Pub Date : 2025-01-01DOI: 10.1016/j.cossms.2024.101213
Seyedeh-Arefeh Safavi-Mirmahalleh , Mohsen Khodadadi Yazdi , Mohammad Reza Saeb , Mehdi Salami-Kalajahi
Flexible multimodal sensors have garnered continued attention due to their tunable structural performance and sensitivity to electric signals, adaptability to various environments, and outstanding mechanical properties. However, the limited self-healing capabilities, degradation, and reversible self-adhesion of sensors made from rubbers, elastomers, and other polymers have hindered their widespread application. Flexible sensors based on hydrogels, which offer exceptional stretchability, flexibility, and biocompatibility, could provide a solution. However, their reliance on external energy sources limits their potential. Thus, efforts have been made to develop conductive hydrogels by incorporating functional groups, additives, or nanofillers into the hydrogel network, which has led to multifunctional wearable sensing capabilities. This review discusses recent advancements in the use of hydrogels in self-powered sensors, including strain/pressure sensors, electronic skin sensors, pressure/strain sensors, temperature monitoring and humidity monitoring applications. Moreover, it focuses on the mechanisms of energy conversion in self-powered sensors. It also provides a concise overview of the various synthesis methods used in developing conductive hydrogels. The current review also outlines the present challenges, besides suggesting potential pathways ahead for future advancement.
{"title":"Conductive Hydrogels: Bioelectronics and Environmental Applications","authors":"Seyedeh-Arefeh Safavi-Mirmahalleh , Mohsen Khodadadi Yazdi , Mohammad Reza Saeb , Mehdi Salami-Kalajahi","doi":"10.1016/j.cossms.2024.101213","DOIUrl":"10.1016/j.cossms.2024.101213","url":null,"abstract":"<div><div>Flexible multimodal sensors have garnered continued attention due to their tunable structural performance and sensitivity to electric signals, adaptability to various environments, and outstanding mechanical properties. However, the limited self-healing capabilities, degradation, and reversible self-adhesion of sensors made from rubbers, elastomers, and other polymers have hindered their widespread application. Flexible sensors based on hydrogels, which offer exceptional stretchability, flexibility, and biocompatibility, could provide a solution. However, their reliance on external energy sources limits their potential. Thus, efforts have been made to develop conductive hydrogels by incorporating functional groups, additives, or nanofillers into the hydrogel network, which has led to multifunctional wearable sensing capabilities. This review discusses recent advancements in the use of hydrogels in self-powered sensors, including strain/pressure sensors, electronic skin sensors, pressure/strain sensors, temperature monitoring and humidity monitoring applications. Moreover, it focuses on the mechanisms of energy conversion in self-powered sensors. It also provides a concise overview of the various synthesis methods used in developing conductive hydrogels. The current review also outlines the present challenges, besides suggesting potential pathways ahead for future advancement.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"34 ","pages":"Article 101213"},"PeriodicalIF":12.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.cossms.2024.101211
Yuan Wang, Matthew S. Dargusch
The capacity of piezoelectric materials for mechanoelectrical transduction has led to a variety of piezoelectric cardiac implants that could revolutionise cardiac-related healthcare delivery. To advance their clinical translation, critical factors including energy output, biocompatibility, biodegradability/durability, and flexibility need to be collectively assessed to ensure successful medical implantation. This review aims to systematically discuss these critical factors, providing insights into corresponding progress and covering relevant mechanisms and strategies in a clinical setting. The concept of additive-free output optimisation has been proposed which focuses on enhancing piezoelectric output based on existing material systems so that biosafety risks and the time-consuming examination processes induced by introducing additional components can be minimised. Critical discussions regarding the biocompatibility and biodegradability of piezoelectric implants were subsequently conducted. This involved reviewing the biocompatibility of material systems associated with piezoelectric implants and introducing biodegradability mechanisms and potential manipulation strategies. The flexibility of implants was also discussed in conjunction with fabrication methods. Current novel piezoelectric cardiac treatments were summarised covering in vivo energy harvesting, hemodynamic sensing, and cardiac tissue regeneration and stimulation. Lastly, challenges and future perspectives were proposed to inspire future work focused on the translation of reliable piezoelectric implants for addressing cardiac diseases.
{"title":"Optimisation and material considerations of piezoelectric implants for cardiac applications","authors":"Yuan Wang, Matthew S. Dargusch","doi":"10.1016/j.cossms.2024.101211","DOIUrl":"10.1016/j.cossms.2024.101211","url":null,"abstract":"<div><div>The capacity of piezoelectric materials for mechanoelectrical transduction has led to a variety of piezoelectric cardiac implants that could revolutionise cardiac-related healthcare delivery. To advance their clinical translation, critical factors including energy output, biocompatibility, biodegradability/durability, and flexibility need to be collectively assessed to ensure successful medical implantation. This review aims to systematically discuss these critical factors, providing insights into corresponding progress and covering relevant mechanisms and strategies in a clinical setting. The concept of additive-free output optimisation has been proposed which focuses on enhancing piezoelectric output based on existing material systems so that biosafety risks and the time-consuming examination processes induced by introducing additional components can be minimised. Critical discussions regarding the biocompatibility and biodegradability of piezoelectric implants were subsequently conducted. This involved reviewing the biocompatibility of material systems associated with piezoelectric implants and introducing biodegradability mechanisms and potential manipulation strategies. The flexibility of implants was also discussed in conjunction with fabrication methods. Current novel piezoelectric cardiac treatments were summarised covering <em>in vivo</em> energy harvesting, hemodynamic sensing, and cardiac tissue regeneration and stimulation. Lastly, challenges and future perspectives were proposed to inspire future work focused on the translation of reliable piezoelectric implants for addressing cardiac diseases.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"34 ","pages":"Article 101211"},"PeriodicalIF":12.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.cossms.2024.101212
Myriel Kim, Rebecca Avrutin, Sean Chryz Iranzo, Honggang Cui
High-affinity binding is a crucial aspect in the design of advanced biomaterials, enabling the creation of materials that can specifically and effectively interact with target objects such as tissues, cells, or biomolecules, mimicking the sophisticated yet well-controlled interactions found in nature. Peptide-based high-affinity biomaterials have emerged as a promising class due to their versatility in chemical design, simplicity in synthesis and formulation, intrinsic ability to mediate biological communication, and key materials features such as tunable biodegradability and modulable biocompatibility. This Opinion article highlights the critical factors to consider in the development of high-affinity peptide materials, including the selection of appropriate peptide ligands, ensuring conformational stability, and optimizing ligand density and conjugation strategies. It also explores how these design considerations have been successfully employed in various applications, including regenerative medicine, drug delivery, and molecular purification.
{"title":"High-affinity peptide biomaterials","authors":"Myriel Kim, Rebecca Avrutin, Sean Chryz Iranzo, Honggang Cui","doi":"10.1016/j.cossms.2024.101212","DOIUrl":"10.1016/j.cossms.2024.101212","url":null,"abstract":"<div><div>High-affinity binding is a crucial aspect in the design of advanced biomaterials, enabling the creation of materials that can specifically and effectively interact with target objects such as tissues, cells, or biomolecules, mimicking the sophisticated yet well-controlled interactions found in nature. Peptide-based high-affinity biomaterials have emerged as a promising class due to their versatility in chemical design, simplicity in synthesis and formulation, intrinsic ability to mediate biological communication, and key materials features such as tunable biodegradability and modulable biocompatibility. This Opinion article highlights the critical factors to consider in the development of high-affinity peptide materials, including the selection of appropriate peptide ligands, ensuring conformational stability, and optimizing ligand density and conjugation strategies. It also explores how these design considerations have been successfully employed in various applications, including regenerative medicine, drug delivery, and molecular purification.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"34 ","pages":"Article 101212"},"PeriodicalIF":12.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143102595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1016/j.cossms.2024.101201
Caleb Hatler , Ishtiaque Robin , Hyosim Kim , Nathan Curtis , Bochuan Sun , Eda Aydogan , Saryu Fensin , Adrien Couet , Enrique Martinez , Dan J. Thoma , Osman El Atwani
Developing advanced materials for plasma-facing components (PFCs) in fusion reactors is a crucial aspect for achieving sustained energy production. Tungsten (W) − based refractory high-entropy alloys (RHEAs) have emerged as promising candidates due to their superior radiation tolerance and high-temperature strength. This review paper will focus on recent advancements in W-based RHEA research, with particular emphasis on: predictive modelling with machine learning (ML) to expedite the identification of optimal RHEA compositions; additive manufacturing (AM) techniques, highlighting their advantages for rapid prototyping and high-throughput multi-compositional sample production; mechanical properties relevant to PFC applications, including hardness, high-temperature strength, and ductility; and the radiation tolerance of W-based RHEAs under irradiated conditions. Finally, the key challenges and opportunities for future research, particularly the holistic analysis of candidate compositions as well as the role of radiation activation and oxidation are identified. This review aims to provide a comprehensive overview of W-based RHEAs for fusion applications and their potential to guide the development and validation of advanced refractory high entropy alloys.
{"title":"The path towards plasma facing components: A review of state-of-the-art in W-based refractory high-entropy alloys","authors":"Caleb Hatler , Ishtiaque Robin , Hyosim Kim , Nathan Curtis , Bochuan Sun , Eda Aydogan , Saryu Fensin , Adrien Couet , Enrique Martinez , Dan J. Thoma , Osman El Atwani","doi":"10.1016/j.cossms.2024.101201","DOIUrl":"10.1016/j.cossms.2024.101201","url":null,"abstract":"<div><div>Developing advanced materials for plasma-facing components (PFCs) in fusion reactors is a crucial aspect for achieving sustained energy production. Tungsten (W) − based refractory high-entropy alloys (RHEAs) have emerged as promising candidates due to their superior radiation tolerance and high-temperature strength. This review paper will focus on recent advancements in W-based RHEA research, with particular emphasis on: predictive modelling with machine learning (ML) to expedite the identification of optimal RHEA compositions; additive manufacturing (AM) techniques, highlighting their advantages for rapid prototyping and high-throughput multi-compositional sample production; mechanical properties relevant to PFC applications, including hardness, high-temperature strength, and ductility; and the radiation tolerance of W-based RHEAs under irradiated conditions. Finally, the key challenges and opportunities for future research, particularly the holistic analysis of candidate compositions as well as the role of radiation activation and oxidation are identified. This review aims to provide a comprehensive overview of W-based RHEAs for fusion applications and their potential to guide the development and validation of advanced refractory high entropy alloys.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"34 ","pages":"Article 101201"},"PeriodicalIF":12.2,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.cossms.2024.101202
Yuebing Zheng
{"title":"Artificial Intelligence and Machine Learning for materials","authors":"Yuebing Zheng","doi":"10.1016/j.cossms.2024.101202","DOIUrl":"10.1016/j.cossms.2024.101202","url":null,"abstract":"","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"34 ","pages":"Article 101202"},"PeriodicalIF":12.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1016/j.cossms.2024.101200
Amrit Raj Paul , Jayshri Dumbre , Dong Qiu , Mark Easton , Maciej Mazur , Manidipto Mukherjee
Intermetallic compounds (IMCs) are ordered solid-state compounds formed from chemical reactions between two or more metals exhibiting distinctive crystal arrangements and precise stoichiometric ratios, setting them apart from the matrix of the alloys. In general, IMCs are formed in three configurations: In the form of secondary phase precipitates distributed within the matrix phase, in the form of an IMC alloy, and at the bimetallic interfaces of functionally/transitionally graded structures. However, the IMCs as precipitates in the matrix phase, do not possess many challenges and are often desirable to improve the strength by imparting precipitation hardening. But, in the case of IMC alloys and bimetallic structures, the grain size and morphology of IMCs directly influence the integrity and durability of the developed structure. Given the inherent brittleness of most IMCs, the utilisation of IMCs in critical applications is substantially restricted. In response to this long-standing challenge, there has been extensive research into methods for improving the ductility of IMCs. This review emphasises two key methodologies: solidification-based and non-solidification-based approaches, both aiming to enhance IMC’s mechanical properties either by transitioning large to smaller grain microstructure or dendritic to equiaxed morphology. Solidification-based strategies, including heterogeneous nucleation and external-field-induced morphological alteration like the use of ultrasonic vibration, magnetic, and electric fields, are meticulously evaluated, uncovering research gaps. Non-solidification-based methods like severe plastic deformation and mechanical alloying are critically examined on the suitability of modern manufacturing techniques such as additive manufacturing. Among these, ultrasonic vibration emerges as the most promising for IMCs morphological transformation. Although static magnetic and electric fields exhibit potential, further investigation is required. Despite knowledge gaps, these techniques hold the potential to elevate IMC-containing alloy characteristics. Future research, especially for specific IMC groups and emerging manufacturing processes, is encouraged to propel metallurgical grain refinement or morphological transformation. In addition, the current and emerging application of various IMCs are thoroughly discussed to identify the importance of IMCs in various science and engineering domains. This comprehensive review enhances comprehension of IMC-based grain alteration, paving the way to design advanced materials across various applications.
{"title":"Grain refinement and morphological control of intermetallic compounds: A comprehensive review","authors":"Amrit Raj Paul , Jayshri Dumbre , Dong Qiu , Mark Easton , Maciej Mazur , Manidipto Mukherjee","doi":"10.1016/j.cossms.2024.101200","DOIUrl":"10.1016/j.cossms.2024.101200","url":null,"abstract":"<div><div>Intermetallic compounds (IMCs) are ordered solid-state compounds formed from chemical reactions between two or more metals exhibiting distinctive crystal arrangements and precise stoichiometric ratios, setting them apart from the matrix of the alloys. In general, IMCs are formed in three configurations: In the form of secondary phase precipitates distributed within the matrix phase, in the form of an IMC alloy, and at the bimetallic interfaces of functionally/transitionally graded structures. However, the IMCs as precipitates in the matrix phase, do not possess many challenges and are often desirable to improve the strength by imparting precipitation hardening. But, in the case of IMC alloys and bimetallic structures, the grain size and morphology of IMCs directly influence the integrity and durability of the developed structure. Given the inherent brittleness of most IMCs, the utilisation of IMCs in critical applications is substantially restricted. In response to this long-standing challenge, there has been extensive research into methods for improving the ductility of IMCs. This review emphasises two key methodologies: solidification-based and non-solidification-based approaches, both aiming to enhance IMC’s mechanical properties either by transitioning large to smaller grain microstructure or dendritic to equiaxed morphology. Solidification-based strategies, including heterogeneous nucleation and external-field-induced morphological alteration like the use of ultrasonic vibration, magnetic, and electric fields, are meticulously evaluated, uncovering research gaps. Non-solidification-based methods like severe plastic deformation and mechanical alloying are critically examined on the suitability of modern manufacturing techniques such as additive manufacturing. Among these, ultrasonic vibration emerges as the most promising for IMCs morphological transformation. Although static magnetic and electric fields exhibit potential, further investigation is required. Despite knowledge gaps, these techniques hold the potential to elevate IMC-containing alloy characteristics. Future research, especially for specific IMC groups and emerging manufacturing processes, is encouraged to propel metallurgical grain refinement or morphological transformation. In addition, the current and emerging application of various IMCs are thoroughly discussed to identify the importance of IMCs in various science and engineering domains. This comprehensive review enhances comprehension of IMC-based grain alteration, paving the way to design advanced materials across various applications.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"33 ","pages":"Article 101200"},"PeriodicalIF":12.2,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.cossms.2024.101188
D.B. Miracle , D.J. Thoma
Blending artificial intelligence and automation enables the new field of autonomous research and development for materials science. A recent review of this still new field was evaluated to seek new opportunities, and structural materials were identified as a topic for future growth. A workshop was organized in Denver, CO on 20–22 April 2022 to explore this theme. The results from this workshop are given in this viewpoint set. The present paper describes four new themes introduced to the autonomous research and development field by structural materials: new artificial intelligence methods; a vision for rapid on-demand synthesis (RODS) of bulk (≥100 gm) metallic and ceramic materials; new methods for measuring properties; and a new synergy between materials development and engineering design. The remaining papers in this viewpoint set present ideas and discussions from the Denver workshop and more in-depth presentations of major workshop themes.
{"title":"Autonomous research and development of structural materials – An introduction and vision","authors":"D.B. Miracle , D.J. Thoma","doi":"10.1016/j.cossms.2024.101188","DOIUrl":"10.1016/j.cossms.2024.101188","url":null,"abstract":"<div><div>Blending artificial intelligence and automation enables the new field of autonomous research and development for materials science. A recent review of this still new field was evaluated to seek new opportunities, and structural materials were identified as a topic for future growth. A workshop was organized in Denver, CO on 20–22 April 2022 to explore this theme. The results from this workshop are given in this viewpoint set. The present paper describes four new themes introduced to the autonomous research and development field by structural materials: new artificial intelligence methods; a vision for rapid on-demand synthesis (RODS) of bulk (≥100<!--> <!-->gm) metallic and ceramic materials; new methods for measuring properties; and a new synergy between materials development and engineering design. The remaining papers in this viewpoint set present ideas and discussions from the Denver workshop and more in-depth presentations of major workshop themes.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"33 ","pages":"Article 101188"},"PeriodicalIF":12.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.cossms.2024.101199
Yijia Fan , Ran An , Jianshi Tang, Yijun Li, Ting Liu, Bin Gao, He Qian, Huaqiang Wu
As emerging technologies like artificial intelligence (AI) and big data continue to evolve, the demand for high-performance computing (HPC) has been increasing, driving the development of computing chips towards greater energy efficiency and multifunctionality. Monolithic 3D integration (M3D) is poised to be a key enabling technology, by vertically stacking multiple functional layers made of backend-of-the-line (BEOL)-compatible devices on top of Si circuits and interconnecting them with high-density interlayer vias (ILVs). Currently, contenders for functional materials and devices in M3D include carbon nanotubes, two-dimensional (2D) materials, oxide semiconductors and a variety of emerging memories, such as resistive random-access memory (RRAM). This article first discusses the key properties and latest research developments of those materials and their device applications. As a representative example, we then review the recent progress on RRAM-based M3D architectures that integrate memory, computing, and other functional elements to facilitate computing-in-memory (CIM). Finally, we further discuss the opportunities and challenges of M3D as a promising pathway to energy-efficient computing.
{"title":"Monolithic 3D integration as a pathway to energy-efficient computing and beyond: From materials and devices to architectures and chips","authors":"Yijia Fan , Ran An , Jianshi Tang, Yijun Li, Ting Liu, Bin Gao, He Qian, Huaqiang Wu","doi":"10.1016/j.cossms.2024.101199","DOIUrl":"10.1016/j.cossms.2024.101199","url":null,"abstract":"<div><div>As emerging technologies like artificial intelligence (AI) and big data continue to evolve, the demand for high-performance computing (HPC) has been increasing, driving the development of computing chips towards greater energy efficiency and multifunctionality. Monolithic 3D integration (M3D) is poised to be a key enabling technology, by vertically stacking multiple functional layers made of backend-of-the-line (BEOL)-compatible devices on top of Si circuits and interconnecting them with high-density interlayer vias (ILVs). Currently, contenders for functional materials and devices in M3D include carbon nanotubes, two-dimensional (2D) materials, oxide semiconductors and a variety of emerging memories, such as resistive random-access memory (RRAM). This article first discusses the key properties and latest research developments of those materials and their device applications. As a representative example, we then review the recent progress on RRAM-based M3D architectures that integrate memory, computing, and other functional elements to facilitate computing-in-memory (CIM). Finally, we further discuss the opportunities and challenges of M3D as a promising pathway to energy-efficient computing.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"33 ","pages":"Article 101199"},"PeriodicalIF":12.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.cossms.2024.101191
Han Fu , Liyan Zhai , Hongyu Wang , Melody M.H. Li , Gerard C.L. Wong , Yue Zhang
At present, we do not understand precisely how the SARS-CoV-2 coronavirus induces a spectrum of immune responses in different infected hosts, including severe inflammation in some, or how post-acute infection sequelae come about. In this review, we consider a conceptual framework whereby the virus itself is a reservoir of peptide motifs with pro-inflammatory activity. These motifs can potentially be liberated by highly variable proteolytic processing by the host. We focus on the ability of viral peptide motifs that can mimic innate immune peptides (more commonly known as ‘antimicrobial peptides’ (AMPs)). AMPs (and their ‘xenoAMP’ mimics) are not themselves pathogen-associated molecular patterns (PAMPs) that activate innate immunity via recognition by host pattern recognition receptors (PRRs) but can strongly amplify PRR activation via promoting multivalent PAMP presentation. An important mechanism in the host’s immune amplification machinery and is implicated in a range of autoimmune conditions, including lupus and rheumatoid arthritis, which are among the sequelae of COVID-19. We review experiments that show AMPs and SARS-CoV-2-derived xenoAMP can assemble with PAMPs such as dsRNA into pro-inflammatory complexes, resulting in cooperative, multivalent immune recognition by PRRs and grossly amplified inflammatory responses, a phenomenon generally not observed in harmless coronavirus homologs. We also review the persistence of viral remnants from other viral infections and their association with inflammatory sequelae long after the infection has been cleared.
{"title":"SARS-CoV-2 viral remnants and implications for inflammation and post-acute infection sequelae","authors":"Han Fu , Liyan Zhai , Hongyu Wang , Melody M.H. Li , Gerard C.L. Wong , Yue Zhang","doi":"10.1016/j.cossms.2024.101191","DOIUrl":"10.1016/j.cossms.2024.101191","url":null,"abstract":"<div><div>At present, we do not understand precisely how the SARS-CoV-2 coronavirus induces a spectrum of immune responses in different infected hosts, including severe inflammation in some, or how post-acute infection sequelae come about. In this review, we consider a conceptual framework whereby the virus itself is a reservoir of peptide motifs with pro-inflammatory activity. These motifs can potentially be liberated by highly variable proteolytic processing by the host. We focus on the ability of viral peptide motifs that can mimic innate immune peptides (more commonly known as ‘antimicrobial peptides’ (AMPs)). AMPs (and their ‘xenoAMP’ mimics) are not themselves pathogen-associated molecular patterns (PAMPs) that activate innate immunity via recognition by host pattern recognition receptors (PRRs) but can strongly amplify PRR activation via promoting multivalent PAMP presentation. An important mechanism in the host’s immune amplification machinery and is implicated in a range of autoimmune conditions, including lupus and rheumatoid arthritis, which are among the sequelae of COVID-19. We review experiments that show AMPs and SARS-CoV-2-derived xenoAMP can assemble with PAMPs such as dsRNA into pro-inflammatory complexes, resulting in cooperative, multivalent immune recognition by PRRs and grossly amplified inflammatory responses, a phenomenon generally not observed in harmless coronavirus homologs. We also review the persistence of viral remnants from other viral infections and their association with inflammatory sequelae long after the infection has been cleared.</div></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"33 ","pages":"Article 101191"},"PeriodicalIF":12.2,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142315828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11DOI: 10.1016/j.cossms.2024.101189
Anubhav Jain
The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials science methods, and ML methods) used within papers that apply ML to materials science. The analysis demonstrates that despite the growth of deep learning techniques, the use of classical machine learning is still dominant as a whole. It also demonstrates how new research can effectively build upon past research, particular in the domain of ML models trained on density functional theory calculation data. Next, I present the progression of best scores as a function of time on the matbench materials science benchmark for formation enthalpy prediction. In particular, a dramatic improvement of 7 times reduction in error is obtained when progressing from feature-based methods that use conventional ML (random forest, support vector regression, etc.) to the use of graph neural network techniques. Finally, I provide views on future challenges and opportunities, focusing on data size and complexity, extrapolation, interpretation, access, and relevance.
在过去十年中，将机器学习（ML）应用于材料科学的研究数量以每年约 1.67 倍的速度增长。在这篇综述中，我将从多个方面考察这一增长。首先，我分析了将机器学习应用于材料科学的论文中最常用的工具（软件、数据库、材料科学方法和 ML 方法）。分析表明，尽管深度学习技术在不断发展，但从整体上看，经典机器学习的使用仍占主导地位。它还展示了新研究如何有效地借鉴过去的研究，尤其是在根据密度泛函理论计算数据训练的 ML 模型领域。接下来，我介绍了在 matbench 材料科学基准中，随着时间的推移，最佳分数在形成焓预测方面的进展情况。特别是，从使用传统 ML（随机森林、支持向量回归等）的基于特征的方法到使用图神经网络技术，误差大幅减少了 7 倍。最后，我就未来的挑战和机遇发表了看法，重点是数据规模和复杂性、外推、解释、访问和相关性。
{"title":"Machine learning in materials research: Developments over the last decade and challenges for the future","authors":"Anubhav Jain","doi":"10.1016/j.cossms.2024.101189","DOIUrl":"10.1016/j.cossms.2024.101189","url":null,"abstract":"<div><p>The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials science methods, and ML methods) used within papers that apply ML to materials science. The analysis demonstrates that despite the growth of deep learning techniques, the use of classical machine learning is still dominant as a whole. It also demonstrates how new research can effectively build upon past research, particular in the domain of ML models trained on density functional theory calculation data. Next, I present the progression of best scores as a function of time on the matbench materials science benchmark for formation enthalpy prediction. In particular, a dramatic improvement of 7 times reduction in error is obtained when progressing from feature-based methods that use conventional ML (random forest, support vector regression, <em>etc.</em>) to the use of graph neural network techniques. Finally, I provide views on future challenges and opportunities, focusing on data size and complexity, extrapolation, interpretation, access, and relevance.</p></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"33 ","pages":"Article 101189"},"PeriodicalIF":12.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S135902862400055X/pdfft?md5=daf1f5860dd3d81b7ae5c13746fc62e9&pid=1-s2.0-S135902862400055X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号