jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Vaishakh Kedambaimoole | Kajol Harsh | K. Rajanna | Prosenjit Sen | M. M. Nayak | Saurabh Kumar
Source: Materials Advances (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

MXene wearables: properties, fabrication strategies, sensing mechanism and applications Schematic representation of MXene based wearable sensors for various applications. Schematic ; Wearable computer ; Fabrication ; Mechanism (biology) ; Computer science ; Wearable technology ; Representation (politics) ; Human–computer interaction ; Nanotechnology ; Materials science ; Embedded system ; Engineering ; Electronic engineering ; Physics ; Medicine MXene and MAX Phase Materials ; Advanced Sensor and Energy Harvesting Materials ; Advanced Memory and Neural Computing
Authors: Xiaolin Pei | Zhiyuan Luo | Li Qiao | Qinjie Xiao | Pengfei Zhang | Anming Wang | Roger A. Sheldon
Source: Chemical Society Reviews (review, 2022-01-01)
Field: Chemistry — Organic Chemistry

Putting precision and elegance in enzyme immobilisation with bio-orthogonal chemistry The covalent immobilisation of enzymes generally involves the use of highly reactive crosslinkers, such as glutaraldehyde, to couple enzyme molecules to each other or to carriers through, for example, the free amino groups of lysine residues, on the enzyme surface. Unfortunately, such methods suffer from a lack of precision. Random formation of covalent linkages with reactive functional groups in the enzyme leads to disruption of the three dimensional structure and accompanying activity losses. This review focuses on recent advances in the use of bio-orthogonal chemistry in conjunction with rec-DNA to affect highly precise immobilisation of enzymes. In this way, cost-effective combination of production, purification and immobilisation of an enzyme is achieved, in a single unit operation with a high degree of precision. Various bio-orthogonal techniques for putting this precision and elegance into enzyme immobilisation are elaborated. These include, for example, fusing (grafting) peptide or protein tags to the target enzyme that enable its immobilisation in cell lysate or incorporating non-standard amino acids that enable the application of bio-orthogonal chemistry. Chemistry ; Elegance ; Enzyme ; Covalent bond ; Combinatorial chemistry ; Amino acid ; Biochemistry ; Organic chemistry Click Chemistry and Applications ; Biochemical and Structural Characterization ; Chemical Synthesis and Analysis
Authors: Pierre C. Havugimana | Raghuveera Kumar Goel | Sadhna Phanse | Ahmed Youssef | Dzmitry Padhorny | Sergei Kotelnikov | Dima Kozakov | Andrew Emili
Source: Nature Communications (article, 2022-07-13)
Field: Chemistry — Spectroscopy

Scalable multiplex co-fractionation/mass spectrometry platform for accelerated protein interactome discovery Co-fractionation/mass spectrometry (CF/MS) enables the mapping of endogenous macromolecular networks on a proteome scale, but current methods are experimentally laborious, resource intensive and afford lesser quantitative accuracy. Here, we present a technically efficient, cost-effective and reproducible multiplex CF/MS (mCF/MS) platform for measuring and comparing, simultaneously, multi-protein assemblies across different experimental samples at a rate that is up to an order of magnitude faster than previous approaches. We apply mCF/MS to map the protein interaction landscape of non-transformed mammary epithelia versus breast cancer cells in parallel, revealing large-scale differences in protein-protein interactions and the relative abundance of associated macromolecules connected with cancer-related pathways and altered cellular processes. The integration of multiplexing capability within an optimized workflow renders mCF/MS as a powerful tool for systematically exploring physical interaction networks in a comparative manner. Interactome ; Multiplex ; Computational biology ; Mass spectrometry ; Scalability ; Fractionation ; Computer science ; Chemistry ; Bioinformatics ; Biology ; Chromatography ; Database ; Biochemistry Advanced Proteomics Techniques and Applications ; RNA and protein synthesis mechanisms ; Protein Structure and Dynamics
Authors: Quan Xu | Xiaoqiang Su | Xueqian Zhang | Lijuan Dong | Lifeng Liu | Yunlong Shi | Qiu Wang | Ming Kang | Andrea Alù | Shuang Zhang | Jiaguang Han | Weili Zhang
Source: Advanced Photonics (article, 2022-02-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Mechanically reprogrammable Pancharatnam–Berry metasurface for microwaves Metasurfaces have enabled the realization of several optical functionalities over an ultrathin platform, fostering the exciting field of flat optics. Traditional metasurfaces are achieved by arranging a layout of static meta-atoms to imprint a desired operation on the impinging wavefront, but their functionality cannot be altered. Reconfigurability and programmability of metasurfaces are the next important step to broaden their impact, adding customized on-demand functionality in which each meta-atom can be individually reprogrammed. We demonstrate a mechanical metasurface platform with controllable rotation at the meta-atom level, which can implement continuous Pancharatnam-Berry phase control of circularly polarized microwaves. As the proof-of-concept experiments, we demonstrate metalensing, focused vortex beam generation, and holographic imaging in the same metasurface template, exhibiting versatility and superior performance. Such dynamic control of electromagnetic waves using a single, low-cost metasurface paves an avenue towards practical applications, driving the field of reprogrammable intelligent metasurfaces for a variety of applications. Reconfigurability ; Geometric phase ; Holography ; Wavefront ; Microwave ; Metamaterial ; Realization (probability) ; Computer science ; Optics ; Physics ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Orbital Angular Momentum in Optics
Authors: Eugene Krissinel | Andrey A. Lebedev | Ville Uski | Charles Ballard | Ronan M. Keegan | Oleg Kovalevskiy | Robert A. Nicholls | Neesh Pannu | Pavol Skubák | John M. Berrisford | Maria Fando | Bernhard Lohkamp | Marcin Wojdyr | Adam J. Simpkin | Jens M. H. Thomas | Christopher Oliver | Clemens Vonrhein | Grzegorz Chojnowski | Arnaud Baslé | Andrew G. Purkiss | Michail N. Isupov | Stuart McNicholas | E.D. Lowe | Josep Triviño | Kevin Cowtan | Jon Agirre | Daniel J. Rigden | Isabel Usón | Victor S. Lamzin | Ivo Tews | G. Bricogne | Andrew G. W. Leslie | D. Brown
Source: Acta Crystallographica Section D Structural Biology (article, 2022-08-30)
Field: Materials Science — Materials Chemistry

<i>CCP</i>4 Cloud for structure determination and project management in macromolecular crystallography Nowadays, progress in the determination of three-dimensional macromolecular structures from diffraction images is achieved partly at the cost of increasing data volumes. This is due to the deployment of modern high-speed, high-resolution detectors, the increased complexity and variety of crystallographic software, the use of extensive databases and high-performance computing. This limits what can be accomplished with personal, offline, computing equipment in terms of both productivity and maintainability. There is also an issue of long-term data maintenance and availability of structure-solution projects as the links between experimental observations and the final results deposited in the PDB. In this article, CCP4 Cloud, a new front-end of the CCP4 software suite, is presented which mitigates these effects by providing an online, cloud-based environment for crystallographic computation. CCP4 Cloud was developed for the efficient delivery of computing power, database services and seamless integration with web resources. It provides a rich graphical user interface that allows project sharing and long-term storage for structure-solution projects, and can be linked to data-producing facilities. The system is distributed with the CCP4 software suite version 7.1 and higher, and an online publicly available instance of CCP4 Cloud is provided by CCP4. Cloud computing ; Computer science ; Operating system Enzyme Structure and Function ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Zhiping Ye | Liang Zhao | Anton Nikiforov | Jean‐Marc Giraudon | Yue Chen | Jiade Wang | Xin Tu
Source: Advances in Colloid and Interface Science (review, 2022-08-16)
Field: Materials Science — Materials Chemistry

A review of the advances in catalyst modification using nonthermal plasma: Process, Mechanism and Applications With the continuous development of catalytic processes in chemistry, biology, organic synthesis, energy generation and many other fields, the design of catalysts with novel properties has become a new paradigm in both science and industry. Nonthermal plasma has aroused extensive interest in the synthesis and modification of catalysts. An increasing number of researchers are using plasma for the modification of target catalysts, such as modifying the dispersion of active sites, regulating electronic properties, enhancing metal-support interactions, and changing the morphology. Plasma provides an alternative choice for catalysts in the modification process of oxidation, reduction, etching, coating, and doping and is especially helpful for unfavourable thermodynamic processes or heat-sensitive reactions. This review focuses on the following points: (i) the fundamentals behind the nonthermal plasma modification of catalysts; (ii) the latest research progress on the application of plasma modified catalysts; and (iii) main challenges in the field and a vision for future development. Catalysis ; Nanotechnology ; Plasma ; Surface modification ; Coating ; Nonthermal plasma ; Materials science ; Mechanism (biology) ; Process (computing) ; Plasma etching ; Chemical engineering ; Chemistry ; Etching (microfabrication) ; Computer science ; Organic chemistry ; Engineering ; Physics Catalytic Processes in Materials Science ; Advanced Photocatalysis Techniques ; Copper-based nanomaterials and applications
Authors: Hajir Hilal | Qiang Zhao | Jeongwon Kim | Sungwoo Lee | MohammadNavid Haddadnezhad | Sungjae Yoo | Soohyun Lee | Woongkyu Park | Woocheol Park | Jaewon Lee | Joong Wook Lee | Insub Jung | Sungho Park
Source: Nature Communications (article, 2022-08-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Three-dimensional nanoframes with dual rims as nanoprobes for biosensing Three-dimensional (3D) nanoframe structures are very appealing because their inner voids and ridges interact efficiently with light and analytes, allowing for effective optical-based sensing. However, the realization of complex nanoframe architecture with high yield is challenging because the systematic design of such a complicated nanostructure lacks an appropriate synthesis protocol. Here, we show the synthesis method for complex 3D nanoframes wherein two-dimensional (2D) dual-rim nanostructures are engraved on each facet of octahedral nanoframes. The synthetic scheme proceeds through multiple executable on-demand steps. With Au octahedral nanoparticles as a sacrificial template, sequential processes of edge-selective Pt deposition and inner Au etching lead to Pt octahedral mono-rim nanoframes. Then, adlayers of Au are grown on Pt skeletons via the Frank-van der Merwe mode, forming sharp and well-developed edges. Next, Pt selective deposition on both the inner and outer boundaries leads to tunable geometric patterning on Au. Finally, after the selective etching of Au, Pt octahedral dual-rim nanoframes with highly homogeneous size and shape are achieved. In order to endow plasmonic features, Au is coated around Pt frames while retaining their geometric shape. The resultant plasmonic dual-rim engraved nanoframes possess strong light entrapping capability verified by single-particle surface-enhanced Raman scattering (SERS) and show the potential of nanoprobes for biosensing through SERS-based immunoassay. Materials science ; Nanotechnology ; Nanostructure ; Nanoparticle ; Etching (microfabrication) ; Plasmon ; Discrete dipole approximation ; Optoelectronics ; Scattering ; Optics ; Layer (electronics) Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Quantum Dots Synthesis And Properties
Authors: I. Brian Becerril‐Castro | Irene Calderón | Nicolás Pazos‐Pérez | Luca Guerrini | Florian Schulz | Neus Feliu | Indranath Chakraborty | Vincenzo Giannini | Wolfgang J. Parak | Ramón A. Álvarez‐Puebla
Source: Analysis & Sensing (article, 2022-03-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Gold Nanostars: Synthesis, Optical and SERS Analytical Properties Abstract Gold nanostars are among the most efficient plasmonic nanomaterials for optical sensing with surface enhanced Raman scattering. In recent years, gold nanostars have increased relevance in physics, analytical chemistry, environmental science, biology and medicine, and in particular in sensing and therapy. These colloids can sustain ultrastrong electromagnetic fields which allow their use as single particles optical enhancers; are colloidally stable and may have a marked catalytical activity. Due to their exotic shape, these colloids present characteristic optical and reactive behaviors. Here, we briefly discuss the optical properties, the synthetic routes and the analytical applications of these nanoparticles. Nanotechnology ; Raman scattering ; Nanomaterials ; Plasmon ; Colloidal gold ; Materials science ; Colloid ; Nanoparticle ; Raman optical activity ; Raman spectroscopy ; Chemistry ; Physics ; Optoelectronics ; Optics ; Physical chemistry Gold and Silver Nanoparticles Synthesis and Applications ; Nanocluster Synthesis and Applications ; Nanoparticles: synthesis and applications
Authors: Alessandro Lunghi | Stefano Sanvito
Source: Nature Reviews Chemistry (review, 2022-10-10)
Field: Materials Science — Materials Chemistry

Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations Spintronics ; Spins ; Degrees of freedom (physics and chemistry) ; Ab initio ; Computer science ; Quantum ; Molecule ; Electron ; Physics ; Nanotechnology ; Materials science ; Quantum mechanics ; Condensed matter physics Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications ; Electron and X-Ray Spectroscopy Techniques
Authors: Gabriele M. Coli | Emanuele Boattini | Laura Filion | Marjolein Dijkstra
Source: Science Advances (article, 2022-01-19)
Field: Materials Science — Materials Chemistry

Inverse design of soft materials via a deep learning–based evolutionary strategy Colloidal self-assembly—the spontaneous organization of colloids into ordered structures—has been considered key to produce next-generation materials. However, the present-day staggering variety of colloidal building blocks and the limitless number of thermodynamic conditions make a systematic exploration intractable. The true challenge in this field is to turn this logic around and to develop a robust, versatile algorithm to inverse design colloids that self-assemble into a target structure. Here, we introduce a generic inverse design method to efficiently reverse-engineer crystals, quasicrystals, and liquid crystals by targeting their diffraction patterns. Our algorithm relies on the synergetic use of an evolutionary strategy for parameter optimization, and a convolutional neural network as an order parameter, and provides a way forward for the inverse design of experimentally feasible colloidal interactions, specifically optimized to stabilize the desired structure. Inverse ; Computer science ; Variety (cybernetics) ; Field (mathematics) ; Colloidal crystal ; Convolutional neural network ; Colloid ; Nanotechnology ; Algorithm ; Mathematical optimization ; Materials science ; Artificial intelligence ; Mathematics ; Engineering Pickering emulsions and particle stabilization ; Proteins in Food Systems ; Advanced Materials and Mechanics
Authors: Ziyang Zhang | Qingyang Liu | Dazhong Wu
Source: Materials & Design (article, 2022-04-29)
Field: Materials Science — Materials Chemistry

Predicting stress–strain curves using transfer learning: Knowledge transfer across polymer composites The engineering stress–strain curve of a material allows one to determine mechanical properties such as elastic modulus, strength, and toughness. While machine learning has recently been used to predict stress–strain curves, large volumes of experimental data are required to achieve high prediction accuracy. More importantly, conventional machine learning models are not generalizable from one material to another. To address this issue, a novel transfer learning approach is introduced to predict stress–strain curves across different fiber reinforced polymer (FRP) composites fabricated via additive manufacturing. Optimal transport (OT) is integrated with the transfer learning approach by mapping the source label space to the target label space, which further improves knowledge transferability across different FRP composites. The stress–strain curves of the additively manufactured FRP composites are generated under flexural loading conditions. Experimental results show that the OT-integrated transfer learning approach can predict the complex stress–strain curves of FRP composites with small training data. The predictive model achieved a mean absolute percentage error (MAPE) of less than 10%. The extracted modulus and strength from the predicted stress–strain curves achieved MAPEs of less than 5% and 10%, respectively. This work demonstrates that transfer learning has the potential to transform how stress–strain curves are generated. Materials science ; Composite material ; Stress–strain curve ; Stress (linguistics) ; Modulus ; Fibre-reinforced plastic ; Toughness ; Flexural strength ; Transfer of learning ; Strain (injury) ; Elastic modulus ; Machine learning ; Computer science ; Deformation (meteorology) Machine Learning in Materials Science ; Ultrasonics and Acoustic Wave Propagation ; Non-Destructive Testing Techniques
Authors: Vishnu Sankar Sivasankarapillai | Tata Sanjay Kanna Sharma | Kuo‐Yuan Hwa | Saikh Mohammad Wabaidur | Subramania Angaiah | Ragupathy Dhanusuraman
Source: ES Energy & Environments (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

MXene Based Sensing Materials: Current Status and Future Perspectives MXenes are a family of two-dimensional multifunctional materials in a rapid development phase since their discovery in 2011. MXenes possess excellent features like high conductivity and surface area, improved mechanical properties, hydrophilicity, and the ability to tune surface properties by modifying functional groups. These features make MXenes suitable candidates for a wide range of applications, including biomedical and energy storage. This review is focused on various types of MXenes which are recently been reported for sensor applications. The current scenario regarding the fabrication and properties of MXenes are initially described, followed by a discussion of their applications as piezoresistive and biochemical sensors. This involves mechanical strain detection and the detection of biomolecules, biomarkers, and drug molecules relevant to biomedical applications. Finally, the future perspectives are briefly discussed, which will help the researchers identify the limitations of the current scenario and develop new strategies that focus on developing novel, efficient and sensitive MXenebased sensors. Current (fluid) ; Computer science ; Data science ; Environmental science ; Engineering ; Electrical engineering MXene and MAX Phase Materials ; 2D Materials and Applications ; Graphene research and applications
Authors: Margarita R. Chetyrkina | Fedor S. Fedorov | Albert G. Nasibulin
Source: RSC Advances (review, 2022-01-01)
Field: Materials Science — Materials Chemistry

<i>In vitro</i>toxicity of carbon nanotubes: a systematic review Carbon nanotube (CNT) toxicity-related issues provoke many debates in the scientific community. The controversial and disputable data about toxicity doses, proposed hazard effects, and human health concerns significantly restrict CNT applications in biomedical studies, laboratory practices, and industry, creating a barrier for mankind in the way of understanding how exactly the material behaves in contact with living systems. Raising the toxicity question again, many research groups conclude low toxicity of the material and its potential safeness at some doses for contact with biological systems. To get new momentum for researchers working on the intersection of the biological field and nanomaterials, <i>i.e.</i>, CNT materials, we systematically reviewed existing studies with <i>in vitro</i> toxicological data to propose exact doses that yield toxic effects, summarize studied cell types for a more thorough comparison, the impact of incubation time, and applied toxicity tests. Using several criteria and different scientific databases, we identified and analyzed nearly 200 original publications forming a "golden core" of the field to propose safe doses of the material based on a statistical analysis of retrieved data. We also differentiated the impact of various forms of CNTs: on a substrate and in the form of dispersion because in both cases, some studies demonstrated good biocompatibility of CNTs. We revealed that CNTs located on a substrate had negligible impact, <i>i.e.</i>, 90% of studies report good viability and cell behavior similar to control, therefore CNTs could be considered as a prospective conductive substrate for cell cultivation. In the case of dispersions, our analysis revealed mean values of dose/incubation time to be 4-5 μg mL<sup>-1</sup> h<sup>-1</sup>, which suggested the material to be a suitable candidate for further studies to get a more in-depth understanding of its properties in biointerfaces and offer CNTs as a promising platform for fundamental studies in targeted drug delivery, chemotherapy, tissue engineering, biosensing fields, <i>etc</i>. We hope that the present systematic review will shed light on the current knowledge about CNT toxicity, indicate "dark" spots and offer possible directions for the subsequent studies based on the demonstrated here tabulated and statistical data of doses, cell models, toxicity tests, viability, <i>etc</i>. Carbon nanotube ; In vitro ; Toxicity ; Chemistry ; Nanotechnology ; Materials science ; Biochemistry ; Organic chemistry Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Anesthesia and Neurotoxicity Research