bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring structure–property landscape of non-fullerene acceptors for organic solar cells
Authors: Patel Khantil , Khatua Rudranarayan , Patrikar Kalyani , Mondal Anirban 
Published: April 2024

We present a comprehensive analysis of the structure–property relationship in small molecule non-fullerene acceptors (NFAs) featuring an acceptor–donor–acceptor configuration employing state-of-the-art quantum chemical computational methods. Our focus lies in the strategic functionalization of halogen groups at the terminal positions of NFAs as an effective means to mitigate non-radiative voltage losses and augment photovoltaic and photophysical properties relevant to organic solar cells. Through photophysical studies, we observe a bathochromic shift in the visible region for all halogen-functionalized NFAs, except type-2, compared to the unmodified compound. Most of these functionalized compounds exhibit exciton binding energies below 0.3 eV and ΔLUMO less than 0.3 eV, indicating their potential as promising candidates for organic solar cells. Selected candidate structures undergo an analysis of charge transport properties using the semi-classical Marcus theory based on hopping transport formalism. Molecular dynamics simulations followed by charge transport simulations reveal an ambipolar nature of charge transport in the investigated NFAs, with equivalent hole and electron mobilities compared to the parent compound. Our findings underscore the crucial role of end-group functionalization in enhancing the photovoltaic and photophysical characteristics of NFAs, ultimately improving the overall performance of organic solar cells. This study advances our understanding of the structure–property relationships in NFAs and provides valuable insights into the design and optimization of organic solar cell materials.
Towards a protyposis-based semiotic theory of translation
Authors: De la Cruz Recio Manuel 
Published: April 2024

Abstract
This contribution presents a semiotic theory of translation based on protyposis that bridges the gap between quantum
physics, semiotics, and translation studies. Protyposis, an elementary quantum structure, underlies all possibilities for
generating meaningful information. The theory critiques traditional notions of information and examines its development from
the communication theory of Shannon and Weaver to more complex biosemiotic perspectives. It addresses the interplay between
protyposis and semiotic processes and shows how meaning emerges from relationships and functions that go beyond the quantum
level. It integrates Marais’ work on semiotic translation theory, which proposes translation as a negentropic semiotic process
that works within constraints to create relations. The study culminates in the advocacy of a transdisciplinary approach
underpinned by protyposis to comprehensively understand the complexity of translation and information processes, opening a new
perspective for understanding communication, perception and knowledge construction in different scientific fields.
Infoautopoiesis and translation
Authors: Cárdenas-García Jaime F. 
Published: April 2024

Abstract
A biosemiotic perspective of translation entails the study of signs and meaning in living organisms, an
infoautopoietic process existing since the origin of life. Infoautopoiesis makes the external environment meaningful to the
organism, so it can mould it in its own image to satisfy its needs, and be moulded in turn. Self-created internalised semantic
information results from interpreting environmental sensory signals as “differences which make a difference”. The content of
individuated, inaccessible internalised semantic information may be translated into externalised syntactic expressions that
comprise outward artificial expressions that lack semantic content. Yet, despite our ability for creation of sophisticated
syntactic information, we are unable to make them produce semantic information. In short, infoautopoiesis is fundamental to
translation at any level.
Degradation mechanism of measuring performance of optical particle counter under temperature-pressure coupling effect
Authors: Lu Lifeng , Li Yanbo , Wang Yixin , Wu Xin , Xiong Liling , Liu Longlong , Wei Liejiang 
Published: April 2024

Abstract
To investigate the degradation mechanism of measuring the performance of an optical particle counter (OPC) under temperature-pressure coupling, this study first establishes a theoretical calculation model of gas refractive index and then elucidates the comprehensive influence mechanism of temperature and pressure on gas optical properties. Furthermore, the experimental measurement technique and measuring device for gas refractive index are built. By comparing the theoretical and experimental results in the temperature range of 48 °C–560 °C and the pressure range of 0.9–4.6 MPa, the difference between the two errors is just 0.05%, indicating the accuracy of the theoretical model of the refractive index of gas. Secondly, a dynamic model of optical measurement volume (OMV) under high-temperature and high-pressure conditions was established using geometrical optics theory, and the impacts of gas temperature and pressure variations on OPC measurement performance were investigated. The gas temperature (100 °C–1000 °C) and pressure (1–4.6 MPa) are shown to have opposing effects on the OMV, with gas pressure being more relevant. Finally, in order to eliminate the effect of gas refractive index change on the optical measurement performance of OPC, a parallel light model is proposed to solve the problem of the degradation of OPC measurement performance under temperature and pressure coupling conditions.
Solution-processable low-voltage carbon nanotube field-effect transistors with high-k relaxor ferroelectric polymer gate insulator
Authors: Yang Dongseong , Moon Yina , Han Nara , Lee Minwoo , Beak Jeongwoo , Lee Seung-Hoon , Kim Dong-Yu 
Published: April 2024

Abstract
Achieving energy-efficient and high-performance field-effect transistors (FETs) is one of the most important goals for future electronic devices. This paper reports semiconducting single-walled carbon nanotube FETs (s-SWNT-FETs) with an optimized high-k relaxor ferroelectric insulator P(VDF-TrFE-CFE) thickness for low-voltage operation. The s-SWNT-FETs with an optimized thickness (∼800 nm) of the high-k insulator exhibited the highest average mobility of 14.4 cm2 V−1s−1 at the drain voltage (I
D) of 1 V, with a high current on/off ratio (I
on/off >105). The optimized device performance resulted from the suppressed gate leakage current (I
G) and a sufficiently large capacitance (>50 nF cm−2) of the insulating layer. Despite the extremely high capacitance (>100 nF cm−2) of the insulating layer, an insufficient thickness (<450 nm) induces a high I
G, leading to reduced I
D and mobility of s-SWNT-FETs. Conversely, an overly thick insulator (>1200 nm) cannot introduce sufficient capacitance, resulting in limited device performance. The large capacitance and sufficient breakdown voltage of the insulating layer with an appropriate thickness significantly improved p-type performance. However, a reduced n-type performance was observed owing to the increased electron trap density caused by fluorine proportional to the insulator thickness. Hence, precise control of the insulator thickness is crucial for achieving low-voltage operation with enhanced s-SWNT-FET performance.
From Spherical Cows to Schrödinger’s Cat: what students want to learn in physics
Authors: Richardson T 
Published: April 2024

Abstract
This paper reflects on feedback received from 161 Ontario grade 12 physics students between 2017–2018 and 2020–2023, on the content and delivery in different modes (face-to-face, online, hybrid) of the 2008 Ontario Grade 12 Physics—University Preparation course (SPH4U). Across modes, students considered Revolutions in Modern Physics significantly more interesting and less stressful than any of the other four units. Students also identified Dynamics as significantly less interesting than all of the units, and found it significantly more stressful than all units other than Fields. Students were most interested in topics not previously studied (e.g. Special Theory of Relativity) that they felt promoted new ways of thinking. Adjusting to grade 12 expectations combined with more challenging course concepts were the primary contributors of stress. Included is a discussion of physics education reform, and the role of physics education in science, technology, engineering and mathematics.
Non-equilibrium structural and dynamic behaviors of active polymers in complex and crowded environments
Authors: Zhu Guolong , Gao Lijuan , Sun Yihang , Wei Wenjie , Yan Li-Tang 
Published: April 2024

Abstract
Active matter systems, which convert internal chemical energy or energy from the environment into directed motion, are ubiquitous in nature and exhibit a range of emerging non-equilibrium behaviors. However, most of the current works on active matter have been devoted to particles, and the study of active polymers has only recently come into the spotlight due to their prevalence within living organisms. The intricate interplay between activity and conformational degrees of freedom gives rise to novel structural and dynamical behaviors of active polymers. Research in active polymers remarkably broadens diverse concepts of polymer physics, such as molecular architecture, dynamics, scaling and so on, which is of significant importance for the development of new polymer materials with unique performance. Furthermore, active polymers are often found in strongly interacting and crowded systems and in complex environments, so that the understanding of this behavior is essential for future developments of novel polymer-based biomaterials. This review thereby focuses on the study of active polymers in complex and crowded environments, and aims to provide insights into the fundamental physics underlying the adaptive and collective behaviors far from equilibrium, as well as the open challenges that the field is currently facing.
Tailored efficient and reliable double luminescent layer hybrid WOLEDs via doping engineering
Authors: Zhang Wenxin , Zhang Gang , Chang Xi , Dong He , Lang Jihui , Xing Guoliang , Wang Dandan , Mai Zhihong , Wang Xinying 
Published: April 2024

Abstract
Doping engineering has been widely utilized to increase the efficiency of White organic light-emitting diodes (WOLEDs). In this study, a blue phosphor material named DMAC-DPS and an orange phosphor material named PO-01 are integrated into the host materials Bis[2-(diphenylphosphino)phenyl] ether oxide (DPEPO) and carbazole-based 4,4′-biscarbazole-p-biphenyl (CBP) by incorporating the principle of complementary color luminescence, resulting in a doped double-luminescent layer hybrid WOLED. The developed device structure consists of ITO/MoO3/TCTA/DPEPO:DMAC-DPS/CBP:PO-01 (or CBP:PO-01/DPEPO:DMAC-DPS)/TAZ/Alq3/LiF/Al. The transfer of energy between the host and guest materials is achieved by controlling the thickness and position of the emitting layer, leading to a more balanced emission of blue and yellow light and an overall increase in device efficiency. The developed WOLED exhibits a maximum current efficiency of 26.8 cd A−1, a power efficiency of 16.8 lm W−1, and an external quantum efficiency of 10.95%. The stable color coordinates of the device remains consistent, varying from (0.34, 0.40) to (0.33, 0.39) at brightness levels ranging from 100 to 1000 cd m−2. Technically, the incorporation of blue and orange phosphor materials into the host materials DPEPO and CBP, respectively, resulting in a doped double-luminescent layer hybrid WOLED, has shown a more balanced emission of blue and yellow light and resulted in increased efficiency. The reliable color coordinates corroborate the good color stability, making it a promising candidate for various applications. Furthermore, the controlled transfer of energy between the host and guest materials has led to a more balanced emission of blue and yellow light. Our developed doping engineering methods have shown potential for increased efficiency and good color stability, making the developed WOLED a promising candidate for various applications.
Surface engineering by rogue wave induced by energetic carbon clusters
Authors: El-Said A S , Moslem W M , Tolba R E , Sabry R , Bahlouli H 
Published: April 2024

Abstract
Swift heavy ions are effective in nanostructuring material surfaces. The irradiation of lanthanum fluoride with 30 MeV C60 leads to the creation of surface nanohillocks of size larger than the ones produced by monoatomic heavy ions. The generation of the observed nano-sized hillocks is described here by a new approach that is based on ion-induced intensive electronic excitations that create localized rogue waves. Consequently, the induced nonlinear ion-acoustic rogue waves are considered a hallmark of nanohillock formation. Plasma hydrodynamic equations produce a relationship between normalised electron number density and crystal lattice spacing. Similarities to the hillock profile suggest the crucial primary role of electron density in the fabrication of surface nanostructures.
Hybrid quantum neural network structures for image multi-classification
Authors: Shi Mingrui , Situ Haozhen , Zhang Cai 
Published: April 2024

Abstract
Image classification is a fundamental problem in computer vision, and neural networks provide an effective solution. With the advancement of quantum technology, quantum neural networks have attracted a lot of attention. However, they are only suitable for low-dimensional data and require dimensionality reduction and quantum encoding. Two image classification methods have recently emerged: one employs PCA for dimensionality reduction and angular encoding, and the other integrates QNN into a CNN to improve performance. Despite numerous algorithms, the differences between them remain unclear. This study explores these algorithms’ performance in multi-class image classification and proposes an optimized hybrid quantum neural network suitable for the current environment. As the number of classes increases, research on PCA-based quantum algorithms reveals the barren plateau problem of QNN, which is not suitable for multiple classes in a hybrid setting. Our proposed model combining traditional CNN with QNN addresses QNN’s multi-class training difficulties to some extent and achieves satisfactory classification results. Nevertheless, its accuracy remains below that of the top-performing CNN models. Furthermore, we investigate transfer learning in hybrid quantum neural network models and assess the performance of our models on the quantum hardware from IBM. In conclusion, quantum neural networks show promise but require further research and optimization, facing challenges ahead.
Active control of Fano resonance in side-coupled resonator-cavity systems
Authors: Jiang Rui , Gao Lei , Yang Lei , Wang Jun , Wu Qian , Sun Yong , Chen Yongqiang 
Published: April 2024

Abstract
The study delves into actively controlling Fano resonance within a single-mode microstrip cavity, coupled with a split ring resonator (SRR) incorporating a varactor diode. This resonance arises from the interference between the SRR and a Fabry–Pérot cavity, resulting in a sharply asymmetric transmission spectrum. The varactor diode, situated within the SRR gap, is biased electrically via an external DC voltage source. Through manipulation of this bias voltage, both the transmission frequency and amplitude of the pronounced Fano resonance can be dynamically adjusted. Notably, a significant frequency shift of 345 MHz is achieved, accompanied by a transmission modulation depth of up to 34.2 dB. Moreover, at the Fano peak frequency of 2.65 GHz, the composite SRR-cavity structure exhibits a notable change in group delay, shifting by 21.3 ns with the bias voltage varying from 5 V to 2.6 V. These findings hold promise for the development of electrically controlled functional photonic devices, facilitating their adaptability and versatility in practical applications.
Modified Korteweg–de Vries solitons with quartic nonlinearity in a dusty plasma
Authors: Das Dulal Chandra , Das Samiran , Kalita Rekha 
Published: April 2024

Abstract
The present multicomponent dusty plasma with ions, Cairns distributed electrons and immobile dusts has been investigated first time through modified Korteweg–de Vries (mKdV) equation of quartic nonlinearity derived by reductive perturbation technique. In this new investigation, it is found that the dust ion-acoustic (DIA) solitary waves have smaller amplitudes compared to the amplitudes of mKdV-DIA compressive solitons of our previous investigation [38]. Roles of non-thermal parameter (β), dust to ion density ratio (σ), number of dust charge (Z

d
) and initial streaming speed of ion (u

i0) in the growth of amplitudes and widths of this new mKdV-DIA solitons are investigated.
Verifying hierarchical network nonlocality in general quantum networks
Authors: Yang 杨 Shu-Yuan 舒媛 , Hou 侯 Jin-Chuan 晋川 , He 贺 Kan 衎 
Published: April 2024

Abstract
Recently, a class of innovative notions on quantum network nonlocality (QNN), called full quantum network nonlocality (FQNN), have been proposed in Phys. Rev. Lett.
128 010403 (2022). As the generalization of full network nonlocality (FNN), l-level quantum network nonlocality (l-QNN) was defined in arxiv. 2306.15717 quant-ph (2024). FQNN is a NN that can be generated only from a network with all sources being non-classical. This is beyond the existing standard network nonlocality, which may be generated from a network with only a non-classical source. One of the challenging tasks is to establish corresponding Bell-like inequalities to demonstrate the FQNN or l-QNN. Up to now, the inequality criteria for FQNN and l-QNN have only been established for star and chain networks. In this paper, we devote ourselves to establishing Bell-like inequalities for networks with more complex structures. Note that star and chain networks are special kinds of tree-shaped networks. We first establish the Bell-like inequalities for verifying l-QNN in k-forked tree-shaped networks. Such results generalize the existing inequalities for star and chain networks. Furthermore, we find the Bell-like inequality criteria for l-QNN for general acyclic and cyclic networks. Finally, we discuss the demonstration of l-QNN in the well-known butterfly networks.
Cross-tokamak disruption prediction based on domain adaptation
Authors: Shen Chengshuo , Zheng Wei , Guo Bihao , Ding Yonghua , Chen Dalong , Ai Xinkun , Xue Fengming , Zhong Yu , Wang Nengchao , Shen Biao , Xiao Binjia , Chen Zhongyong , Pan Yuan ,   J-TEXT Team
Published: April 2024

Abstract
The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research. In this paper, we demonstrated a novel approach to predict disruption in a future tokamak using only a few discharges based on domain adaptation (DA). The approach aims to predict disruption by finding a feature space that is universal to all tokamaks. The first step is to use the existing understanding of physics to extract physics-guided features from the diagnostic signals of each tokamak, called physics-guided feature extraction (PGFE). The second step is to align a few data from the future tokamak (target domain) and a large amount of data from existing tokamaks (source domain) based on a DA algorithm called CORrelation ALignment (CORAL). It is the first attempt at applying DA in the cross-tokamak disruption prediction task. PGFE has been successfully applied in J-TEXT to predict disruption with excellent performance. PGFE can also reduce the data volume requirements due to extracting the less device-specific features, thereby establishing a solid foundation for cross-tokamak disruption prediction. We have further improved CORAL called supervised CORAL (S-CORAL) to enhance its appropriateness in feature alignment for the disruption prediction task. To simulate the existing and future tokamak case, we selected J-TEXT as the existing tokamak and EAST as the future tokamak, which has a large gap in the ranges of plasma parameters. The utilization of the S-CORAL improves the disruption prediction performance on future tokamak. Through interpretable analysis, we discovered that the learned knowledge of the disruption prediction model through this approach exhibits more similarities to the model trained on large data volumes of future tokamak. This approach provides a light, interpretable and few data-required ways by aligning features to predict disruption using small data volume from the future tokamak.
Flight quotas outperform focused mitigation strategies in reducing the carbon footprint of academic travel
Authors: Ben-Ari Tamara , Lefort Gaëlle , Mariette Jérome , Aumont Olivier , Jeanneau Laurent , Santerne Alexandre , Spiga Aymeric , Roche Philippe-e 
Published: April 2024

Abstract
The carbon footprint of academia has become a prominent concern and a burgeoning research area, with a notable focus on greenhouse gas emissions (GHG) from research-related travels. Mitigation strategies often promote alternatives, such as developing virtual communication or adopting sustainable transportation modes for short distances. While more ambitious strategies involving the transformation of research practices are increasingly discussed, these mitigation solutions are rarely subjected to rigorous quantitative assessments or meaningful comparisons. This study analyzes a unique database of about 130 000 travel segments by car, train and plane in 159 research entities across a wide array of disciplines in France. We investigate the patterns and associated carbon footprint of these research travels and explore a diversity of mitigation options. Our analysis shows that air travel overwhelmingly outweighs the carbon footprint of research travel, representing more than 96% of GHG emissions. Intercontinental flights are infrequent (less than 10% of all plane trips) but dominate GHG travel emissions, accounting for over 64% of total emissions. In contrast, domestic and continental flights are the most common but their mitigation potential by modal shift to train is limited (e.g. less than 15% for trips under 1000 km). Similar reductions can be achieved by targeting a small subset of travels, for example by modulating the frequency of conference attendance. The greatest and possibly most robust mitigation potential lies in combining modal shift with moderating air mileage (e.g. reducing travelled distance or number of flights). Strategies focusing on electrification or modal shifts for cars, proposed in official guidelines, are found to have negligible impact. In the absence of low-carbon alternatives for long-haul flights, we contend that only comprehensive strategies and policies which include moderating air travel distance or frequency can achieve a robust significant reduction in the GHG emissions from academic travel.