jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Stuart C. Smith | Christopher S. Horbaczewskyj | Theo F. N. Tanner | Jacob J. Walder | Ian J. S. Fairlamb
Source: Digital Discovery (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Automated approaches, reaction parameterisation, and data science in organometallic chemistry and catalysis: towards improving synthetic chemistry and accelerating mechanistic understanding This review discusses the use of automation for organometallic reactions to generate rich datasets and, with statistical analysis and reaction component parameterisation, how organometallic reaction mechanisms can be probed to gain understanding. Organometallic chemistry ; Chemistry ; Catalysis ; Group 2 organometallic chemistry ; Automation ; Computational chemistry ; Biochemical engineering ; Computer science ; Combinatorial chemistry ; Nanotechnology ; Organic chemistry ; Engineering ; Molecule ; Materials science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Asymmetric Hydrogenation and Catalysis
Authors: Mohammad Mizanur Rahman Khan | Nilave Chakraborty
Source: Gels (review, 2024-08-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Conducting Polymer-Based Gel Materials: Synthesis, Morphology, Thermal Properties, and Applications in Supercapacitors Despite the numerous ongoing research studies in the area of conducting polymer-based electrode materials for supercapacitors, the implementation has been inadequate for commercialization. Further understanding is required for the design and synthesis of suitable materials like conducting polymer-based gels as electrode materials for supercapacitor applications. Among the polymers, conductive polymer gels (CPGs) have generated great curiosity for their use as supercapacitors, owing to their attractive qualities like integrated 3D porous nanostructures, softness features, very good conductivity, greater pseudo capacitance, and environmental friendliness. In this review, we describe the current progress on the synthesis of CPGs for supercapacitor applications along with their morphological behaviors and thermal properties. We clearly explain the synthesis approaches and related phenomena, including electrochemical approaches for supercapacitors, especially their potential applications as supercapacitors based on these materials. Focus is also given to the recent advances of CPG-based electrodes for supercapacitors, and the electrochemical performances of CP-based promising composites with CNT, graphene oxides, and metal oxides is discussed. This review may provide an extensive reference for forthcoming insights into CPG-based supercapacitors for large-scale applications. Supercapacitor ; Materials science ; Nanotechnology ; Conductive polymer ; Capacitance ; Polymer ; Electrode ; Graphene ; Composite material ; Chemistry Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Emily E. Morgan | Arava Zohar | Sophia Lipkin | Bartomeu Monserrat | Subramanian Vaidyanathan | Daniel Loeffler | Rui Zhang | Kerstin Schierle‐Arndt | Anthony K. Cheetham | Ram Seshadri
Source: Chemistry of Materials (article, 2024-02-02)
Field: Materials Science — Materials Chemistry

Screening Aluminum-Based Compounds as Low-κ Dielectrics for High-Frequency Applications Advances in telecommunications require electronics that operate at ever-increasing frequencies, exemplified by 5G or fifth-generation technologies that operate in the GHz regime. At high frequencies, electrical circuits are plagued by so-called RC delays, arising from the time constant τ = RC for electrical signals which is the product of the resistance R and the capacitance C, respectively, of conductors and their insulating substrates. Besides using high quality, low-R electrical conductors such as high-purity Cu with low surface roughness, small RC delays are achieved by lowering the dielectric constant κ of the materials used in printed circuit board substrates. These largely comprise particles of an inorganic material, notably functionalized SiO2, embedded in a polymer-based matrix. The value of κ of the composite is primarily dictated by κ of the inorganic material. The properties of the inorganic component also impact other relevant parameters such as the quality factor, mechanical strength, and thermal expansion of the substrate. Here, we ask whether there are inorganic compounds with dielectric constants (measured at 10 GHz) that are lower than that of SiO2 and potentially replace it in electronics. We describe the key characteristics for low-κ materials and develop a framework for screening such compounds by employing some guiding principles, followed by using a combination of empirical estimates and density functional perturbation theory-based calculations. We then report experimental results on two promising aluminum-based low-κ compounds for high-frequency applications. The first is the cristobalite form of AlPO4. The second is the simplest 3D metal–organic framework, aluminum formate Al(HCOO)3. The measured values of κ at 10 GHz, which are 4.0 for AlPO4 and 3.8 for Al(HCOO)3, compare well with what is measured on SiO2 particles. Dielectric ; Materials science ; Aluminium ; Optoelectronics ; Nanotechnology ; Composite material Ferroelectric and Piezoelectric Materials ; Semiconductor materials and devices ; Microwave Dielectric Ceramics Synthesis
Authors: Mikhail Mironov | Dmitry I. Yakubovsky | Georgy A. Ermolaev | Igor A. Khramtsov | Roman V. Kirtaev | Aleksandr S. Slavich | Gleb Tselikov | Andrey A. Vyshnevyy | Aleksey V. Arsenin | Valentyn S. Volkov | Kostya S. Novoselov
Source: Nano Letters (article, 2024-12-12)
Field: Materials Science — Materials Chemistry

Graphene-Inspired Wafer-Scale Ultrathin Gold Films As the trajectory toward the graphene era continues, there is a compelling need to harness 2D technology further for the transformation of three-dimensional (3D) materials production and applications. Here, we resolve this challenge for one of the most widely utilized 3D materials in modern electronics─gold─using graphene-inspired fabrication technology that allows us to develop a multistep production method of ultrathin gold films. Such films demonstrate continuous morphology, low sheet resistance (10 Ω/sq), and high transparency (80%), offering opportunities in a variety of technological and scientific sectors. To this end, we demonstrate smart contact lenses and thermal camouflage based on ultrathin gold. Technologically, the record-breaking characteristics of ultrathin gold films open new horizons for flexible and transparent electrodes for photonics and optoelectronics. Most importantly, the demonstration of transferable wafer-scale ultrathin gold changes the paradigm of the field of 2D crystals and dramatically expands the range of available quasi-2D materials. Nanotechnology ; Materials science ; Wafer ; Graphene ; Electronics ; Fabrication ; Photonics ; Transparency (behavior) ; Optoelectronics ; Computer science ; Chemistry Graphene research and applications ; 2D Materials and Applications ; Plasmonic and Surface Plasmon Research
Authors: Charitha Thambiliyagodage | Heshan Liyanaarachchi | Madara Jayanetti | Geethma Ekanayake | Amavin Mendis | Upeka Samarakoon | S. Vigneswaran
Source: Scientific Reports (article, 2024-05-31)
Field: Materials Science — Materials Chemistry

Persulfate assisted photocatalytic and antibacterial activity of TiO2–CuO coupled with graphene oxide and reduced graphene oxide Photocatalysts of TiO<sub>2</sub>-CuO coupled with 30% graphene oxide (GO) were hydrothermally fabricated, which varied the TiO<sub>2</sub> to CuO weight ratios to 1:4, 1:2, 1:1, 2:1 and 4:1 and reduced to form TiO<sub>2</sub>-CuO/reduced graphene oxide (rGO) photocatalysts. They were characterized using XRD, TEM, SEM, XPS, Raman, and DRS technologies. TiO<sub>2</sub>-CuO composites and TiO<sub>2</sub>-CuO/GO degrade methylene blue when persulfate ions are present. Persulfate concentration ranged from 1, 2, 4 to 8 mmol/dm<sup>-3</sup> in which the highest activity of 4.4 × 10<sup>-2</sup> and 7.35 × 10<sup>-2</sup> min<sup>-1</sup> was obtained with 4 mmol/dm<sup>-3</sup> for TiO<sub>2</sub>-CuO (1:4) and TiO<sub>2</sub>-CuO/GO (1:1), respectively. The presence of EDTA and isopropyl alcohol reduced the photodegradation. TiO<sub>2</sub>-CuO coupled with rGO coagulates methylene blue in the presence of persulfate ions and such coagulation is independent of light. The catalyst dosage and the concentration of the dye were varied for the best-performing samples. The antibacterial activity of the synthesized samples was evaluated against the growth of Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Klebsiella pneumonia. Ti:Cu (1:2)-GO and Ti:Cu (1:4)-GO had the highest antibacterial activity against K. pneumoniae (16.08 ± 0.14 mm), P. aeruginosa (22.33 ± 0.58 mm), E. coli (16.17 ± 0.29 mm) and S. aureus (16.08 ± 0.88). Graphene ; Oxide ; Photocatalysis ; Persulfate ; Materials science ; Chemical engineering ; Chemistry ; Nanotechnology ; Biochemistry ; Catalysis ; Metallurgy Advanced Nanomaterials in Catalysis ; Advanced Photocatalysis Techniques ; Graphene and Nanomaterials Applications
Authors: Ana-Mihaela Gavrilă | Aurel Diacon | Tanta‐Verona Iordache | Traian Rotariu | Mariana Ioniţă | Gabriela Toader
Source: Polymers (review, 2024-09-24)
Field: Chemistry — Analytical Chemistry

Hazardous Materials from Threats to Safety: Molecularly Imprinted Polymers as Versatile Safeguarding Platforms Hazards associated with highly dangerous pollutants/contaminants in water, air, and land resources, as well as food, are serious threats to public health and the environment. Thus, it is imperative to detect or decontaminate, as risk-control strategies, the possible harmful substances sensitively and efficiently. In this context, due to their capacity to be specifically designed for various types of hazardous compounds, the synthesis and use of molecularly imprinted polymers (MIPs) have become widespread. By molecular imprinting, affinity sites with complementary shape, size, and functionality can be created for any template molecule. MIPs' unique functions in response to external factors have attracted researchers to develop a broad range of MIP-based sensors with increased sensitivity, specificity, and selectivity of the recognition element toward target hazardous compounds. Therefore, this paper comprehensively reviews the very recent progress of MIPs and smart polymer applications for sensing or decontamination of hazardous compounds (e.g., drugs, explosives, and biological or chemical agents) in various fields from 2020 to 2024, providing researchers with a rapid tool for investigating the latest research status. Hazardous waste ; Molecularly imprinted polymer ; Context (archaeology) ; Molecular imprinting ; Smart polymer ; Nanotechnology ; Hazardous air pollutants ; Explosive material ; Safeguarding ; Biochemical engineering ; Risk analysis (engineering) ; Computer science ; Environmental science ; Polymer ; Pollutant ; Materials science ; Business ; Chemistry ; Waste management ; Engineering ; Selectivity Analytical chemistry methods development ; Advanced Chemical Sensor Technologies ; Mass Spectrometry Techniques and Applications
Authors: Xiaobo Lin | Shern R. Tee | Paul R. C. Kent | Debra J. Searles | Peter T. Cummings
Source: Journal of Chemical Theory and Computation (article, 2024-01-11)
Field: Materials Science — Materials Chemistry

Development of Heteroatomic Constant Potential Method with Application to MXene-Based Supercapacitors We describe a method for modeling constant-potential charges in heteroatomic electrodes, keeping pace with the increasing complexity of electrode composition and nanostructure in electrochemical research. The proposed "heteroatomic constant potential method" (HCPM) uses minimal added parameters to handle differing electronegativities and chemical hardnesses of different elements, which we fit to density functional theory (DFT) partial charge predictions in this paper by using derivative-free optimization. To demonstrate the model, we performed molecular dynamics simulations using both HCPM and conventional constant potential method (CPM) for MXene electrodes with Li-TFSI/AN (lithium bis(trifluoromethane sulfonyl)imide/acetonitrile)-based solvent-in-salt electrolytes. Although the two methods show similar accumulated charge storage on the electrodes, the results indicated that HCPM provides a more reliable depiction of electrode atom charge distribution and charge response compared with CPM, accompanied by increased cationic attraction to the MXene surface. These results highlight the influence of elemental composition on electrode performance, and the flexibility of our HCPM opens up new avenues for studying the performance of diverse heteroatomic electrodes including other types of MXenes, two-dimensional materials, metal-organic frameworks (MOFs), and doped carbonaceous electrodes. Electrode ; Supercapacitor ; Materials science ; Electrolyte ; Acetonitrile ; Electrochemistry ; Density functional theory ; Nanotechnology ; Chemistry ; Physical chemistry ; Computational chemistry ; Organic chemistry MXene and MAX Phase Materials ; Supercapacitor Materials and Fabrication ; Advanced Memory and Neural Computing
Authors: Elham Sadeghi | Peter Mastracco | Anna Gonzàlez‐Rosell | Stacy M. Copp | Petko Bogdanov
Source: ACS Nano (article, 2024-09-17)
Field: Materials Science — Materials Chemistry

Multi-Objective Design of DNA-Stabilized Nanoclusters Using Variational Autoencoders With Automatic Feature Extraction DNA-stabilized silver nanoclusters (Ag<sub><i>N</i></sub>-DNAs) have sequence-tuned compositions and fluorescence colors. High-throughput experiments together with supervised machine learning models have recently enabled design of DNA templates that select for Ag<sub><i>N</i></sub>-DNA properties, including near-infrared (NIR) emission that holds promise for deep tissue bioimaging. However, these existing models do not enable simultaneous selection of multiple Ag<sub><i>N</i></sub>-DNA properties, and require significant expert input for feature engineering and class definitions. This work presents a model for multiobjective, continuous-property design of Ag<sub><i>N</i></sub>-DNAs with automatic feature extraction, based on variational autoencoders (VAEs). This model is generative, i.e., it learns both the forward mapping from DNA sequence to Ag<sub><i>N</i></sub>-DNA properties and the inverse mapping from properties to sequence, and is trained on an experimental data set of DNA sequences paired with Ag<sub><i>N</i></sub>-DNA fluorescence properties. Experimental testing shows that the model enables effective design of Ag<sub><i>N</i></sub>-DNA emission, including bright NIR Ag<sub><i>N</i></sub>-DNAs with 4-fold greater abundance compared to training data. In addition, Shapley analysis is employed to discern learned nucleobase patterns that correspond to fluorescence color and brightness. This generative model can be adapted for a range of biomolecular systems with sequence-dependent properties, enabling precise design of emerging biomolecular nanomaterials. Nanoclusters ; Artificial intelligence ; Feature extraction ; Feature (linguistics) ; Materials science ; Pattern recognition (psychology) ; Computer science ; Extraction (chemistry) ; Nanotechnology ; Chemistry ; Chromatography Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Supramolecular Self-Assembly in Materials
Authors: Amy V. Hall | Aurora J. Cruz‐Cabeza | Jonathan W. Steed
Source: Crystal Growth & Design (article, 2024-06-21)
Field: Chemistry — Physical and Theoretical Chemistry

What Has Carbamazepine Taught Crystal Engineers? The antiepilepsy drug carbamazepine is one of the most studied pharmaceuticals in the world. The rich story of its solid forms, cocrystals, and formulation is a microcosm of the topical world of pharmaceutical materials. Understanding carbamazepine has required time, money, and dedication from numerous researchers and pharmaceutical companies worldwide. This wealth of knowledge provides the opportunity to reflect on progress within the crystal engineering field in general. This Perspective covers the extensive solid form landscape of carbamazepine and applies these examples to discuss and answer fundamental questions in the discipline. The story encompasses screening methods, computational solid form discovery, the power and influence of crystal engineering in understanding and controlling crystals and the amorphous state, and the environmental legacy of modern pharmaceuticals. This broad but in-depth analysis of carbamazepine is a vehicle into modern crystal engineering, not only in its own right but across the spectrum of organic materials science and pharmaceutical formulation. Discoveries of carbamazepine demonstrate the potential richness in the materials chemistry of every drug. Carbamazepine ; Crystal engineering ; Nanotechnology ; Chemistry ; Engineering ethics ; Biochemical engineering ; Engineering ; Organic chemistry ; Materials science ; Supramolecular chemistry ; Psychology ; Crystal structure ; Neuroscience Crystallography and molecular interactions ; Crystallization and Solubility Studies ; Analytical Chemistry and Chromatography
Authors: Jorge L. Mejía-Méndez | Edwin E. Reza-Zaldívar | A. Sánchez-Martínez | O. Ceballos-Sánchez | Diego E. Navarro-López | Luis Marcelo Lozano | Juan Armendáriz‐Borunda | Naveen Tiwari | Daniel A. Jacobo‐Velázquez | Gildardo Sanchez‐Ante | Edgar R. López-Mena
Source: Journal of Nanobiotechnology (article, 2024-11-10)
Field: Materials Science — Materials Chemistry

Exploring the cytotoxic and antioxidant properties of lanthanide-doped ZnO nanoparticles: a study with machine learning interpretation This study demonstrates, for the first time, the synthesis of ZnO NPs doped with Er and Yb via a solution polymerization route. According to characterization results, it was unveiled that the effect of optical bandgap variations influenced the cytotoxic performance of the developed lanthanide-doped ZnO NPs, being the undoped ZnO NPs the most cytotoxic ones. The presence alone or in combination of Er and Yb enhanced their scavenging capacity. ML models such as ET and RF efficiently demonstrated that the concentration and cell line type are key parameters that influence the cytotoxicity of (Er, Yb)-doped ZnO NPs achieving high accuracy rates of 98.96% and 98.67%, respectively. This study expands the knowledge of lanthanides as dopants of nanomaterials for biological and medical applications and supports their potential in cancer therapy by integrating robust ML approaches. Lanthanide ; Nanoparticle ; Interpretation (philosophy) ; Doping ; Nanotechnology ; Antioxidant ; Materials science ; Chemistry ; Computer science ; Optoelectronics ; Ion ; Biochemistry ; Organic chemistry Advanced Nanomaterials in Catalysis ; Gold and Silver Nanoparticles Synthesis and Applications ; Machine Learning in Materials Science
Authors: Masao Shibata | Yu Morimoto | Iryna V. Zenyuk | Adam Z. Weber
Source: Journal of Chemical Theory and Computation (article, 2024-07-05)
Field: Chemistry — Physical and Theoretical Chemistry

Parameter-Fitting-Free Continuum Modeling of Electric Double Layer in Aqueous Electrolyte Electric double layers (EDLs) play fundamental roles in various electrochemical processes. Despite the extensive history of EDL modeling, there remain challenges in the accurate prediction of its structure without expensive computation. Herein, we propose a predictive multiscale continuum model of EDL that eliminates the need for parameter fitting. This model computes the distribution of the electrostatic potential, electron density, and species' concentrations by taking the extremum of the total grand potential of the system. The grand potential includes the microscopic interactions that are newly introduced in this work: polarization of solvation shells, electrostatic interaction in parallel plane toward the electrode, and ion-size-dependent entropy. The parameters that identify the electrode and electrolyte materials are obtained from independent experiments in the literature. The model reproduces the trends in the experimental differential capacitance with multiple electrode and nonadsorbing electrolyte materials (Ag(110) in NaF, Ag(110) in NaClO<sub>4</sub>, and Hg in NaF), which verifies the accuracy and predictiveness of the model and rationalizes the observed values to be due to changes in electron stability. However, our calculation on Pt(111) in KClO<sub>4</sub> suggests the need for the incorporation of electrode/ion-specific interactions. Sensitivity analyses confirmed that effective ion radius, ion valence, the electrode's Wigner-Seitz radius, and the bulk modulus of the electrode are significant material properties that control the EDL structure. Overall, the model framework and findings provide insights into EDL structures and predictive capability at low computational cost. Electrolyte ; Aqueous solution ; Double layer (biology) ; Layer (electronics) ; Chemical physics ; Materials science ; Computer science ; Statistical physics ; Chemistry ; Nanotechnology ; Physics ; Physical chemistry ; Electrode Electrostatics and Colloid Interactions ; Spectroscopy and Quantum Chemical Studies ; Advanced Physical and Chemical Molecular Interactions