Mechanistic insights and catalytic enhancement of phenolic wastewater supercritical water gasification: A combined experiment and density functional theory study.

Supercritical water gasification technology provides a favorable technology to achieve pollution elimination and resource utilization of phenolic wastewater. In this study, the reaction mechanism of phenolic wastewater supercritical water gasification was investigated using a combination of experimental and computational methods. Five reaction channels were identified to elucidate the underlying pathway of phenol decomposition. Importantly, the rate-determining step was found to be the dearomatization reaction. By integrating computational and experimental analyses, it was found that phenol decomposition via the path with the lowest energy barrier generates cyclopentadiene, featuring a dearomatization barrier of 70.97 kcal/mol. Additionally, supercritical water plays a catalytic role in the dearomatization process by facilitating proton transfer. Based on the obtained reaction pathway, alkali salts (Na2CO3 and K2CO3) are employed as a catalyst to diminish the energy barrier of the rate-determining step to 40.00 kcal/mol and 37.14 kcal/mol. Alkali salts catalysis significantly improved carbon conversion and pollutant removal from phenolic wastewater, increasing CGE from 58.44% to 93.55% and COD removal efficiency from 94.11% to 99.79%. Overall, this study provides a comprehensive understanding of the decomposition mechanism of phenolic wastewater in supercritical water.

Relationship between individual differences in pain empathy and task- and resting-state EEG.

Pain empathy is a complex form of psychological inference that enables us to understand how others feel in the context of pain. Since pain empathy may be grounded in our own pain experiences, it exhibits huge inter-individual variability. However, the neural mechanisms behind the individual differences in pain empathy and its association with pain perception are still poorly understood. In this study, we aimed to characterize brain mechanisms associated with individual differences in pain empathy in adult participants (n = 24). The 32-channel electroencephalography (EEG) was recorded at rest and during a pain empathy task, and participants viewed static visual stimuli of the limbs submitted to painful and nonpainful stimulation to solicit empathy. The pain sensitivity of each participant was measured using a series of direct current stimulations. In our results, the N2 of Fz and the LPP of P3 and P4 were affected by painful pictures. We found that both delta and alpha bands in the frontal and parietal cortex were involved in the regulation of pain empathy. For the delta band, a close relationship was found between average power, either in the resting or task state, and individual differences in pain empathy. It suggested that the spectral power in Fz's delta band may reflect subjective pain empathy across individuals. For the alpha band, the functional connectivity between Fz and P3 under painful picture stimulation was correlated to individuals' pain sensitivity. It indicated that the alpha band may reflect individual differences in pain sensitivity and be involved in pain empathy processing. Our results suggested the distinct role of the delta and alpha bands of EEG signals in pain empathy processing and may deepen our understanding of the neural mechanisms underpinning pain empathy.

Characteristics of pain empathic networks in healthy and primary dysmenorrhea women: an fMRI study.

Pain empathy enables us to understand and share how others feel pain. Few studies have investigated pain empathy-related functional interactions at the whole-brain level across all networks. Additionally, women with primary dysmenorrhea (PDM) have abnormal pain empathy, and the association among the whole-brain functional network, pain, and pain empathy remain unclear. Using resting-state functional magnetic resonance imaging (fMRI) and machine learning analysis, we identified the brain functional network connectivity (FNC)-based features that are associated with pain empathy in two studies. Specifically, Study 1 examined 41 healthy controls (HCs), while Study 2 investigated 45 women with PDM. Additionally, in Study 3, a classification analysis was performed to examine the differences in FNC between HCs and women with PDM. Pain empathy was evaluated using a visual stimuli experiment, and trait and state of menstrual pain were recorded. In Study 1, the results showed that pain empathy in HCs relied on dynamic interactions across whole-brain networks and was not concentrated in a single or two brain networks, suggesting the dynamic cooperation of networks for pain empathy in HCs. In Study 2, PDM exhibited a distinctive network for pain empathy. The features associated with pain empathy were concentrated in the sensorimotor network (SMN). In Study 3, the SMN-related dynamic FNC could accurately distinguish women with PDM from HCs and exhibited a significant association with trait menstrual pain. This study may deepen our understanding of the neural mechanisms underpinning pain empathy and suggest that menstrual pain may affect pain empathy through maladaptive dynamic interaction between brain networks.