jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kazuharu Arakawa | Nobuaki Kono | Ali D. Malay | Ayaka Tateishi | Nao Ifuku | Hiroyasu Masunaga | Ryota Sato | Kousuke Tsuchiya | Rintaro Ohtoshi | Daniel Pedrazzoli | Asaka Shinohara | Yusuke Ito | Hiroyuki Nakamura | Akio Tanikawa | Yuya Suzuki | Takeaki Ichikawa | Shohei Fujita | Masayuki Fujiwara | Masaru Tomita | Sean J. Blamires | Jo‐Ann Chuah | Hamish C. Craig | Choon Pin Foong | Gabriele Greco | Juan Guan | Chris Holland | David L. Kaplan | Kumar Sudesh | Biman B. Mandal | Yusoff Norma‐Rashid | Nur Alia Oktaviani | Rucsanda C. Preda | Nicola M. Pugno | Rangam Rajkhowa | Xiaoqin Wang | Kenjiro Yazawa | Zhaozhu Zheng | Keiji Numata
Source: Science Advances (article, 2022-10-12)
Field: Materials Science — Biomaterials

1000 spider silkomes: Linking sequences to silk physical properties Spider silks are among the toughest known materials and thus provide models for renewable, biodegradable, and sustainable biopolymers. However, the entirety of their diversity still remains elusive, and silks that exceed the performance limits of industrial fibers are constantly being found. We obtained transcriptome assemblies from 1098 species of spiders to comprehensively catalog silk gene sequences and measured the mechanical, thermal, structural, and hydration properties of the dragline silks of 446 species. The combination of these silk protein genotype-phenotype data revealed essential contributions of multicomponent structures with major ampullate spidroin 1 to 3 paralogs in high-performance dragline silks and numerous amino acid motifs contributing to each of the measured properties. We hope that our global sampling, comprehensive testing, integrated analysis, and open data will provide a solid starting point for future biomaterial designs. SILK ; Spider silk ; Spider ; Biomaterial ; Polymer science ; Evolutionary biology ; Biology ; Nanotechnology ; Materials science ; Ecology ; Composite material Silk-based biomaterials and applications ; Spider Taxonomy and Behavior Studies ; Biochemical and Structural Characterization
Authors: Min Hong | Meng Li | Yuan Wang | Xiao‐Lei Shi | Zhi‐Gang Chen
Source: Advanced Materials (review, 2022-11-11)
Field: Materials Science — Materials Chemistry

Advances in Versatile GeTe Thermoelectrics from Materials to Devices Driven by the intensive efforts in the development of high-performance GeTe thermoelectrics for mass-market application in power generation and refrigeration, GeTe-based materials display a high figure of merit of >2.0 and an energy conversion efficiency beyond 10%. However, a comprehensive review on GeTe, from fundamentals to devices, is still needed. In this regard, the latest progress on the state-of-the-art GeTe is timely reviewed. The phase transition, intrinsic high carrier concentration, and multiple band edges of GeTe are fundamentally analyzed from the perspectives of the native atomic orbital, chemical bonding, and lattice defects. Then, the fabrication methods are summarized with a focus on large-scale production. Afterward, the strategies for enhancing electronic transports of GeTe by energy filtering effect, resonance doping, band convergence, and Rashba band splitting, and the methods for strengthening phonon scatterings via nanoprecipitates, planar vacancies, and superlattices, are comprehensively reviewed. Besides, the device assembly and performance are highlighted. In the end, future research directions are concluded and proposed, which enlighten the development of broader thermoelectric materials. Materials science ; Thermoelectric materials ; Figure of merit ; Engineering physics ; Nanotechnology ; Phonon ; Doping ; Fabrication ; Thermoelectric effect ; Superlattice ; Optoelectronics ; Effective mass (spring–mass system) ; Condensed matter physics ; Physics Advanced Thermoelectric Materials and Devices ; Chalcogenide Semiconductor Thin Films ; Phase-change materials and chalcogenides
Authors: Xiaoping Zhu | Tianyi Xu | Peng Chen | Shihua Wu
Source: Frontiers in Chemistry (review, 2022-02-03)
Field: Chemistry — Spectroscopy

Advances in MALDI Mass Spectrometry Imaging Single Cell and Tissues Compared with conventional optical microscopy techniques, mass spectrometry imaging (MSI) or imaging mass spectrometry (IMS) is a powerful, label-free analytical technique, which can sensitively and simultaneously detect, quantify, and map hundreds of biomolecules, such as peptides, proteins, lipid, and other organic compounds in cells and tissues. So far, although several soft ionization techniques, such as desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS) have been used for imaging biomolecules, matrix-assisted laser desorption/ionization (MALDI) is still the most widespread MSI scanning method. Here, we aim to provide a comprehensive review of MALDI-MSI with an emphasis on its advances of the instrumentation, methods, application, and future directions in single cell and biological tissues. Mass spectrometry imaging ; MALDI imaging ; Mass spectrometry ; Biomolecule ; Chemistry ; Desorption electrospray ionization ; Matrix-assisted laser desorption/ionization ; Capillary electrophoresis–mass spectrometry ; Analytical Chemistry (journal) ; Desorption ; Ionization ; Electrospray ionization ; Chromatography ; Ion ; Chemical ionization ; Biochemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Bahareh Azimi | Homa Maleki | Vito Gigante | Roohollah Bagherzadeh | Andrea Mezzetta | Mario Milazzo | Lorenzo Guazzelli | Patrizia Cinelli | Andrea Lazzeri | Serena Danti
Source: Cellulose (article, 2022-03-07)
Field: Materials Science — Biomaterials

Cellulose-based fiber spinning processes using ionic liquids Abstract Cellulose, a natural, renewable, and environment friendly biopolymer, has been considered as a sustainable feedstock in the near future. However, only 0.3% of cellulose is today processed since it is not soluble in conventional solvents due to the strong hydrogen bonding network and highly ordered structure. Hence, the search of effective and eco-friendly solvents for cellulose dissolution has been a key pillar for decades. In the recent years, ionic liquids (ILs) have been proposed as green solvents for cellulose and have been applied for the production of cellulose-based fibers. This review aims to focus the attention toward fiber spinning methods of cellulose based on ILs, as well as recent progress in cellulose dissolution using ILs. Moreover, the development of cellulosic fibers blended with other biopolymers, and cellulose composites are presented. Finally, different applications of cellulose fibers and composites are summarized and discussed. Cellulose ; Ionic liquid ; Cellulose fiber ; Materials science ; Dissolution ; Spinning ; Environmentally friendly ; Biopolymer ; Fiber ; Cellulosic ethanol ; Raw material ; Polymer science ; Composite material ; Chemical engineering ; Polymer ; Organic chemistry ; Chemistry ; Catalysis Advanced Cellulose Research Studies ; Nanocomposite Films for Food Packaging ; Electrospun Nanofibers in Biomedical Applications
Authors: Moh Tariq | Khan Nazima Mohammad | Bilal Ahmed | Mansoor A. Siddiqui | Jintae Lee
Source: Molecules (review, 2022-07-25)
Field: Materials Science — Materials Chemistry

Biological Synthesis of Silver Nanoparticles and Prospects in Plant Disease Management Exploration of nanoparticles (NPs) for various biological and environmental applications has become one of the most important attributes of nanotechnology. Due to remarkable physicochemical properties, silver nanoparticles (AgNPs) are the most explored and used NPs in wide-ranging applications. Also, they have proven to be of high commercial use since they possess great chemical stability, conductivity, catalytic activity, and antimicrobial potential. Though several methods including chemical and physical methods have been devised, biological approaches using organisms such as bacteria, fungi, and plants have emerged as economical, safe, and effective alternatives for the biosynthesis of AgNPs. Recent studies highlight the potential of AgNPs in modern agricultural practices to control the growth and spread of infectious pathogenic microorganisms since the introduction of AgNPs effectively reduces plant diseases caused by a spectrum of bacteria and fungi. In this review, we highlight the biosynthesis of AgNPs and discuss their applications in plant disease management with recent examples. It is proposed that AgNPs are prospective NPs for the successful inhibition of pathogen growth and plant disease management. This review gives a better understanding of new biological approaches for AgNP synthesis and modes of their optimized applications that could contribute to sustainable agriculture. Nanotechnology ; Silver nanoparticle ; Plant disease ; Plant growth ; Antimicrobial ; Biotechnology ; Biochemical engineering ; Broad spectrum ; Microorganism ; Agriculture ; Nanoparticle ; Chemistry ; Bacteria ; Biology ; Materials science ; Combinatorial chemistry ; Microbiology ; Engineering ; Ecology ; Botany Nanoparticles: synthesis and applications
Authors: Walid Ahmad | Elana P. Simon | Seyone Chithrananda | Gabriel Grand | Bharath Ramsundar
Source: arXiv (Cornell University) (preprint, 2022-09-05)
Field: Materials Science — Materials Chemistry

ChemBERTa-2: Towards Chemical Foundation Models Large pretrained models such as GPT-3 have had tremendous impact on modern natural language processing by leveraging self-supervised learning to learn salient representations that can be used to readily finetune on a wide variety of downstream tasks. We investigate the possibility of transferring such advances to molecular machine learning by building a chemical foundation model, ChemBERTa-2, using the language of SMILES. While labeled data for molecular prediction tasks is typically scarce, libraries of SMILES strings are readily available. In this work, we build upon ChemBERTa by optimizing the pretraining process. We compare multi-task and self-supervised pretraining by varying hyperparameters and pretraining dataset size, up to 77M compounds from PubChem. To our knowledge, the 77M set constitutes one of the largest datasets used for molecular pretraining to date. We find that with these pretraining improvements, we are competitive with existing state-of-the-art architectures on the MoleculeNet benchmark suite. We analyze the degree to which improvements in pretraining translate to improvement on downstream tasks. Computer science ; Benchmark (surveying) ; Suite ; Artificial intelligence ; Hyperparameter ; Task (project management) ; Salient ; Machine learning ; PubChem ; Set (abstract data type) ; Natural language processing ; Process (computing) ; Foundation (evidence) ; Variety (cybernetics) ; Programming language Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Topic Modeling
Authors: Alex Yong Sheng Eng | Chhail Bihari Soni | Yanwei Lum | Edwin Khoo | Zhenpeng Yao | S. K. Vineeth | Vipin Kumar | Jun Lü | Christopher S. Johnson | Christopher Wolverton | Zhi Wei Seh
Source: Science Advances (review, 2022-05-11)
Field: Materials Science — Materials Chemistry

Theory-guided experimental design in battery materials research A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical and experimental understanding of electrochemical mechanisms and structure-property relationships will allow us to accelerate the development of safer batteries with higher energy densities and longer lifetimes. This Review discusses the interplay between theory and experiment in battery materials research, enabling us to not only uncover hitherto unknown mechanisms but also rationally design more promising electrode and electrolyte materials. We examine specific case studies of theory-guided experimental design in lithium-ion, lithium-metal, sodium-metal, and all-solid-state batteries. We also offer insights into how this framework can be extended to multivalent batteries. To close the loop, we outline recent efforts in coupling machine learning with high-throughput computations and experiments. Last, recommendations for effective collaboration between theorists and experimentalists are provided. Battery (electricity) ; Computer science ; Energy storage ; Nanotechnology ; SAFER ; Lithium (medication) ; Throughput ; Biochemical engineering ; Systems engineering ; Materials science ; Power (physics) ; Engineering ; Physics ; Telecommunications Machine Learning in Materials Science ; Advanced Battery Technologies Research ; Advancements in Battery Materials
Authors: Danfei Liu | Changfan Zhang | Yumei Pu | Siyuan Chen | Lei Liu | Zijie Cui | Yunfei Zhong
Source: Foods (review, 2022-06-25)
Field: Chemistry — Analytical Chemistry

Recent Advances in pH-Responsive Freshness Indicators Using Natural Food Colorants to Monitor Food Freshness Recently, due to the enhancement in consumer awareness of food safety, considerable attention has been paid to intelligent packaging that displays the quality status of food through color changes. Natural food colorants show useful functionalities (antibacterial and antioxidant activities) and obvious color changes due to their structural changes in different acid and alkali environments, which could be applied to detect these acid and alkali environments, especially in the preparation of intelligent packaging. This review introduces the latest research on the progress of pH-responsive freshness indicators based on natural food colorants and biodegradable polymers for monitoring packaged food quality. Additionally, the current methods of detecting food freshness, the preparation methods for pH-responsive freshness indicators, and their applications for detecting the freshness of perishable food are highlighted. Subsequently, this review addresses the challenges and prospects of pH-responsive freshness indicators in food packaging, to assist in promoting their commercial application. Food packaging ; Active packaging ; Natural food ; Food quality ; Food industry ; Biochemical engineering ; Food science ; Food safety ; Biotechnology ; Environmental science ; Business ; Chemistry ; Engineering ; Biology Dye analysis and toxicity ; Biochemical Analysis and Sensing Techniques ; Advanced Chemical Sensor Technologies
Authors: Priti Tagde | Agnieszka Najda | Kalpana Nagpal | Giriraj T. Kulkarni | Muddaser Shah | Obaid Ullah | Sebastian Balant | Md. Habibur Rahman
Source: International Journal of Molecular Sciences (review, 2022-03-05)
Field: Materials Science — Biomaterials

Nanomedicine-Based Delivery Strategies for Breast Cancer Treatment and Management Breast cancer is one of the most common types of cancer among women globally. It is caused by mutations in the estrogen/progesterone receptors and conventional treatment methods are commonly utilized. About 70-80 percent of individuals with the early-stage non-metastatic disease may be cured. Conventional treatment is far less than the optimal ratio, as demonstrated through the high mortality rate of women with this cancer. However, conventional treatment methods like surgery, radiotherapy, and chemotherapy are not as effective as expected and lead to concerns about low bioavailability, low cellular uptake, emerging resistance, and adverse toxicities. A nanomedicine-based approach is a promising alternative for breast cancer treatment. The present era is witnessing rapid advancements in nanomedicine as a platform for investigating novel therapeutic applications and modern intelligent healthcare management strategies. This paper focuses on nanomedicine-based therapeutic interventions that are becoming more widely accepted for improving treatment effectiveness and reducing undesired side effects in breast cancer patients. By evaluating the state-of-the-art tools and taking the challenges involved into consideration, various aspects of the proposed nano-enabled therapeutic approaches have been discussed in this review. Nanomedicine ; Breast cancer ; Medicine ; Drug delivery ; Cancer ; Nanotechnology ; Internal medicine ; Nanoparticle ; Materials science Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Advanced Drug Delivery Systems
Authors: Yulou Ouyang | Cuiqian Yu | Jia He | Pengfei Jiang | Weijun Ren | Jie Chen
Source: Physical review. B./Physical review. B (article, 2022-03-09)
Field: Materials Science — Materials Chemistry

Accurate description of high-order phonon anharmonicity and lattice thermal conductivity from molecular dynamics simulations with machine learning potential Phonon anharmonicity is critical for accurately predicting the material's thermal conductivity ($\ensuremath{\kappa}$). However, its calculation based on the perturbation theory is a difficult and time-consuming task, especially for the high-order phonon scattering process. In this work, using cubic boron arsenide (BAs) and diamond as examples, we combine the machine learning potential (MLP) with molecular dynamics simulations to predict $\phantom{\rule{4pt}{0ex}}\ensuremath{\kappa}$ and assess the effect of anharmonicity on thermal transport properties. A MLP based on the matrix tensor algorithm is developed in this work, which can accurately describe lattice dynamics behaviors in both BAs and diamond. The phonon spectral energy density analysis reveals that MLP can effectively capture both the phonon mode softening and the linewidth broadening induced by the anharmonicity at finite temperatures in both materials. Compared to diamond, BAs exhibits a stronger anharmonicity revealed by the larger deviation from equilibrium position and more pronounced phonon broadening effect, especially at high temperatures. Furthermore, based on the phonon Boltzmann transport equation and three-phonon scattering process, our calculation results demonstrate that the accuracy of the MLP in predicting the $\ensuremath{\kappa}$ is comparable to that of density-functional theory calculations for both diamond and BAs. However, this framework can only predict $\ensuremath{\kappa}$ of diamond in agreement with experimental measurements, but significantly overestimates the $\ensuremath{\kappa}$ of BAs compared to the experimental results, due to the significant impact of high-order phonon scattering process in BAs. In contrast, the $\ensuremath{\kappa}$ values predicted by equilibrium molecular dynamics simulations combined with MLP agree well with experimental values for both BAs and diamond. Our study suggests that molecular dynamics simulation combined with MLP is a reliable and computationally efficient tool to account for full orders of anharmonicity and provide accurate predictions of material's thermal conductivity without any a priori knowledge of the importance of high-order phonon anharmonicity. Phonon ; Anharmonicity ; Thermal conductivity ; Condensed matter physics ; Diamond ; Molecular dynamics ; Boltzmann equation ; Phonon scattering ; Scattering ; Interatomic potential ; Physics ; Materials science ; Quantum mechanics Thermal properties of materials ; Thermal Expansion and Ionic Conductivity ; Advanced Thermoelectric Materials and Devices
Authors: Arpana Parihar | Ayushi Singhal | Neeraj Kumar | Raju Khan | Mohd. Akram Khan | Avanish Kumar Srivastava
Source: Nano-Micro Letters (review, 2022-04-11)
Field: Materials Science — Materials Chemistry

Next-Generation Intelligent MXene-Based Electrochemical Aptasensors for Point-of-Care Cancer Diagnostics Delayed diagnosis of cancer using conventional diagnostic modalities needs to be addressed to reduce the mortality rate of cancer. Recently, 2D nanomaterial-enabled advanced biosensors have shown potential towards the early diagnosis of cancer. The high surface area, surface functional groups availability, and excellent electrical conductivity of MXene make it the 2D material of choice for the fabrication of advanced electrochemical biosensors for disease diagnostics. MXene-enabled electrochemical aptasensors have shown great promise for the detection of cancer biomarkers with a femtomolar limit of detection. Additionally, the stability, ease of synthesis, good reproducibility, and high specificity offered by MXene-enabled aptasensors hold promise to be the mainstream diagnostic approach. In this review, the design and fabrication of MXene-based electrochemical aptasensors for the detection of cancer biomarkers have been discussed. Besides, various synthetic processes and useful properties of MXenes which can be tuned and optimized easily and efficiently to fabricate sensitive biosensors have been elucidated. Further, futuristic sensing applications along with challenges will be deliberated herein. Nanotechnology ; Biosensor ; MXenes ; Materials science ; Computer science ; Biochemical engineering ; Engineering MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; 2D Materials and Applications
Authors: Jenifer da Silva Mendonça | Rita de Cássia Avellaneda Guimarães | Verônica Assalin Zorgetto-Pinheiro | Carolina Di Pietro Fernandes | Gabriela Marcelino | Danielle Bogo | Karine de Cássia Freitas | Priscila Aiko Hiane | Elaine Silva de Pádua Melo | Marcelo Luiz Brandão Vilela | Valter Aragão do Nascimento
Source: Molecules (review, 2022-06-01)
Field: Chemistry — Organic Chemistry

Natural Antioxidant Evaluation: A Review of Detection Methods Antioxidants have drawn the attention of the scientific community due to being related to the prevention of various degenerative diseases. The antioxidant capacity has been extensively studied in vitro, and different methods have been used to assess its activity. However, the main issues related to studying natural antioxidants are evaluating whether these antioxidants demonstrate a key role in the biological system and assessing their bioavailability in the organism. The majority of outcomes in the literature are controversial due to a lack of method standardization and their proper application. Therefore, this study aims to compile the main issues concerning the natural antioxidant field of study, comparing the most common in vitro methods to evaluate the antioxidant activity of natural compounds, demonstrating the antioxidant activity in biological systems and the role of the main antioxidant enzymes of redox cellular signaling and explaining how the bioavailability of bioactive compounds is evaluated in animal models and human clinical trials. Antioxidant ; Bioavailability ; Organism ; Standardization ; Biochemical engineering ; Computational biology ; Biotechnology ; Chemistry ; Pharmacology ; Biology ; Biochemistry ; Computer science ; Engineering Free Radicals and Antioxidants ; Vitamin C and Antioxidants Research ; Antioxidant Activity and Oxidative Stress
Authors: Chaobo Liang | Jie He | Yali Zhang | Wei Zhang | Chunlei Liu | X. T. | Yaqing Liu | Junwei Gu
Source: Composites Science and Technology (article, 2022-04-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

MOF-derived CoNi@C-silver nanowires/cellulose nanofiber composite papers with excellent thermal management capability for outstanding electromagnetic interference shielding Materials science ; Electromagnetic shielding ; Composite number ; Composite material ; Electromagnetic interference ; EMI ; Electrical conductor ; Telecommunications ; Computer science Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Electromagnetic Compatibility and Noise Suppression