Physical States Research Articles

Low Bandgap Organic Semiconductors for Photovoltaic Applications

Photovoltaic is one of the best low-cost alternative energy sources. In this paper, organic semiconductors were explored as light harvesters due to their extraordinary properties, but initially, the scientific community focused on synthesizing the large bandgap organic semiconductors, which were unsuitable for photovoltaic applications. Wide bandgap organic semiconductors can capture light only from the UV–Vis region of the solar spectrum, thus showing solar cells’ power conversion efficiency (PCE) of less than 5%. By reducing the bandgap, organic semiconductors can show good compatibility with the air mass (AM) of 1.5 solar spectrums. So, the attention came toward synthesizing low bandgap semiconductors, which led to the enhancement of PCE from 5% to 17%. This review summarizes the overall development of the last 15 years in the field of organic photovoltaic semiconductors. The significant parameters in organic semiconductors are their bandgap, the position of the highest occupied molecular orbital (HOMO), and the lowest unoccupied molecular orbital (LUMO) that can easily be tuned chemically by molecular designing. One of the issues in organic photovoltaic solar devices is the need for absorbers with a narrow bandgap to maximize power conversion efficiencies to a great extent. Moreover, several factors, such as conjugation length, bond length alteration, intermolecular interaction, donor–acceptor charge transfer, planarity, and physical states, are responsible for tuning the bandgap. This review also classifies low bandgap semiconductors based on the core skeleton with their bandgaps, structures, and power conversion efficiencies.

Movement-based experiential learning in dance/movement therapy graduate education: facilitating and hindering factors for competency development

Dance and movement are used as the primary means of learning in graduate education programmes for dance/movement therapy in the United States. This paper reports the findings of a qualitative study that used thematic analysis to identify factors that facilitate and hinder student learning in movement-based experiential learning. Learning was facilitated when the learning community, the students, and the faculty worked synergistically and enabled the students to enter personal journeys into developing competencies and the self of the therapist. Factors that hindered learning were those that were internal to the learner, such as their mental, emotional, and physical states, as well as factors that were external to the learners. These included lack of clarity about the purposes for experiential learning, unclear boundaries, and lack of structure. Social constructivist embodied pedagogy is proposed as a pedagogical philosophy for movement-based experiential learning.

Effective data-driven collective variables for free energy calculations from metadynamics of paths

Abstract A variety of enhanced sampling methods predict multidimensional free energy landscapes associated with biological and other molecular processes as a function of a few selected collective variables (CVs). The accuracy of these methods is crucially dependent on the ability of the chosen CVs to capture the relevant slow degrees of freedom of the system. For complex processes, finding such CVs is the real challenge. Machine learning (ML) CVs offer, in principle, a solution to handle this problem. However, these methods rely on the availability of high-quality datasets – ideally incorporating information about physical pathways and transition states – which are difficult to access, therefore greatly limiting their domain of application. Here, we demonstrate how these datasets can be generated by means of enhanced sampling simulations in trajectory space via the metadynamics of paths (Mandelli et al., 2020) algorithm. The approach is expected to provide a general and efficient way to generate efficient ML-based CVs for the fast prediction of free energy landscapes in enhanced sampling simulations. We demonstrate our approach with two numerical examples, a two-dimensional model potential and the isomerization of alanine dipeptide, using deep targeted discriminant analysis as our ML-based CV of choice.

Bimetallic Organic Frameworks via In Situ Solvothermal Sol-Gel-Crystal and Sol-Crystal Transformation as Durable Electrocatalysts for Oxygen Reduction Reaction.

The in situ solvothermal conversion of metal-organic gels (MOGs) to crystalline metal-organic frameworks (MOFs) represents a versatile and ingenious strategy that has been employed for the synthesis of MOF materials with specific morphologies, high yield, and improved functional properties. Herein, we have adopted an in situ solvothermal conversion of bimetallic MOGs to crystalline bimetallic MOFs with the aim of introducing a redox-active metal heterogeneity into the monometallic counterpart. The formation of bimetallic NiZn-MOF and CoZn-MOF via in situ solvothermal sol-gel-crystal and sol-crystal transformation is found to depend on the solvent systems used. The sol-to-gel-to-crystal transformation of NiZn-MOF via the formation of NiZn-MOG is found to occur through the gradual disruption of gel fibers leading to subsequent formation of microcrystals and single crystals of NiZn-MOF. These bimetallic MOFs and MOGs serve as promising electrocatalysts for oxygen reduction reaction (ORR) with an excellent methanol tolerance property, which can be attributed to the enhanced mass and charge transfer, higher oxygen vacancies, and bimetallic synergistic interactions among the heterometals. This work demonstrates a convenient strategy for producing bimetallic MOGs to MOFs through the introduction of a redox-active metal heterogeneity in the inorganic hybrid functional materials for fundamental and applied research. Our results connect MOGs and MOFs which have been regarded as having opposite physical states, that is, soft vs hard, and provide promising structural correlation between MOGs and MOFs at the molecular level.

Mechanical state transitions in the regulation of tissue form and function.

From embryonic development, postnatal growth and adult homeostasis to reparative and disease states, cells and tissues undergo constant changes in genome activity, cell fate, proliferation, movement, metabolism and growth. Importantly, these biological state transitions are coupled to changes in the mechanical and material properties of cells and tissues, termed mechanical state transitions. These mechanical states share features with physical states of matter, liquids and solids. Tissues can switch between mechanical states by changing behavioural dynamics or connectivity between cells. Conversely, these changes in tissue mechanical properties are known to control cell and tissue function, most importantly the ability of cells to move or tissues to deform. Thus, tissue mechanical state transitions are implicated in transmitting information across biological length and time scales, especially during processes of early development, wound healing and diseases such as cancer. This Review will focus on the biological basis of tissue-scale mechanical state transitions, how they emerge from molecular and cellular interactions, and their roles in organismal development, homeostasis, regeneration and disease.

Effect of Tensing Toe Relaxation Technique on Test Anxiety among B.Sc Nursing 1st Year Students in Selected Colleges, Bhubaneswar, Odisha

Background: Test anxiety is a psychological condition that causes extreme stress and anxiety in exam situations. Students feel stress and anxiety before exams. It can disrupt their learning and lead to poor performance. Relaxation techniques, like tensing toe relaxation, are the most effective non-pharmacological techniques for reducing stress because they affect mental and physical states like depression, mood, anxiety, and self-blaming.Objective: To evaluate the effect of the tensing toe relaxation technique on test anxiety among first-year B.S.nursing students and the association of the level of test anxiety with their selected demographic variables.Methods: The Quasi-experimental research study was conducted in two selected colleges in Bhubaneswar, Odisha, among B. Sc. Nursing 1st year students. Thirty-four (34) students were selected for each Experimental and Control group by using the Purposive sampling technique. Nist, Diehl A test anxiety scale and a self-structured socio-demographic tool were used for collecting the data through the questioning method. After demonstrating the tensing toe relaxation technique to the experimental group, they were asked to practice for 2 weeks. The post- test was conducted at the end of two weeks.Results: Study findings show a reduction of test anxiety with (t = 6.02) (p = 0.000), which is highly significant at p 0.001, and also the unpaired t-test post-test values show a significant change at p 0.001. Furthermore, there is a significant association between the level of test anxiety and selected demographic variables at p <0.05.Conclusion: The Tensing toe relaxation technique is an effective intervention to reduce test anxiety.

Least-cost and 2 °C-compliant mitigation pathways robust to physical uncertainty, economic paradigms, and intergenerational cost distribution

Each run of an integrated assessment models produces a single mitigation pathway consistent with stated objectives (e.g. maximum temperature) and optimizing some objective function (e.g. minimizing total discounted costs of mitigation). Even though models can be run thousands of times, it is unclear how built-in assumptions constrain the final set of pathways. Here we aim at broadly exploring the space of possible mitigation scenarios for a given mitigation target, and at characterizing the sets of pathways that are (near-)optimal, taking uncertainties into account. We produce an extensive set of CO2 emission pathways that stay below 2 °C of warming using a reduced-form climate-carbon model with a 1000 different physical states. We then identify 18 sets of quasi ‘least-cost’ mitigation pathways, under six assumptions about cost functions and three different cost minimization functions embarking different visions of intergenerational cost distribution. A first key outcome is that the absence or presence of inertia in the cost function plays a pivotal role in the resulting set of least-cost pathways. Second, despite inherent structural differences, we find common pathways across the 18 combinations in 96% of the physical states studied. Interpreting these common pathways as robust economically and in terms of intergenerational distribution, we shed light on some of their characteristics, even though these robust pathways differ for each physical state.

Infiltration effect of Mg with different matter states in the reaction of MgB2 bulks

MgB2 superconductor bulks were fabricated using Mg and B precursors. The physical state of Mg (solid, liquid, or gas) significantly influences the final product, MgB2 bulk. In this study, the Solid-Solid, Liquid-Solid, and Gas-Solid methods were employed to fabricate MgB2 bulks. The superconducting properties and microstructure of various samples were systematically investigated. Notably, for the first time, nano-CT was utilized to comprehensively and non-destructively analyze the microstructure of MgB2 bulks, particularly the size and distribution of voids, which serve as the primary barrier affecting the superconducting properties. By examining the microstructure characteristics, the infiltration effect of Mg in different physical states during the reaction was analyzed, and a feasible reaction model was established. This research contributes to a better understanding of the reaction mechanism of MgB2, which may aid other researchers in enhancing the properties of MgB2 superconductors.

Investigation of friction modeling on numerical Ti6Al4V cutting simulations

Friction significantly influences chip formation, thereby highlighting its modeling critical in numerical cutting simulations. Notably, issues like the underestimation of feed force in simulations are often attributed to inadequate friction models. Nevertheless, diverse conclusions in the literature regarding friction’s behavior complicate the accurate implementation of this input. Additionally, the enormous of the available friction models and their varied calibration methods introduce further debates over which aspects of friction modeling should receive more focus. These controversies and deficiencies hinder progress in further understanding friction’s role in chip formation through numerical studies. Instead of proposing or calibrating new friction models, the current study, based on Ti6Al4V machining simulations, attempts to readdress the aforementioned controversies in a neutral stance by conducting sensitivity studies using a hybrid Smoothed Particle Hydrodynamics (SPH) - Finite Element Method (FEM) solver with Graphics Processing Units (GPU) acceleration, which is capable of efficiently executing high-resolution computations. The significant impact of friction particularly at the end of the tool-chip contact on the chip formation, physical contact states and process forces are highlighted. The behaviors of physical parameters including normal contact pressure, sliding velocity, and temperature-dependent friction models in the literature are also evaluated. Several aspects such as the shear flow stress limit, the relationship between friction and process forces, and the selection of different models are discussed. In conclusion, pragmatic recommendations for friction modeling and cutting simulation work are provided. On the one hand, the available complex physical parameter dependent friction models could not prove their necessity and should be approached cautiously. Instead, the constant Coulomb friction model without the shear stress limit, despite its simplicity, demonstrates effective and sufficient for a single set of metal cutting simulations. On the other hand, reliable on-site measurement techniques of the coefficient of friction (COF) at the tool-chip sliding contact area should be developed, with consideration of the contact length and the state of material flow. Combined with careful cutting edge preparation and suitable constitutive models, the overall accuracy of numerical cutting simulations including the feed force prediction are expected to be improved.

A multimodal driver monitoring benchmark dataset for driver modeling in assisted driving automation

In driver monitoring various data types are collected from drivers and used for interpreting, modeling, and predicting driver behavior, and designing interactions. Aim of this contribution is to introduce manD 1.0, a multimodal dataset that can be used as a benchmark for driver monitoring in the context of automated driving. manD is the short form of human dimension in automated driving. manD 1.0 refers to a dataset that contains data from multiple driver monitoring sensors collected from 50 participants, gender-balanced, aged between 21 to 65 years. They drove through five different driving scenarios in a static driving simulator under controlled laboratory conditions. The automation level (SAE International, Standard J3016) ranged from SAE L0 (no automation, manual) to SAE L3 (conditional automation, temporal). To capture data reflecting various mental and physical states of the subjects, the scenarios encompassed a range of distinct driving events and conditions. manD 1.0 includes environmental data such as traffic and weather conditions, vehicle data like the SAE level and driving parameters, and driver state that covers physiology, body movements, activities, gaze, and facial information, all synchronized. This dataset supports applications like data-driven modeling, prediction of driver reactions, crafting of interaction strategies, and research into motion sickness.

Recovery from Adversarial Attacks in Cyber-physical Systems: Shallow, Deep and Exploratory Works

Cyber-physical systems (CPS) have experienced rapid growth in recent decades. However, like any other computer-based systems, malicious attacks evolve mutually, driving CPS to undesirable physical states and potentially causing catastrophes. Although the current state-of-the-art is well aware of this issue, the majority of researchers have not focused on CPS recovery, the procedure we defined as restoring a CPS’s physical state back to a target condition under adversarial attacks. To call for attention on CPS recovery and identify existing efforts, we have surveyed a total of 30 relevant papers. We identify a major partition of the proposed recovery strategies: shallow recovery vs. deep recovery, where the former does not use a dedicated recovery controller while the latter does. Additionally, we surveyed exploratory research on topics that facilitate recovery. From these publications, we discuss the current state-of-the-art of CPS recovery, with respect to applications, attack type, attack surfaces and system dynamics. Then, we identify untouched sub-domains in this field and suggest possible future directions for researchers.

What is Real in Virtual Reality?

The paper discusses the thesis of virtual realism presented by David Chalmers in his paper “The Virtual and the Real” (2017). Here, I suggest an even stronger version of the claim that I call “virtual physicalism”. According to this view, virtual objects are not only real but physical as they are identical to the physical states of computers that run VR software. I suggest that virtual objects should have a similar ontological status to toys—they should be treated as models or simplifications of ordinary objects. Just like toys, virtual objects can sometimes be good enough to be used instead of their ordinary counterparts. In these cases, virtual objects start to be treated as instantiations of the same kind. In the last part of the paper, I use Johan Huizinga’s notion of a “magic circle” to suggest how different objects could be successfully “virtualized”, that is, moved into a digital realm while remaining objects of the same kind as their non-virtual counterparts. I suggest this will happen once virtual reality becomes permanent and causally connected with non-virtual reality. I finish the paper by looking at examples of natural kind objects and individuals, which seem to be the hardest cases for successful virtualization.

Bulk-Edge Correspondence for Nonlinear Eigenvalue Problems.

Although topological phenomena attract growing interest not only in linear systems but also in nonlinear systems, the bulk-edge correspondence under the nonlinearity of eigenvalues has not been established so far. We address this issue by introducing auxiliary eigenvalues. We reveal that the topological edge states of auxiliary eigenstates are topologically inherited as physical edge states when the nonlinearity is weak but finite (i.e., auxiliary eigenvalues are monotonic as for the physical one). This result leads to the bulk-edge correspondence with the nonlinearity of eigenvalues.

Formation of the skills of developing psycho-physical training methods as a key task of the training of future teachers

The purpose of the study was to clarify the views of the authors on the peculiarities of the formation of skills to use methods of psychophysical training in the educational preparation of students in the conditions of martial law and an extreme situation of education. Formation of students' skills in understanding the means of physical culture and their impact on the physical and mental state of a person as regulators of emotional states and training processes to resist stressful conditions. Methodology. The work sheds light on the views of the authors of scientific literature on the technology of regulating the psychological states of a person with the help of physical exercises; a review of the theoretical justifications of the interdependence of physical and mental states was carried out; references to the historical sources of the theoretical study of stress are presented. The authors presented the introductory part of the study of the psychological states of first-year students during the period of the military invasion and emphasized the need for empirical research in order to develop methodological recommendations for the formation of the ability to independently use the means of psychophysical training. The novelty of the study should be considered the forms and methods of research and methodical implementation proposed by the authors regarding taking into account the psychological states of students and their influence on the educational process with the further use of their results in pedagogical control and the process of developing methodological recommendations. The conclusions indicate that the use of psychophysical training methods can be an effective way to solve the problems of organizing the educational process. It is emphasized that the regulation of the consciousness of those who study with the help of psychophysical training is an effective opportunity to direct attention to the fulfillment of educational tasks, reduce emotional tension, and increase efficiency in achieving the planned results.

Three-dimensional ultrafast charge-density-wave dynamics in CuTe

Charge density waves (CDWs) involved with electronic and phononic subsystems simultaneously are a common quantum state in solid-state physics, especially in low-dimensional materials. However, CDW phase dynamics in various dimensions are yet to be studied, and their phase transition mechanism is currently moot. Here we show that using the distinct temperature evolution of orientation-dependent ultrafast electron and phonon dynamics, different dimensional CDW phases are verified in CuTe. When the temperature decreases, the shrinking of c-axis length accompanied with the appearance of interchain and interlayer interactions causes the quantum fluctuations (QF) of the CDW phase until 220 K. At T < 220 K, the CDWs on the different ab-planes are finally locked with each other in anti-phase to form a CDW phase along the c-axis. This study shows the dimension evolution of CDW phases in one CDW system and their stabilized mechanisms in different temperature regimes.

A New Battery SOC/SOH/eSOH Estimation Method Using a PBM and Interconnected SPKFs: Part I. SOC and Internal Variable Estimation

Battery management systems (BMSs) are required to estimate many non-measurable values that describe the actual operating condition of batteries; such as the state of charge (SOC) or the state of health (SOH). In order to improve this evaluation, many physical states and parameters can be estimated using physics-based models (PBMs). These estimates could be used to improve the control and prognosis of batteries. In a series of papers we propose a new method to estimate the internal physical states, the SOC, the SOH and the electrode-specific state of health (eSOH) parameters of a lithium-ion battery, using interconnected sigma-point Kalman filters (SPKFs) and a single-particle model with electrolyte dynamics (SPMe). This first paper focuses on state estimation for non-aged cells. To begin, we describe and validate our electrochemical model against a high-fidelity P2D model. The interconnected SPKF algorithm is then described and the observability of our system is analyzed, showing that the interconnected estimator approach improves an observability measure of the system. Finally, the results of the estimator are discussed, comparing the estimated variables with the truth values under initialization, measurement and modeling uncertainties. The results show that the algorithm can estimate the internal battery states with high accuracy.

Postmortem 7Li NMR analysis for assessing the reversibility of lithium metal electrodes in lithium metal batteries

Despite the proficiency of lithium (Li)-7 NMR spectroscopy in delineating the physical and chemical states of Li metal electrodes, challenges in specimen preparation and interpretation impede its progress. In this study, we conducted a comprehensive postmortem analysis utilizing 7Li NMR, employing a standard magic angle spinning probe to examine protective-layer coated Li metal electrodes and LiAg alloy electrodes against bare Li metal electrodes within Li metal batteries (LMBs). Our investigation explores the effects of sample burrs, alignment with the magnetic field, the existence of liquid electrolytes, and precycling on the 7Li NMR signals. Through contrasting NMR spectra before and after cycling, we identified alterations in Li0 and Li+ signals attributable to the degradation of the Li metal electrode. Our NMR analyses decisively demonstrate the efficacy of the protective layer in mitigating dendrite and solid electrolyte interphase formation. Moreover, we noted that Li+ ions near the Li metal surface exhibit magnetic susceptibility anisotropy, revealing a novel approach to studying diamagnetic species on Li metal electrodes in LMBs. This study provides valuable insights and practical guidelines for characterizing distinct lithium states within LMBs.

Quantum mechanics on a p-adic Hilbert space: Foundations and prospects

We review some recent results on the mathematical foundations of a quantum theory over a scalar field that is a quadratic extension of the non-Archimedean field of [Formula: see text]-adic numbers. In our approach, we are inspired by the idea — first postulated in [I. V. Volovich, [Formula: see text]-adic string, Class. Quantum Grav. 4 (1987) L83–L87] — that space, below a suitably small scale, does not behave as a continuum and, accordingly, should be modeled as a totally disconnected metrizable topological space, ruled by a metric satisfying the strong triangle inequality. The first step of our construction is a suitable definition of a [Formula: see text]-adic Hilbert space. Next, after introducing all necessary mathematical tools — in particular, various classes of linear operators in a [Formula: see text]-adic Hilbert space — we consider an algebraic definition of physical states in [Formula: see text]-adic quantum mechanics. The corresponding observables, whose definition completes the statistical interpretation of the theory, are introduced as SOVMs, a [Formula: see text]-adic counterpart of the POVMs associated with a standard quantum system over the complex numbers. Interestingly, it turns out that the typical convex geometry of the space of states of a standard quantum system is replaced, in the [Formula: see text]-adic setting, with an affine geometry; therefore, a symmetry transformation of a [Formula: see text]-adic quantum system may be defined as a map preserving this affine geometry. We argue that, as a consequence, the group of all symmetry transformations of a [Formula: see text]-adic quantum system has a richer structure with respect to the case of standard quantum mechanics over the complex numbers.

Impact of synthesizing surfactant-modified catalytic ceria nanoparticles on the performance and environmental behaviors of coconut oil/diesel-fueled CI engine: An optimization attempt

The present study deals with the characterization as well as synthesis of surfactant-modified catalytic ceria nanoparticles and their application as fuel additives in a 4-stroke diesel engine fueled by biodiesel obtained from coconut oil. The synthesis of coconut oil biodiesel is made possible by the transesterification process and its chemical tests such as Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), and Fourier-transform infrared spectroscopy (FTIR), and their physiochemical properties are carried out to verify and confirm its suitability as fuel. Cerium oxide (CeO2) is selected as a catalytic nanoparticle and is synthesized by the precipitation method. The characterization technique which includes Scanning electron microscopy (SEM), high-resolutions transmission electron microscope (HR-TEM), X-ray diffraction spectroscopy (XRD), energy dispersive spectroscopy (EDS), FTIR, and zeta potential (ZP) analyses were used to examine the chemical and physical states of distinct nanoparticles. Nanoparticles are modified by a surfactant of oleic acid for the evaluation of dispersion stabilities as compared to their bare forms. It is found to be economical and has shown superior characteristics in stability and morphology. The engine emission characteristics and performance are performed in a DI-CI engine using different concentrations of CeO2 nanoparticles. The emissions are mitigated with the addition of nanoparticles and 35 ppm is the optimum level of dosing of the nanoparticles in terms of engine performance, and emission behaviors. A blend of 20% biodiesel with diesel is found to be optimal for the preparation of nano-fuel. For the load test the efficiency increased up to 5% and at higher loads, the hydrocarbon (HC) emissions decreased by 45%, and Nitrogen Oxide (NOx) emissions were reduced by 30%. Response Surface Methodology (RSM) models correctly fit the experimental data, producing R2 values that ranged from 91 to 94.5%, respectively.

Bloch sphere analog of qudits using Heisenberg-Weyl Operators

We study an analogous Bloch sphere representation of higher-level quantum systems using the Heisenberg-Weyl operator basis. We introduce a parametrization method that will allow us to identify a real-valued Bloch vector for an arbitrary density operator. Before going into arbitrary d-level (d ≥ 3) quantum systems (qudits), we start our analysis with three-level ones (qutrits). It is well known that we need at least eight real parameters in the Bloch vector to describe arbitrary three-level quantum systems (qutrits). However, using our method we can divide these parameters into four weight, and four angular parameters, and find that the weight parameters are inducing a unit sphere in four-dimension. And, the four angular parameters determine whether a Bloch vector is physical. Therefore, unlike its qubit counterpart, the qutrit Bloch sphere does not exhibit a solid structure. Importantly, this construction allows us to define different properties of qutrits in terms of Bloch vector components. We also examine the two and three-dimensional sections of the sphere, which reveal a non-convex yet closed structure for physical qutrit states. Further, we apply our representation to derive mutually unbiased bases (MUBs), characterize unital maps for qutrits, and assess ensembles using the Hilbert-Schmidt and Bures metrics. Moreover, we extend this construction to qudits, showcasing its potential applicability beyond the qutrit scenario.