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1.
J Mater Chem B ; 12(27): 6519-6520, 2024 Jul 10.
Artigo em Inglês | MEDLINE | ID: mdl-38946598

RESUMO

We would like to take this opportunity to thank all of Journal of Materials Chemistry B's reviewers for helping to preserve quality and integrity in chemical science literature. We would also like to highlight the Outstanding Reviewers for Journal of Materials Chemistry B in 2023.


Assuntos
Publicações Periódicas como Assunto , Ciência dos Materiais
3.
Org Biomol Chem ; 22(23): 4625-4636, 2024 06 12.
Artigo em Inglês | MEDLINE | ID: mdl-38804977

RESUMO

Both natural and unnatural amino acids, peptides, and proteins are widely recognized as green and sustainable organic chemicals, not only in the field of biological sciences but also in materials science. It has been discovered that artificially designed unnatural peptides and proteins exhibit advanced properties in medical and materials science. In this context, the development of precise chemical modification methods for amino acids and peptides is acknowledged as an important research project in the field of organic synthesis. While a wide variety of modification methods for amino acid residues have been developed to artificially modify peptides and proteins, the representative methods for modifying amino acid residues have traditionally relied on the nucleophilic properties of the functionalities on the residues. In this context, the development of different modification methods using an umpolung-like approach by utilizing the electrophilic nature of amino acid derivatives appears to be very attractive. One of the promising electrophilic amino acid compounds for realizing important modification methods of amino acid derivatives is α,ß-dehydroamino acids, which possess an α,ß-unsaturated carbonyl structure. This review article summarizes methods for the preparation of α,ß-dehydroamino acids derived from natural and unnatural amino acid derivatives. The utilities of α,ß-dehydroamino acid derivatives, including peptides and proteins containing dehydroalanine units, in bioconjugations are also discussed.


Assuntos
Aminoácidos , Aminoácidos/química , Aminoácidos/síntese química , Proteínas/química , Proteínas/síntese química , Ciência dos Materiais , Peptídeos/química , Peptídeos/síntese química , Química Verde , Técnicas de Química Sintética/métodos , Alanina/química , Alanina/análogos & derivados , Alanina/síntese química
4.
Appl Microbiol Biotechnol ; 108(1): 217, 2024 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-38372792

RESUMO

Pleurotus ostreatus, also known as the oyster mushroom, is a popular edible mushroom cultivated worldwide. This review aims to survey recent progress in the molecular genetics of this fungus and demonstrate its potential as a model mushroom for future research. The development of modern molecular genetic techniques and genome sequencing technologies has resulted in breakthroughs in mushroom science. With efficient transformation protocols and multiple selection markers, a powerful toolbox, including techniques such as gene knockout and genome editing, has been developed, and numerous new findings are accumulating in P. ostreatus. These include molecular mechanisms of wood component degradation, sexual development, protein secretion systems, and cell wall structure. Furthermore, these techniques enable the identification of new horizons in enzymology, biochemistry, cell biology, and material science through protein engineering, fluorescence microscopy, and molecular breeding. KEY POINTS: • Various genetic techniques are available in Pleurotus ostreatus. • P. ostreatus can be used as an alternative model mushroom in genetic analyses. • New frontiers in mushroom science are being developed using the fungus.


Assuntos
Agaricales , Pleurotus , Pleurotus/genética , Agaricales/genética , Ciência dos Materiais , Parede Celular , Embaralhamento de DNA
5.
Proc Natl Acad Sci U S A ; 121(7): e2312775121, 2024 Feb 13.
Artigo em Inglês | MEDLINE | ID: mdl-38324570

RESUMO

Self-assembly of complex and functional materials remains a grand challenge in soft material science. Efficient assembly depends on a delicate balance between thermodynamic and kinetic effects, requiring fine-tuning affinities and concentrations of subunits. By contrast, we introduce an assembly paradigm that allows large error-tolerance in the subunit affinity and helps avoid kinetic traps. Our combined experimental and computational approach uses a model system of triangular subunits programmed to assemble into T = 3 icosahedral capsids comprising 60 units. The experimental platform uses DNA origami to create monodisperse colloids whose three-dimensional geometry is controlled to nanometer precision, with two distinct bonds whose affinities are controlled to kBT precision, quantified in situ by static light scattering. The computational model uses a coarse-grained representation of subunits, short-ranged potentials, and Langevin dynamics. Experimental observations and modeling reveal that when the bond affinities are unequal, two distinct hierarchical assembly pathways occur, in which the subunits first form dimers in one case and pentamers in another. These hierarchical pathways produce complete capsids faster and are more robust against affinity variation than egalitarian pathways, in which all binding sites have equal strengths. This finding suggests that hierarchical assembly may be a general engineering principle for optimizing self-assembly of complex target structures.


Assuntos
Capsídeo , Ciência dos Materiais , Capsídeo/metabolismo , Proteínas do Capsídeo/química , DNA/química , Cinética , Termodinâmica , Montagem de Vírus , Ciência dos Materiais/métodos
6.
J Chem Inf Model ; 64(3): 799-811, 2024 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-38237025

RESUMO

The pursuit of designing smart and functional materials is of paramount importance across various domains, such as material science, engineering, chemical technology, electronics, biomedicine, energy, and numerous others. Consequently, researchers are actively involved in the development of innovative models and strategies for material design. Recent advancements in analytical tools, experimentation, and computer technology additionally enhance the material design possibilities. Notably, data-driven techniques like artificial intelligence and machine learning have achieved substantial progress in exploring various applications within material science. One such approach, ChatGPT, a large language model, holds transformative potential for addressing complex queries. In this article, we explore ChatGPT's understanding of material science by assigning some simple tasks across various subareas of computational material science. The findings indicate that while ChatGPT may make some minor errors in accomplishing general tasks, it demonstrates the capability to learn and adapt through human interactions. However, issues like output consistency, probable hidden errors, and ethical consequences should be addressed.


Assuntos
Inteligência Artificial , Eletrônica , Humanos , Idioma , Aprendizado de Máquina , Ciência dos Materiais
7.
J Chem Inf Model ; 64(7): 2383-2392, 2024 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-37706462

RESUMO

The pKa of C-H acids is an important parameter in the fields of organic synthesis, drug discovery, and materials science. However, the prediction of pKa is still a great challenge due to the limit of experimental data and the lack of chemical insight. Here, a new model for predicting the pKa values of C-H acids is proposed on the basis of graph neural networks (GNNs) and data augmentation. A message passing unit (MPU) was used to extract the topological and target-related information from the molecular graph data, and a readout layer was utilized to retrieve the information on the ionization site C atom. The retrieved information then was adopted to predict pKa by a fully connected network. Furthermore, to increase the diversity of the training data, a knowledge-infused data augmentation technique was established by replacing the H atoms in a molecule with substituents exhibiting different electronic effects. The MPU was pretrained with the augmented data. The efficacy of data augmentation was confirmed by visualizing the distribution of compounds with different substituents and by classifying compounds. The explainability of the model was studied by examining the change of pKa values when a specific atom was masked. This explainability was used to identify the key substituents for pKa. The model was evaluated on two data sets from the iBonD database. Dataset1 includes the experimental pKa values of C-H acids measured in DMSO, while dataset2 comprises the pKa values measured in water. The results show that the knowledge-infused data augmentation technique greatly improves the predictive accuracy of the model, especially when the number of samples is small.


Assuntos
Descoberta de Drogas , Eletrônica , Bases de Dados Factuais , Ciência dos Materiais , Naftalenossulfonatos , Redes Neurais de Computação
8.
Anal Bioanal Chem ; 416(9): 2247-2259, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38006442

RESUMO

Centralized laboratories in which analytical processes are automated to enable the analysis of large numbers of samples at relatively low cost are used for analytical testing throughout the world. However, healthcare is changing, partly due to the general recognition that care needs to be more patient-centered and putting the patient at the center of action. One way to achieve this goal is to consider point-of-care testing (PoC) devices as alternative analytical concepts. This requires miniaturization of current analytical concepts and the use of cost-effective diagnostic tools with appropriate sensitivity and specificity. Electrochemical sensors are ideally adapted as they provide robust, low-cost, and miniaturized solutions for the detection of variable analytes, yet lack the high sensitivity comparable to more classical diagnosis approaches. Advances in nanotechnology have opened up a plethora of different nanomaterials to be applied as electrode and/or sensing materials in electrochemical biosensors. The choice of materials significantly influences the sensor's sensitivity, selectivity, and overall performance. A critical review of the state of the art with respect to the development of the utilized materials (between 2019 and 2023) and where the field is heading to are the focus of this article.


Assuntos
Técnicas Biossensoriais , Nanoestruturas , Humanos , Ciência dos Materiais , Técnicas Biossensoriais/métodos , Nanotecnologia/métodos , Sensibilidade e Especificidade , Técnicas Eletroquímicas
9.
J Chem Inf Model ; 63(24): 7605-7609, 2023 Dec 25.
Artigo em Inglês | MEDLINE | ID: mdl-38084508

RESUMO

The artificial intelligence (AI) tools based on large-language models may serve as a demonstration that we are reaching a groundbreaking new paradigm in which machines themselves will generate knowledge autonomously. This statement is based on the assumption that the ability to master natural languages is the ultimate frontier for this new paradigm and perhaps an essential step to achieving the so-called general artificial intelligence. Autonomous knowledge generation implies that a machine will be able, for instance, to retrieve and understand the contents of the scientific literature and provide interpretations for existing data, allowing it to propose and address new scientific problems. While one may assume that the continued development of AI tools exploiting large-language models, with more data used for training, may lead these systems to learn autonomously, this learning can be accelerated by devising human-assisted strategies to deal with specific tasks. For example, strategies may be implemented for AI tools to emulate the analysis of multivariate data by human experts or in identifying and explaining patterns in temporal series. In addition to generic AI tools, such as Chat AIs, one may conceive personal AI agents, potentially working together, that are likely to serve end users in the near future. In this perspective paper, we discuss the development of this type of agent, focusing on its architecture and requirements. As a proof-of-concept, we exemplify how such an AI agent could work to assist researchers in materials sciences.


Assuntos
Inteligência Artificial , Ciência dos Materiais , Humanos , Idioma , Aprendizagem , Pesquisadores
10.
Sci Adv ; 9(44): eadi6129, 2023 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-37910613

RESUMO

Acoustic beam shaping with high degrees of freedom is critical for applications such as ultrasound imaging, acoustic manipulation, and stimulation. However, the ability to fully control the acoustic pressure profile over its propagation path has not yet been achieved. Here, we demonstrate an acoustic diffraction-resistant adaptive profile technology (ADAPT) that can generate a propagation-invariant beam with an arbitrarily desired profile. By leveraging wave number modulation and beam multiplexing, we develop a general framework for creating a highly flexible acoustic beam with a linear array ultrasonic transducer. The designed acoustic beam can also maintain the beam profile in lossy material by compensating for attenuation. We show that shear wave elasticity imaging is an important modality that can benefit from ADAPT for evaluating tissue mechanical properties. Together, ADAPT overcomes the existing limitation of acoustic beam shaping and can be applied to various fields, such as medicine, biology, and material science.


Assuntos
Acústica , Transdutores , Ultrassonografia/métodos , Elasticidade , Ciência dos Materiais
11.
Biomater Sci ; 11(22): 7229-7246, 2023 Nov 07.
Artigo em Inglês | MEDLINE | ID: mdl-37791425

RESUMO

Fimbriae are long filamentous polymeric protein structures located upon the surface of bacteria. Often implicated in pathogenicity, the biosynthesis and function of fimbriae has been a productive topic of study for many decades. Evolutionary pressures have ensured that fimbriae possess unique structural and mechanical properties which are advantageous to bacteria. These properties are also difficult to engineer with well-known synthetic and natural fibres, and this has raised an intriguing question: can we exploit the unique properties of bacterial fimbriae in useful ways? Initial work has set out to explore this question by using Capsular antigen fragment 1 (Caf1), a fimbriae expressed naturally by Yersina pestis. These fibres have evolved to 'shield' the bacterium from the immune system of an infected host, and thus are rather bioinert in nature. Caf1 is, however, very amenable to structural mutagenesis which allows the incorporation of useful bioactive functions and the modulation of the fibre's mechanical properties. Its high-yielding recombinant synthesis also ensures plentiful quantities of polymer are available to drive development. These advantageous features make Caf1 an archetype for the development of new polymers and materials based upon bacterial fimbriae. Here, we cover recent advances in this new field, and look to future possibilities of this promising biopolymer.


Assuntos
Antígenos de Bactérias , Yersinia pestis , Antígenos de Bactérias/química , Antígenos de Bactérias/metabolismo , Proteínas de Bactérias/química , Fímbrias Bacterianas/metabolismo , Polímeros/química , Ciência dos Materiais , Yersinia pestis/química , Yersinia pestis/metabolismo
12.
BMC Med Educ ; 23(1): 716, 2023 Oct 02.
Artigo em Inglês | MEDLINE | ID: mdl-37784112

RESUMO

BACKGROUND: Dental materials science is an important subject, but research on curriculum mapping in preclinical dental materials science courses is still scarce. The present study aimed to conduct a curriculum mapping in analysing elements and suggesting recommendations for an institutional dental materials science course. METHODS: Curriculum mapping was conducted for the Year 2 undergraduate dental materials science course (Bachelor of Dental Surgery programme) in a Malaysian dental school. Based on Harden's framework, the following steps were used to map the curriculum of the institutional dental materials science course: (1) scoping the task; (2) deciding the mapping format; (3) populating the windows, and (4) establishing the links. Two analysts reviewed the curriculum independently. Their respective analyses were compared, and discrepancies were discussed until reaching a consensus. A SWOT analysis was also conducted to evaluate the strengths, weaknesses, opportunities, and threats associated with the curriculum. RESULTS: Course learning outcomes, course contents, levels of cognitive and psychomotor competencies, learning opportunities, learning resources, learning locations, assessments, timetable, staff, curriculum management and students' information were successfully scoped from the institutional dental materials science course. The present curriculum's strengths included comprehensiveness, alignment with standards, adequate learning opportunities, well-defined assessment methods, and sufficient learning resources. However, the identified weaknesses were repetition in curriculum content, limited emphasis on the psychomotor domain, dependency on a single academic staff, and limited integration of technology. The SWOT analysis highlighted the opportunities for curriculum improvement, such as revising repetitive content, emphasising the psychomotor domain, and incorporating advanced teaching strategies and technology. CONCLUSIONS: The present dental materials science curriculum demonstrated several strengths with some areas for improvement. The findings suggested the need to revise and optimise the course content to address gaps and enhance student learning outcomes. Ongoing monitoring and evaluation are necessary to ensure the curriculum remains aligned with emerging trends and advancements in dental materials science.


Assuntos
Currículo , Ciência dos Materiais , Humanos , Aprendizagem , Estudos Longitudinais
13.
BMC Oral Health ; 23(1): 571, 2023 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-37574553

RESUMO

BACKGROUND: Effective teaching of dental materials science is crucial for dental students to develop a comprehensive understanding of materials used in clinical practice. However, literature on educators' views on teaching this subject is still scarce. This qualitative study aimed to explore the lived experiences of dental educators in teaching dental materials science subjects, thereby addressing potential gaps and enhancing teaching practices. METHODS: Thirteen dental educators from East and Southeast Asian countries (Malaysia, China, Indonesia, Thailand, South Korea, and Japan) participated in the present study. The present study adopted a transcendental phenomenological approach. One-to-one semi-structured online interviews were conducted. Interviews were recorded and transcribed verbatim. Thematic analysis was employed to identify patterns in the educators' experiences. RESULTS: Three themes emerged from the present study. First, perceptions of the importance of dental materials science, highlighting its relevance in clinical practice, patient care, and lifelong learning. Second, the challenges faced in teaching dental materials science include limited instructional time, complex content, and insufficient resources. Third, specific strategies, such as applying interactive teaching methods, integrating clinical scenarios, and promoting critical thinking skills have been suggested to enhance teaching and learning. CONCLUSION: Understanding dental educators' experiences can improve dental materials science education, curriculum development, teaching methods, and faculty training programmes, ultimately enhancing the knowledge and skills of dental students in this field.


Assuntos
Currículo , Odontologia , Ciência dos Materiais , Humanos , Odontologia/métodos , População do Leste Asiático , Docentes , Aprendizagem , Ciência dos Materiais/educação , População do Sudeste Asiático , Ensino , Ásia Oriental , Sudeste Asiático
14.
J R Soc Interface ; 20(203): 20230242, 2023 06.
Artigo em Inglês | MEDLINE | ID: mdl-37340781

RESUMO

The Johnson-Mehl-Avrami-Kolmogorov (JMAK) formalization, often referred to as the Avrami equation, was originally developed to describe the progress of phase transformations in material systems. Many other transformations in the life, physical and social sciences follow a similar pattern of nucleation and growth. The Avrami equation has been applied widely to modelling such phenomena, including COVID-19, regardless of whether they have a formal thermodynamic basis. We present here an analytical overview of such applications of the Avrami equation outside its conventional use, emphasizing examples from the life sciences. We discuss the similarities that at least partially justify the extended application of the model to such cases. We point out the limitations of such adoption; some are inherent to the model itself, and some are associated with the extended contexts. We also propose a reasoned justification for why the model performs well in many of these non-thermodynamic applications, even when some of its fundamental assumptions are not satisfied. In particular, we explore connections between the relatively accessible verbal and mathematical language of everyday nucleation- and growth-based phase transformations, represented by the Avrami equation, and the more challenging language of the classic SIR (susceptible-infected-removed) model in epidemiology.


Assuntos
COVID-19 , Ciência dos Materiais , Humanos , COVID-19/epidemiologia , Termodinâmica
15.
Macromol Rapid Commun ; 44(17): e2300217, 2023 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-37280769

RESUMO

The use of light for shaping and changing matter is of high relevance in polymer and material science. Herein, a photopolymer method is presented, which comprises the combination of 3D photo-printing at 405 nm light and subsequent modification under two-photon absorption (TPA) conditions at 532 nm light, adding the fourth dimension. The TPA-triggered cycloreversion reaction of an intramolecular coumarin dimer (ICD) structure occurs within the absorbing material. The 3D-printable matrix does not show any degradation under the TPA conditions. With the presented photochemical tool of TPA processes inside absorbing 3D photo-printable matrices, new possibilities for post-printing modification, e. g. for smart materials, are added.


Assuntos
Cumarínicos , Ciência dos Materiais , Fótons , Polímeros , Impressão Tridimensional
16.
J Mater Chem B ; 11(22): 4842-4854, 2023 06 07.
Artigo em Inglês | MEDLINE | ID: mdl-37194349

RESUMO

Bacterial microcompartments (BMCs) are sophisticated all-protein bionanoreactors widely spread in bacterial phyla. BMCs facilitate diverse metabolic reactions, which assist bacterial survivability in normal (by fixing carbon dioxide) and energy dearth conditions. The past seven decades have uncovered numerous intrinsic features of BMCs, which have attracted researchers to tailor them for customised applications, including synthetic nanoreactors, scaffold nano-materials for catalysis or electron conduction, and delivery vehicles for drug molecules or RNA/DNA. In addition, BMCs provide a competitive advantage to pathogenic bacteria and this can pave a new path for antimicrobial drug design. In this review, we discuss different structural and functional aspects of BMCs. We also highlight the potential employment of BMCs for novel applications in bio-material science.


Assuntos
Proteínas de Bactérias , Ciência dos Materiais , Proteínas de Bactérias/metabolismo , Organelas/metabolismo , Bactérias/metabolismo , Dióxido de Carbono
17.
J Pharm Sci ; 112(9): 2463-2482, 2023 09.
Artigo em Inglês | MEDLINE | ID: mdl-37031865

RESUMO

Ball-milling and harsh manufacturing processes often generate crystal disorder which have practical implications on the physical and chemical stabilities of solid drugs during subsequent storage, transport, and handling. The impact of the physical state of solid drugs, containing different degrees/levels of crystal disorder, on their autoxidative stability under storage has not been widely investigated. This study investigates the impact of differing degrees of crystal disorder on the autoxidation of Mifepristone (MFP) to develop a predictive (semi-empirical) stability model. Crystalline MFP was subjected to different durations of ambient ball milling, and the resulting disorder/ amorphous content was quantified using a partial least square (PLS) regression model based on Raman spectroscopy data. Samples of MFP milled to generate varying levels of disorder were subjected to a range of (accelerated) stability conditions, and periodically sampled to examine their recrystallization and degradation extents. Crystallinity was monitored by Raman spectroscopy, and the degradation was evaluated by liquid chromatography. The analyses of milled samples demonstrated a competition between recrystallization and degradation via autoxidation of MFP, to different extents depending on stability conditions/exposure time. The degradation kinetics were analyzed by accounting for the preceding amorphous content, and fitted with a diffusion model. An extended Arrhenius equation was used to predict the degradation of stored samples under long-term (25°C/60% RH) and accelerated (40°C/75% RH, 50°C/75% RH) stability conditions. This study highlights the utility of such a predictive stability model for identifying the autoxidative instability in non-crystalline/partially crystalline MFP, owing to the degradation of the amorphous phases. This study is particularly useful for identifying drug-product instability by leveraging the concept of material sciences.


Assuntos
Ciência dos Materiais , Mifepristona , Cristalização , Estabilidade de Medicamentos , Varredura Diferencial de Calorimetria
18.
BMC Oral Health ; 23(1): 243, 2023 04 27.
Artigo em Inglês | MEDLINE | ID: mdl-37106354

RESUMO

BACKGROUND: Dental materials science is an important core course in undergraduate dental programs which integrates foundational concepts of chemical engineering and materials science into clinical dentistry. The present study aimed to identify relevant dental materials science topics for Malaysian undergraduate dental curricula and to determine their appropriate competency levels in terms of cognitive and psychomotor taxonomies. METHODS: Potential dental materials science topics were drafted in alignment with the revised national competency statement. The list of topics was further amended after comparing it with those recommended topics in the literature. Fuzzy Delphi method was applied. Experts were selected based on the different inclusion criteria. They ranked the topics using a five-point Likert scale and recommended the appropriate cognitive and psychomotor levels. Next, fuzzy evaluation was performed. Consensus was deemed for a topic to be included if (a) the average expert agreement was ≥ 75%, (b) the d-construct threshold value for each topic was ≤ 0.2 and (c) the average fuzzy number was ≥ 0.5. RESULTS: Sixty-two experts participated in the study. They accepted 33 out of 36 potential dental materials science topics. The average Likert score and fuzzy number ranged from 3.63 to 4.92 and 0.526 to 0.784, respectively. Furthermore, "Endodontic materials" was ranked as the most significant topic. Meanwhile, many topics required dental students to demonstrate a cognitive level of "Apply" and a psychomotor level of "Guided response". Based on mean scores, "Impression materials" was rated as the most cognitively demanding topic, whilst "Temporary restorative materials" was the most demanding topic for psychomotor taxonomy. CONCLUSION: The present study has identified relevant dental materials science topics and their appropriate cognitive and psychomotor levels using the Fuzzy Delphi approach. The findings of the present study form the basis for future studies to develop measurable learning outcomes, design corresponding innovative pedagogy and propose assessment criteria for each topic.


Assuntos
Currículo , Ciência dos Materiais , Humanos , Técnica Delphi , Aprendizagem , Consenso
19.
J Chem Inf Model ; 63(7): 1961-1981, 2023 04 10.
Artigo em Inglês | MEDLINE | ID: mdl-36940385

RESUMO

Text mining in the optical-materials domain is becoming increasingly important as the number of scientific publications in this area grows rapidly. Language models such as Bidirectional Encoder Representations from Transformers (BERT) have opened up a new era and brought a significant boost to state-of-the-art natural-language-processing (NLP) tasks. In this paper, we present two "materials-aware" text-based language models for optical research, OpticalBERT and OpticalPureBERT, which are trained on a large corpus of scientific literature in the optical-materials domain. These two models outperform BERT and previous state-of-the-art models in a variety of text-mining tasks about optical materials. We also release the first "materials-aware" table-based language model, OpticalTable-SQA. This is a querying facility that solicits answers to questions about optical materials using tabular information that pertains to this scientific domain. The OpticalTable-SQA model was realized by fine-tuning the Tapas-SQA model using a manually annotated OpticalTableQA data set which was curated specifically for this work. While preserving its sequential question-answering performance on general tables, the OpticalTable-SQA model significantly outperforms Tapas-SQA on optical-materials-related tables. All models and data sets are available to the optical-materials-science community.


Assuntos
Mineração de Dados , Fontes de Energia Elétrica , Idioma , Ciência dos Materiais , Processamento de Linguagem Natural
20.
Chem Soc Rev ; 52(7): 2497-2527, 2023 Apr 03.
Artigo em Inglês | MEDLINE | ID: mdl-36928878

RESUMO

Ionic liquid (IL)-based gels (ionogels) have received considerable attention due to their unique advantages in ionic conductivity and their biphasic liquid-solid phase property. In ionogels, the negligibly volatile ionic liquid is retained in the interconnected 3D pore structure. On the basis of these physical features as well as the chemical properties of well-chosen ILs, there is emerging interest in the anti-bacterial and biocompatibility aspects. In this review, the recent achievements of ionogels for biomedical applications are summarized and discussed. Following a brief introduction of the various types of ILs and their key physicochemical and biological properties, the design strategies and fabrication methods of ionogels are presented by means of different confining networks. These sophisticated ionogels with diverse functions, aimed at biomedical applications, are further classified into several active domains, including wearable strain sensors, therapeutic delivery systems, wound healing and biochemical detections. Finally, the challenges and possible strategies for the design of future ionogels by integrating materials science with a biological interface are proposed.


Assuntos
Líquidos Iônicos , Condutividade Elétrica , Ciência dos Materiais
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