jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jorge Ramón Robledo‐Ortíz | Alan Salvador Martín del Campo | Juan A. Blackaller | Martín Esteban González‐López | Aida Alejandra Pérez‐Fonseca
Source: Polymers (article, 2021-09-29)
Field: Materials Science — Polymers and Plastics

Valorization of Sugarcane Straw for the Development of Sustainable Biopolymer-Based Composites Sugarcane straw (SCS) is a common agro-industrial waste that is usually incinerated or discarded in fields after harvesting, increasing the importance of developing added-value applications for this residue. In this study, sustainable biocomposites were produced, and the effect of sugarcane straw as a filler/reinforcement of commercial biopolymers was evaluated. Biocomposites were prepared using polylactic acid (PLA), polyhydroxybutyrate (PHB), polyhydroxybutyrate-co-hydroxyvalerate (PHBV), or green polyethylene (Green-PE) with different fiber contents (20, 30, and 40 wt.%). Dry-blending followed by compression molding was used for the biocomposites preparation. The results showed that PLA, PHB, and PHBV biocomposites retained the same impact strength as the neat matrices, even with 40 wt.% of sugarcane straw. The flexural and tensile modulus of PLA, PHB, and PHBV biocomposites increased with 20% of SCS, whereas, in Green-PE biocomposites, these properties increased at all fiber contents. Since any compatibilizer was used, both the flexural and tensile strength decreased with the addition of SCS. However, even with the highest content of SCS, the tensile and flexural strength values were around 20 MPa, making these materials competitive for specific industrial applications. Polyhydroxybutyrate ; Ultimate tensile strength ; Flexural strength ; Polylactic acid ; Materials science ; Biopolymer ; Straw ; Composite material ; Biocomposite ; Izod impact strength test ; Flexural modulus ; Compression molding ; Pulp and paper industry ; Polymer ; Composite number ; Chemistry ; Mold Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Advanced Cellulose Research Studies
Authors: Rong Cai | Long Xiao | Meixiu Liu | F. Du | Wang Zhi-rong
Source: International Journal of Nanomedicine (review, 2021-10-01)
Field: Materials Science — Materials Chemistry

Recent Advances in Functional Carbon Quantum Dots for Antitumour Carbon quantum dots (CQDs) are an emerging class of quasi-zero-dimensional photoluminescent nanomaterials with particle sizes less than 10 nm. Owing to their favourable water dispersion, strong chemical inertia, stable optical performance, and good biocompatibility, CQDs have become prominent in biomedical fields. CQDs can be fabricated by "top-down" and "bottom-up" methods, both of which involve oxidation, carbonization, pyrolysis and polymerization. The functions of CQDs include biological imaging, biosensing, drug delivery, gene carrying, antimicrobial performance, photothermal ablation and so on, which enable them to be utilized in antitumour applications. The purpose of this review is to summarize the research progress of CQDs in antitumour applications from preparation and characterization to application prospects. Furthermore, the challenges and opportunities of CQDs are discussed along with future perspectives for precise individual therapy of tumours. Biocompatibility ; Nanotechnology ; Materials science ; Photothermal therapy ; Nanomaterials ; Carbonization ; Drug delivery ; Carbon quantum dots ; Carbon fibers ; Polymerization ; Nanocomposite ; Quantum dot ; Polymer ; Composite number Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Ahmed F. Saber | Kuan-Ying Chen | Ahmed F. M. EL‐Mahdy | Shiao‐Wei Kuo
Source: Journal of Polymer Research (article, 2021-10-23)
Field: Materials Science — Materials Chemistry

Designed azo-linked conjugated microporous polymers for CO2 uptake and removal applications Conjugated microporous polymer ; Materials science ; Microporous material ; Polymer ; Monomer ; Carbazole ; Chemical engineering ; Adsorption ; Sodium borohydride ; Thermal stability ; Conjugated system ; Phenothiazine ; Organic chemistry ; Catalysis ; Chemistry ; Composite material Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies
Authors: Xianghui Li | Shichao Ai | Xiaofeng Lu | Song Liu | Wenxian Guan
Source: RSC Advances (review, 2021-01-01)
Field: Materials Science — Biomaterials

Nanotechnology-based strategies for gastric cancer imaging and treatment Gastric cancer is the second biggest cause of cancer-related deaths worldwide. Despite the improvement in deciphering molecular mechanisms, advances of detection and imaging, implementation of prevention programs, and personalized treatment, the overall curative rate remains low. In particular, with the emergence of nanomaterials, different imaging modalities can be integrated into one single platform, and combined therapies with synergetic effects against gastric cancer were established. Moreover, the development of theranostic strategies with simultaneous diagnostic and therapeutic ability was boosted by multifunctional nanoparticles. Herein, we present a comprehensive review of major nanotechnology-based breakthroughs for gastric cancer imaging and treatment. We will describe the superiority of nanomaterials used in gastric cancer and summarize nanotechnology applications for the improvement of cancer imaging and therapeutic efficacy. Cancer ; Nanotechnology ; Cancer imaging ; Materials science ; Medicine ; Internal medicine Nanoparticle-Based Drug Delivery ; Gastric Cancer Management and Outcomes ; Nanoplatforms for cancer theranostics
Authors: Tian Lan | Qi An
Source: Journal of the American Chemical Society (article, 2021-10-04)
Field: Materials Science — Materials Chemistry

Discovering Catalytic Reaction Networks Using Deep Reinforcement Learning from First-Principles Determining the reaction pathways, which is central to illustrating the working mechanisms of a catalyst, is severely hindered by the high complexity of the reaction and the extreme scarcity of the data. Here, we develop a novel artificial intelligence framework integrating deep reinforcement learning (DRL) techniques with density functional theory simulations to automate the quantitative search and evaluation on the complex catalytic reaction networks from zero knowledge. Our framework quantitatively transforms the first-principles-derived free energy landscape of the chemical reactions to a DRL environment and the corresponding actions. By interacting with this dynamic environment, our model evolves by itself from scratch to a complete reaction path. We demonstrate this framework using the Haber-Bosch process on the most active Fe(111) surface. The new path found by our framework has a lower overall free energy barrier than the previous study based on domain knowledge, demonstrating its outstanding capability in discovering complicated reaction paths. Looking forward, we anticipate that this framework will open the door to exploring the fundamental reaction mechanisms of many catalytic reactions. Reinforcement learning ; Chemistry ; Path (computing) ; Domain (mathematical analysis) ; Catalysis ; Artificial intelligence ; Computer science ; Nanotechnology Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; CO2 Reduction Techniques and Catalysts
Authors: Tae‐Yeon Kim | Sungho Park | Byung Jun Kim | Su Been Heo | Jong Hun Yu | Jae Seung Shin | Jong‐Am Hong | Beom‐Su Kim | Young Duck Kim | Yongsup Park | Seong Jun Kang
Source: Scientific Reports (article, 2021-01-18)
Field: Materials Science — Materials Chemistry

Dual-functional quantum-dots light emitting diodes based on solution processable vanadium oxide hole injection layer Dual-functional quantum-dots light emitting diodes (QLEDs) have been fabricated using solution processable vanadium oxide (V<sub>2</sub>O<sub>5</sub>) hole injection layer to control the carrier transport behavior. The device shows selectable functionalities of photo-detecting and light-emitting behaviors according to the different operating voltage conditions. The device emitted a bright green light at the wavelength of 536 nm, and with the maximum luminance of 31,668 cd/m<sup>2</sup> in a forward bias of 8.6 V. Meanwhile, the device could operate as a photodetector in a reverse bias condition. The device was perfectly turned off in a reverse bias, while an increase of photocurrent was observed during the illumination of 520 nm wavelength light on the device. The interfacial electronic structure of the device prepared with different concentration V<sub>2</sub>O<sub>5</sub> solution was measured in detail using x-ray and ultraviolet photoelectron spectroscopy. Both the highest occupied molecular orbital and the gap state levels were moved closer to the Fermi level, according to increase the concentration of V<sub>2</sub>O<sub>5</sub> solution. The change of gap state position enables to fabricate a dual-functional QLEDs. Therefore, the device could operate both as a photodetector and as a light-emitting diode with different applied bias. The result suggests that QLEDs can be used as a photosensor and as a light-emitting diode for the future display industry. Optoelectronics ; Materials science ; Photodetector ; Diode ; Light-emitting diode ; Quantum dot ; Photocurrent Quantum Dots Synthesis And Properties ; ZnO doping and properties ; Transition Metal Oxide Nanomaterials
Authors: Danial Khatamsaz | Abhilash Molkeri | Richard Couperthwaite | Jaylen James | Raymundo Arróyave | Douglas Allaire | Ankit Srivastava
Source: Acta Materialia (article, 2021-01-12)
Field: Materials Science — Materials Chemistry

Efficiently exploiting process-structure-property relationships in material design by multi-information source fusion Bayesian optimization ; Material Design ; Computer science ; Property (philosophy) ; Process (computing) ; Microstructure ; Flexibility (engineering) ; Materials science ; Function (biology) ; Systems engineering ; Mathematical optimization ; Machine learning ; Mathematics Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; Welding Techniques and Residual Stresses
Authors: Meng Lv | Xicun Lu | Yanrong Jiang | María Eugenia Sandoval‐Salinas | David Casanova | Haitao Sun | Zhenrong Sun | Jianhua Xu | Youjun Yang | Jinquan Chen
Source: Angewandte Chemie International Edition (article, 2021-11-18)
Field: Materials Science — Materials Chemistry

Near‐Unity Triplet Generation Promoted via Spiro‐Conjugation An intersystem crossing (ISC) rate constant of 1.0×10<sup>11</sup> s<sup>-1</sup> was previously registered with a spiro-bis-benzophenone scaffold. Triplet generation efficiency could be further enhanced by stabilizing the spiro-charge-transfer (CT) state and rationally designing spiro-compounds (SCTs) that consist of electron-rich diphenyl ether as the spiro-CT donor and electron-deficient dinaphthyl ketone as the spiro-CT acceptor. Through fine-tuning of the energy level between the CT and high energy triplet states, near-unity triplet generation quantum yield was achieved and the underlying ISC mechanism is revealed by using ultrafast spectroscopy and quantum chemical calculations. Potential triplet sensitizing application was demonstrated in SCTs. Our findings suggest that a spiro-bichromophoric molecular system with an enhanced spiro-charge transfer warrants efficient triplet generation and is a powerful strategy of heavy-atom-free triplet sensitizers with predictable ISC properties. Intersystem crossing ; Benzophenone ; Chemistry ; Photochemistry ; Triplet state ; Quantum yield ; Acceptor ; Molecule ; Atomic physics ; Fluorescence ; Physics ; Singlet state ; Excited state ; Organic chemistry Luminescence and Fluorescent Materials ; Porphyrin and Phthalocyanine Chemistry ; Photochemistry and Electron Transfer Studies
Authors: Fandi Sutanto | Shabnam Shaabani | Rick Oerlemans | Deniz Eriş | Pravin Patil | Mojgan Hadian | Meitian Wang | M.E. Sharpe | Matthew R. Groves | Alexander Dömlingꝉ
Source: Angewandte Chemie International Edition (article, 2021-06-07)
Field: Materials Science — Materials Chemistry

Combining High‐Throughput Synthesis and High‐Throughput Protein Crystallography for Accelerated Hit Identification Protein crystallography (PX) is widely used to drive advanced stages of drug optimization or to discover medicinal chemistry starting points by fragment soaking. However, recent progress in PX could allow for a more integrated role into early drug discovery. Here, we demonstrate for the first time the interplay of high throughput synthesis and high throughput PX. We describe a practical multicomponent reaction approach to acrylamides and -esters from diverse building blocks suitable for mmol scale synthesis on 96-well format and on a high-throughput nanoscale format in a highly automated fashion. High-throughput PX of our libraries efficiently yielded potent covalent inhibitors of the main protease of the COVID-19 causing agent, SARS-CoV-2. Our results demonstrate, that the marriage of in situ HT synthesis of (covalent) libraires and HT PX has the potential to accelerate hit finding and to provide meaningful strategies for medicinal chemistry projects. Throughput ; Identification (biology) ; Computer science ; Computational biology ; Biology ; Operating system Enzyme Structure and Function ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Masato Morita | Shigeyuki Yamada | Tsutomu Konno
Source: Molecules (article, 2021-04-14)
Field: Materials Science — Materials Chemistry

Systematic Studies on the Effect of Fluorine Atoms in Fluorinated Tolanes on Their Photophysical Properties In this study, we synthesized a series of fluorinated and non-fluorinated tolanes, in which one or more fluorine atoms were systematically introduced into one aromatic ring of a tolane scaffold, and systematically evaluated their photophysical properties. All the tolanes with or without fluorine substituents were found to have poor photoluminescence (PL) in tetrahydrofuran (THF) solutions. On the other hand, in the crystalline state, non-fluorinated and fluorinated tolanes with one or four fluorine atoms were less emissive, whereas fluorinated tolanes with three or five fluorine atoms exhibited high PL efficiencies (Ф<sub>PL</sub>) up to 0.51. X-ray crystallographic analyses of the emissive fluorinated tolanes revealed that the position of the fluorine substituent played a key role in achieving a high Ф<sub>PL</sub>. Fluorine substituents at the ortho (2/6) and para (4) positions led to tight and rigid packing due to plural π-π stacking and/or hydrogen bonding interactions, resulting in enhanced Ф<sub>PL</sub> caused by the suppression of non-radiative deactivation. Additionally, fluorinated tolanes with three fluorine atoms exhibited notable aggregation-induced PL emission enhancement in THF/water mixed solvents. This demonstrates that the PL characteristics of small PL materials can be tuned depending on the usage requirements. Fluorine ; Substituent ; Stacking ; Photoluminescence ; Photochemistry ; Chemistry ; Ring (chemistry) ; Tetrahydrofuran ; Hydrogen bond ; Materials science ; Organic chemistry ; Molecule Luminescence and Fluorescent Materials ; Fluorine in Organic Chemistry ; Synthesis and Properties of Aromatic Compounds
Authors: Harish K. Singh | Ilias Samathrakis | Nuno M. Fortunato | Jan Zemen | Chen Shen | Oliver Gutfleisch | Hongbin Zhang
Source: npj Computational Materials (article, 2021-06-30)
Field: Materials Science — Materials Chemistry

Multifunctional antiperovskites driven by strong magnetostructural coupling Abstract Based on density functional theory calculations, we elucidated the origin of multifunctional properties for cubic antiperovskites with noncollinear magnetic ground states, which can be attributed to strong isotropic and anisotropic magnetostructural coupling. Of 54 stable magnetic antiperovskites M 3 XZ (M = Cr, Mn, Fe, Co, and Ni; X = selected elements from Li to Bi except for noble gases and 4f rare-earth metals; and Z = C and N), 14 are found to exhibit the Γ 4 g /Γ 5 g (i.e., characterized by irreducible representations) antiferromagnetic magnetic configurations driven by frustrated exchange coupling and strong magnetocrystalline anisotropy. Using the magnetic deformation as an effective proxy, the isotropic magnetostructural coupling is characterized, and it is observed that the paramagnetic state is critical to understand the experimentally observed negative thermal expansion and to predict the magnetocaloric performance. Moreover, the piezomagnetic and piezospintronic effects induced by biaxial strain are investigated. It is revealed that there is not a strong correlation between the induced magnetization and anomalous Hall conductivities by the imposed strain. Interestingly, the anomalous Hall/Nernst conductivities can be significantly tailored by the applied strain due to the fine-tuning of the Weyl points energies, leading to promising spintronic applications. Coupling (piping) ; Materials science ; Composite material Thermal Expansion and Ionic Conductivity ; Magnetic and transport properties of perovskites and related materials ; Ferroelectric and Piezoelectric Materials
Authors: Sagar Kumar Dutta | Morsheda Akhter | Jamil Ahmed | Muhamad Amin | Palash Kumar Dhar | S Ramesh | B Dhanalakshmi | B Chandra Sekhar | P Subba Rao | B Parvatheeswara Rao | A Sathiya Priya | D Geetha | N Kavitha | S Khan | S Irfan | S Lee | K Sathiyamurthy | C Rajeevgandhi | L Guganathan | S Bharanidharan | S Savithiri | A Manikandan | Y Slimani | A Dinesh | A Khan | K Thanrasu | A Baykal | S Jaganathan | H Dzudzevic-Cancar | A Asiri | K Kefeni | T Msagati | B Mamba | M Khan | M Sabir | A Mahmood | M Asghar | K Mahmood | I Ahmad | M Sher | M Warsi | M Gonalves | P Rocha | T Silva | R Martins | E Nossol | L Angnes | S Rout | A Rodrigo | S Ayyappan | S Mahadevan | P Chandramohan | M Srinivasan | J Philip | B Raj | T Shahjuee | S Mortezamasoudpanah | S Mohammadmirkazemi | A Mayeen | A Sajan | N Kalarikkal | S Gul | M Yousuf | A Anwar | P Agboola | I Shakir | M Shahid | M Kurian | D Nair | K Sanchez-Lievanos | J Stair | K Knowles | T Abbas | M Islam | A Maqsood | G Shahane | A Kumar | M Arora | R Pant | K Lal | R Pawar | S Shirsath | R Kadam | R Joshi | S Patange | T Bromho | K Ibrahim | H Kabir | M Rahman | K Hasan | T Ferdous | H Taha | M Altarawneh | Z Jiang
Source: Biointerface Research in Applied Chemistry (review, 2021-08-15)
Field: Materials Science — Materials Chemistry

Synthesis and Catalytic Activity of Spinel Ferrites: A Brief Review The spinel ferrites have earned enormous interest worldwide because of their attractive potential applications. This review highlights different synthetic protocols of spinel ferrites such as co-precipitation, sol-gel, microemulsion, solid-state, hydrothermal, and thermal decomposition, where each method can influence the properties of ferrites. The use of ferrites in heterogeneous catalysis of various organic syntheses is discussed therein; the activity is mostly particle size-dependent. The catalytic activity of spinel ferrites towards photo-irradiated dye degradation is also studied. In the presence of H2O2 producing a Fenton-type system, ferrites have tremendous potential for dye degradation in an advanced oxidation process. Spinel ; Catalysis ; Hydrothermal circulation ; Degradation (telecommunications) ; Chemical engineering ; Materials science ; Microemulsion ; Decomposition ; Precipitation ; Chemistry ; Metallurgy ; Computer science ; Organic chemistry Magnetic Properties and Synthesis of Ferrites
Authors: André Colliard-Granero | Mariah Batool | Jasna Janković | Jenia Jitsev | Michael Eikerling | Kourosh Malek | Mohammad J. Eslamibidgoli
Source: Nanoscale (article, 2021-11-23)
Field: Materials Science — Materials Chemistry

Deep learning for the automation of particle analysis in catalyst layers for polymer electrolyte fuel cells The rapidly growing use of imaging infrastructure in the energy materials domain drives significant data accumulation in terms of their amount and complexity. The applications of routine techniques for image processing in materials research are often <i>ad hoc</i>, indiscriminate, and empirical, which renders the crucial task of obtaining reliable metrics for quantifications obscure. Moreover, these techniques are expensive, slow, and often involve several preprocessing steps. This paper presents a novel deep learning-based approach for the high-throughput analysis of the particle size distributions from transmission electron microscopy (TEM) images of carbon-supported catalysts for polymer electrolyte fuel cells. A dataset of 40 high-resolution TEM images at different magnification levels, from 10 to 100 nm scales, was annotated manually. This dataset was used to train the U-Net model, with the StarDist formulation for the loss function, for the nanoparticle segmentation task. StarDist reached a precision of 86%, recall of 85%, and an F1-score of 85% by training on datasets as small as thirty images. The segmentation maps outperform models reported in the literature for a similar problem, and the results on particle size analyses agree well with manual particle size measurements, albeit at a significantly lower cost. Computer science ; Segmentation ; Preprocessor ; Task (project management) ; Automation ; Particle (ecology) ; Deep learning ; Artificial intelligence ; Particle size ; Materials science ; Chemical engineering ; Mechanical engineering Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Electrocatalysts for Energy Conversion
Authors: M. Ross Kunz | Adam Yonge | Zongtang Fang | Rakesh Batchu | Andrew J. Medford | Denis Constales | Gregory S. Yablonsky | Rebecca Fushimi
Source: Chemical Engineering Journal (article, 2021-04-19)
Field: Materials Science — Materials Chemistry

Data driven reaction mechanism estimation via transient kinetics and machine learning Transient (computer programming) ; Chemical kinetics ; Kinetics ; Work (physics) ; Catalysis ; Elementary reaction ; Biological system ; Reaction mechanism ; Kinetic energy ; Mechanism (biology) ; Chemistry ; Reaction rate ; Set (abstract data type) ; Computer science ; Thermodynamics ; Physics Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Catalytic Processes in Materials Science