Boosting Electrocatalytic Carbon Dioxide Reduction via Self-Relaxation of Asymmetric Coordination in Fe-Based Single Atom Catalyst.

Addressing the limitations arising from the consistent catalytic behavior observed for various intermediates during the electrochemical carbon dioxide reduction reaction (CO2 RR) poses a significant challenge in the optimization of catalytic activity. In this study, we aimed to address this challenge by constructing an asymmetric coordination Fe single atom catalyst (SCA) with a dynamically evolved structure. Our catalyst, consisting of a Fe atom coordinated with one S atom and three N atoms (Fe-S1 N3 ), exhibited exceptional selectivity (CO Faradaic efficiency of 99.02 %) and demonstrated a high intrinsic activity (TOF of 7804.34 h-1 ), and remarkable stability. Using operando XAFS spectra and Density Functional Theory (DFT) calculations, we elucidated the self-relaxation of geometric distortion and dynamic evolution of bond lengths within the catalyst. These structure changes enabled independent regulation of the *COOH and *CO intermediate adsorption energies, effectively breaking the linear scale relationship and enhancing the intrinsic activity of CO2 RR. This study provides valuable insights into the dynamic evolution of SACs and paves the way for targeted catalyst designs aimed to disrupt the linear scaling relationships.

Atomic Dispersed Hetero-Pairs for Enhanced Electrocatalytic CO2 Reduction.

Electrochemical carbon dioxide reduction reaction (CO2RR) involves a variety of intermediates with highly correlated reaction and ad-desorption energies, hindering optimization of the catalytic activity. For example, increasing the binding of the *COOH to the active site will generally increase the *CO desorption energy. Breaking this relationship may be expected to dramatically improve the intrinsic activity of CO2RR, but remains an unsolved challenge. Herein, we addressed this conundrum by constructing a unique atomic dispersed hetero-pair consisting of Mo-Fe di-atoms anchored on N-doped carbon carrier. This system shows an unprecedented CO2RR intrinsic activity with TOF of 3336 h-1, high selectivity toward CO production, Faradaic efficiency of 95.96% at - 0.60 V and excellent stability. Theoretical calculations show that the Mo-Fe diatomic sites increased the *COOH intermediate adsorption energy by bridging adsorption of *COOH intermediates. At the same time, d-d orbital coupling in the Mo-Fe di-atom results in electron delocalization and facilitates desorption of *CO intermediates. Thus, the undesirable correlation between these steps is broken. This work provides a promising approach, specifically the use of di-atoms, for breaking unfavorable relationships based on understanding of the catalytic mechanisms at the atomic scale.

Comparing product quality between translation and paraphrasing: Using NLP-assisted evaluation frameworks.

Translation and paraphrasing, as typical forms in second language (L2) communication, have been considered effective learning methods in second language acquisition (SLA). While many studies have investigated their similarities and differences in a process-oriented approach, little attention has been paid to the correlation in product quality between them, probably due to difficulties in assessing the quality of translation and paraphrasing. Current quality evaluation methods tend to be either subjective and one-sided or lack consistency and standardization. To address these limitations, we proposed preliminary evaluation frameworks for translation and paraphrasing by incorporating indices from natural language processing (NLP) tools into teachers' rating rubrics and further compared the product quality of the two activities. Twenty-nine translators were recruited to perform a translation task (translating from Chinese to English) and a paraphrasing task (paraphrasing in English). Their output products were recorded by key-logging technique and graded by three professional translation teachers by using a 10-point Likert Scale. This rating process adopted rubrics consisting of both holistic and analytical assessments. Besides, indices containing textual features from lexical and syntactic levels were extracted from TAASSC and TAALES. We identified indices that effectively predicted product quality using Pearson's correlation analysis and combined them with expert evaluation rubrics to establish NLP-assisted evaluation frameworks for translation and paraphrasing. With the help of these frameworks, we found a closely related performance between the two tasks, evidenced by several shared predictive indices in lexical sophistication and strong positive correlations between translated and paraphrased text quality according to all the rating metrics. These similarities suggest a shared language competence and mental strategies in different types of translation activities and perhaps in other forms of language tasks. Meanwhile, we also observed differences in the most salient textual features between translations and paraphrases, mainly due to the different processing costs required by the two tasks. These findings enrich our understanding of the shared ground and divergences in product quality between translation and paraphrasing and shed light on the pedagogical application of translation activities in classroom teaching. Moreover, the proposed evaluation framework can also bring insights into the development of standardized evaluation frameworks in translation and paraphrasing in the future.

A cognitive inquiry into similarities and differences between translation and paraphrase: Evidence from eye movement data.

Intralingual translation has long been peripheral to empirical studies of translation. Considering its many similarities with interlingual translation, also described as translation proper, we adopted eye-tracking technology to investigate the cognitive process during translation and paraphrase, an exemplification of intralingual translation. Twenty-four postgraduate students were required to perform four types of tasks (Chinese paraphrase, English-Chinese translation, English paraphrase, Chinese-English translation) for source texts (ST) of different genres. Their eye movements were recorded for analysis of the cognitive effort and attention distribution pattern. The result demonstrated that: (1) Translation elicited significantly greater cognitive efforts than paraphrase; (2) Differences between translation and paraphrase on cognitive effort were modulated by text genre and target language; (3) Translation and paraphrase did not differ strikingly in terms of attention distribution. This process-oriented study confirmed higher cognitive efforts in inter-lingual translation, which was likely due to the additional complexity of bilingual transfer. Moreover, it revealed significant modulating effects of text genre and target language.

A Modified Brain MR Image Segmentation and Bias Field Estimation Model Based on Local and Global Information.

Because of the poor radio frequency coil uniformity and gradient-driven eddy currents, there is much noise and intensity inhomogeneity (bias) in brain magnetic resonance (MR) image, and it severely affects the segmentation accuracy. Better segmentation results are difficult to achieve by traditional methods; therefore, in this paper, a modified brain MR image segmentation and bias field estimation model based on local and global information is proposed. We first construct local constraints including image neighborhood information in Gaussian kernel mapping space, and then the complete regularization is established by introducing nonlocal spatial information of MR image. The weighting between local and global information is automatically adjusted according to image local information. At the same time, bias field information is coupled with the model, and it makes the model reduce noise interference but also can effectively estimate the bias field information. Experimental results demonstrate that the proposed algorithm has strong robustness to noise and bias field is well corrected.