The coordination microenvironment of metal active sites in metal–organic frameworks (MOFs) plays a crucial role in its performance for electrochemical CO2 reduction reaction (CO2RR). However, it ...remains a challenge to clarify the structure–performance relationship for CO2RR catalyzed by MOFs. Herein, a series of MOFs with different coordination microenvironments of Cu(I) sites (CuCl, CuBr, and CuI) to evaluate their performances for CO2RR is synthesized. With the increasing radius of halogen atom, the CO2 adsorption capacity increases and d‐band center of Cu positively shifts to the Fermi level, leading to enhance the selectivity of CO2 to CH4 conversion. CuI gives the highest total Faradaic efficiency (FE) of 83.2%, with a FE of CH4 up to 57.2% and CH4 partial current density of 60.7 mA cm−2 at −1.08 V versus reversible hydrogen electrode. Theoretical calculations reveal that the shifted d‐band center of Cu site contributes to reduced formation energies of *CH2O and *CH3O intermediates, which is the potential‐determining step of CO2RR and thus facilitates the electrocatalytic CO2 reduction to CH4. This study opens a new avenue for studying the relationship between the coordination microenvironment of active site and electroreduction reaction performance of MOFs.
Exploring the structure−performance relationship of electrocatalytic CO2 reduction on metal–organic frameworks (MOFs) remains a challenge. Herein, a series of stable MOFs (CuCl, CuBr, CuI) are synthesized and comprehensive analysis is undertaken to reveal the relationship between the coordination microenvironment of Cu active site and performance of converting CO2 to CH4.
The 2-body hyperon-nucleon interaction softens the equation of state of neutron star matter and leads to the maximum mass of neutron star to be 1.3-1.6M⊙, which deviates from the recent observation ...with the masses of PSR J0348+0432 (2.01±0.04M⊙) and J0740+6620 (2.14−0.09+0.10M⊙). One attempt is to introduce the more repulsive hyperon-nucleon interaction above the saturation density. A phenomenological Λ potential by fitting the 3-body ΛNN results of chiral effective field theory is implemented into the quantum molecular dynamics transport model to solve the ‘hyperon puzzle’ in neutron stars. It is found that the directed and elliptic flows are sensitive to the high-density hyperon-nucleon potentials in collisions of 197Au + 197Au and 124Sn + 124Sn. The influence of the phenomenological potential on the Λ yields, rapidity distributions and transverse momentum spectra is negligible in comparison with the ones calculated by the well-known relativistic mean-field model. The inclusion of the ΛN, ΣN and ΞN potentials leads to the reduction of hyperon production in the midrapidity region. The Λ directed flows and the slope in the midrapidity region are enhanced with the phenomenological potential and more consistent with the STAR data in collisions of 197Au + 197Au at sNN=3 GeV.
The hyperon dynamics in heavy-ion collisions near threshold energy has been investigated within the quantum molecular dynamics transport model. The isospin and momentum dependent hyperon-nucleon ...potential and the threshold energy correction on the hyperon elementary cross section are included in the model. It is found that the high-density symmetry energy is dependent on the isospin ratios Σ−/Σ+ and Ξ−/Ξ0, in particular in the domain of high kinetic energies. The isospin diffusion in heavy-ion collisions influences the neutron/proton ratio in the high-density region. The Σ−/Σ+ ratio depends on the stiffness of symmetry energy, in particular at the beam energy below the threshold value (Eth=1.58 GeV), i.e., the kinetic energy spectra of the single ratios, excitation functions and energy spectra of the double ratios in the isotopic reactions of 108Sn + 112Sn, 112Sn + 112Sn, 124Sn + 124Sn and 132Sn + 124Sn. The double strangeness ratio Ξ−/Ξ0 weakly depends on the symmetry energy because of the hyperon-hyperon collision mainly contributing the Ξ production below the threshold energy (Eth = 3.72 GeV).
During the artistic journey, creators frequently encounter challenges stemming from pressure, resource constraints, and waning inspiration, all of which can impede their creative flow. Addressing ...these obstacles requires a multifaceted strategy aimed at nurturing creativity throughout the artistic process. Procedural art generation emerges as a viable solution to invigorate artistic creativity. In this study, the deep Q-network (DQN) was constructed to solve the shortage of artistic creativity through its automatic decision-making ability. The model was trained with different types of artistic styles (abstract and minimalism) in WikiArt dataset. The model generates various artistic elements of different styles, forms, or thinking according to the input parameters or constraints, and selects specific colors, textures, or shapes to help the artist maintain focus in the creation process and expand the creativity in the creation process. In order to achieve this goal, in the process of performing the procedural art generation task with DQN, the experiment collected the generation speed, interpretability, and creativity evaluation feedback of each style of art. The feedback results show that the scores of color field painting and minimalism were 83.2, 93.5, 86.3 and 86.6, 91.5, 82.1 respectively. The research shows that employing dynamic mass spectrometry networks enables the automation of the art creation process. This innovative approach facilitates the exploration of diverse creative ideas tailored to various artistic tasks, thereby fostering advancements in art creation and nurturing creativity.
Due to the limitation of the local spatial information in an image, fuzzy c-means clustering algorithms with the local spatial information cannot obtain the satisfying segmentation performance on the ...image heavily contaminated by noise. In order to compensate this drawback of the local spatial information, an effective kind of non-local spatial information is extracted from the image in this paper. In the acquisition of non-local spatial information, the filtering degree parameter h is a very crucial parameter and needs to be set appropriately. Instead of using a single h value for all the pixels, the calculation of the adaptive parameter h for each pixel is done by studying the statistical characteristics in its search window. Therefore, the non-local spatial information obtained by using the adaptive h value for each pixel is called self-tuning non-local spatial information. In this paper, two novel fuzzy clustering algorithms using the self-tuning non-local spatial information are proposed. In the first algorithm framework, a spatial constraint term by utilizing the self-tuning non-local spatial information for each pixel is defined and then introduced into the objective function of FCM. This algorithm is called fuzzy c-means clustering algorithm with self-tuning non-local spatial information (FCM_SNLS). In the second algorithm framework, a novel gray level histogram is constructed by using the self-tuning non-local spatial information for each pixel, and then clustering is performed on this gray level histogram. This algorithm is called fast fuzzy c-means clustering algorithm with self-tuning non-local spatial information (FFCM_SNLS). Experimental results show that these two proposed methods are not only more effective than fuzzy clustering algorithms with the local spatial information in noise suppression and edge preservation, but also more robust than fuzzy clustering algorithms with the non-local spatial information.
We explored whether medical health workers had more psychosocial problems than nonmedical health workers during the COVID-19 outbreak.
An online survey was run from February 19 to March 6, 2020; a ...total of 2,182 Chinese subjects participated. Mental health variables were assessed via the Insomnia Severity Index (ISI), the Symptom Check List-revised (SCL-90-R), and the Patient Health Questionnaire-4 (PHQ-4), which included a 2-item anxiety scale and a 2-item depression scale (PHQ-2).
Compared with nonmedical health workers (n = 1,255), medical health workers (n = 927) had a higher prevalence of insomnia (38.4 vs. 30.5%, p < 0.01), anxiety (13.0 vs. 8.5%, p < 0.01), depression (12.2 vs. 9.5%; p< 0.04), somatization (1.6 vs. 0.4%; p < 0.01), and obsessive-compulsive symptoms (5.3 vs. 2.2%; p < 0.01). They also had higher total scores of ISI, GAD-2, PHQ-2, and SCL-90-R obsessive-compulsive symptoms (p ≤ 0.01). Among medical health workers, having organic disease was an independent factor for insomnia, anxiety, depression, somatization, and obsessive-compulsive symptoms (p < 0.05 or 0.01). Living in rural areas, being female, and being at risk of contact with COVID-19 patients were the most common risk factors for insomnia, anxiety, obsessive-compulsive symptoms, and depression (p < 0.01 or 0.05). Among nonmedical health workers, having organic disease was a risk factor for insomnia, depression, and obsessive-compulsive symptoms (p < 0.01 or 0.05).
During the COVID-19 outbreak, medical health workers had psychosocial problems and risk factors for developing them. They were in need of attention and recovery programs.
Fluorine‐containing moieties are widely used in the pharmaceutical, agrochemical, and material fields. Thus, these structures are of immense interest in the fields of organic synthesis and medicinal ...chemistry. Among various fluorinated groups, the difluoromethyl unit has drawn increasing attention due to its unique pharmaceutical properties. In recent years, several methods for the synthesis of difluoromethylated compounds have been rapidly developed. However, most of these methods treat aromatic compounds with excess difluoromethylating reagents, which often contain organometallic compounds, so these transformations are generally less environmentally friendly and atom‐economical. In this review, we summarize the recent development of new methods for the synthesis of difluoromethyl motifs or difluoroalkenes from trifluoromethylated aromatic compounds or trifluoromethyl alkenes via single C(sp3)−F bond cleavage.
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