Phase Sequence Research Articles

Analyzing the Sequence of Phases Leading to the Formation of the Active Region 13664, with Potential Carrington-like Characteristics

Abstract Several recurrent X-class flares from Active Region (AR) 13664 triggered a severe G5-class geomagnetic storm between 2024 May 10 and 11. The morphology and compactness of this AR closely resemble the AR responsible for the famous Carrington Event of 1859. Although the induced geomagnetic currents produced a value of the Dst index, probably 1 order of magnitude weaker than that of the Carrington Event, the characteristics of AR 13664 warrant special attention. Understanding the mechanisms of magnetic field emergence and transformation in the solar atmosphere that lead to the formation of such an extensive, compact, and complex AR is crucial. Our analysis of the emerging flux and horizontal motions of the magnetic structures observed in the photosphere reveals the fundamental role of a sequence of emerging bipoles at the same latitude and longitude, followed by converging and shear motions. This temporal order of processes frequently invoked in magnetohydrodynamic models—emergence, converging motions, and shear motions—is critical for the storage of magnetic energy preceding strong solar eruptions that, under the right timing, location, and direction conditions, can trigger severe space weather events on Earth.

Towards Reducing Continuous Emotion Annotation Effort During Video Consumption: A Physiological Response Profiling Approach

Emotion-aware video applications (e.g., gaming, online meetings, online tutoring) strive to moderate the content presentations for a more engaging and improved user experience. These services typically deploy a machine-learning model that continuously infers the user's emotion (based on different physiological signals, facial expressions, etc.) to adapt the content delivery. Therefore, to train such models, the emotion ground truth labels also need to be collected continuously. Typically, those are collated as emotion self-reports from users in a continuous manner (using an auxiliary device such as a joystick) when they watch some videos. This process of continuous emotion annotation not only increases the cognitive load and survey fatigue but also significantly deteriorates the viewing experience. To address this problem, we propose a framework, PResUP that probes a user for emotion self-reports opportunistically based on the physiological response variations of the user. Specifically, the framework implements a sequence of phases - (a) user profile construction based on physiological responses, (b) similar user clustering based on the user profile, and (c) training a parameterized activation-guided LSTM (Long short-term memory) model by sharing data among similar users to detect the opportune self-report collection moments. All these steps together help to reduce the continuous emotion annotation overhead by probing at the opportune moments without compromising the annotation quality. We evaluated PResUP by conducting a user study (N=36) during which the participants watched eight videos, and their physiological responses and continuous emotion self-reports were recorded. The key results from this evaluation reveal that PResUP reduces the annotation overhead by reducing the probing rate by an average of 34.80% and detects the opportune probing moments with an average TPR of 80.07% without compromising the annotation quality. Motivated by these findings, we deployed PResUP by performing a follow-up user study (N=18). In this deployment scenario, we also obtained similar performance in terms of the probing rate reduction (average reduction of 38.05%), and opportune moment detection performance (average TPR of 82.26%). These findings underscore the utility of PResUP in reducing the continuous emotion annotation effort during video consumption.

Conversion of An Existing 3 – Phase BLDC Hub motor to A 6 – Phase BLDC Hub Motor and their Performance Analysis for EV Application

In this research work a six–phase BLDC Hub motor designed, developed by using an existing 3–phase BLDC Hub motor material. This conversion orients towards design modifications in the stator winding layout, the number of phases, the number of hall-sensors, placement of hall-sensors and stator winding commutation. Also, a new controller is designed to commutate the six-phase stator winding. The rotor is kept the same without any modification in geometry and number of magnets. The existing 3–phase BLDC Hub motor, which is used in two – wheel EV application, has 48 slots and 52 magnets and a concentrated double layer winding layout is observed in it. This paper presents a novel direct approach for the conversion of the existing 3–phase BLDC Hub motor to a six–phase BLDC Hub motor. Using this proposed approach, a six-phase winding layout is designed and developed for the existing 48 slots stator of the BLDC Hub motor. This approach reduces the number of iterations to determine the proper phase sequence and phase offset among the phase windings compared to regular Cros’ method. In this work, first the existing 3–phase BLDC Hub motor is dismantled, and its stator is rewound with the six – phase winding layout, which is determined by author’s presented direct approach. The winding was designed in such a way to keep the stator slot fill factor in practical limits. Six hall-sensors placed in the stator slots to identify the position of the rotor. Secondly, a new controller is designed to run the developed six-phase BLDC Hub motor. Six-phase and 3–phase BLDC Hub motors are loaded at common load conditions, for performance comparison, and experimental results of both the motors presented. The results show that the six-phase BLDC Hub motor performs better than the existing 3–phase BLDC Hub motor. Hence, this work proves that the conversion of existing 3–phase BLDC Hub motor to a six–phase BLDC Hub motor is viable and can be adopted commercially.

Methodological Framework for Integrating Cultural Impact in Sustainability Assessments of Cultural Events

Based on the three dimensions model of sustainability, different studies that address the integration of the culture and sustainability concepts from a theoretical field propose that culture should be included as another sustainability dimension to a greater degree. This approach has not been put into practice to date. In fact, when sustainability application is examined in cultural activities such as museums and exhibitions, in most cases it is associated with only one dimension and evaluation methodologies based on a holistic approach; the Life Cycle Sustainability Assessment (LCSA) is used in very few cases. In this work, a methodological framework is proposed to add the cultural dimension to the study of the environmental, economic, and social dimensions of sustainability. A sequence of phases in line with the LCSA methodology is used to achieve the simultaneous evaluation of impacts associated with a sustainability approach based on four dimensions. A thorough literature review revealed cultural indicators, which were classified and organized in order to facilitate the cultural impact assessment and complement the indicators already used to evaluate other dimensions. Additionally, the approaches and methods proposed are put into practice in a case study, which consists of an experimental exhibition room. The different phases of the methodology have been successively developed, and indicators for all sustainability dimensions have been obtained. Thus, the theoretical contribution of this work is embellished with the development of a practical case, which demonstrate that cultural dimensions can be evaluated together with the rest of the dimensions in order to obtain a multidimensional assessment of sustainability.

Emergent Ferroelectric Nematic and Heliconical Ferroelectric Nematic States in an Achiral "Straight" Polar Rod Mesogen.

Ferroelectric nematic liquid crystals (NFLCs) are distinguished by their remarkable polarization characteristics and diverse physical phenomena, sparking significant interest and excitement within the scientific community. To date, over 150 NFLC molecules are developed; however, there are no reports regarding straight linear polar molecules with a parallel alignment of the permanent dipole moment and the molecular axis. The straight polar mesogen nBOE exhibits an enantiotropic NF phase with a wide temperature window (up to 100 K) despite having a longer alkyl chain (up to n = 6) than the critical alkyl chain length of conventional models. Interestingly, nBOE with a medium-length alkyl chain displays an exotic phase sequence of NF-HCNF-SmXF during the elimination of positional displacement among adjacent molecules. Furthermore, the reflective color modulation of the HCNFLC over the entire VIS-NIR spectral regime by ultralow E-field (up to 0.14V µm-1) is demonstrated.

Impact of main sequence mass loss on the appearance, structure, and evolution of Wolf-Rayet stars

Context. Stellar winds are one of the most important drivers of massive star evolution and are a vital source of chemical, mechanical, and radiative feedback on the galactic scale. Despite its significance, mass loss remains a major uncertainty in stellar evolution models. In particular, the interdependencies between the different approaches and the subsequent evolutionary stages and predicted observable phenomena are far from being systematically understood. Aims. In this study, we examine the impact of main sequence mass loss on the structure of massive stars throughout their entire evolution. Particular focus is placed on the consequences in terms of entrance into the Wolf-Rayet (WR) regime and the subsequent evolution. Methods. Using the Geneva stellar evolution code (GENEC), we computed grids of single, nonrotating stellar models at solar and Large Magellanic Cloud (LMC) metallicities of initial masses between 20 and 120 solar masses, with two representative prescriptions for high and low main sequence mass loss. Results. We obtain detailed numerical predictions regarding the structure and evolution of massive stars, and infer the role of main sequence mass loss by comparison of the mass-loss rate prescriptions. We present implications for the overall evolutionary trajectory, including the evolution of WR stars, as well as the effect on stellar yields and stellar populations. Conclusions. Mass loss during the main sequence plays an important role because of its ability to affect the sequence and duration of all subsequent phases. We identify several distinct evolutionary paths for massive stars, which are significantly influenced by the chosen main sequence mass-loss description. We also discuss the impact of uncertainties – other than that regarding mass loss – on the evolution, in particular those relating to convection. We further demonstrate that not only the total mass loss but also the specific mass-loss history throughout a star’s life is a crucial determinant of many aspects, such as the resulting stellar yields.

Joint PAPR reduction and channel estimation in low-complexity VLC systems

In recent times, there has been a surge in interest surrounding visible light communication (VLC) as a compelling adjunct to radio frequency (RF) technology. This enthusiasm stems from deployments showcasing its efficacy in high-speed data transmission, characterized by low complexity, robust security, and high reliability. Among the variants of orthogonal frequency division multiplexing (OFDM), direct current-biased optical OFDM (DCO-OFDM) stands out in the realm of VLC systems, owing to its ability to furnish rapid data provisioning. However, a significant drawback of selective mapping (SLM) based DCO-OFDM transceivers lies in its computational complexity and practical implementation challenges. To address this limitation, this paper presents a modified SLM technique termed selective phase modulation (SPM) aimed at mitigating the peak-to-average power ratio (PAPR) in the transmitter section while simplifying the data decoding process at the receiver end. The SPM method utilizes a phase modulation and demodulation process based on clusters and assisted by pilot signals, streamlining the transceiver architecture. The SPM methodology offers reduced computational complexity at the transmitter by selectively applying phase sequences to data, circumventing the necessity for side information (SI) transmission and SI estimation at the receiver with a known pilot symbol inserted in the data. This dual-functionality mechanism not only achieves complexity reduction but also facilitates channel estimation at the receiver for proper data recovery. Based on complexity analysis and simulation outcomes, the computational complexity reduction strategy outperforms the conventional selective mapping (CSLM) technique, VLC-based pilot-assisted PAPR reduction systems, and embedded coded modulation (ECM). This allows for smooth incorporation of this technology into future VLC systems.

Two‐stage algorithm for traffic signal optimization and web‐service system development

AbstractEfficient control of traffic signals for vehicles and pedestrians at intersections is critical for relieving traffic congestion. Considering the unique characteristics of intersections, such as the number of roads, the presence or absence of crosswalks, road geometric shapes, and traffic demand patterns, an appropriate phase sequence and duration for traffic signals must be established at each intersection. This paper proposes a simulation‐based two‐stage algorithm comprising integer‐constrained Adam (ICA) and tabu search (TS) to optimize the phase sequence and duration for arbitrary intersections with arbitrary traffic‐demand patterns. The ICA promptly identifies a promising region in which a global optimal solution is likely to be obtained, whereas TS determines the best solution near the region. The performance of the proposed algorithm that optimizes phase durations with fixed phase sequence is evaluated against several baseline methods using 24 instances across six actual intersections. Experimental results show that the proposed algorithm reduces the average travel time by 20.2% compared with existing traffic signals within a computation time of 4 min, thus providing a near‐optimal solution eight times faster than commonly used population‐based metaheuristics. Furthermore, the algorithm demonstrates robust performance across heterogeneous vehicles and recommends the best phase sequence that effectively alleviates congestion in current traffic signal systems. The optimized phase sequence with best phase durations further reduces the average travel time by approximately 11.3% compared with the existing phase sequence with best phase durations at an actual intersection. To facilitate its widespread use, a free, open web‐service system named “Smart Intersection for Traffic Efficiency” is developed, which enables users to optimize traffic signal systems without requiring optimization background or simulation knowledge.

Multiple pandemic waves vs multi-period/multi-phasic epidemics: Global shape of the COVID-19 pandemic

The overall course of the COVID-19 pandemic in Western countries has been characterized by complex sequences of phases. In the period before the arrival of vaccines, these phases were mainly due to the alternation between the strengthening/lifting of social distancing measures, with the aim to balance the protection of health and that of the society as a whole. After the arrival of vaccines, this multi-phasic character was further emphasized by the complicated deployment of vaccination campaigns and the onset of virus’ variants. To cope with this multi-phasic character, we propose a theoretical approach to the modeling of overall pandemic courses, that we term multi-period/multi-phasic, based on a specific definition of phase. This allows a unified and parsimonious representation of complex epidemic courses even when vaccination and virus’ variants are considered, through sequences of weak ergodic renewal equations that become fully ergodic when appropriate conditions are met. Specific hypotheses on epidemiological and intervention parameters allow reduction to simple models. The framework suggest a simple, theory driven, approach to data explanation that allows an accurate reproduction of the overall course of the COVID-19 epidemic in Italy since its beginning (February 2020) up to omicron onset, confirming the validity of the concept.

Green Wave Control Model Simultaneously Considering Passenger Cars and Buses in Closed Road Networks

Existing green wave control methods for passenger cars and buses mainly focus on maximizing bandwidths at the arterial level. There is little research on green wave control for both at the closed road network level, which makes it difficult to improve the efficiency of the entire area. To address this, a green wave control model that considers both passenger cars and buses in closed road networks is presented in this paper. The objective function of the model is to maximize the sum of the weighted bandwidths of passenger cars and buses on each segment of the road network. The relationships between car green bands, bus green bands, offsets, phase sequences, red time, green time, etc. are analyzed on the level of arterials and road networks, respectively, using time–space diagrams. Based on these analyses, the key constraints of the model are constructed accordingly. In addition, 0/1 variables and a sufficiently large positive number M are introduced to relax some of the constraints to ensure that the presented model has feasible solutions. The results of the numerical example demonstrate that compared with the fixed phase sequence schemes 1, 2, and 3, the total weighted bandwidth generated by the presented model increased by 9.5%, 16.4%, and 17%, respectively. Compared with the model without constraint relaxation, the presented model can still find a global, optimal solution when the common cycle time is fixed, while the model without constraint relaxation has no feasible solution.

Kinetics of diffusion and phase formation in a solid-state reaction in Al/Au thin films

The kinetics of diffusion and formation of Al-Au intermetallic compounds in a solid-state reaction between layers of aluminum and gold has been studied by the method of in situ electron diffraction. The phase sequence in the solid-state reaction in Al/Au thin films is found to depend on the atomic ratio of aluminum and gold at the initial state. Specifically, with the atomic ratio being Al:Au=2:1, one observes the formation sequence: Al3Au8→AlAu2→Al2Au, while with the ratio Al:Au=1:4, the sequence is Al3Au8→AlAu4. The observed change in the sequence is explained using the theoretical model of EHF (Effective Heat of Formation). The kinetic parameters of the diffusion of gold through the layer of reaction products in the Al/Au thin films have been determined, including the apparent activation energy of the diffusion Ea=1.17 eV and pre-exponential factor D0=120 cm2/s. Based on the data obtained by in situ electron diffraction, the kinetic parameters of the phase formation have been estimated by the Kissinger-Akahira-Sunose method. In addition, the kinetic parameters of the formation of the Al-Au intermetallic compounds have been determined (apparent activation energy Ea, pre-exponential factor A) in the solid-state reaction in the Al/Au thin films, namely, Ea = 0.77 eV, log(A, s−1) = 9 for Al3Au8; Ea = 1.08 eV, log(A, s−1) = 13 for AlAu2; Ea = 1.13 eV, log(A, s−1) = 13 for Al2Au; and Ea = 1.35 eV, log(A, s−1) = 16 for the phase AlAu4. The kinetic parameters of the formation of the AlAu4 phase have been estimated for the first time.

Radiomics analysis based on contrast-enhanced MRI for predicting short-term efficacy of drug-eluting beads transarterial chemoembolization in hepatocellular carcinoma.

We developed and validated a clinical-radiomics model for preoperative prediction of the short-term efficacy of initial drug-eluting beads transarterial chemoembolization (D-TACE) treatment in patients with hepatocellular carcinoma (HCC). In this retrospective cohort study of 113 patients with intermediate and advanced HCC, 5343 features were extracted based on three sequences of the arterial phase (AP), diffusion-weighted imaging, and T2-weighted images based on contrast-enhanced magnetic resonance imaging, and minimum redundancy maximum correlation and least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection and model construction. Multifactor logistic regression was used to build a clinical-imaging model based on clinical factors and a clinical-radiomics model. The area under the curve (AUC) and calibration curves were used to assess model performance, and the clinical value of the model was analyzed using decision curve analysis. The relationship between the actual and predicted short-term efficacy of the combined model and progression-free survival (PFS) was evaluated using Kaplan-Meier survival curves and log-rank tests. A total of 34 radiomics features were selected by LASSO, and the clinical-radiomics model had the best predictive performance (AUC = 0.902 and AUC = 0.845 for the training and testing sets, respectively), and the model based on AP had the best predictive performance among the four radiomics models (AUC = 0.89 for the training set and AUC = 0.85 for the testing set); the multifactorial logistic regression results showed that microsphere type (p = 0.042) and AP Rad-score (p = 0.01) were associated with short-term efficacy. In addition, a difference in PFS was observed in patients with HCC with different short-term efficacies predicted by the combined model. Moreover, prognosis was better in the objective versus non-objective response group. The combined clinical-radiomics model is an effective predictor of the short-term efficacy of initial D-TACE in patients with HCC, contributing to clinical and economic benefits for patients.

Phase reassignment strategy and load phase-swapping device for three-phase unbalance in the power distribution area

The three-phase unbalance brings a severe challenge to power quality, and the load phase-swapping severs as an effective method can regulate that. Currently most of the phase-swapping strategies tend to exchange the phase sequence of power consumers. However, little attention has been paid to analyze how the phase sequence of distributed generation(DG) injected into the station area makes impact on three-phase unbalance. on top of that, here exist phase-swapping delays in the current load phase-swapping devices, which causes short-time power outages and affect the electricity safety. In the light of this, the present study endeavors to propose a new method of phase reassignment: exchanging the phase sequence of electricity users, controlling the phase sequence of DG, offsetting the unbalanced loads via using DG for the purpose of reducing the frequency of phase swapping,and designing a load phase-swapping device.which forces the phase swapped at the zero-crossing point for line voltage to realize load phase swapping without power outages. Firstly, an objective function with the minimum unbalance index, the minimum times of phase-swappings, and the maximum participation of DG were established. Secondly, an improved multi-objective optimization squirrel search algorithm(IMOSSA) was used to solve this objective function. Finally, a load phase-swapping device with zero-milliseconds delay and no power-off was established, containing phase-swapping control terminal(PSCT) and phase-swapping switches(PSS). The case simulation results show that the proposed strategy can reduce the number of phase reassignments with the participation of DG, reducing the unbalance index from 69.96 % to 8.43 %. Additionally the distribution laboratory test results show that the PSCT can calculate and send phase swapping commands, and the PSS exchange phase sequence can be applied without delays and no power outages for users.

Disruptive market-shaping processes: Exploring market formation for autonomous vehicle solutions

In the race toward autonomous vehicle solutions, providers engage in disruptive market-shaping processes to overcome barriers to commercialization and trigger market formation. This study investigates how disruptive market-shaping processes unfold by employing a multiple case study of 10 AVS providers. Our findings reveal a disruptive market-shaping process comprising four dimensions: shaping the value logic, nurturing the demand side, forging ecosystem alliances, and catalyzing institutional changes. Furthermore, we analyze the temporal unfolding of these activities to illustrate a comprehensive market-shaping process comprising three phases: market exploration, market preparation, and market experimentation. We make significant contributions to the market-shaping and AVS literature. By showing empirically how disruptive market-shaping processes unfold, we refine existing knowledge on the broader market formation stage, anchoring it to the emergence of new markets. Our framework offers micro-level insights into the sequencing of activities and phases embedded in shaping new markets. We argue that successful disruptive market shaping is contingent on creating an attractive market value proposition. Finally, we identify the foundational activities required to overcome market barriers and advance the commercialization of autonomous solutions. We find that granular systems logic reveals AVS's true value, questioning traditional market logic and paving the way for a sustainable, autonomous future.

Universal Measurement-Based Quantum Computation in a One-Dimensional Architecture Enabled by Dual-Unitary Circuits.

A powerful tool emerging from the study of many-body quantum dynamics is that of dual-unitary circuits, which are unitary even when read "sideways," i.e., along the spatial direction. Here, we show that this provides the ideal framework to understand and expand on the notion of measurement-based quantum computation (MBQC). In particular, applying a dual-unitary circuit to a many-body state followed by appropriate measurements effectively implements quantum computation in the spatial direction. We show how the dual-unitary dynamics generated by the dynamics of the paradigmatic one-dimensional kicked Ising chain with certain parameter choices generate resource states for universal deterministic MBQC. Specifically, after k time steps, equivalent to a depth-k quantum circuit, we obtain a resource state for universal MBQC on ∼3k/4 encoded qubits. Our protocol allows generic quantum circuits to be "rotated" in space-time and gives new ways to exchange between resources like qubit number and coherence time in quantum computers. Beyond the practical advantages, we also interpret the dual-unitary evolution as generating an infinite sequence of new symmetry-protected topological phases with spatially modulated symmetries, which gives a vast generalization of the well-studied one-dimensional cluster state and shows that our protocol is robust to symmetry-respecting deformations.

Pressure-induced novel phases with the high-Tc superconductivity in zirconium dihydride

The unprecedented structures in hydrides could be uncovered under high pressure, which probably possess unusual properties, such as high-Tc superconductivity. Here, the structural transition of ZrH2 at 0−500 GPa are comprehensively explored by using the evolutionary algorithm in the universal structure predictor combined with first-principles calculations. Three new phases are found: Pnma-ZrH2, P-3m1-ZrH2 and R-3m-ZrH2, with dynamic stability. Moreover, the sequence of phases of ZrH2 under pressure is I4/mmm → P4/nmm → Pnma → P-3m1 → R-3m with the zero-point energy effects. Structural feature, electronic properties, bonding characters and superconductivity of all the ZrH2 are analyzed in detail. More importantly, the superconducting critical temperature Tc values for P-3m1 at 440 GPa and R-3m at 500 GPa are 17.70–20.14 K and 26.68–30.03 K, respectively, which stems from the strong electron-phonon coupling.

A Comparative Study of Traffic Signal Control Based on Reinforcement Learning Algorithms

In recent years, the increasing production and sales of automobiles have led to a notable rise in congestion on urban road traffic systems, particularly at ramps and intersections with traffic signals. Intelligent traffic signal control represents an effective means of addressing traffic congestion. Reinforcement learning methods have demonstrated considerable potential for addressing complex traffic signal control problems with multidimensional states and actions. In this research, the team propose Q-learning and Deep Q-Network (DQN) based signal control frameworks that use variable phase sequences and cycle times to adjust the order and the duration of signal phases to obtain a stable traffic signal control strategy. Experiments are simulated using the traffic simulator Simulation of Urban Mobility (SUMO) to test the average speed and the lane occupancy rate of vehicles entering the ramp to evaluate its safety performance and test the vehicle’s traveling time to assess its stability. The simulation results show that both reinforcement learning algorithms are able to control cars in dynamic traffic environments with higher average speed and lower lane occupancy rate than the no-control method and that the DQN control model improves the average speed by about 10% and reduces the lane occupancy rate by about 30% compared to the Q-learning control model, providing a higher safety performance.

Impact of annealing treatment on adlayer structures of terphenylmethanethiol self-assembled monolayers on Au(111)

The scanning tunneling microscopy (STM) technique was employed to investigate the adlayer structure and morphology of Self-assembled monolayers (SAMs) fabricated from terphenylmethanethiol (TP1) molecules on Au(111) by preparing from an ethanolic solution at room temperature and subsequently annealed at various temperatures, reaching up to 468 K. Upon heat treatment, the TP1 adlayer exhibited a sequence of distinct structural phases characterized by varying molecular arrangements, namely α, β, γ, δ, ε, σ, and θ, emerging successively for both the as-prepared and annealed samples. The progressive transformation from α→β→ γ→δ→ε→σ→α→θ phases, driven by escalating annealing temperatures, entailed a gradual decrease in molecular packing density until the transition from γ→δ, followed by a subsequent increase leading to the formation of the most densely packed molecular network with molecules standing almost upright, referred to as the α phase, which is the same phase observed for non-heat-treated films. Interestingly, the desorption process for the annealed SAMs occurred from the densest packing TP1 molecular structure of the α phase, contrary to those of biphenyl-based organothiol and n-alkanethiol SAMs where desorption takes place from lying-down striped phases. Almost all TP1 molecules were desorbed at an annealing temperature of 468 K, leading to a significant alteration in the surface structure. During the annealing process, our results showed that the gold surface underwent remarkable changes, including the disappearance of the vacancy islands and the emergence of surface cracks in the form of trenches, along with the formation of rounded monoatomic gold islands with a densely packed α phase.

Hydrogen bond thermotropic ferroelectric liquid crystal of DL-tartaric acid and 4-heptyloxybenzoic acid (1:1): Experimental and density functional theory (DFT) approach

The current research work incorporates structural, experimental and computational studies of a hydrogen bond thermotropic ferroelectric liquid crystal (HBTFLC) complex synthesised from DL-tartaric acid (DLTA) and 4-heptyloxybenzoic acid (7OBA) with 1:1 ratio. Spectroscopic studies (XRD, NMR, FTIR, UV–Vis) and Density Functional Theory (DFT) are utilized to confirm intermolecular hydrogen bonds in the synthesised complex. Polarizing Optical Microscope (POM) study confirms the phase sequence (N*, Sm C*, Sm F* and Sm G*) while Differential Scanning Calorimetry (DSC) explore the thermal properties of the mesophases. The Frontier Molecular Orbital (FMO) and Molecular Electrostatic Potential (MEP) surface analysis also explore the donor-acceptor interactions, stability and chemical reactivity of the complex. The nature of H-bond is estimated by Natural Bond Orbital (NBO) studies with the support of Atom-in-Molecules (AIM) and Reduced Density Gradient (RDG) analysis. Nonlinear Optical (NLO) properties of the complex are studied by calculating its polarizability and hyperpolarizability.

Formation of skyrmion phase in the Fe–Co–Si system by mechanochemical activation

Fe, Co and Si powders were exposed to mechanochemical activation by high-energy ball milling for 0, 2, 4, 8 and 12 h. The samples were subsequently characterized by Mössbauer spectroscopy, X-ray powder diffraction (XRPD), magnetic measurements and optical diffuse reflectance spectroscopy. The room temperature Mössbauer measurements were consistent with the occurrence of FeCo2Si and Fe0.5Co0.5Si crystalline phases. The low temperature Mössbauer spectra confirmed the absence of superparamagnetism up to 44 K in the milled system. XRPD patterns supported the phase sequence derived from Mössbauer spectroscopy. The coercive field was found to increase with the ball milling time (BMT). Zero-field-cooling-field-cooling (ZFC-FC) measurements performed at 200 Oe in the temperature range 5–300 K evidenced the transition to the skyrmion phase of the Fe0.5Co0.5Si material below the critical temperature of 44 K. The optical absorption in the UV–Vis–NIR region of the spectrum was found to increase with BMT.