This article discusses the copyright issues involved in China's artificial intelligence-generated works,focusing on two core controversial points:"copyrightability"and"copyright attribution".Th...This article discusses the copyright issues involved in China's artificial intelligence-generated works,focusing on two core controversial points:"copyrightability"and"copyright attribution".The article systematically reviews the different views of academic circles and judicial practice at home and abroad:in terms of copyrightability,supporters believe that the works generated by artificial intelligence meet the basic standards of originality and intellectual creation,while opponents emphasize that they lack human subjectivity and direct intellectual control.In terms of copyright attribution,the main views include the theory of artificial intelligence attribution,the theory of artificial intelligence user attribution and the theory of investor attribution.The author believes that the works generated by artificial intelligence should be copyrighted,and proposes to adopt the practice of"user ownership as the principle".This method will include clarifying the legislation on the nature of the work,establishing a traceability mechanism,and limiting the protection period to a certain range to balance innovation incentives and public interests,so as to provide theoretical reference for China's artificial intelligence copyright framework.展开更多
The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situati...The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situation is raising significant concerns regarding the integrity and authenticity of academic work.In light of the above,the current research evaluates the effectiveness of Bidirectional Long Short-TermMemory(BiLSTM)networks enhanced with pre-trained GloVe(Global Vectors for Word Representation)embeddings to detect AIgenerated scientific Abstracts drawn from the AI-GA(Artificial Intelligence Generated Abstracts)dataset.Two core BiLSTM variants were assessed:a single-layer approach and a dual-layer design,each tested under static or adaptive embeddings.The single-layer model achieved nearly 97%accuracy with trainable GloVe,occasionally surpassing the deeper model.Despite these gains,neither configuration fully matched the 98.7%benchmark set by an earlier LSTMWord2Vec pipeline.Some runs were over-fitted when embeddings were fine-tuned,whereas static embeddings offered a slightly lower yet stable accuracy of around 96%.This lingering gap reinforces a key ethical and procedural concern:relying solely on automated tools,such as Turnitin’s AI-detection features,to penalize individuals’risks and unjust outcomes.Misclassifications,whether legitimate work is misread as AI-generated or engineered text,evade detection,demonstrating that these classifiers should not stand as the sole arbiters of authenticity.Amore comprehensive approach is warranted,one which weaves model outputs into a systematic process supported by expert judgment and institutional guidelines designed to protect originality.展开更多
The rapid advancement of large language models(LLMs)has driven the pervasive adoption of AI-generated content(AIGC),while also raising concerns about misinformation,academic misconduct,biased or harmful content,and ot...The rapid advancement of large language models(LLMs)has driven the pervasive adoption of AI-generated content(AIGC),while also raising concerns about misinformation,academic misconduct,biased or harmful content,and other risks.Detecting AI-generated text has thus become essential to safeguard the authenticity and reliability of digital information.This survey reviews recent progress in detection methods,categorizing approaches into passive and active categories based on their reliance on intrinsic textual features or embedded signals.Passive detection is further divided into surface linguistic feature-based and language model-based methods,whereas active detection encompasses watermarking-based and semantic retrieval-based approaches.This taxonomy enables systematic comparison of methodological differences in model dependency,applicability,and robustness.A key challenge for AI-generated text detection is that existing detectors are highly vulnerable to adversarial attacks,particularly paraphrasing,which substantially compromises their effectiveness.Addressing this gap highlights the need for future research on enhancing robustness and cross-domain generalization.By synthesizing current advances and limitations,this survey provides a structured reference for the field and outlines pathways toward more reliable and scalable detection solutions.展开更多
Zinc-ion batteries(ZIBs)are inexpensive and safe,but side reactions on the Zn anode and Zn dendrite growth hinder their practical applications.In this study,1,3,5-triformylphloroglycerol(Tp)and various diamine monomer...Zinc-ion batteries(ZIBs)are inexpensive and safe,but side reactions on the Zn anode and Zn dendrite growth hinder their practical applications.In this study,1,3,5-triformylphloroglycerol(Tp)and various diamine monomers(p-phenylenediamine(Pa),benzidine(BD),and 4,4"-diamino-p-terphenyl(DATP))were used to synthesize a series of two-dimensional covalent-organic frameworks(COFs).The resulting COFs were named TpPa,TpBD,and TpDATP,respectively,and they showed uniform zincophilic sites,different pore sizes,and high Young's moduli on the Zn anode.Among them,TpPa and TpBD showed lower surface work functions and higher ion transfer numbers,which were conducive to uniform galvanizing/stripping zinc and inhibited dendrite growth.Theoretical calculations showed that TpPa and TpBD had wider negative potential region and greater adsorption capacity for Zn2+than TpDATP,providing more electron donor sites to coordinate with Zn^(2+).Symmetric cells protected by TpPa and TpBD stably cycled for more than 2300 h,whereas TpDATP@Zn and the bare zinc symmetric cells failed after around 150 and200 h.The full cells containing TpPa and TpBD modification layers also showed excellent cycling capacity at 1 A/g.This study provides comprehensive insights into the construction of highly reversible Zn anodes via COF modification layers for advanced rechargeable ZIBs.展开更多
In this study,it aims at examining the differences between humangenerated and AI-generated texts in IELTS Writing Task 2.It especially focuses on lexical resourcefulness,grammatical accuracy,and contextual appropriate...In this study,it aims at examining the differences between humangenerated and AI-generated texts in IELTS Writing Task 2.It especially focuses on lexical resourcefulness,grammatical accuracy,and contextual appropriateness.We analyzed 20 essays,including 10 human written ones by Chinese university students who have achieved an IELTS writing score ranging from 5.5 to 6.0,and 10 ChatGPT-4 Turbo-generated ones,using a mixed-methods approach,through corpus-based tools(NLTK,SpaCy,AntConc)and qualitative content analysis.Results showed that AI texts exhibited superior grammatical accuracy(0.4%–3%error rates for AI vs.20–26%for university students)but higher lexical repetition(17.2%to 23.25%for AI vs.17.68%for university students)and weaker contextual adaptability(3.33/10–3.69/10 for AI vs.3.23/10 to 4.14/10 for university students).While AI’s grammatical precision supports its utility as a corrective tool,human writers outperformed AI in lexical diversity and task-specific nuance.The findings advocate for a hybrid pedagogical model that leverages AI’s strengths in error detection while retaining human instruction for advanced lexical and contextual skills.Limitations include the small corpus and single-AI-model focus,suggesting future research with diverse datasets and longitudinal designs.展开更多
This conceptual study proposes a pedagogical framework that integrates Generative Artificial Intelligence tools(AIGC)and Chain-of-Thought(CoT)reasoning,grounded in the cognitive apprenticeship model,for the Pragmatics...This conceptual study proposes a pedagogical framework that integrates Generative Artificial Intelligence tools(AIGC)and Chain-of-Thought(CoT)reasoning,grounded in the cognitive apprenticeship model,for the Pragmatics and Translation course within Master of Translation and Interpreting(MTI)programs.A key feature involves CoT reasoning exercises,which require students to articulate their step-by-step translation reasoning.This explicates cognitive processes,enhances pragmatic awareness,translation strategy development,and critical reflection on linguistic choices and context.Hypothetical activities exemplify its application,including comparative analysis of AI and human translations to examine pragmatic nuances,and guided exercises where students analyze or critique the reasoning traces generated by Large Language Models(LLMs).Ethically grounded,the framework positions AI as a supportive tool,thereby ensuring human translators retain the central decision-making role and promoting critical evaluation of machine-generated suggestions.Potential challenges,such as AI biases,ethical concerns,and overreliance,are addressed through strategies including bias-awareness discussions,rigorous accuracy verification,and a strong emphasis on human accountability.Future research will involve piloting the framework to empirically evaluate its impact on learners’pragmatic competence and translation skills,followed by iterative refinements to advance evidence-based translation pedagogy.展开更多
During the past few decades,we have witnessed the phenomenon of constant warming occurring everywhere on the globe.Cities have suffered from urban warming to a greater extent than any other part of the world,and Kolka...During the past few decades,we have witnessed the phenomenon of constant warming occurring everywhere on the globe.Cities have suffered from urban warming to a greater extent than any other part of the world,and Kolkata has one of the highest levels of urban warming of any city around the world.In Kolkata,73%of the buildings are residential,and it is this type of building that contributes to a significant amount of this warming.With the city of Kolkata as the case study,this paper aims at understanding the multiple domains of urban heat islands and thermal comfort within the context of the city,from a macro perspective of an urban heat island down to a micro perspective of a building level,with the ultimate aim of mitigating global warming through this study.Various research works have been undertaken in India and abroad to understand the individual as well as composite effect of various building components on the indoor thermal comfort.Researches have also been undertaken to compare and comprehend the differential thermal comfort of old indigenous residences with that of the new residential buildings.Hence,this paper discusses methods that have been applied in past works to evaluate the thermal comfort of old and new residential buildings in a non-subjective manner,without having recourse to user feedback,in the final segment that views the process of learning from comparing old and new residential buildings.展开更多
Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first c...Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first collected book reviews from these two well-known websites by Python.Through topic analysis of these reviews,we identified recurring topics,including details of her translated works and appreciation of their translation quality.Then,employing sentiment and content analysis methods,the paper explored the emotional attitudes and the specific thoughts of readers toward Can Xue and her translated works.The fingdings revealed that,among the 408 reviews,though the reception of Can Xue’s translated works was relatively positive,the current level of attention and recognition remains insufficient.However,based on the research results,the paper can derive valuable insights into the translation and dissemination processes such as adjusting translation and dissemination strategies,so that the global reach of Chinese literature and culture can be better facilitated.展开更多
This study examined the relationship between inclusive leadership and authenticity at work in racial minority groups of South Africa,taking into account the mediating role of psychological safety and the moderator rol...This study examined the relationship between inclusive leadership and authenticity at work in racial minority groups of South Africa,taking into account the mediating role of psychological safety and the moderator role of gender,in that relationship.The sample was composed of 94 employees predominantly working in the professional services sector from South Africa(41.5%females;mean age=37.1),who self-identified as racial minority groups(coloured/black/Indian).Results indicate that inclusive leadership has no direct effect on authenticity at work;however,psychological safety fully mediates this relationship.Regarding the moderation effect of gender,results showed that males are more likely to diminish their self-alienation(a specific component of authenticity at work)when levels of psychological safety are higher.These results are consistent with Social Identity Theory,which posits that individuals derive part of their self-concept from their membership in social groups.In contexts where inclusive leadership fosters psychological safety,individuals(particularly men in traditionally male-dominated work environments)may feel a stronger sense of belonging and group identity,which in turn enhances their willingness to express their authentic selves and reduces self-alienation.Practical implications for companies include the need to improve leadership styles to foster more of an inclusive and psychologically safe culture,where minority groups can be authentic and flourish.展开更多
Surface properties of crystals are critical in many fields,including electrochemistry and photoelectronics,the efficient prediction of which can expedite the design and optimization of catalysts,batteries,alloys etc.H...Surface properties of crystals are critical in many fields,including electrochemistry and photoelectronics,the efficient prediction of which can expedite the design and optimization of catalysts,batteries,alloys etc.However,we are still far from realizing this vision due to the rarity of surface property-related databases,especially for multicomponent compounds,due to the large sample spaces and limited computing resources.In this work,we present a surface emphasized multi-task crystal graph convolutional neural network(SEM-CGCNN)to predict multiple surface properties simultaneously from crystal structures.The model is evaluated on a dataset of 3526 surface energies and work functions of binary magnesium intermetallics obtained through first-principles calculations,and obvious improvements are observed both in efficiency and accuracy over the original CGCNN model.By transferring the pre-trained model to the datasets of pure metals and other intermetallics,the fine-tuned SEM-CGCNN outperforms learning from scratch and can be further applied to other surface properties and materials systems.This study could be a paradigm for the end-to-end mapping of atomic structures to anisotropic surface properties of crystals,which provides an efficient framework to understand and screen materials with desired surface characteristics.展开更多
In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhausti...In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.展开更多
文摘This article discusses the copyright issues involved in China's artificial intelligence-generated works,focusing on two core controversial points:"copyrightability"and"copyright attribution".The article systematically reviews the different views of academic circles and judicial practice at home and abroad:in terms of copyrightability,supporters believe that the works generated by artificial intelligence meet the basic standards of originality and intellectual creation,while opponents emphasize that they lack human subjectivity and direct intellectual control.In terms of copyright attribution,the main views include the theory of artificial intelligence attribution,the theory of artificial intelligence user attribution and the theory of investor attribution.The author believes that the works generated by artificial intelligence should be copyrighted,and proposes to adopt the practice of"user ownership as the principle".This method will include clarifying the legislation on the nature of the work,establishing a traceability mechanism,and limiting the protection period to a certain range to balance innovation incentives and public interests,so as to provide theoretical reference for China's artificial intelligence copyright framework.
文摘The increasing fluency of advanced language models,such as GPT-3.5,GPT-4,and the recently introduced DeepSeek,challenges the ability to distinguish between human-authored and AI-generated academic writing.This situation is raising significant concerns regarding the integrity and authenticity of academic work.In light of the above,the current research evaluates the effectiveness of Bidirectional Long Short-TermMemory(BiLSTM)networks enhanced with pre-trained GloVe(Global Vectors for Word Representation)embeddings to detect AIgenerated scientific Abstracts drawn from the AI-GA(Artificial Intelligence Generated Abstracts)dataset.Two core BiLSTM variants were assessed:a single-layer approach and a dual-layer design,each tested under static or adaptive embeddings.The single-layer model achieved nearly 97%accuracy with trainable GloVe,occasionally surpassing the deeper model.Despite these gains,neither configuration fully matched the 98.7%benchmark set by an earlier LSTMWord2Vec pipeline.Some runs were over-fitted when embeddings were fine-tuned,whereas static embeddings offered a slightly lower yet stable accuracy of around 96%.This lingering gap reinforces a key ethical and procedural concern:relying solely on automated tools,such as Turnitin’s AI-detection features,to penalize individuals’risks and unjust outcomes.Misclassifications,whether legitimate work is misread as AI-generated or engineered text,evade detection,demonstrating that these classifiers should not stand as the sole arbiters of authenticity.Amore comprehensive approach is warranted,one which weaves model outputs into a systematic process supported by expert judgment and institutional guidelines designed to protect originality.
基金supported in part by the Science and Technology Innovation Program of Hunan Province under Grant 2025RC3166the National Natural Science Foundation of China under Grant 62572176the National Key R&D Program of China under Grant 2024YFF0618800.
文摘The rapid advancement of large language models(LLMs)has driven the pervasive adoption of AI-generated content(AIGC),while also raising concerns about misinformation,academic misconduct,biased or harmful content,and other risks.Detecting AI-generated text has thus become essential to safeguard the authenticity and reliability of digital information.This survey reviews recent progress in detection methods,categorizing approaches into passive and active categories based on their reliance on intrinsic textual features or embedded signals.Passive detection is further divided into surface linguistic feature-based and language model-based methods,whereas active detection encompasses watermarking-based and semantic retrieval-based approaches.This taxonomy enables systematic comparison of methodological differences in model dependency,applicability,and robustness.A key challenge for AI-generated text detection is that existing detectors are highly vulnerable to adversarial attacks,particularly paraphrasing,which substantially compromises their effectiveness.Addressing this gap highlights the need for future research on enhancing robustness and cross-domain generalization.By synthesizing current advances and limitations,this survey provides a structured reference for the field and outlines pathways toward more reliable and scalable detection solutions.
基金financially supported by the National Natural Science Foundation of China(62464010)Spring City Plan-Special Program for Young Talents(K202005007)+3 种基金Yunnan Talents Support Plan for Yong Talents(XDYC-QNRC-2022-0482)Yunnan Local Colleges Applied Basic Research Projects(202101BA070001-138)Key Laboratory of Artificial Microstructures in Yunnan Higher EducationFrontier Research Team of Kunming University 2023。
文摘Zinc-ion batteries(ZIBs)are inexpensive and safe,but side reactions on the Zn anode and Zn dendrite growth hinder their practical applications.In this study,1,3,5-triformylphloroglycerol(Tp)and various diamine monomers(p-phenylenediamine(Pa),benzidine(BD),and 4,4"-diamino-p-terphenyl(DATP))were used to synthesize a series of two-dimensional covalent-organic frameworks(COFs).The resulting COFs were named TpPa,TpBD,and TpDATP,respectively,and they showed uniform zincophilic sites,different pore sizes,and high Young's moduli on the Zn anode.Among them,TpPa and TpBD showed lower surface work functions and higher ion transfer numbers,which were conducive to uniform galvanizing/stripping zinc and inhibited dendrite growth.Theoretical calculations showed that TpPa and TpBD had wider negative potential region and greater adsorption capacity for Zn2+than TpDATP,providing more electron donor sites to coordinate with Zn^(2+).Symmetric cells protected by TpPa and TpBD stably cycled for more than 2300 h,whereas TpDATP@Zn and the bare zinc symmetric cells failed after around 150 and200 h.The full cells containing TpPa and TpBD modification layers also showed excellent cycling capacity at 1 A/g.This study provides comprehensive insights into the construction of highly reversible Zn anodes via COF modification layers for advanced rechargeable ZIBs.
基金supported by the Macao Science and Technology Development Fund(FDCT)(No.0071/2023/RIB3)Joint Research Funding Program between the Macao Science and Technology Development Fund(FDCT)and the Department of Science and Technology of Guangdong Province(FDCTGDST)(No.0003-2024-AGJ).
文摘In this study,it aims at examining the differences between humangenerated and AI-generated texts in IELTS Writing Task 2.It especially focuses on lexical resourcefulness,grammatical accuracy,and contextual appropriateness.We analyzed 20 essays,including 10 human written ones by Chinese university students who have achieved an IELTS writing score ranging from 5.5 to 6.0,and 10 ChatGPT-4 Turbo-generated ones,using a mixed-methods approach,through corpus-based tools(NLTK,SpaCy,AntConc)and qualitative content analysis.Results showed that AI texts exhibited superior grammatical accuracy(0.4%–3%error rates for AI vs.20–26%for university students)but higher lexical repetition(17.2%to 23.25%for AI vs.17.68%for university students)and weaker contextual adaptability(3.33/10–3.69/10 for AI vs.3.23/10 to 4.14/10 for university students).While AI’s grammatical precision supports its utility as a corrective tool,human writers outperformed AI in lexical diversity and task-specific nuance.The findings advocate for a hybrid pedagogical model that leverages AI’s strengths in error detection while retaining human instruction for advanced lexical and contextual skills.Limitations include the small corpus and single-AI-model focus,suggesting future research with diverse datasets and longitudinal designs.
文摘This conceptual study proposes a pedagogical framework that integrates Generative Artificial Intelligence tools(AIGC)and Chain-of-Thought(CoT)reasoning,grounded in the cognitive apprenticeship model,for the Pragmatics and Translation course within Master of Translation and Interpreting(MTI)programs.A key feature involves CoT reasoning exercises,which require students to articulate their step-by-step translation reasoning.This explicates cognitive processes,enhances pragmatic awareness,translation strategy development,and critical reflection on linguistic choices and context.Hypothetical activities exemplify its application,including comparative analysis of AI and human translations to examine pragmatic nuances,and guided exercises where students analyze or critique the reasoning traces generated by Large Language Models(LLMs).Ethically grounded,the framework positions AI as a supportive tool,thereby ensuring human translators retain the central decision-making role and promoting critical evaluation of machine-generated suggestions.Potential challenges,such as AI biases,ethical concerns,and overreliance,are addressed through strategies including bias-awareness discussions,rigorous accuracy verification,and a strong emphasis on human accountability.Future research will involve piloting the framework to empirically evaluate its impact on learners’pragmatic competence and translation skills,followed by iterative refinements to advance evidence-based translation pedagogy.
文摘During the past few decades,we have witnessed the phenomenon of constant warming occurring everywhere on the globe.Cities have suffered from urban warming to a greater extent than any other part of the world,and Kolkata has one of the highest levels of urban warming of any city around the world.In Kolkata,73%of the buildings are residential,and it is this type of building that contributes to a significant amount of this warming.With the city of Kolkata as the case study,this paper aims at understanding the multiple domains of urban heat islands and thermal comfort within the context of the city,from a macro perspective of an urban heat island down to a micro perspective of a building level,with the ultimate aim of mitigating global warming through this study.Various research works have been undertaken in India and abroad to understand the individual as well as composite effect of various building components on the indoor thermal comfort.Researches have also been undertaken to compare and comprehend the differential thermal comfort of old indigenous residences with that of the new residential buildings.Hence,this paper discusses methods that have been applied in past works to evaluate the thermal comfort of old and new residential buildings in a non-subjective manner,without having recourse to user feedback,in the final segment that views the process of learning from comparing old and new residential buildings.
基金supported by the 2023 Youth Fund for Humanities and Social Sciences Research by the Ministry of Education of the People’s Republic of China(Grant No.23YJC740004).
文摘Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first collected book reviews from these two well-known websites by Python.Through topic analysis of these reviews,we identified recurring topics,including details of her translated works and appreciation of their translation quality.Then,employing sentiment and content analysis methods,the paper explored the emotional attitudes and the specific thoughts of readers toward Can Xue and her translated works.The fingdings revealed that,among the 408 reviews,though the reception of Can Xue’s translated works was relatively positive,the current level of attention and recognition remains insufficient.However,based on the research results,the paper can derive valuable insights into the translation and dissemination processes such as adjusting translation and dissemination strategies,so that the global reach of Chinese literature and culture can be better facilitated.
文摘This study examined the relationship between inclusive leadership and authenticity at work in racial minority groups of South Africa,taking into account the mediating role of psychological safety and the moderator role of gender,in that relationship.The sample was composed of 94 employees predominantly working in the professional services sector from South Africa(41.5%females;mean age=37.1),who self-identified as racial minority groups(coloured/black/Indian).Results indicate that inclusive leadership has no direct effect on authenticity at work;however,psychological safety fully mediates this relationship.Regarding the moderation effect of gender,results showed that males are more likely to diminish their self-alienation(a specific component of authenticity at work)when levels of psychological safety are higher.These results are consistent with Social Identity Theory,which posits that individuals derive part of their self-concept from their membership in social groups.In contexts where inclusive leadership fosters psychological safety,individuals(particularly men in traditionally male-dominated work environments)may feel a stronger sense of belonging and group identity,which in turn enhances their willingness to express their authentic selves and reduces self-alienation.Practical implications for companies include the need to improve leadership styles to foster more of an inclusive and psychologically safe culture,where minority groups can be authentic and flourish.
基金supported by the National Key R&D Program(No.2021YFB3501002)supported by the Ministry of Science and Technology of China,National Natural Science Foundation of China(No.51825101,52127801).
文摘Surface properties of crystals are critical in many fields,including electrochemistry and photoelectronics,the efficient prediction of which can expedite the design and optimization of catalysts,batteries,alloys etc.However,we are still far from realizing this vision due to the rarity of surface property-related databases,especially for multicomponent compounds,due to the large sample spaces and limited computing resources.In this work,we present a surface emphasized multi-task crystal graph convolutional neural network(SEM-CGCNN)to predict multiple surface properties simultaneously from crystal structures.The model is evaluated on a dataset of 3526 surface energies and work functions of binary magnesium intermetallics obtained through first-principles calculations,and obvious improvements are observed both in efficiency and accuracy over the original CGCNN model.By transferring the pre-trained model to the datasets of pure metals and other intermetallics,the fine-tuned SEM-CGCNN outperforms learning from scratch and can be further applied to other surface properties and materials systems.This study could be a paradigm for the end-to-end mapping of atomic structures to anisotropic surface properties of crystals,which provides an efficient framework to understand and screen materials with desired surface characteristics.
基金funded by the Huaiyin Institute of Technology—Institute of Smart Energy.
文摘In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.
