affects band parameters like density-of-states effective mass (&lt;i&gt;m&lt;sub&gt;d&lt;/sub&gt;&lt;/i&gt; *), non-degenerate mobility (&lt;i&gt;μ&lt;sub&gt;0&lt;/sub&gt;&lt;/i&gt;), weighted mobility (&lt;i&gt;μ&lt;sub&gt;W&lt;/sub&gt;&lt;/i&gt;), and B-factor using the Single Parabolic Band (SPB) model. For &lt;i&gt;x&lt;/i&gt; greater than 8, precipitation of the secondary phase (CuSe) was observed, and the band parameters changed differently for &lt;i&gt;x&lt;/i&gt; greater than 8. The &lt;i&gt;m&lt;sub&gt;d&lt;/sub&gt;&lt;/i&gt; * increases up to &lt;i&gt;x&lt;/i&gt; = 8 and then rapidly decreases for &lt;i&gt;x&lt;/i&gt; &gt; 8. For &lt;i&gt;μ&lt;sub&gt;0&lt;/sub&gt;&lt;/i&gt;, an overall decrease is observed for increasing &lt;i&gt;x&lt;/i&gt;, but the rate of decrease is suppressed for &lt;i&gt;x&lt;/i&gt; &gt; 8. The &lt;i&gt;μ&lt;sub&gt;W&lt;/sub&gt;&lt;/i&gt; reaches the maximum at &lt;i&gt;x&lt;/i&gt; = 8. As &lt;i&gt;x&lt;/i&gt; increases, the experimental lattice thermal conductivity also increases, especially for &lt;i&gt;x&lt;/i&gt; &gt; 8. Therefore, the B-factor, which is directly related to the theoretical maximum zT, becomes maximum at = 8. Hence the SPB model predicts a maximum &lt;i&gt;zT&lt;/i&gt; of 0.0484 for &lt;i&gt;x&lt;/i&gt; = 8 at 300 K, which is 15.5% higher than the experimental &lt;i&gt;zT&lt;/i&gt; of 0.0419, which can be achieved by tuning the Hall carrier concentration to 4.44 × 10&lt;sup&gt;19&lt;/sup&gt; cm&lt;sup&gt;-3&lt;/sup&gt;.

Gradient Doping Enables an Extraordinary Efficiency in Thermoelectric PbTe1-xIx.

The conversion efficiency of thermoelectric generators that have to be operated under a temperature difference (ΔT) is mainly determined by material's dimensionless figure of merit (zT). However, maximization of zT at each temperature requires an optimization of carrier concentration (nopt) which strongly depends on the temperature and band parameters. Commonly utilized strategy of chemical doping usually enables a homogeneous carrier concentration throughout the material, leading the maximal zT to be achievable only within a narrow temperature range. In this work, a gradiently doping is successfully realized in PbTe1-xIx using a vertical gradient solidification technique, enabling a spatial gradient in carrier concentration that correspondingly optimizes zT at each portion of the material under its operating temperature. Such a gradient doping results in an extraordinary device efficiency of ≈14% at a ΔT of ≈500K, corresponding to a ≈40% improvement as compared to that of homogeneous doping. Since directional solidification technique commonly enables gradient dopant concentrations in semiconductors, the resultant gradient carrier concentration is illustrated here as an effective approach for advancing thermoelectrics.

Understanding the role of additional Cu intercalation in electronic and thermal properties of p-type Cu2.9Te2-incorporated Bi0.5Sb1.5Te3 thermoelectric alloys

While extensive research has explored Cu doping in n-type Bi2(Te,Se)3 for its beneficial effects on reproducibility and mobility, its impact on p-type (Bi,Sb)2Te3 remains incompletely understood. Recently, Saglik et al. demonstrated Cu2.9Te2 incorporation into Bi0.5Sb1.5Te3 as a novel approach for simultaneous Cu doping and intercalation, surpassing prior studies focused solely on Cu doping at Bi/Sb sites. The influence of additional Cu intercalation on both electronic band parameters (density-of-states effective mass, deformation potential, and weighted mobility) and phonon scattering by point defects has yet to be investigated. Here, we employ the Effective Mass model to comparatively assess the impact of Cu intercalation on these band parameters relative to single Cu doping. Furthermore, the Callaway-von Baeyer and Debye-Callaway models are employed to evaluate the effect of Cu intercalation in scattering phonons. Our findings reveal that additional Cu intercalation effectively suppresses the lattice thermal conductivity of Bi0.5Sb1.5Te3 to the amorphous limit, offering the potential to improve the figure-of-merit (zT) to ∼2.0 near 420 K with optimized carrier concentration. This approach highlights Cu intercalation as a readily applicable and powerful tool for maximizing the thermoelectric performance of Bi2Te3-based materials.

Nernst Effect of High-Mobility Weyl Electrons in NdAlSi Enhanced by a Fermi Surface Nesting Instability

The thermoelectric Nernst effect of solids converts heat flow to beneficial electronic voltages. Here, using a correlated topological semimetal with high carrier mobility μ in the presence of magnetic fluctuations, we demonstrate an enhancement of the Nernst effect close to a magnetic phase transition. A magnetic instability in NdAlSi modifies the carrier relaxation time on “hot spots” in momentum space, causing a strong band filling dependence of μ. We quantitatively derive electronic band parameters from a novel two-band analysis of the Nernst effect Sxy, in good agreement with quantum oscillation measurements and band calculations. While the Nernst response of NdAlSi behaves much like conventional semimetals at high temperatures, an additional contribution ΔSxy from electronic correlations appears just above the magnetic transition. Our work demonstrates the engineering of the relaxation time, or the momentum-dependent self-energy, to generate a large Nernst response independent of a material’s carrier density, i.e., for metals, semimetals, and semiconductors with large μ. Published by the American Physical Society 2024

Analysis of Skin Neoplasms’ Raman Spectra Using the Lorentz Approximation Method: Pilot Studies

Confocal Raman microspectroscopy provides the ability to diagnose cancer by quantitatively analyzing spectral features and identifying underlying biochemical changes. The differentiation of malignant skin neoplasms (basal cell carcinoma, squamous cell carcinoma), benign skin neoplasms (papilloma) and healthy skin was carried out by obtaining Raman spectra in vitro with excitation wavelengths of 532 and 785 nm. We present a new method for analyzing the parameters of spectral bands, based on the calculation of the second derivative and Lorentz approximation of the spectra. Using this method on a small selection of skin tumors, we have demonstrated that processes in skin tumors can cause deformation of the proteins’ secondary structure, leading to degradation and shift of the corresponding bands (972, 1655 cm–1) to the lower frequency. Bands corresponding to lipids in skin neoplasms either broaden and increase or split into two peaks (bands 1061, 1127, 1297, 1439, 1745 cm–1). The disruption of lipid structure, also indicated in several bands as a shift to lower wavenumbers, is possibly due to increased cell membrane fluidity in tumors. The results of the study may be useful for the development of optical biopsy methods for early diagnosis of tumors.