jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Gummalla Vijayamma | Nirmala S Nirmala
Source: Journal of Young Pharmacists (article, 2025-11-13)
Field: Chemistry — Spectroscopy

Eco-Friendly AQbD-Driven HPLC: A Sustainable Approach to Method Development and Validation Using Green Chemistry The integration of Analytical Quality by Design (AQbD) with Green Analytical Chemistry (GAC) represents a transformative approach in High-Performance Liquid Chromatography (HPLC) method development and validation. This review aims to provide a comprehensive overview of how AQbD frameworks can be systematically combined with GAC principles to achieve robust, reproducible, and environmentally sustainable analytical methods. AQbD facilitates method optimization through tools such as risk assessment, Design of Experiments (DoE), and Method Operable Design Region (MODR) establishment, while GAC focuses on minimizing hazardous solvent use, energy consumption, and waste production. This review evaluates peer-reviewed studies published between 2022 and mid-2025 that demonstrate AQbD-based HPLC and UPLC methods employing eco-friendly solvents, particularly ethanol and water, and assessing environmental sustainability using green metrics including AGREE, GAPI, AMGS, and Analytical Eco-Scale. Case studies on pharmaceutical analytes such as metronidazole, nicotinamide, irbesartan, metformin, and empagliflozin illustrate the practical implementation of these approaches, with several studies reporting high green scores and regulatory alignment with ICH guidelines. Despite significant progress, challenges persist, including inconsistent application of greenness metrics, limited availability of green solvent alternatives, and the need for integrated software tools that combine AQbD and GAC evaluation. This review highlights key methodological gaps and future opportunities, including extending AQbD-GAC approaches to complex matrices and integrating Artificial Intelligence (AI) to enhance optimization and sustainability. Overall, the convergence of AQbD and GAC not only ensures analytical reliability and regulatory compliance but also aligns with global sustainability goals and emerging eco-conscious scientific practices. Sustainability ; Hazardous waste ; Process (computing) ; Environmental engineering science ; Sustainable development ; Quality (philosophy) Analytical Chemistry and Chromatography ; Pesticide Residue Analysis and Safety ; Chemistry and Chemical Engineering
Authors: Francesco Rusciano | Raffaele Pastore | Francesco Greco | Walter Kob
Source: ArXiv.org (preprint, 2025-01-16)
Field: Materials Science — Materials Chemistry

At low temperatures, glass-forming liquids relax in a simple way Glass-forming liquids have only a modest tendency to crystallize and hence their dynamics can be studied even below the melting temperature. The relaxation dynamics of most of these liquids shows at a temperature $T_c$, somewhat above the glass-transition temperature $T_g$, a crossover, which indicates the conjunction of two different dynamical regimes. For temperatures slightly above $T_c$, experiments and computer simulations have extensively probed this dynamics on the particle level and identified several universal scaling laws that are often compatible with theoretical predictions. Using large scale computer simulations we extend these studies to temperatures below $T_c$ and find that the relaxation mechanism is qualitatively different from the one found at higher temperatures. We identify new scaling laws that allow to give a simple description of the relaxation dynamics at very low $T$s. Specifically we reveal that the cage-escape process is related to rare but large particle displacements that give rise to a distinctive sub-diffusive power-law in the time correlation functions. This insight helps to advance our understanding on the relaxation dynamics of glass-forming systems at temperatures that are close to the experimental glass transition. Simple (philosophy) ; Materials science ; Composite material Material Dynamics and Properties
Authors: Gözde S. Demirer | Mark Legendre | Carlos A Heredia | Clair M. Colee
Source: Research Square (preprint, 2025-08-26)
Field: Materials Science — Biomaterials

Extracellular contractile injection systems for high efficiency protein delivery to plants Extracellular ; Cell biology ; Chemistry ; Delivery system ; Biophysics ; Biology ; Pharmacology Electrospun Nanofibers in Biomedical Applications ; Electrohydrodynamics and Fluid Dynamics ; Tissue Engineering and Regenerative Medicine
Authors: Ghias Kharmanda
Source: Journal of Modern Polymer Chemistry and Materials (article, 2025-06-09)
Field: Materials Science — Polymers and Plastics

Towards Industrialization of Poly-Ethylene Terephthalate Glycol Material Fabricated by Fused Filament Fabrication Technique The material properties of Polyethylene terephthalate glycol (PETG) can be highly improved when adding other polymers or materials, however, we focus on this mini review only on pure PETG material fabricated by Fused Filament Fabrication (FFF) technique to overcome the corresponding issues with the object of industrializing the pure PETG material. In our previous works, deterioration concept was introduced to extend far beyond the concept of traditional failure concept, and its corresponding cases were classified into two categories: certainty and uncertainty cases. So, to industrialize this material fabricated by FFF technique, only certainty cases (reasons behind deterioration cases (defect/ fault/ failure/ damage)) can be characterized. These cases are treated here and next compared to other polymers such as Poly lactic acid (PLA) and/or Acrylonitrile Butadiene Styrene (ABS) materials if needed to overcome the different issues occurred when the studied this material by FFF technique. Several roadmaps are proposed considering the use of advanced techniques such as Artificial Intelligence (AI) and multi-level optimization. Ethylene glycol ; Fabrication ; Materials science ; Fused filament fabrication ; Poly ethylene ; Ethylene ; Composite material ; Protein filament ; Chemical engineering ; Polymer science ; Polymer chemistry ; Nanotechnology ; Polymer ; Organic chemistry ; Chemistry ; Catalysis ; Engineering Synthesis and properties of polymers ; biodegradable polymer synthesis and properties ; Fiber-reinforced polymer composites
Authors: Dexter C. Apolona
Source: International Journal of Apllied Mathematics (article, 2025-11-09)
Field: Chemistry — Analytical Chemistry

SWEET POTATOES QUALITY ANALYZER BASED ON NATIONAL PHILIPPINES STANDARDS USING DIGITAL IMAGE PROCESSING AND MACHINE LEARNING Sweet potato (Ipomoea batatas) is an important root crop for the Filipinos and farmers are still performing the grading manually and inconsistently by mostly relying on their judgment. This research introduces a computerized system using MATLAB for the digital image processing of sweet potatoes and grading per the Philippine Bureau of Agriculture and Fisheries Standards and an automated classification. The system consists of image acquisition, preprocessing, HSV color segmentation, morphological filtering, and feature extraction to identify defects on the surface, pest damage, and irregularities of shape. The user-friendly graphical interface presents individual analyses, batch summaries, and standard references for easy understanding. Evaluation of samples of sweet potatoes showed an accuracy of 92.6% when compared to manual grading which indicates the system as reliable, consistent, and human errors reduced. The system is a low-cost, standardized tool for post-harvest quality control that supports farmers, cooperatives, and agricultural technicians in their efforts to get a better market position. Future developments may consist of mixing machine learning, multispectral imaging for the detection of internal defects, and mobile platforms for real-time and in-field assessment thus encouraging wider adoption and digitalization of the Philippine agriculture industry. Grading (engineering) ; Agriculture ; Multispectral image ; Image processing ; Digital image ; Machine vision ; Digital image processing ; Feature extraction ; Graphical user interface Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Innovations in Aquaponics and Hydroponics Systems
Authors: Pong Kau Yuen | Cheng Man Diana Lau | Karen Yuen
Source: International Journal of Chemistry (article, 2025-04-28)
Field: Chemistry — Physical and Theoretical Chemistry

Buswell’s Model for Calculating Theoretical Higher Heating Value of Organic Matter Anaerobic digestion is a microbe-mediated process for producing biomethane, recovering energy, and assessing biodegradability of organic matter. Higher heating value of organic matter and biomethane are used for counting energy conversion efficiency. Anaerobic digestion is an energy conversion process that is tied to the parameters of Buswell&amp;rsquo;s equation. However, there is no study that attempts to integrate the parameters of Buswell&amp;rsquo;s equation with higher heating value to form a unified mathematical framework. This study introduces Buswell&amp;rsquo;s model as a theoretical parameter-derived approach, in which the mathematical framework is constructed by parameters of organic matter, parameters of Buswell&amp;rsquo;s equation, and higher heating value of organic matter. It is critically important that the theoretical higher heating value of any empirical formula or structural formula can be calculated by the derived mathematical equations. Chemistry ; Value (mathematics) ; Organic matter ; Thermodynamics ; Environmental chemistry ; Organic chemistry ; Statistics thermodynamics and calorimetric analyses
Authors: Chiat Oon Tan | Shigenobu Ogata | Hwa Jen Yap | Ichiro Nakamoto | Zuriani Usop | Mohd ‘Akashah Fauthan | Shaer Jin Liew | Siew‐Cheok Ng
Source: European Journal of Wood and Wood Products (article, 2025-06-24)
Field: Chemistry — Analytical Chemistry

Insights into a new overclustering technique using machine learning for a self-selecting bin-restricted colour sorting setup for light red meranti (Rubroshorea spp.) Abstract Timber colour sorting is an important woodworking process in producing a homogeneously coloured and pleasant looking product. However, for multispecific timber such as light red meranti, LRM ( Rubroshorea spp.), which spans a wide gamut of colours, there is an antagonistic compromise between having good separability of colour and the number of bins. This research attempts to solve this by intentionally overclustering the intensity gamut and then automating the selection of ideal colour sorting bins (CSB) for a given batch size to produce high-similarity coloured sorting. 178,327 unique LRM wood samples collected over 8 months of production were used. Machine learning clustering algorithms such as k-means and Otsu multithresholding were tested against percentile and equal spacing methods. Batch sizes of 250 (B250) and 1,000 (B1000) pieces were evaluated. Maximum likelihood estimation was tested against statistical methods to select the CSB, and ideal overcluster setups were determined using the average delta E ( $$\Delta E^*_{00}$$ ) assessment. The ‘burn-in rates’ of 3–30 pieces were then evaluated. For the B250 four-bin setup, six overclusters (6C4) performed best, with a recommended ‘burn-in rate’ of 12 pieces. For B1000, 5C4 performed best with a ‘burn-in rate’ of 10 pieces. The 4C3 configuration and the ‘burn-in rate’ of 10 pieces were found to be the best for three-CSB for both B250 and B1000. This study shows the feasibility of using machine learning to automate the bin selection process when the overclustering technique is used to improve colour sorting in situations with a restricted number of bins. Sorting ; Bin ; Artificial intelligence ; Computer science ; Materials science ; Mathematics ; Algorithm Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Yulan Gu | Jiangwei Zhang
Source: Interdisciplinary materials (article, 2025-09-01)
Field: Materials Science — Materials Chemistry

Response to [Reassessing Machine Learning Techniques for Electrocatalyst Design: A Call for Robust Methodologies] ABSTRACT This article is a response to the comment “Reassessing Machine Learning Techniques for Electrocatalyst Design: A Call for Robust Methodologies”. First, we clarify that the artificial neural network–SHapley Additive exPlanation (ANN–SHAP) method mentioned in the comment originates from the original work of Ding et al., which we only briefly summarized. In that study, nine different machine learning models were employed to predict the performance of proton exchange membrane fuel cells, among which the ANN model performed best. SHAP, together with multiple interpretability techniques (PDP, Tree‐based Rule, EIX, etc.), was used to cross‐validate feature importance, which was further compared with the results from manual feature selection, PCA, and t‐distributed stochastic neighbor embedding, and complemented by experimental validation to reduce the risk of bias amplification. We agree with the commenter that model interpretability should be approached with caution, as the absence of a definitive “ground truth” for feature importance remains a current challenge. However, benchmarking SHAP explanations against domain knowledge or validating them using synthetic datasets can help reduce the risk of misinterpretation. Regarding the unsupervised methods suggested in the comment (FA and HVGS), we consider them to have exploratory value for certain data structures, but caution is needed when applying them to experimental systems involving nonlinearity or high noise. Interpretability ; Feature (linguistics) ; Benchmarking ; Artificial neural network ; Domain (mathematical analysis) ; Experimental data Machine Learning in Materials Science
Authors: María Loreto Bravo | Guillermo Solís‐Fernández | Sandra Krzyzowska | Steven Huysecom | Ana Montero‐Calle | Indra Van Zundert | Boris Louis | James A. Hutchison | Rodrigo Barderas | Beatrice Fortuni | Susana Rocha
Source: Research Square (preprint, 2025-11-03)
Field: Materials Science — Biomaterials

Beyond One-Size-Fits-All: Cancer Biology Shapes Nanoparticle Behavior Internalization ; Endocytic cycle ; Extracellular matrix ; Nanomedicine ; Cancer ; Cancer therapy ; Cancer cell Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Nanoparticles: synthesis and applications
Authors: Kamil KOZA | Karel Gryc | Ladislav Socha | Jana SVIŽELOVÁ | Roman KUBEŠ | Václav SOCHACKÝ
Source: Metal ... (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Using computed tomography to investigate the effect of various casting parameters on zinc alloy castings Computed tomography (CT) was used to evaluate the internal quality of the zinc alloy castings.The castings are produced by high pressure die casting process from ZP0430 zinc alloy, which contains also aluminium and copper.High pressure die casting process is very complicated and sensitive to casting parameters such as filling rate, solidification time, die tempering and others.A certain percentage of porosity is always present in the castings.As part of the research into the die casting process, the internal porosity of Langmutter castings produced in an eight-cavity die was investigated.Castings produced using normal casting parameters and modified casting parameters based on numerical simulation of the casting process were evaluated.Computed tomography was used to determine the distribution of cavities in the casting, their quantity and subsequently their volume and porosity.In the castings produced using the normal casting parameters, the average number of cavities was 679 and the porosity was 0.108 %.When the modified casting parameters were implemented, the average number of cavities in the castings decreased to 454 and the porosity to 0.077 %.It has been shown that the modified casting parameters are more suitable for the high pressure die casting process in terms of porosity formation. Casting ; Computed tomography ; Alloy ; Zinc ; Copper alloy ; Zinc alloys Microstructure and mechanical properties ; Aluminum Alloy Microstructure Properties ; Metallurgical Processes and Thermodynamics
Authors: Hai-Van Thi | Phạm Văn Huỳnh
Source: Tạp chí điện tử Khoa học và Công nghệ Giao thông (article, 2025-05-28)
Field: Materials Science — Materials Chemistry

Dự báo độ dẻo Marshall của hỗn hợp bê tông nhựa chặt bằng mô hình tăng cường độ dốc Bê tông nhựa chặt (BTNC) là một trong số các vật liệu chủ yếu dùng xây dựng kết cấu áo đường ô tô. Để thiết kế thành phần và đánh giá chất lượng hỗn hợp BTNC cần dựa vào nhiều chỉ tiêu. Trong đó, độ dẻo Marshall (MF) là một chỉ tiêu quan trọng. Nghiên cứu đã thu thập bộ dữ liệu gồm 90 mẫu BTNC với 9 biến đầu vào và một biến đầu ra là MF. Trên cơ sở đó đã tiến hành xây dựng, phát triển 3 mô hình (MH) máy học: Tăng cường độ dốc - Gradient Boosting (GB), Tăng cường độ dốc nhẹ - Light Gradient Boosting (LGB) và Cây quyết định- Decision Tree (DT) để dự báo MF. Hiệu suất dự báo (DB) của các MH sau 20 lần mô phỏng được so sánh, từ đó đề xuất được một MH tối ưu trong dự báo MF của BTNC (mô hình GB), với có khả năng dự báo MF của BTNC rất cao (R2kiểm tra = 0,91). Nghiên cứu đã xây dựng được một hướng dẫn sử dụng MH để DB độ dẻo Marshall của BTNC một cách chính xác, tiết kiệm thời gian và chi phí. Ngoài ra, biểu đồ SHAP cũng được xây dựng để DB mức độ ảnh hưởng của các biến đầu vào đối với MF của BTNC. Chemistry Structural mechanics and materials ; Geodetic Measurements and Engineering Structures
Authors: Tiange Tao | Dominique T. Capraro | Patricia A. Jennings
Source: Biomolecular NMR Assignments (article, 2025-12-18)
Field: Materials Science — Materials Chemistry

1H, 13C, 15N Backbone Assignment of the Minimally Tied Trefoil Knot, MTTSA , a 23s rRNA SPOUT Methyltransferase <title>Abstract</title> Knotted Methyltransferases (MTase) from the SpoU-TrmD (SPOUT) family offer a unique opportunity to study a protein knot topology and enzymatic function. The knotted methyltransferase from <italic>Staphylococcus aureus</italic> , MTT <sub>SA</sub> (PDB: 1vh0, 4fak), is an ɑ/β-knotted 23s rRNA MTase containing only the minimal scaffold among the SPOUT family members. This dimeric enzyme is a minimalist model to study the deep + 3 <sub>1</sub> knot. Here, we report the non-proline backbone assignments with 98.8% completion using TROSY-based NMR experiments on uniformly labeled <sup>2</sup> H/ <sup>13</sup> C/ <sup>15</sup> N-labeled protein. Complementary HBHA(CO)NH experiments on <sup>13</sup> C/ <sup>15</sup> N-labeled protein were completed for Hα/Hβ sidechain assignments. Both backbone and sidechain assignments were deposited in the Biological Magnetic Resonance Bank (BMRB ID: 53391). Of 164 assigned residues, TALOS-N predictions provided 88.4% unambiguous assignments based on the H <sub>N</sub> , H <sub>α</sub> , C <sub>α</sub> , C <sub>β</sub> and N chemical shifts. In addition, the predicted secondary structure based on torsion angels and the ΔδC <sub>α</sub> -ΔδC <sub>β</sub> profile are in agreement with the crystal structures. Trefoil ; Methyltransferase ; 23S ribosomal RNA ; Protein Data Bank ; Enzyme ; Ribosomal RNA ; Transferase ; Protein secondary structure Enzyme Structure and Function ; Microbial Natural Products and Biosynthesis ; Biochemical and Structural Characterization
Authors: Annisa Rositasari | Izzati Muhimmah | Linda Rosita
Source: Jurnal Sains Nalar dan Aplikasi Teknologi Informasi (article, 2025-07-06)
Field: Chemistry — Physical and Theoretical Chemistry

Pemodelan Sistem Urinalisis Mikroskopik Untuk Kristal Amorf Sebagai Solusi Pada Laboratorium Dalam penelitian ini mikroskop berfungsi untuk melihat objek terkecil yang ada di dalam kandungan urin. Ahli Tenaga Laboratorium Medis (ATLM) merupakan tenaga kesehatan yang menggunakan mikroskop untuk pengamatan. Penelitian dilaksanakan dengan mengambil data dari Rumah Sakit Islam Yogyakarta PDHI dan mendapat 153 data pemeriksaan urin dari pasien yang datang ke Unit Gawat Darurat (UGD), rawat jalan, dan rawat inap. Dari 153 data yang diperoleh, di mana 53 di antaranya menunjukkan adanya urin dengan enam jenis kristal yang terdeteksi. Keenam jenis kristal tersebut meliputi kristal kalsium oksalat, kristal fosfat triple, fosfat amorf, kalsium karbonat, kristal amonium biurat, dan kristal asam urat. Sistem yang dikembangkan menggunakan bahasa pemrograman Python ini fokus pada identifikasi jenis kristal amorf. Dalam sistem tersebut, hasil marking yang dilakukan oleh ahli pada objek kristal berhasil dikenali oleh sistem. Sistem sudah sesuai dengan hasil yang diperoleh dari pakar. Pengujian ini menggunakan Single Decision Threshold dan memperoleh hasil nilai sensitivity sebesar 0.63 atau dalam bentuk persen yaitu 63%. Sistem mendapatkan hasil nilai specificity sebesar 0.17 atau 17%. Sistem mendapatkan hasil nilai accuracy sebesar 0.36 atau 36% dan sistem mendapatkan hasil nilai precision sebesar 0.35 atau 35%. Kinerja sistem sebesar 26%. Art Various Chemistry Research Topics
Authors: Fei Cai | Fang Liu | Yong Zhang
Source: Scientia Sinica Vitae (article, 2025-04-17)
Field: Chemistry — Spectroscopy

Urinary glycoproteomics: opening a new window for disease diagnosis 尿液是一种可非侵入性收集、反复采样监测的生物样本，反映了机体的诸多变化，已成为疾病生物标志物研究重要的样本来源。糖基化修饰在蛋白质功能调控中起着关键作用，因而尿液蛋白质糖基化修饰作为疾病诊断标志物极具潜力，开启了疾病诊断新窗口。近年来，尽管尿液糖蛋白质组学研究受到广泛关注，但缺乏对既往相关研究的全面总结与归纳分析，以及对具有临床转化价值糖蛋白的探讨。基于此，本文综述了尿液糖蛋白组学的最新研究进展，涵盖最新的分析方法策略以及临床应用，讨论了尿糖蛋白质作为多种疾病新型生物标志物的潜在价值，强调其重要性并针对应用难题提出可能的解决方向，以促进尿液糖蛋白质组学的临床应用转化。 Political science Advanced Proteomics Techniques and Applications ; Glycosylation and Glycoproteins Research ; Urinary Tract Infections Management