Optical studies on two-dimensional organic conductors under high pressure

The prosperity of modern society and technological development largely rely on discoveries and further applications of new materials with novel functional properties. The ability to control these properties play a key role in technological developments, such as new generation of photonic and electronic devices. Quantum materials, i.e., the materials with complex interplay of charge, spin and orbital degrees of freedom, constitute a large and continuously growing group of potentially functional materials. The macroscopic state of such materials can be manipulated via external stimuli, such as hydrostatic pressure, intense magnetic or electric field, carrier doping, etc [Basov17]. Thus, fundamental understanding of the physical mechanisms underlying the phase transitions between these states, i.e., quantum phase transitions, in quantum materials is a central task of current condensed matter physics. Low-dimensional organic conductors are good candidates for studies of quantum phase transitions, because various ground states, ranging from ordered insulators to metals or superconductors, can be continuously tuned in these materials by external pressure [Dressel11]. Owning to the recent progress in the development of pressure cells for optical measurements [Beyer15, Kimura13], the microscopic interaction parameters, which govern the phase transitions, can be extracted via the broadband optical measurements. In this thesis, we present the results of pressure-dependent infrared spectroscopy measurements on a series of quasi-two-dimensional organic materials, including the Dirac semimetal α-(BEDT-TTF)2I3, the quantum spin-liquid candidate compounds β‘-EtMe3Sb[Pd(dmit))2] and κ-(BEDT-TTF)2Cu2(CN)3, and the charge-ordered insulator β‘‘-(BEDT-TTF)2SF5CHFCF2SO3. By these studies, optical spectroscopy have been proved to be an important tool to probe not only the low-energy electronic excitation but also the lattice degrees of freedom under pressure. In α-(BEDT-TTF)2I3, we reveal that the charge-ordered insulating state at ambient pressure gradually gets suppressed and evolves into a metal. Above around 0.8 GPa the low-temperature electronic bands possess tilted Dirac-like cones. The high-pressure metallic state is well described by a Drude component and a frequency-independent optical conductivity, which strongly indicates the coexistence of the trivial and massless Dirac electrons in this system. In addition, our infrared investigations disclose that an energy gap opens in the vicinity of the phase transition between insulating and metallic states as a result of the correlated massive Dirac fermions. The gap can be gradually suppressed when pressure increases. For the half-filled Mott insulator β‘-EtMe3Sb[Pd(dmit))2]2, systematic pressure- and temperature-dependent infrared studies unveil both the electronic and lattice evolution upon crossing the Mott insulator-metal transition. The insulating ground state is continuously suppressed with increasing hydrostatic pressure. For p ≥ 0.6 GPa, a zero-frequency Drude-like component appears, strongly indicating the appearance of coherent quasi-particles at the Fermi level. In the vicinity of the Mott transition, both the electronic state and vibration modes exhibit abrupt changes, evidencing the strong coupling between the lattice and the free carriers. Additionally, we observe an unexpected inverse of the anisotropy of the in-plane optical response above 0.6 GPa. Finally, we summarize these findings in a phase diagram consisting of different experimental methods. In the case of the Mott-insulating quantum spin-liquid candidate compound κ-(BEDT-TTF)2Cu2(CN)3, we clearly identify the T- and p-driven first order transition from the analysis of the far-infrared data. Furthermore, based on the infrared vibrational spectroscopy we find out that the microscopic origin of the insulator-metal transition induced by physical and chemical pressure is intrinsically different. Regardless of the aforementioned distinct mechanism for the Mott transition, the metallic state is found to obey the universal local Fermi liquid theory. Additionally, in the STF-doped compound κ-[(BEDT-STF)x(BEDT-TTF)1-x]2Cu2(CN)3 with x=0.28 we observe an unconventional low-energy mode in the optical conductivity spectra, which can be well described in the formalism of disorder pinned fluctuating density wave theory [Delarcretaz17]. Finally, we investigate the pressure effect on the quarter-filled charge-ordered insulator β‘‘-(BEDT-TTF)2SF5CHFCF2SO3. At ambient pressure, the charge sensitive vibrational modes clearly reveal the development of a charge-ordered state with a structural dimerization, which is in accord with the X-ray measurements. With the application of hydrostatic pressure, the charge order transition in β‘‘-(BEDT-TTF)2SF5CHFCF2SO3 is surprisingly enhanced as obtained from dc transport and infrared measurements. These findings can not be accounted for with the extended Hubbard model, indicating the importance of lattice degrees of freedom for stabilizing the charge ordering in β‘‘-(BEDT-TTF)2SF5CHFCF2SO3

Exploring the Relationship between Residential Location and Long-Term Settlement Intentions: A Study of Migrant Workers in Urban China

This study delves into the link between the residential locations of migrant workers in China and their intentions to settle, set against the backdrop of the household registration system’s liberalization and the rise of a market economy. While migrant workers have significantly contributed to the societal development of China, research indicates their struggles with local community integration, leading many to eventually return to their hometowns. The influence of migrant workers’ residential choices on their migration patterns has been underexplored in Chinese scholarly discussions, a stark contrast to the attention it has received in Western academia. Employing segmented assimilation theory and spatial assimilation theory as theoretical frameworks, the study scrutinizes the relationship between migrant workers’ residential location and their long-term settlement intentions, utilizing questionnaire data collected in 2020. The empirical findings indicate that residential location is significantly related to their long-term settlement intentions, as migrant workers residing in urban centers exhibit a more pronounced intention to remain in their host cities compared to their suburban counterparts. Furthermore, the relationship is also shaped by the degree of their social integration. The study further emphasizes the importance of accounting for migration timing and homeownership status when examining this relationship, contributing to a deeper understanding of the factors that shape migration decisions in the context of China’s rapid urbanization

Optical conductivity of the Weyl semimetal NbP

The optical properties of (001)-oriented NbP single crystals have been studied in a wide spectral range from 6 meV to 3 eV from room temperature down to 10 K. The itinerant carriers lead to a Drude-like contribution to the optical response; we can further identify two pronounced phonon modes and interband transitions starting already at rather low frequencies. By comparing our experimental findings to the calculated interband optical conductivity, we can assign the features observed in the measured conductivity to certain interband transitions. In particular, we find that transitions between the electronic bands spilt by spin-orbit coupling dominate the interband conductivity of NbP below 100 meV. At low temperatures, the momentum-relaxing scattering rate of the itinerant carriers in NbP is very small, leading to macroscopic characteristic length scales of the momentum relaxation of approximately 0.5 $\mu$m.Comment: 7.5 page

Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation

Federated Learning has gained popularity among medical institutions since it enables collaborative training between clients (e.g., hospitals) without aggregating data. However, due to the high cost associated with creating annotations, especially for large 3D image datasets, clinical institutions do not have enough supervised data for training locally. Thus, the performance of the collaborative model is subpar under limited supervision. On the other hand, large institutions have the resources to compile data repositories with high-resolution images and labels. Therefore, individual clients can utilize the knowledge acquired in the public data repositories to mitigate the shortage of private annotated images. In this paper, we propose a federated few-shot learning method with dual knowledge distillation. This method allows joint training with limited annotations across clients without jeopardizing privacy. The supervised learning of the proposed method extracts features from limited labeled data in each client, while the unsupervised data is used to distill both feature and response-based knowledge from a national data repository to further improve the accuracy of the collaborative model and reduce the communication cost. Extensive evaluations are conducted on 3D magnetic resonance knee images from a private clinical dataset. Our proposed method shows superior performance and less training time than other semi-supervised federated learning methods. Codes and additional visualization results are available at https://github.com/hexiaoxiao-cs/fedml-knee

Isolation, Identification and Antibacterial Screening of Spoilage Organism in Guilin Rice Noodles

Guilin rice noodles belong to fresh wet rice noodles, which are difficult to be preserved due to their high moisture content and susceptibility to microbial contamination. Therefore, it is very important to analyze its putrefactive bacteria and screen bacteriostatic agents for extending the shelf life, and maintain the taste and nutritional value. In order to study the microbial growth during the storage of Guilin rice noodles, 13 strains of spoilage organism were isolated and purified from Guilin rice noodles stored at room temperature for 1 to 3 days, and six main spoilage organism MF1, MF2, MF3, MF4, MF6 and MF12 were obtained through the counterfactual experiment. Then the main spoilage organism were identified as Bacillus thuringiensis, B. cereus, B. velezensis, Citrobacter sp. and Exiguobacterium acetylicum through routine identification combined with molecular identification. Furthermore, the effective antibacterial agents and optimal inhibitory concentrations were selected from five food additives through the plate culture. The results showed that different concentrations of ascorbic acid and citric acid had good antibacterial effects on six types of spoilage bacteria, with the optimal inhibitory concentrations being 90 and 120 mg/mL, respectively. This shows that ascorbic acid and citric acid can be used as preservatives of Guilin rice noodles and have a certain application prospect in the storage and fresh-keeping of Guilin rice noodles

A machine learning-based radiomics approach for differentiating patellofemoral osteoarthritis from non-patellofemoral osteoarthritis using Q-Dixon MRI

This prospective diagnostic study aimed to assess the utility of machine learning-based quadriceps fat pad (QFP) radiomics in distinguishing patellofemoral osteoarthritis (PFOA) from non-PFOA using Q-Dixon MRI in patients presenting with anterior knee pain. This diagnostic accuracy study retrospectively analyzed data from 215 patients (mean age: 54.2 ± 11.3 years; 113 women). Three predictive models were evaluated: a proton density-weighted image model, a fat fraction model, and a merged model. Feature selection was conducted using analysis of variance, and logistic regression was applied for classification. Data were collected from training, internal, and external test cohorts. Radiomics features were extracted from Q-Dixon MRI sequences to distinguish PFOA from non-PFOA. The diagnostic performance of the three models was compared using the area under the curve (AUC) values analyzed with the Delong test. In the training set (109 patients) and internal test set (73 patients), the merged model exhibited optimal performance, with AUCs of 0.836 [95% confidence interval (CI): 0.762–0.910] and 0.826 (95% CI: 0.722–0.929), respectively. In the external test set (33 patients), the model achieved an AUC of 0.885 (95% CI: 0.768–1.000), with sensitivity and specificity values of 0.833 and 0.933, respectively (p < 0.001). Fat fraction features exhibited a stronger predictive value than shape-related features. Machine learning-based QFP radiomics using Q-Dixon MRI accurately distinguishes PFOA from non-PFOA, providing a non-invasive diagnostic approach for patients with anterior knee pain

Detuning the Honeycomb of α\alpha-RuCl3_{3}: Pressure-Dependent Optical Studies Reveal Broken Symmetry

The honeycomb Mott insulator $\alpha$-RuCl$_3$ loses its low-temperature magnetic order by pressure. We report clear evidence for a dimerized structure at $P>1$ GPa and observe the breakdown of the relativistic $j_{\rm eff}$ picture in this regime strongly affecting the electronic properties. A pressure-induced Kitaev quantum spin liquid cannot occur in this broken symmetry state. We shed light on the new phase by broad-band infrared spectroscopy of the low-temperature properties of $\alpha$-RuCl$_{3}$ and ab initio density functional theory calculations, both under hydrostatic pressure.Comment: 5 pages, 4 figure