jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: David Parker | Jack D. Fradgley | Ka‐Leung Wong
Source: Chemical Society Reviews (review, 2021-01-01)
Field: Materials Science — Materials Chemistry

The design of responsive luminescent lanthanide probes and sensors The principles of the design of responsive luminescent probes and sensors based on lanthanide emission are summarised, based on a mechanistic understanding of their mode of action. Competing kinetic pathways for deactivation of the excited states that occur are described, highlighting the need to consider each of the salient quenching processes. Such an analysis dictates the choice of both the ligand and its integral sensitising moiety for the particular application. The key aspects of quenching involving electron transfer and vibrational and electronic energy transfer are highlighted and exemplified. Responsive systems for pH, pM, pX and pO<sub>2</sub> and selected biochemical analytes are distinguished, according to the nature of the optical signal observed. Signal changes include both simple and ratiometric intensity measurements, emission lifetime variations and the unique features associated with the observation of circularly polarised luminescence (CPL) for chiral systems. A classification of responsive lanthanide probes is introduced. Examples of the operation of probes for reactive oxygen species, citrate, bicarbonate, α<sub>1</sub>-AGP and pH are used to illustrate reversible and irreversible transformations of the ligand constitution, as well as the reversible changes to the metal primary and secondary coordination sphere that sensitively perturb the ligand field. Finally, systems that function by modulation of dynamic quenching of the ligand or metal excited states are described, including real time observation of endosomal acidification in living cells, rapid urate analysis in serum, accurate temperature assessment in confined compartments and high throughput screening of drug binding to G-protein coupled receptors. Lanthanide ; Luminescence ; Luminescent Measurements ; Nanotechnology ; Computer science ; Chemistry ; Materials science ; Optoelectronics ; Organic chemistry Lanthanide and Transition Metal Complexes ; Analytical Chemistry and Sensors ; Atomic and Subatomic Physics Research
Authors: Aditya Nandy | Chenru Duan | Michael G. Taylor | Fang Liu | Adam H. Steeves | Heather J. Kulik
Source: Chemical Reviews (review, 2021-07-14)
Field: Materials Science — Materials Chemistry

Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning Transition-metal complexes are attractive targets for the design of catalysts and functional materials. The behavior of the metal-organic bond, while very tunable for achieving target properties, is challenging to predict and necessitates searching a wide and complex space to identify needles in haystacks for target applications. This review will focus on the techniques that make high-throughput search of transition-metal chemical space feasible for the discovery of complexes with desirable properties. The review will cover the development, promise, and limitations of "traditional" computational chemistry (i.e., force field, semiempirical, and density functional theory methods) as it pertains to data generation for inorganic molecular discovery. The review will also discuss the opportunities and limitations in leveraging experimental data sources. We will focus on how advances in statistical modeling, artificial intelligence, multiobjective optimization, and automation accelerate discovery of lead compounds and design rules. The overall objective of this review is to showcase how bringing together advances from diverse areas of computational chemistry and computer science have enabled the rapid uncovering of structure-property relationships in transition-metal chemistry. We aim to highlight how unique considerations in motifs of metal-organic bonding (e.g., variable spin and oxidation state, and bonding strength/nature) set them and their discovery apart from more commonly considered organic molecules. We will also highlight how uncertainty and relative data scarcity in transition-metal chemistry motivate specific developments in machine learning representations, model training, and in computational chemistry. Finally, we will conclude with an outlook of areas of opportunity for the accelerated discovery of transition-metal complexes. Chemistry ; Throughput ; High-throughput screening ; Drug discovery ; Transition metal ; Nanotechnology ; Catalysis ; Organic chemistry ; Biochemistry ; Computer science ; Telecommunications Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Catalysis and Oxidation Reactions
Authors: Omnia Samy | Shuwen Zeng | Muhammad Danang Birowosuto | Amine El Moutaouakil
Source: Crystals (review, 2021-03-29)
Field: Materials Science — Materials Chemistry

A Review on MoS2 Properties, Synthesis, Sensing Applications and Challenges Molybdenum disulfide (MoS2) is one of the compounds discussed nowadays due to its outstanding properties that allowed its usage in different applications. Its band gap and its distinctive structure make it a promising material to substitute graphene and other semiconductor devices. It has different applications in electronics especially sensors like optical sensors, biosensors, electrochemical biosensors that play an important role in the detection of various diseases’ like cancer and Alzheimer. It has a wide range of energy applications in batteries, solar cells, microwave, and Terahertz applications. It is a promising material on a nanoscale level, with favorable characteristics in spintronics and magnetoresistance. In this review, we will discuss MoS2 properties, structure and synthesis techniques with a focus on its applications and future challenges. Nanotechnology ; Molybdenum disulfide ; Materials science ; Biosensor ; Graphene ; Electronics ; Semiconductor ; Optoelectronics ; Engineering ; Electrical engineering 2D Materials and Applications ; MXene and MAX Phase Materials ; Perovskite Materials and Applications
Authors: Jimmy Lin | Xueguang Ma | Sheng-Chieh Lin | Jheng-Hong Yang | Ronak Pradeep | Rodrigo Nogueira
Source:  (article, 2021-07-11)
Field: Materials Science — Materials Chemistry

Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage retrieval in a multi-stage ranking architecture. Our toolkit is self-contained as a standard Python package and comes with queries, relevance judgments, pre-built indexes, and evaluation scripts for many commonly used IR test collections. We aim to support, out of the box, the entire research lifecycle of efforts aimed at improving ranking with modern neural approaches. In particular, Pyserini supports sparse retrieval (e.g., BM25 scoring using bag-of-words representations), dense retrieval (e.g., nearest-neighbor search on transformer-encoded representations), as well as hybrid retrieval that integrates both approaches. This paper provides an overview of toolkit features and presents empirical results that illustrate its effectiveness on two popular ranking tasks. Around this toolkit, our group has built a culture of reproducibility through shared norms and tools that enable rigorous automated testing. Python (programming language) ; Computer science ; Information retrieval ; Scripting language ; Ranking (information retrieval) ; Relevance (law) ; Data mining ; Programming language Machine Learning in Materials Science ; Explainable Artificial Intelligence (XAI) ; Domain Adaptation and Few-Shot Learning
Authors: Oliver T. Unke | Stefan Chmiela | Michael Gastegger | Kristof T. Schütt | Huziel E. Sauceda | Klaus‐Robert Müller
Source: Nature Communications (article, 2021-12-14)
Field: Materials Science — Materials Chemistry

SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects Machine-learned force fields combine the accuracy of ab initio methods with the efficiency of conventional force fields. However, current machine-learned force fields typically ignore electronic degrees of freedom, such as the total charge or spin state, and assume chemical locality, which is problematic when molecules have inconsistent electronic states, or when nonlocal effects play a significant role. This work introduces SpookyNet, a deep neural network for constructing machine-learned force fields with explicit treatment of electronic degrees of freedom and nonlocality, modeled via self-attention in a transformer architecture. Chemically meaningful inductive biases and analytical corrections built into the network architecture allow it to properly model physical limits. SpookyNet improves upon the current state-of-the-art (or achieves similar performance) on popular quantum chemistry data sets. Notably, it is able to generalize across chemical and conformational space and can leverage the learned chemical insights, e.g. by predicting unknown spin states, thus helping to close a further important remaining gap for today's machine learning models in quantum chemistry. Degrees of freedom (physics and chemistry) ; Computer science ; Physics ; Statistical physics ; Classical mechanics ; Quantum mechanics Machine Learning in Materials Science ; Force Microscopy Techniques and Applications ; Electronic and Structural Properties of Oxides
Authors: Zhiqiang Li | Guannan Wang | Bin Li | Hongzhong Chen | Huanrong Li | Yanli Zhao
Source: Nature Communications (article, 2021-03-01)
Field: Materials Science — Materials Chemistry

Photoresponsive supramolecular coordination polyelectrolyte as smart anticounterfeiting inks While photoluminescence printing is a widely applied anticounterfeiting technique, there are still challenges in developing new generation anticounterfeiting materials with high security. Here we report the construction of a photoresponsive supramolecular coordination polyelectrolyte (SCP) through hierarchical self-assembly of lanthanide ion, bis-ligand and diarylethene unit, driven by metal-ligand coordination and ionic interaction. Owing to the conformation-dependent photochromic fluorescence resonance energy transfer between the lanthanide donor and diarylethene acceptor, the ring-closure/ring-opening isomerization of the diarylethene unit leads to a photoreversible luminescence on/off switch in the SCP. The SCP is then utilized as security ink to print various patterns, through which photoreversible multiple information patterns with visible/invisible transformations are realized by simply alternating the irradiation with UV and visible light. This work demonstrates the possibility of developing a new class of smart anticounterfeiting materials, which could be operated in a noninvasive manner with a higher level of security. Diarylethene ; Photochromism ; Supramolecular chemistry ; Photochemistry ; Ligand (biochemistry) ; Isomerization ; Materials science ; Förster resonance energy transfer ; Lanthanide ; Nanotechnology ; Chemistry ; Fluorescence ; Ion ; Catalysis ; Organic chemistry ; Molecule Luminescence and Fluorescent Materials ; Photochromic and Fluorescence Chemistry ; Advanced Polymer Synthesis and Characterization
Authors: Shi En Kim | Fauzia Mujid | Akash Rai | Fredrik Eriksson | Joonki Suh | Preeti Poddar | Ariana Ray | Chibeom Park | Erik Fransson | Yu Zhong | David A. Muller | Paul Erhart | David G. Cahill | Jiwoong Park
Source: Nature (article, 2021-09-29)
Field: Materials Science — Materials Chemistry

Extremely anisotropic van der Waals thermal conductors The densification of integrated circuits requires thermal management strategies and high thermal conductivity materials<sup>1-3</sup>. Recent innovations include the development of materials with thermal conduction anisotropy, which can remove hotspots along the fast-axis direction and provide thermal insulation along the slow axis<sup>4,5</sup>. However, most artificially engineered thermal conductors have anisotropy ratios much smaller than those seen in naturally anisotropic materials. Here we report extremely anisotropic thermal conductors based on large-area van der Waals thin films with random interlayer rotations, which produce a room-temperature thermal anisotropy ratio close to 900 in MoS<sub>2</sub>, one of the highest ever reported. This is enabled by the interlayer rotations that impede the through-plane thermal transport, while the long-range intralayer crystallinity maintains high in-plane thermal conductivity. We measure ultralow thermal conductivities in the through-plane direction for MoS<sub>2</sub> (57 ± 3 mW m<sup>-1</sup> K<sup>-1</sup>) and WS<sub>2</sub> (41 ± 3 mW m<sup>-1</sup> K<sup>-1</sup>) films, and we quantitatively explain these values using molecular dynamics simulations that reveal one-dimensional glass-like thermal transport. Conversely, the in-plane thermal conductivity in these MoS<sub>2</sub> films is close to the single-crystal value. Covering nanofabricated gold electrodes with our anisotropic films prevents overheating of the electrodes and blocks heat from reaching the device surface. Our work establishes interlayer rotation in crystalline layered materials as a new degree of freedom for engineering-directed heat transport in solid-state systems. Thermal conductivity ; Anisotropy ; Materials science ; Thermal conduction ; van der Waals force ; Electrical conductor ; Thermal ; Condensed matter physics ; Composite material ; Thermodynamics ; Optics ; Chemistry ; Physics Thermal properties of materials ; Graphene research and applications ; Advanced Thermoelectric Materials and Devices
Authors: Yifei Wang | Patrick Landreman | David Schoen | Kye Okabe | Ann Marshall | Umberto Celano | H.-S. Philip Wong | Junghyun Park | Mark L. Brongersma
Source: Nature Nanotechnology (article, 2021-04-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Electrical tuning of phase-change antennas and metasurfaces Plasmon ; Optical switch ; Semiconductor ; Resonator ; Antenna (radio) ; Electronics ; Modulation (music) ; Scattering ; Refractive index Metamaterials and Metasurfaces Applications ; Phase-change materials and chalcogenides ; Plasmonic and Surface Plasmon Research
Authors: Md Golam Rasul | Alper Kızıltaş | Babak Arfaei | Reza Shahbazian‐Yassar
Source: npj 2D Materials and Applications (article, 2021-05-17)
Field: Materials Science — Materials Chemistry

2D boron nitride nanosheets for polymer composite materials Abstract Hexagonal boron nitride nanosheets (BNNSs) are promising two-dimensional materials to boost the mechanical, thermal, electrical, and optical properties of polymer nanocomposites. Yet, BNNS-polymer composites face many challenges to meet the desired properties owing to agglomeration of BNNSs, incompatibility, and weak interactions of BNNSs with the host polymers. This work systematically reviews the fundamental parameters that control the molecular interactions of BNNSs with polymer matrices. The surface modification of BNNSs, as well as size, dispersion, and alignment of these nanosheets have a profound effect on polymer chain dynamics, mass barrier properties, and stress-transfer efficiency of the nanocomposites. Boron nitride ; Materials science ; Polymer ; Nanocomposite ; Polymer nanocomposite ; Economies of agglomeration ; Dispersion (optics) ; Composite number ; Nanotechnology ; Surface modification ; Composite material ; Chemical engineering Graphene research and applications ; Thermal properties of materials ; 2D Materials and Applications
Authors: Andrew J. Miles | Robert W. Janes | B.A. Wallace
Source: Chemical Society Reviews (review, 2021-01-01)
Field: Chemistry — Spectroscopy

Tools and methods for circular dichroism spectroscopy of proteins: a tutorial review Circular dichroism (CD) spectroscopy is a widely-used method in biochemistry, structural biology and pharmaceutical chemistry. More than 24 000 papers published in the past decade have included CD characterisations of proteins; many of those studies have also included other complementary chemical, biophysical, and computational chemistry methods. This tutorial review describes the background to the technique of CD spectroscopy and good practice methods for high quality data collection. It specifically focuses on both established and new methods and tools available for experimental design and interpretation, data processing, visualisation, analysis, validation, archiving, and accession, including tools developed to enhance the complementarity of this method with other structural and chemical biology studies. Complementarity (molecular biology) ; Circular dichroism ; Structural biology ; Chemistry ; Spectroscopy ; Computer science ; Nanotechnology ; Computational biology ; Materials science ; Biochemistry ; Physics ; Biology ; Genetics Molecular spectroscopy and chirality ; Protein Structure and Dynamics ; Spectroscopy and Quantum Chemical Studies
Authors: Mehran Ghasemlou | Fügen Daver | Elena P. Ivanova | Youssef Habibi | Benu Adhikari
Source: Progress in Polymer Science (article, 2021-05-29)
Field: Materials Science — Biomaterials

Surface modifications of nanocellulose: From synthesis to high-performance nanocomposites Nanocellulose ; Materials science ; Nanotechnology ; Nanocomposite ; Surface modification ; Polymer nanocomposite ; Polymer ; Composite material ; Chemical engineering ; Cellulose Advanced Cellulose Research Studies ; Electrospun Nanofibers in Biomedical Applications ; Nanocomposite Films for Food Packaging
Authors: Stylianos Sarrigiannidis | Jose Manuel Rey | Oana Dobre | Cristina González‐García | Matthew J. Dalby | Manuel Salmerón‐Sánchez
Source: Materials Today Bio (review, 2021-02-16)
Field: Materials Science — Biomaterials

A tough act to follow: collagen hydrogel modifications to improve mechanical and growth factor loading capabilities Collagen hydrogels are among ​the most well-studied platforms for drug delivery and <i>in situ</i> tissue engineering, thanks to their low cost, low immunogenicity, versatility, biocompatibility, and similarity to the natural extracellular matrix (ECM). Despite collagen being largely responsible for the tensile properties of native connective tissues, collagen hydrogels have relatively low mechanical properties in the absence of covalent cross-linking. This is particularly problematic when attempting to regenerate stiffer and stronger native tissues such as bone. Furthermore, in contrast to hydrogels based on ECM proteins such as fibronectin, collagen hydrogels do not have any growth factor (GF)-specific binding sites and often cannot sequester physiological (small) amounts of the protein. GF binding and <i>in situ</i> presentation are properties that can aid significantly in the tissue regeneration process by dictating cell fate without causing adverse effects such as malignant tumorigenic tissue growth. To alleviate these issues, researchers have developed several strategies to increase the mechanical properties of collagen hydrogels using physical or chemical modifications. This can expand the applicability of collagen hydrogels to tissues subject to a continuous load. GF delivery has also been explored, mathematically and experimentally, through the development of direct loading, chemical cross-linking, electrostatic interaction, and other carrier systems. This comprehensive article explores the ways in which these parameters, mechanical properties and GF delivery, have been optimized in collagen hydrogel systems ​and examines their <i>in vitro</i> or <i>in vivo</i> biological effect. This article can, therefore, be a useful tool to streamline future studies in the field, by pointing researchers into the appropriate direction according to their collagen hydrogel design requirements. Self-healing hydrogels ; Extracellular matrix ; Tissue engineering ; Biocompatibility ; Gelatin ; Regeneration (biology) ; Biophysics ; Fibronectin ; In vivo ; Materials science ; Chemistry ; Biomedical engineering ; Nanotechnology ; Cell biology ; Biochemistry ; Biology ; Engineering ; Biotechnology ; Polymer chemistry Collagen: Extraction and Characterization ; Cellular Mechanics and Interactions ; 3D Printing in Biomedical Research
Authors: David Graff | Eugene I. Shakhnovich | Connor W. Coley
Source: Chemical Science (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Accelerating high-throughput virtual screening through molecular pool-based active learning Structure-based virtual screening is an important tool in early stage drug discovery that scores the interactions between a target protein and candidate ligands. As virtual libraries continue to grow (in excess of 10<sup>8</sup> molecules), so too do the resources necessary to conduct exhaustive virtual screening campaigns on these libraries. However, Bayesian optimization techniques, previously employed in other scientific discovery problems, can aid in their exploration: a surrogate structure-property relationship model trained on the predicted affinities of a subset of the library can be applied to the remaining library members, allowing the least promising compounds to be excluded from evaluation. In this study, we explore the application of these techniques to computational docking datasets and assess the impact of surrogate model architecture, acquisition function, and acquisition batch size on optimization performance. We observe significant reductions in computational costs; for example, using a directed-message passing neural network we can identify 94.8% or 89.3% of the top-50 000 ligands in a 100M member library after testing only 2.4% of candidate ligands using an upper confidence bound or greedy acquisition strategy, respectively. Such model-guided searches mitigate the increasing computational costs of screening increasingly large virtual libraries and can accelerate high-throughput virtual screening campaigns with applications beyond docking. Throughput ; Virtual screening ; High-throughput screening ; Computer science ; Active learning (machine learning) ; Computational biology ; Human–computer interaction ; Chemistry ; Artificial intelligence ; Drug discovery ; Biology ; Telecommunications ; Biochemistry Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation ; Computational Drug Discovery Methods
Authors: Muzahidul I. Anik | M. Khalid Hossain | Imran Hossain | A. M. U. B. Mahfuz | Mehbuba Rahman | Isteaque Ahmed
Source: Nano Select (review, 2021-01-21)
Field: Materials Science — Biomaterials

Recent progress of magnetic nanoparticles in biomedical applications: A review Abstract Magnetic nanoparticles (MNPs) offer tremendous potentialities in biomedical applications for a long while. Since these materials' interactions in biological media largely rely on their crystal structures, sizes, and shapes, detailed studies on their synthesis mechanism for medicinal aspects are crucial. Despite many review reports that have already been published on MNPs, they mainly have focused either on their perspective in biomedical applications or their synthesis and characterization along with functionalization mechanisms as individual entities. For this reason, this review uncovers a comprehensive insight into the ongoing improvement of fabrication processes, surface functionalization of MNPs for biomedical applications together. Besides, various magnetic nanocomposite (MNCs) for smart drug delivery, recent hyperthermia treatment, lab‐on‐a‐chip, and magnetic bio‐separation, and some of the recent emerging imaging techniques using MNPs are discussed. A detailed analysis of toxicity, challenges, and recent progress of clinical trials of MNPs is sketched out to open numerous entryways for advanced research on MNPs for biomedical applications. Nanotechnology ; Magnetic nanoparticles ; Surface modification ; Drug delivery ; Materials science ; Nanoparticle ; Computer science ; Chemistry Nanoparticle-Based Drug Delivery ; Characterization and Applications of Magnetic Nanoparticles ; Gold and Silver Nanoparticles Synthesis and Applications