jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bojun Liu | Jordan G. Boysen | Ilona Christy Unarta | Xuefeng Du | Yixuan Li | Xuhui Huang
Source: Nature Communications (article, 2025-01-02)
Field: Chemistry — Spectroscopy

Exploring transition states of protein conformational changes via out-of-distribution detection in the hyperspherical latent space Identifying transitional states is crucial for understanding protein conformational changes that underlie numerous biological processes. Markov state models (MSMs), built from Molecular Dynamics (MD) simulations, capture these dynamics through transitions among metastable conformational states, and have demonstrated success in studying protein conformational changes. However, MSMs face challenges in identifying transition states, as they partition MD conformations into discrete metastable states (or free energy minima), lacking description of transition states located at the free energy barriers. Here, we introduce Transition State identification via Dispersion and vAriational principle Regularized neural networks (TS-DAR), a deep learning framework inspired by out-of-distribution (OOD) detection in trustworthy artificial intelligence (AI). TS-DAR offers an end-to-end pipeline that can simultaneously detect all transition states between multiple free minima from MD simulations using the regularized hyperspherical embeddings in latent space. The key insight of TS-DAR lies in treating transition state structures as OOD data, recognizing that they are sparsely populated and exhibit a distributional shift from metastable states. We demonstrate the power of TS-DAR by applying it to a 2D potential, alanine dipeptide, and the translocation of a DNA motor protein on DNA, where it outperforms previous methods in identifying transition states. Space (punctuation) ; Transition (genetics) ; Statistical physics ; Distribution (mathematics) ; Physics ; Transition state ; Chemistry ; Computer science ; Mathematics ; Biochemistry Mass Spectrometry Techniques and Applications ; Protein Structure and Dynamics ; Diffusion and Search Dynamics
Authors: Guoling Wan | Jianguo He | Xianghong Meng | Guishan Liu | Jingjing Zhang | Fang Ma | Qian Zhang | Di Wu
Source: Critical Reviews in Food Science and Nutrition (review, 2025-05-02)
Field: Chemistry — Analytical Chemistry

Hyperspectral imaging technology for nondestructive identification of quality deterioration in fruits and vegetables: a review With the increasing demand for high quality agri-food commodities, the issues of internal and external quality of fruits and vegetables have received widespread attention globally. To obtain the healthy fruits and vegetables, it is essential to develop advanced nondestructive detection technologies for identification of quality deterioration of target sample. Hyperspectral imaging (HSI) technology contains rich spectral and imaging information, which is capable of acquiring a detailed response of quality deterioration in fruits and vegetables. The review delves into the fundamental mechanism and damage type of quality deterioration caused by physical, chemical and biological factors within the domain of fruits and vegetables analysis. Various forms of deterioration encompassing surface defects, chilling injury, mechanical damage, wilting, browning, and microbial infection are summarized. Moreover, this overview also provides recent advances of HSI technology coupled with machine learning algorithms for quality evaluation and discrimination of different varieties fruits and vegetables. It also critically discusses the existing challenges and future prospects of the HSI technology in actual applications. Despite the extant limitations resulting from high-dimensional hyperspectral data and limited number of samples, the ongoing evolution of multi-sensor fusion architectures and artificial intelligence algorithms will promote HSI technology from laboratory to on-line monitoring in industrial applications. Hyperspectral imaging ; Identification (biology) ; Environmental science ; Remote sensing ; Biology ; Geography ; Botany Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Meat and Animal Product Quality
Authors: T. Sajini | Jebin Joseph
Source: RSC Sustainability (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Microwave-assisted synthesis of nanomaterials: a green chemistry perspective and sustainability assessment This review highlights sustainable microwave-assisted synthesis of nanomaterials, focusing on green chemistry, environmental benefits, and comparative insights for scalable, eco-friendly production aligned with sustainability goals. Nanomaterials ; Sustainability ; Nanotechnology ; Perspective (graphical) ; Microwave ; Green chemistry ; Materials science ; Chemistry ; Engineering ; Computer science ; Telecommunications ; Ecology ; Physical chemistry Nanoparticles: synthesis and applications ; Chemistry and Chemical Engineering ; Nanomaterials for catalytic reactions
Authors: Austine Ofondu Chinomso Iroegbu | Moipone Linda Lethabane | Emmanuel Rotimi Sadiku | Reinout Meijboom | Shanganyane Percy Hlangothi
Source: npj Clean Water (article, 2025-09-01)
Field: Chemistry — Inorganic Chemistry

Advancing wastewater treatment with green and scalable metal–organic frameworks: from synthetic strategies to real-world deployment The escalating global water crisis demands innovative solutions. This review highlights the transformative role of metal–organic frameworks (MOFs) in wastewater treatment, integrating green, scalable synthesis (e.g., mechanochemistry, continuous-flow, supercritical fluid methods) with advanced functionalization. It covers diverse pollutants, performance in real matrices, removal mechanisms, and practical deployment platforms. Key challenges and future directions are discussed, offering a roadmap toward sustainable, industrial-scale MOF applications for water purification. Software deployment ; Metal-organic framework ; Scalability ; Wastewater ; Sewage treatment ; Environmental science ; Waste management ; Biochemical engineering ; Computer science ; Environmental engineering ; Engineering ; Chemistry ; Software engineering ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation Technologies ; Covalent Organic Framework Applications
Authors: Mohsen Shayanmehr | Sepehr Aarabi | Ahad Ghaemi | Alireza Hemmati
Source: Scientific Reports (article, 2025-01-24)
Field: Chemistry — Inorganic Chemistry

A data driven machine learning approach for predicting and optimizing sulfur compound adsorption on metal organic frameworks This study employed some machine learning (ML) techniques with Python programming to forecast the adsorption capacity of MOF adsorbents for thiophenic compounds namely benzothiophene (BT), dibenzothiophene (DBT), and 4,6-dimethyl dibenzothiophene (4,6-DMDBT). Five ML models were developed with the help of a dataset containing 676 rows to correlate the adsorbent features, adsorption conditions, and adsorbate characteristics to the MOF sample's sulfur adsorption capability. Among the ML approaches, MLP model achieved the best performance with a low mean squared error (MSE) of 0.0032 on the test set and 0.0021 on the training set and mean relative error (MRE) of 15.26% on the test set. Also, Random Forest model yielded a higher test MSE of 0.0045 and MRE of 17.83%. Feature importance analysis was performed by utilizing MLP model and shapely additive plan (SHAP) method, and the findings revealed that "initial concentration of sulfur" (SHAP value 0.51) and "contact time" (SHAP value 0.37) were the crucial factors influenced desulfurization process efficiency. Additionally, a comparative analysis of the features utilizing the MLP network classified the factors into three primary categories: process conditions, adsorbent characteristics, and adsorbate characteristics. Consequently, the process condition was identified as the most significant group compared to others. Finally, the desulfurization process optimization indicated the maximum DBT adsorption of 161.6 mg/g for Zr-based MOF could be achieved when the features including BET, TPV, pore size, oil/adsorbent ration, and temperature were tuned around 756 m<sup>2</sup>/g, 0.955 cm<sup>3</sup>/g, 5.96 nm, 449.85 g/g, 20.1 °C, respectively. Metal-organic framework ; Adsorption ; Computer science ; Sulfur ; Machine learning ; Artificial intelligence ; Chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Catalysis and Hydrodesulfurization Studies ; Chemical Synthesis and Reactions
Authors: Mehrdad Asgari | Pablo Albacete | Dhruv Menon | Ying Lyu | Xu Chen | David Fairen‐Jiménez
Source: Chemical Society Reviews (review, 2025-01-01)
Field: Materials Science — Materials Chemistry

The structuring of porous reticular materials for energy applications at industrial scales Reticular synthesis constructs crystalline architectures by linking molecular building blocks with robust bonds. This process gave rise to reticular chemistry and permanently porous solids. Such precise control over pore shape, size and surface chemistry makes reticular materials versatile for gas storage, separation, catalysis, sensing, and healthcare applications. Despite their potential, the transition from laboratory to industrial applications remains largely limited. Among various factors contributing to this translational gap, the challenges associated with their formulation through structuring and densification for industrial compatibility are significant yet underexplored areas. Here, we focus on the shaping strategies for porous reticular materials, particularly metal-organic frameworks (MOFs) and covalent organic frameworks (COFs), to facilitate their industrial application. We explore techniques that preserve functionality and ensure durability under rigorous industrial conditions. The discussion highlights various configurations - granules, monoliths, pellets, thin films, gels, foams, and glasses - structured to maintain the materials' intrinsic microscopic properties at a macroscopic level. We examine the foundational theory and principles behind these shapes and structures, employing both <i>in situ</i> and post-synthetic methods. Through case studies, we demonstrate the performance of these materials in real-world settings, offering a structuring blueprint to inform the selection of techniques and shapes for diverse applications. Ultimately, we argue that advancing structuring strategies for porous reticular materials is key to closing the gap between laboratory research and industrial utilization. Structuring ; Reticular connective tissue ; Closing (real estate) ; Porosity ; Porous medium ; Key (lock) ; Materials science ; Nanotechnology ; Computer science ; Business ; Composite material ; Medicine Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Supercapacitor Materials and Fabrication
Authors: Wenjie Xuan | X. Li | Honglei Gao | Luyao Zhang | Jili Hu | Liping Sun | Hongxing Kan
Source: Scientific Reports (article, 2025-04-17)
Field: Materials Science — Materials Chemistry

Artificial intelligence driven platform for rapid catalytic performance assessment of nanozymes Traditional methods for synthesizing nanozymes are often time-consuming and complex, hindering efficiency. Artificial intelligence (AI) has the potential to simplify these processes, but there are very few dedicated nanozyme databases available, limiting the resources for research and application. To address this gap, we developed AI-ZYMES, a comprehensive nanozyme database featuring 1,085 entries and 400 types of nanozymes. The platform incorporates several key innovations that distinguish it from existing databases: Firstly, standardized Data Curation: AI-ZYMES resolves inconsistencies in catalytic metrics (e.g., K<sub>m</sub>, V<sub>max</sub>), morphologies, and dispersion systems, enabling reliable cross-study comparisons, something that existing resources like DiZyme and nanozymes.net lack.Secondly, dual AI Framework: A gradient-boosting regressor predicts kinetic constants (K<sub>m</sub>, V<sub>max</sub>, K<sub>cat</sub>) with an R<sup>2</sup> up to 0.85, while an AdaBoost classifier identifies enzyme-mimicking activities based solely on nanozyme names, surpassing traditional random forest models in predictive accuracy.Lastly, ChatGPT-based Synthesis Assistant: The platform includes an AI-driven assistant for literature extraction (67.55% accuracy) and synthesis pathway generation via semantic analysis (90% accuracy). This reduces manual effort and minimizes errors in large language model outputs, ensuring high-quality results.These innovations make AI-ZYMES a valuable tool for accelerating nanozyme research and application, including antimicrobial therapy, biosensing, and environmental remediation. The platform improves data accessibility, reduces experimental redundancy, and speeds up the translation of discoveries into practical use. By bridging the data fragmentation and predictive limitations of existing systems, AI-ZYMES establishes a new benchmark for AI-driven advancements in nanomaterials. Computer science Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Electrochemical sensors and biosensors
Authors: Zhixin Yao | Huifeng Tian | U Sasaki | Huacong Sun | Jingyi Hu | Guodong Xue | Ye Seul Jung | Ruijie Li | Zhenjiang Li | PeiChi Liao | Yihan Wang | Lina Yang Zhang | Ge Yin | Xuanyu Zhang | Yijie Luo | Wenxi Li | Yong Soo Cho | Peizhi Liu | Kaihui Liu | Yanfeng Zhang | Lifen Wang | Junjie Guo | Lei Liu
Source: Nature Communications (article, 2025-02-10)
Field: Materials Science — Materials Chemistry

Transferrable, wet-chemistry-derived high-k amorphous metal oxide dielectrics for two-dimensional electronic devices Two-dimensional (2D) materials hold transformative potential for next-generation electronics. The integration of high dielectric constant (k) dielectrics onto 2D semiconductors, while maintaining their pristine properties by low-defect-density interfaces, has proven challenging and become one performance bottleneck of their practical implementation. Here, we report a wet-chemistry-based method to fabricate amorphous, transferable high-k (42.9) copper calcium titanate (CCTO) thin films as high-quality, dual-function dielectrics for 2D electronic devices. The chelation-based Pechini approach guarantees uniformity in this perovskite-type complex oxide, while the transferrable feature allows its harmless integration to 2D semiconductors interfacing with a nanogap. The CCTO-gated MoS<sub>2</sub> devices exhibit a subthreshold swing down to 67 mV dec<sup>-1</sup> and an ultra-small hysteresis of ~ 1 mV/(MV cm<sup>-1</sup>). Moreover, leveraging its visible-light active characteristics, we implement an electrically-manipulated, optically-activated nonvolatile floating gate in CCTO, enabling the reconfigurable execution of 9 basic Boolean logic in-sensor operations within a single field-effect device architecture. This advancement paves the way for the development of multifunctional, low-power 2D electronic systems by incorporating multifunctional conventional complex oxides. Materials science ; Dielectric ; Nanotechnology ; Optoelectronics ; Amorphous solid ; Electronics ; Semiconductor ; High-κ dielectric ; Thin film ; Computer science ; Electrical engineering ; Chemistry Electronic and Structural Properties of Oxides ; Semiconductor materials and devices ; Ferroelectric and Piezoelectric Materials
Authors: Kawan F. Kayani | Sewara J. Mohammed
Source: Materials Advances (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Mercury in aquatic environments: toxicity and advances in remediation using covalent organic frameworks This review presents recent advances in understanding mercury toxicity, its chemical forms, and the synthesis of covalent organic frameworks (COFs), introducing COFs for the first time as a method for mercury removal. Mercury (programming language) ; Environmental remediation ; Environmental chemistry ; Environmental science ; Aquatic ecosystem ; Chemistry ; Computer science ; Contamination ; Ecology ; Biology Covalent Organic Framework Applications ; Luminescence and Fluorescent Materials ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Keerthana Madhivanan | Raji Atchudan | Sandeep Arya | Ashok K. Sundramoorthy
Source: Nanoscale Advances (article, 2025-01-01)
Field: Chemistry — Electrochemistry

Simultaneous electrochemical detection of heavy metal ions using a sol–gel synthesized BiVO<sub>4</sub> nanosphere modified electrode and its antimicrobial activity This study explores the development of an advanced electrochemical sensor designed for the simultaneous detection of Cd<sup>2+</sup>, Pb<sup>2+</sup>, Cu<sup>2+</sup>, and Hg<sup>2+</sup> ions. The sensor utilizes sol-gel-synthesized bismuth vanadate (BiVO<sub>4</sub>) nanospheres, which are integrated onto a glassy carbon electrode (GCE), and employs square wave anodic stripping voltammetry (SWASV) for electrochemical determination of heavy metal ions. The as-prepared sensor demonstrated exceptional analytical performance and offered a wide linear detection range from 0 μM to 110 μM, along with low detection limits of 2.75 μM for Cd<sup>2+</sup>, 2.32 μM for Pb<sup>2+</sup>, 2.72 μM for Cu<sup>2+</sup>, and 1.20 μM for Hg<sup>2+</sup> ions. These characteristics made the sensor highly suitable for precise monitoring of heavy metal contamination in both environmental and industrial samples. Beyond their sensing capabilities, the BiVO<sub>4</sub> nanospheres also exhibited significant antimicrobial activity against bacterial strains such as <i>E. coli</i> and <i>S. aureus</i>, as well as fungal strains like <i>C. albicans</i> and <i>C. parapsilosis</i>. This antimicrobial effect was attributed to the enhanced surface reactivity and the generation of reactive oxygen species (ROS), which disrupt microbial cellular functions. This dual-functional approach highlighted the substantial progress in both electrochemical sensing and antimicrobial applications. This research presents a strong platform for tackling urgent challenges in environmental monitoring and microbial control. Electrochemistry ; Bismuth vanadate ; Bismuth ; Electrode ; Metal ions in aqueous solution ; Electrochemical gas sensor ; Materials science ; Sol-gel ; Ion ; Metal ; Vanadate ; Inorganic chemistry ; Nanotechnology ; Chemistry ; Catalysis ; Metallurgy ; Photocatalysis ; Organic chemistry Electrochemical Analysis and Applications ; Water Quality Monitoring and Analysis ; Analytical Chemistry and Sensors
Authors: Duyen H. H. Nguyen | Arjun Muthu | Tamer Elsakhawy | Mohamed H. Sheta | Neama Abdalla | Hassan El-Ramady | József Prokisch
Source: Nanomaterials (review, 2025-05-11)
Field: Materials Science — Materials Chemistry

Carbon Nanodots-Based Sensors: A Promising Tool for Detecting and Monitoring Toxic Compounds The increasing prevalence of toxic compounds in food, agriculture, and the environment presents a critical challenge to public health and ecological sustainability. Carbon nanodots (CNDs), with their excellent photoluminescence, biocompatibility, and ease of functionalization, have emerged as highly promising materials for developing advanced sensors that target hazardous substances. This review provides a comprehensive overview of the synthesis, functionalization, and sensing mechanisms of CND-based sensors, highlighting their versatile application in detecting toxic compounds such as heavy metals, pesticides, mycotoxins, and emerging contaminants. The article outlines recent advancements in fluorescence, electrochemical, and colorimetric detection strategies and presents key case studies that illustrate the successful application of CNDs in real-world monitoring scenarios. Furthermore, it addresses the challenges associated with reproducibility, scalability, selectivity, and sensor stability and explores future directions for integrating CNDs with smart and sustainable technologies. This review emphasizes the transformative potential of CNDs in achieving rapid, cost-effective, and environmentally friendly toxin detection solutions across multiple domains. Nanotechnology ; Surface modification ; Computer science ; Environmentally friendly ; Sustainability ; Biochemical engineering ; Materials science ; Engineering Carbon and Quantum Dots Applications ; Heavy Metal Exposure and Toxicity ; Mercury impact and mitigation studies
Authors: Jiayue Han | Ziyi Fu | Jingxuan Wei | Song Han | Wenjie Deng | F. R. Hu | Zhen Wang | Hongxi Zhou | Yu He | Jun Gou | Jun Wang
Source: Light Science & Applications (review, 2025-10-10)
Field: Materials Science — Materials Chemistry

2D materials-based next-generation multidimensional photodetectors With the rapid advancement of the information age, the demand for multi-dimensional light information detection has significantly increased. Traditional Fourier-transform infrared (FTIR) spectrometers and pooptical power, andlarimeters, due to their bulky structure, are no longer suitable for emerging fields such as medical diagnostics, secure communications, and autonomous driving. As a result, there is a pressing need to develop new miniaturized on-chip devices. The abundant two-dimensional (2D) materials, with their unique light-matter interactions, offer the potential to construct high-dimensional spatial mappings of incident light, paving the way for the development of novel ultra-compact multi-dimensional deep optical sensing technologies. Here, we review the interconnections of multi-dimensional information and their relationship with 2D materials. We then focus on recent advances in the development of novel dimensional detectors based on 2D materials, covering dimensions such as intensity, time, space, polarization, phase angle, and wavelength. Furthermore, we discuss cutting-edge technologies in multi-dimensional fusion detection and highlight future technological prospects, with a particular emphasis on on-chip integration and future development. Photodetector ; Focus (optics) ; Emphasis (telecommunications) ; Construct (python library) ; Detector ; Information fusion ; Emerging technologies 2D Materials and Applications ; Gas Sensing Nanomaterials and Sensors ; Nanowire Synthesis and Applications
Authors: Haradhan Kolya | Chun–Won Kang
Source: Discover Water (article, 2025-04-14)
Field: Chemistry — Organic Chemistry

Recent advances in polymer nanocomposites for the adsorptive removal of toxic azo dyes from water Abstract Adequate wastewater treatment technologies are essential for addressing toxic dyes’ environmental pollution and health hazards. Azo dyes which contain one or more azo bonds are widely used in the textile. However, they are known to be carcinogenic, mutagenic, and highly toxic to human health. Traditional wastewater treatments methods, such as coagulation, flocculation, and biological treatment, often fail to eliminate dye molecules due to their complex structures and strong chemical stability. Therefore, there is a need for advanced solutions. Polymer nanocomposites have emerged as a promising alternative, offering high surface area, tunable properties, and exceptional adsorption capacities. This review describes recent reports on the synthesis, characterization, and application of polymer nanocomposites for azo dye removal, incorporating key findings such as the remarkable adsorption capacity of gelatin nanocomposite (950.5 mg/g). However, most studies were used synthetic dye solutions with limited validation in real industrial effluents. This paper also describes future research development with scalability, cost analysis, and biodegradability for practical use. This review aims to guide future research toward more effective adsorbent, eco-friendly, and scalable wastewater treatment for dye removal. Nanocomposite ; Polymer ; Environmental chemistry ; Chemical engineering ; Polymer science ; Materials science ; Chemistry ; Nanotechnology ; Composite material ; Engineering Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal ; Synthesis of Tetrazole Derivatives