jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Maria H. Rasmussen | Magnus Strandgaard | Julius Seumer | Lars Hemmingsen | Angelo Frei | David Balcells | Jan H. Jensen
Source: Journal of Cheminformatics (article, 2025-04-28)
Field: Materials Science — Materials Chemistry

SMILES all around: structure to SMILES conversion for transition metal complexes We present a method for creating RDKit-parsable SMILES for transition metal complexes (TMCs) based on xyz-coordinates and overall charge of the complex. This can be viewed as an extension to the program xyz2mol that does the same for organic molecules. The only dependency is RDKit, which makes it widely applicable. One thing that has been lacking when it comes to generating SMILES from structure for TMCs is an existing SMILES dataset to compare with. Therefore, sanity-checking a method has required manual work. Therefore, we also generate SMILES two other ways; one where ligand charges and TMC connectivity are based on natural bond orbital (NBO) analysis from density functional theory (DFT) calculations utilizing recent work by Kneiding et al. (Digit Discov 2: 618-633, 2023). Another one fixes SMILES available through the Cambridge Structural Database (CSD), making them parsable by RDKit. We compare these three different ways of obtaining SMILES for a subset of the CSD (tmQMg) and find >70% agreement for all three pairs. We utilize these SMILES to make simple molecular fingerprint (FP) and graph-based representations of the molecules to be used in the context of machine learning. Comparing with the graphs made by Kneiding et al. where nodes and edges are featurized with DFT properties, we find that depending on the target property (polarizability, HOMO-LUMO gap or dipole moment) the SMILES based representations can perform equally well. This makes them very suitable as baseline-models. Finally we present a dataset of 227k RDKit parsable SMILES for mononuclear TMCs in the CSD.Scientific contribution We present a method that can create RDKit-parsable SMILES strings of transition metal complexes (TMCs) from Cartesian coordinates and use it to create a dataset of 227k TMC SMILES strings. The RDKit-parsability allows us to generate perform machine learning studies of TMC properties using "standard" molecular representations such as fingerprints and 2D-graph convolution. We show that these relatively simple representations can perform quite well depending on the target property. Computer science ; Smiles rearrangement ; Data science ; Data mining ; Chemistry ; Stereochemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemistry and Chemical Engineering
Authors: Huiju Lee | Vinay I. Hegde | Chris Wolverton | Yi Xia
Source: Materials Today Physics (article, 2025-03-07)
Field: Materials Science — Materials Chemistry

Accelerating high-throughput phonon calculations via machine learning universal potentials Materials science ; Throughput ; Phonon ; Engineering physics ; Chemical physics ; Nanotechnology ; Optoelectronics ; Condensed matter physics ; Computer science ; Physics ; Telecommunications Machine Learning in Materials Science ; Thermal properties of materials ; Electronic and Structural Properties of Oxides
Authors: Yuanhong Yu | Xianyu Song | Yang Xu | Chengjie Wang | Xiaoyu Wu | Ying Wang | Wenjun Xiang | Shuangliang Zhao | Honglai Liu
Source: Separation and Purification Technology (article, 2025-03-27)
Field: Chemistry — Organic Chemistry

Optimization of chitosan-based demulsifiers via interfacial displacement: A molecular dynamics and principal component analysis approach Chitosan ; Principal component analysis ; Component (thermodynamics) ; Displacement (psychology) ; Molecular dynamics ; Dynamics (music) ; Chemistry ; Chemical engineering ; Materials science ; Biological system ; Computer science ; Engineering ; Thermodynamics ; Computational chemistry ; Physics ; Artificial intelligence Surfactants and Colloidal Systems ; Advanced Polymer Synthesis and Characterization ; Advanced Cellulose Research Studies
Authors: Ming-Ming Chen | Yanqing Zhang | Lu-Chen Cheng | Fang‐Jie Zhao | Peng Wang
Source: Biosensors and Bioelectronics (article, 2025-06-18)
Field: Materials Science — Materials Chemistry

Machine learning-powered fluorescent sensor arrays for rapid detection of heavy metals and pesticides in complex environments Pesticide ; Environmental chemistry ; Chemistry ; Pollutant ; Fluorescence Nanocluster Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Mercury impact and mitigation studies
Authors: Do Hyuck Kwon | Min Jun Lee | Heewon Jeong | Sang‐Hun Park | Kyung Hwa Cho
Source: Water Research (article, 2025-01-22)
Field: Chemistry — Analytical Chemistry

Multi-modal learning-based algae phyla identification using image and particle modalities Phylum ; Algae ; Modal ; Modalities ; Identification (biology) ; Artificial intelligence ; Particle (ecology) ; Environmental science ; Computer science ; Pattern recognition (psychology) ; Biological system ; Biology ; Botany ; Ecology ; Materials science ; Bacteria ; Paleontology ; Sociology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Identification and Quantification in Food
Authors: Na Li | Xinyang Li | Tian Wang | Bo Wen | Zhen Yin | Jie Feng | Shengchun Yang | Yawei Yang | Guorui Yang | Shujiang Ding
Source: Chemical Science (review, 2025-01-01)
Field: Materials Science — Materials Chemistry

<i>In situ</i> transmission electron microscopy characterization and manipulation of the morphology, composition and phase evolution of nanomaterials under microenvironmental conditions Nanomaterials possess a broad range of applications in areas such as catalysis, energy, and biomedicine because of their unique properties. However, from the perspective of materials synthesis, there are numerous challenges in the controllable preparation of nanomaterials. These include the control of their size, morphology, crystal structure, and surface properties, which are essential for their performance in specific applications. The fundamental cause of these issues is the limitation in the real-time observation of the growth process of nanomaterials. <i>In situ</i> transmission electron microscopy (TEM), on the other hand, overcomes the limitations of traditional <i>in situ</i> testing techniques. It enables the real-time observation and analysis of the dynamic structural evolution during the growth of nanomaterials at the atomic scale. This contributes to a profound understanding of the nucleation and growth mechanisms of nanomaterials and facilitates the controlled preparation of nanomaterials. This review centers on the utilization of <i>in situ</i> TEM to observe and study the complex dynamic processes of zero-, one-, and two-dimensional nanomaterial growth and evolution in different environments (liquid, gas, and solid phases) at the atomic scale. This is of great significance for the design and preparation of nanomaterials with specific properties. The proposed future development of <i>in situ</i> TEM, in combination with advanced data analysis and integration with other techniques, holds great potential for the further advancement of nanotechnology and its applications. Nanomaterials ; Transmission electron microscopy ; In situ ; Characterization (materials science) ; Morphology (biology) ; Nanotechnology ; Materials science ; Phase (matter) ; Electron microscope ; Chemical engineering ; Chemistry ; Biology ; Physics ; Optics ; Engineering ; Organic chemistry Copper-based nanomaterials and applications ; Electronic and Structural Properties of Oxides ; Quantum Dots Synthesis And Properties
Authors: Yuliang Chen | Ahsan Zohaib | Haobo Sun | Shouheng Sun
Source: Chemical Communications (review, 2025-01-01)
Field: Chemistry — Organic Chemistry

Multi-metallic nanoparticles: synthesis and their catalytic applications Multi-metallic nanoparticles (MMNPs) have recently garnered significant interest due to their inclusion of different metal atoms within a single nanostructure. The interactions among these metal atoms induce novel properties in MMNPs, making them an ideal platform for exploring the complex interplay between structure and properties, particularly in terms of catalytic properties. This review summarizes recent advancements in the synthesis and catalytic studies of MMNPs. It begins by outlining the synthesis of MMNPs with well-defined structures, including solid solutions, intermetallics, composite core/shell structures, heterodimers, and high-entropy alloys. These MMNPs exhibit unique electronic and surface properties that are crucial for enhancing catalysis. Using representative examples, the review further highlights the promising applications of MMNPs in catalyzing important chemical reactions related to energy conversion and green chemistry, achieving high reaction efficiencies. Finally, the review discusses strategies for attaining atomic precision in the synthesis of MMNPs and optimizing their catalytic performance for a broader range of chemical reactions. Catalysis ; Nanoparticle ; Metal ; Nanotechnology ; Materials science ; Combinatorial chemistry ; Chemical engineering ; Chemistry ; Organic chemistry ; Metallurgy ; Engineering Nanomaterials for catalytic reactions ; Electrocatalysts for Energy Conversion ; Catalytic Processes in Materials Science
Authors: Houyi He | Songqiang Deng | Yuyu Liu
Source: Discover Nano (review, 2025-08-08)
Field: Materials Science — Materials Chemistry

Environmentally friendly synthesis of quantum dots and their applications in diverse fields from the perspective of environmental compliance: A review Semiconductor Quantum-dots (QDs), characterized by their unique optoelectronic tunability, high efficiency, and multifunctionality, have emerged as transformative materials in diverse fields, including display technologies, energy conversion, solar cells, biomedical applications, and quantum technologies. With ongoing advancements in material synthesis and device engineering, the application scope of QDs is anticipated to expand further, thereby driving interdisciplinary technological innovations and fostering breakthroughs across multiple scientific fields. However, in recent years, the rapid development of Cd, Pb, and Hg-based QDs has raised significant environmental and biological concerns due to the inherent toxicity of these heavy metals. Consequently, these materials have been classified as restricted substances by major global entities, including international organizations, the European Union, and the United States, through international treaties and domestic legislation. To mitigate legal risks associated with environmental pollution, the development of non-toxic and environmentally friendly (eco-friendly) QDs has become imperative. This review focuses on several eco-friendly QDs, such as indium phosphide (InP), copper indium sulfide (CuInS₂), and graphene QDs (GQDs), from the perspective of environmental compliance. It comprehensively discusses their synthesis methods, application domains, and the advantages and disadvantages of different preparation techniques, along with their environmental impacts. Finally, the review summarizes the existing challenges, limitations, and potential solutions for the development of environmentally benign QDs. Environmentally friendly ; Nanotechnology ; Quantum dot ; Environmental pollution ; Scope (computer science) ; Emerging technologies ; Legislation ; Materials science ; Computer science ; Political science ; Environmental science ; Environmental protection Quantum Dots Synthesis And Properties ; Carbon and Quantum Dots Applications ; Advanced Photocatalysis Techniques
Authors: Wei Li | Xi Su | Tan Su | Long Chen | Zhongmin Su
Source: Chemical Science (review, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Two-dimensional conjugated metal–organic frameworks for electrochemical energy conversion and storage Effective electrocatalysts and electrodes are the core components of energy conversion and storage systems for sustainable carbon and nitrogen cycles to achieve a carbon-neutral economy. Two-dimensional conjugated metal-organic frameworks (2D c-MOFs) have emerged as multifunctional materials for electrochemical applications benefiting from their similarity to graphene with remarkable conductivity, abundant active sites, devisable components, and well-defined crystalline structures. In this review, the structural design strategies to establish active components with a maximum degree through redox-active ligand assembly in 2D c-MOFs are briefly summarized. Next, recent representative examples of 2D c-MOFs applied in electrocatalysis (hydrogen/oxygen evolution and oxygen/carbon dioxide/nitrogen reduction) and energy storage systems (supercapacitors and batteries) are introduced. The synergistic effect of multiple components in 2D c-MOFs is particularly emphasized for enhanced performance in electrochemical energy conversion and storage systems. Finally, an outlook and challenges are proposed for realizing more active components, elucidating the reaction mechanism involving the derived structures, and achieving low-cost economy in practical applications. Conjugated system ; Electrochemistry ; Electrochemical energy conversion ; Electrochemical energy storage ; Energy storage ; Metal ; Materials science ; Energy transformation ; Metal-organic framework ; Nanotechnology ; Combinatorial chemistry ; Chemical engineering ; Chemistry ; Organic chemistry ; Electrode ; Metallurgy ; Supercapacitor ; Engineering ; Physics ; Physical chemistry ; Thermodynamics ; Power (physics) ; Polymer Metal-Organic Frameworks: Synthesis and Applications ; Advanced battery technologies research ; Advancements in Battery Materials
Authors: Min Seok Kang | Jin‐Ho Lee | Ki Su Kim
Source: Biosensors (review, 2025-06-18)
Field: Chemistry — Analytical Chemistry

Small Toxic Molecule Detection and Elimination Using Molecularly Imprinted Polymers (MIPs) Molecularly imprinted polymers (MIPs) provide selective, robust, and cost-effective platforms for the detection and removal of small toxic molecules in environmental, food, and biomedical contexts. This review offers a comprehensive overview of recent advancements in MIP-based systems, emphasizing critical design factors such as template selection, functional monomers, polymerization methods, and binding kinetics. The impact of these parameters on improving sensitivity, selectivity, and reusability is thoroughly examined. Additionally, current advantages, limitations, and enduring challenges are addressed. By highlighting emerging strategies and interdisciplinary innovations, this work aims to guide the development of more efficient and sustainable technologies for small-molecule toxin detection and remediation. Molecularly imprinted polymer ; Reusability ; Nanotechnology ; Molecular imprinting ; Biochemical engineering ; Polymer ; Computer science ; Chemistry ; Combinatorial chemistry ; Selectivity ; Materials science ; Organic chemistry ; Catalysis ; Engineering Analytical chemistry methods development ; Molecular Sensors and Ion Detection ; Carbon and Quantum Dots Applications
Authors: Wael Z. Tawfik | Mohamed Shaban | Athira Raveendran | June Key Lee | Abdullah M. Al‐Enizi
Source: RSC Advances (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Insights into the specific capacitance of CNT-based supercapacitor electrodes using artificial intelligence In this study, the specific capacitance characteristics of a carbon nanotube (CNT) supercapacitor was predicted using different machine learning algorithms, such as artificial neural network (ANN), random forest regression (RFR), <i>k</i>-nearest neighbors regression (KNN), and decision tree regression (DTR), based on experimental studies. The results of the simulation verified the accuracy of the ANN algorithm with respect to the data derived from the specific capacitance of the supercapacitor module. It was observed that there was a strong correlation between the experimental results and the predictions made by the ANN algorithm. Comparative analysis showed that the developed ANN algorithm was consistently superior over other algorithms in terms of different metrics, as indicated by the lowest root mean square error (RMSE) value of roughly 26.24 and the highest <i>R</i> <sup>2</sup> value of approximately 0.91. In contrast, the DTR model recorded the least reliable results in the accuracy analysis, as indicated by the highest RMSE value of about 53.46 and the lowest <i>R</i> <sup>2</sup> value of roughly 0.63. To further explore the impact of independent input parameters including pore structure, specific surface area, and <i>I</i> <sub>D</sub>/<i>I</i> <sub>G</sub> ratio on a single output parameter (particularly, the specific capacitance) the sensitivity analysis was also conducted using the SHapley Additive exPlanations (SHAP) framework. This investigation sheds light on the relative significance and effects of different input variables on the specific capacitance of supercapacitors based on CNTs. The results indicated that the ANN algorithm accurately predicted the capacitance of the CNT-based supercapacitor, demonstrating the feasibility and significance of neural network algorithms in the design of energy storage devices. Supercapacitor ; Capacitance ; Artificial neural network ; Decision tree ; Electrode ; Materials science ; Random forest ; Artificial intelligence ; Computer science ; Tree (set theory) ; Biological system ; Nanotechnology ; Mathematics ; Chemistry ; Biology Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Yifei Hao | Tianlin Li | Xia Hong
Source: Chemical Communications (review, 2025-01-01)
Field: Materials Science — Materials Chemistry

Interface phenomena and emerging functionalities in ferroelectric oxide based heterostructures Capitalizing on the nonvolatile, nanoscale controllable polarization, ferroelectric perovskite oxides can be integrated with various functional materials for designing emergent phenomena enabled by charge, lattice, and polar symmetry mediated interfacial coupling, as well as for constructing novel energy-efficient electronics and nanophotonics with programmable functionalities. When prepared in thin film or membrane forms, the ferroelectric instability of these materials is highly susceptible to the interfacial electrostatic and mechanical boundary conditions, resulting in tunable polarization fields and Curie temperatures and domain formation. This review focuses on two types of ferroelectric oxide-based heterostructures: the epitaxial perovskite oxide heterostructures and the ferroelectric oxides interfaced with two-dimensional van der Waals materials. The topics covered include the basic synthesis methods for ferroelectric oxide thin films, membranes, and heterostructures, characterization of their properties, and various emergent phenomena hosted by the heterostructures, including the polarization-controlled metal-insulator transition and magnetic anisotropy, negative capacitance effect, domain-imposed one-dimensional graphene superlattices, programmable second harmonic generation, and interface-enhanced polar alignment and piezoelectric response, as well as their applications in nonvolatile memory, logic, and reconfigurable optical devices. Possible future research directions are also outlined, encompassing the synthesis <i>via</i> remote epitaxy and oxide moiré engineering, incorporation of binary ferroelectric oxides, realization of topological properties, and functional design of oxygen octahedral rotation. Ferroelectricity ; Heterojunction ; Materials science ; Nanoscopic scale ; Perovskite (structure) ; Polarization (electrochemistry) ; Polar ; Oxide ; Non-volatile memory ; Nanotechnology ; Interface (matter) ; Optoelectronics ; Chemistry ; Dielectric ; Physics ; Crystallography ; Physical chemistry Ferroelectric and Piezoelectric Materials
Authors: Yuxuan Jiang | Xingkun Ning | Renhui Liu | Kepeng Song | Sajjad Ali | Haoyue Deng | Yizhuo Li | Biaohong Huang | Jianhang Qiu | Xiaofei Zhu | Zhen Fan | Qiankun Li | Chengbing Qin | Fei Xue | Teng Yang | Bing Li | Gang Liu | Weijin Hu | Lain‐Jong Li | Zhidong Zhang
Source: Nature Communications (article, 2025-08-09)
Field: Materials Science — Materials Chemistry

2D ferroelectric narrow-bandgap semiconductor Wurtzite’ type α-In2Se3 and its silicon-compatible growth 2D van der Waals ferroelectrics, particularly α-In<sub>2</sub>Se<sub>3</sub>, have emerged as an attractive building block for next-generation information storage technologies due to their moderate band gap and robust ferroelectricity stabilized by dipole locking. α-In<sub>2</sub>Se<sub>3</sub> can adopt either the distorted zincblende or wurtzite structures; however, the wurtzite phase has yet to be experimentally validated, and its large-scale synthesis poses significant challenges. Here, we report an in-situ transport growth of centimeter-scale wurtzite type α-In<sub>2</sub>Se<sub>3</sub> films directly on SiO<sub>2</sub> substrates using a process combining pulsed laser deposition and chemical vapor deposition. We demonstrate that it is a narrow bandgap ferroelectric semiconductor, featuring a Curie temperature exceeding 620 K, a tunable bandgap (0.8-1.6 eV) modulated by charged domain walls, and a large optical absorption coefficient of 1.3 × 10<sup>6</sup>/cm. Moreover, light absorption promotes the dynamic conductance range, linearity, and symmetry of the synapse devices, leading to a high recognition accuracy of 92.3% in a supervised pattern classification task for neuromorphic computing. Our findings demonstrate a ferroelectric polymorphism of In<sub>2</sub>Se<sub>3</sub>, highlighting its potential in ferroelectric synapses for neuromorphic computing. Ferroelectricity ; Materials science ; Wurtzite crystal structure ; Semiconductor ; Band gap ; Optoelectronics ; Condensed matter physics ; Physics 2D Materials and Applications ; Perovskite Materials and Applications ; Advanced Memory and Neural Computing
Authors: Yiran Ma | Meihui Wang | Tianyou Zhai
Source: Advanced Materials (review, 2025-01-31)
Field: Materials Science — Materials Chemistry

2D Molecular Crystals for Electronic and Optoelectronic Devices: Status and Challenges 2D molecular crystals (2D MCs) are an emerging family of 2D materials formed by organic or inorganic molecules held together entirely by weak intermolecular forces. 2D MCs are gaining attention in electronics and optoelectronics due to their structural diversity, scalability, and strong light-matter interactions. This review provides a comprehensive overview of 2D MCs and their potential in electronic and optoelectronic applications. It begins by highlighting the structural features and properties of key 2D MCs discovered to date, focusing on three strategies to manipulate intermolecular forces for better control over crystal morphology and properties. Then various methods are explored for fabricating large-area, highly-oriented 2D MCs, with an emphasis on vapor-phase and liquid-phase techniques. Last, their applications are reviewed in electronic and optoelectronic devices, such as channel materials, photosensitive components, and dielectrics. It is concluded by discussing future challenges and opportunities in the field, offering insights into scalable production and industrial applications of 2D MCs. Materials science ; Nanotechnology ; Optoelectronics 2D Materials and Applications ; Perovskite Materials and Applications ; Luminescence and Fluorescent Materials