jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: June Anne Caladcad
Source:  (article, 2025-02-18)
Field: Chemistry — Inorganic Chemistry

Leveraging Data Augmentation in Improving Machine Learning Algorithms for Coconut Maturity Classification Technological advancements enable the use of intelligent systems in various fields such as operations, management, as well as in agriculture. In the field of agriculture, smart systems create a positive impact on fruit classification, specifically for export needs. Even with its wide application, there have been limited studies on its utilization in coconut exportation. Another challenge identified is that gathering a large amount of dataset has become difficult, expensive, time-consuming, and prone to errors due to human inconsistencies. Due to this majority of the initial datasets in existing studies are unbalanced and sometimes, inadequate to contribute significant analysis and results. In this study, an investigation is conducted using an existing dataset of coconut acoustic signals to generate more data to balance out the samples across the three maturity levels. Data and data augmentation techniques are utilized along with combining techniques for acoustic signals, feature extraction, and data clustering. The data points under three maturity levels were clustered appropriately using the summing method and Mel Frequency Cepstral Coefficient feature. All data synthesizers failed to generate quality synthetic data. However, both audiomentation and procedural audio generation were able to produce quality augmented data after validating using linear layers, 1-dimensional convolution, and long-short term memory model as the audio classification technique. The new dataset was then fed to the same models and the results yielded to significant increase in its classification performance for all models. The study can be further improved by incorporating other coconut features to increase performance and widen its application. Computer science ; Machine learning ; Maturity (psychological) ; Artificial intelligence ; Algorithm ; Statistical classification ; Data mining Coconut Research and Applications
Authors: Viktor Korzhikov‐Vlakh | Lei Wang | Sofia M. Morozova | Ekaterina Sinitsyna | Tatiana Tennikova | Evgenia Korzhikova‐Vlakh
Source: Polymers (review, 2025-12-04)
Field: Materials Science — Materials Chemistry

Brick by Brick the Wall Is Being Built: Particle-Based Scaffolds for Regenerative Medicine Tissue engineering offers a promising solution by developing scaffolds that mimic the extracellular matrix and guide cellular growth and differentiation. Recent evidence suggests that scaffolds must provide not only biocompatibility and appropriate mechanical properties, but also the structural complexity and heterogeneity characteristic of natural tissues. Particle-based scaffolds represent an emerging paradigm in regenerative medicine, wherein micro- and nanoparticles serve as primary building blocks rather than minor additives. This approach offers exceptional control over scaffold properties through precise selection and combination of particles with varying composition, size, rigidity, and surface characteristics. The presented review examines the fundamental principles, fabrication methods, and properties of particle-based scaffolds. It discusses how interparticle connectivity is achieved through techniques such as selective laser sintering, colloidal gel formation, and chemical cross-linking, while scaffold architecture is controlled via molding, templating, cryogelation, electrospinning, and 3D printing. The resulting materials exhibit tunable mechanical properties ranging from soft injectable gels to rigid load-bearing structures, with highly interconnected porosity that is essential for cell infiltration and vascularization. Importantly, particle-based scaffolds enable sophisticated pharmacological functionality through controlled delivery of growth factors, drugs, and bioactive molecules, while their modular nature facilitates the creation of spatial gradients mimicking native tissue complexity. Overall, the versatility of particle-based approaches positions them as prospective tools for tissue engineering applications spanning bone, cartilage, and soft tissue regeneration, offering solutions that integrate structural support with biological instruction and therapeutic delivery on a single platform. Regenerative medicine ; Scaffold ; Tissue engineering ; Biocompatibility ; Modular design ; Extracellular matrix ; Drug delivery ; Biomimetics Pickering emulsions and particle stabilization ; 3D Printing in Biomedical Research ; Bone Tissue Engineering Materials
Authors: Toshio Fujita
Source: ChemRxiv (article, 2025-08-24)
Field: Chemistry — Physical and Theoretical Chemistry

Molecular MetaGraph and Molecular Iterated MetaGraph in Chemistry Graph theory investigates mathematical structures consisting of vertices and edges in order to model relationships and connectivity [1, 2]. A MetaGraph is a higher-level graph whose vertices are themselves graphs, with edges representing specified relations among those graphs. An Iterated MetaGraph extends this idea recursively: its vertices are MetaGraphs, thereby forming a hierarchy of graph-of-graphs structures across multiple levels. In this paper, we study new extensions called the Molecular MetaGraph and the Molecular Iterated MetaGraph, which generalize the notion of molecular graphs using the frameworks of MetaGraphs and Iterated MetaGraphs. Computational biology ; Iterated function ; Chemistry ; Computer science ; Biology ; Mathematics History and advancements in chemistry
Authors: Xiaojie Feng | Xiaoying He | Jiayi Zhu | Li-Hong Lin | Qiaoyan Shang | Zheng-Hong Luo | Yin-Ning Zhou | Fangyou Yan
Source: Chemical Science (article, 2025-12-15)
Field: Chemistry — Organic Chemistry

Symmetry-guided monomer design enables the combinatorial synthesis and targeted screening of polyesters The rational design of polyester materials plays a crucial role in the development of functional polymers with tailored properties. In this work, we introduce a novel symmetry-guided molecular design strategy, which is a symmetry-aware, parameter-controlled design paradigm that both broadens and rationalizes the accessible chemical space of functional molecules. By introducing the concept of a pairwise atomic symmetry index (PASI) metric and applying targeted modifications to small molecules, a library of 10 614 diacids and 9983 diols is constructed, enabling a systematic and unexplored expansion of the chemical space of polyesters. The combinatorial pairing of these diacids and diols leads to the generation of over 100 million polyester structures. High-throughput prediction of the glass transition temperature (<i>T</i> <sub>g</sub>) by the <i>T</i> <sub>g</sub>-QSPR model aligns well with the typical thermal behavior in polyester materials. To validate the design methodology, a two-level verification process is performed. The predicted <i>T</i> <sub>g</sub> values are first examined using molecular dynamics (MD) simulations and subsequently confirmed by differential scanning calorimetry experiments. The calculated <i>T</i> <sub>g</sub> values show good agreement with both MD simulations (average absolute error (AAE) of 17.54 °C) and experimental measurements (AAE of 16.45 °C). These results further confirm the reliability and robustness of the proposed approach. This study not only provides an effective strategy for the large-scale generation of a polyester library and screening of property targeted polyesters, but also carries broader chemical implications beyond polyester design, offering potential insights for the development of functional molecules. Polyester ; Combinatorial synthesis ; Metric (unit) ; Polymer ; Differential scanning calorimetry ; Rational design ; Pairwise comparison ; Chemical space Synthesis and Properties of Aromatic Compounds ; Advanced Polymer Synthesis and Characterization ; Catalysis for Biomass Conversion
Authors: Vasilios Raptis | Ioannis Michos
Source:  (article, 2025-09-12)
Field: Chemistry — Spectroscopy

Chemical Equitable Partitions: A New Perspective on Molecular Symmetries and Its Implications for the Study of Structure–Property Relationships In this work, the concept of equitable partition is applied to molecular graphs to define quantitative descriptors of the symmetry and complexity of molecules, with the ultimate goal of shedding new light on the structure–property relationships of chemical compounds and materials. The ways in which symmetry is reflected in these descriptors and their correlations with molecular properties are demonstrated using simple examples, and their potential for the prediction of properties of complex molecules is underscored. Perspective (graphical) ; Simple (philosophy) ; Symmetry (geometry) ; Homogeneous space ; Partition (number theory) ; Basis (linear algebra) ; Graph Molecular spectroscopy and chirality ; Crystallography and molecular interactions ; History and advancements in chemistry
Authors: Sergii Shevchenko | Dmytro Danylchenko | Roman Hanus | Serhii Radohuz | Roman Tomashevskyi | Mykola Makhonin | Andrii Potryvai
Source: Problems of the Regional Energetics (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Methods of Calculating Moisture Discharge Characteristics of Insulators The article discusses methods for calculating the moisture discharge voltage of insulators under various operating conditions (pollution, humidity, etc.) to identify patterns of environmental influence on operational characteristics, as well as to improve the reliability and safety of power grids. The main aim of the study is to compare two approaches to calculating the moisture discharge characteristics of insulators: the classical method based on the Tepler formula and an alternative approach that utilizes generalized parameters. These parameters can be easily obtained from the technical characteristics of insulators or design standards for automated calculations. To achieve this goal, the authors addressed several important tasks. First, a comprehensive analysis of the behavior of electrical discharges on the surface of insulators under various operating conditions, including standard and adverse environments, was conducted. Second, an automated tool was developed to quickly and accurately determine the values of moisture discharge voltage. Third, the proposed method was experimentally validated using the LK 70-110 insulator. The tests revealed a discharge voltage of 549 kV and an electric field intensity of 2.1 kV/cm, confirming the accuracy of the calculation method. The key findings of the study highlight the importance of considering factors such as the properties of insulator surfaces and the degree of contamination, especially in underground substations where humidity and pollution exhibit specific characteristics. The proposed approach proved effective both in standard and challenging operating conditions. The significance of the results lies in the creation of a tool that simplifies the calculation of moisture discharge characteristics of insulators. Moisture ; Environmental science ; Materials science ; Composite material High voltage insulation and dielectric phenomena ; Thermal Analysis in Power Transmission
Authors: Aoyan Liang | Nicolas Bertin | Xinran Zhou | Sylvie Aubry | Vasily V. Bulatov
Source: npj Computational Materials (article, 2025-12-18)
Field: Materials Science — Materials Chemistry

Computational alchemy clarifies origins of alloy strengthening Solid solution strengthening (SSS) is widely used to enhance mechanical properties of metals. Originally developed for dilute alloys, classical SSS theories are presently challenged by the rise of complex concentrated alloys (CCA) with nearly equiatomic compositions. Here, we propose and develop a method of “computational alchemy” in which interatomic interactions are modified to systematically vary two key physical parameters defining SSS - atomic size misfit and elastic stiffness misfit - over a maximally wide range of two misfits. The resulting alchemical alloys are subjected to massive (~108 atoms) molecular dynamics (MD) simulations reproducing full complexity of plastic strength response. At variance with prevailing views, stiffness misfit is observed to contribute to SSS on par if not more than size misfit. Furthermore, depending on exactly how two misfits are combined, they result in synergistic (amplification) or antagonistic (compensation) effect on alloy strengthening. Unlike real CCAs in which each component element comes with its own specific size and stiffness, our alchemical model alloys span the space of two misfits continuously revealing trends in alloy strengthening unrecognized so far. Our study demonstrates unique value of intentionally unrealistic models for gaining deep physical insights into material behaviors that are difficult to reveal otherwise. Alloy ; Stiffness ; Molecular dynamics ; Alchemy ; Component (thermodynamics) ; Value (mathematics) Microstructure and mechanical properties ; High Entropy Alloys Studies ; Advanced Materials Characterization Techniques
Authors: Kristiyan Stiliyanov Atanasov | P. K. Basu
Source: Fibers (article, 2025-11-04)
Field: Materials Science — Biomaterials

Molecular Self-Reassembled Regenerated Fibres and Their Significance in Tissue Engineering Bio-Composites Due to their interesting physicochemical and bioactive properties, regenerated fibres (including cellulose and collagen regenerated fibres) have been considered attractive biomaterials for biomedical applications. These regenerated fibres have an altered molecular arrangement compared to the native fibres and exhibit unique properties. Despite their distinctive structural characteristics, a meagre amount of research explores their potential for the development of tissue-engineering bio-composites. This work focuses on exploring the promise of cellulose and collagen-based regenerated fibres in tissue-regeneration bio-composite development. Initially, the work investigates the similarities and dissimilarities between the collagen and cellulose structures, which are linked to their specific properties, such as crystallinity, chemical characteristics, and mechanical properties. It then delves deeper into their molecular structural reassembly and various aspects of the already reported bio-composites developed using them. Finally, their promise in the development of tissue-engineering bio-composites is explored through a meticulous comparative analysis of their advantages and challenges. It was found that efficient biodegradability is one of the key advantages of regenerated fibres, whereas difficulty in processing presents a significant disadvantage. Despite these facts, regenerated fibres can incorporate enhanced and desired properties into the bio-composite matrix, which could lead to tissue-specific bio-regenerative applications. Regenerated cellulose ; Cellulose ; Tissue engineering ; Biodegradation ; Biocompatible material ; Work (physics) Collagen: Extraction and Characterization ; Electrospun Nanofibers in Biomedical Applications ; Advanced Cellulose Research Studies
Authors: Dong-Xu Yu | Ke-Qi Zeng | Zhe Wang
Source: arXiv (Cornell University) (preprint, 2025-06-04)
Field: Materials Science — Materials Chemistry

Understanding Flow Behaviors of Supercooled Liquids by Embodying Solid-Liquid Duality at Particle Level Understanding the flow behaviors of supercooled liquids presents a major challenge in liquid-state physics due to the strong nonlinearity and rich phenomena. To unravel this complexity, we introduce the concept of local configurational relaxation time $τ_\rm{LC}$, which allows us to embody the solid-liquid duality, proposed by Maxwell for phenomenologically describing materials' response to external load, at the particle level. The spatial distribution of $τ_\rm{LC}$ in flow is heterogeneous. Depending on the comparison between the local mobility measured by $τ_\rm{LC}$ and the external shear rate, the shear response of local regions is either solid-like or liquid-like. In this way, $τ_\rm{LC}$ plays a role similar to the Maxwell time. By applying this microscopic solid-liquid duality to different conditions of shear flow with a wide range of shear rates, we describe the emergence of shear thinning in steady shear, and predict the major characteristics of the transient response to start-up shear. Furthermore, we reveal a clear structural foundation for $τ_\rm{LC}$ and the solid-liquid duality associated with it by introducing an order parameter extracted from local configuration. Thus, we establish a framework that connects microscopic structure, dynamics, local mechanical response, and flow behaviors for supercooled liquids. Finally, we rationalize our framework in terms of activations from energy basins that are facilitated by shear. This model illustrates how local structure, convection and thermal activation collectively determine $τ_\rm{LC}$. Notably, it predicts two distinct response groups, which well correspond to the microscopic solid-liquid duality. Supercooling ; Duality (order theory) ; Flow (mathematics) ; Shear (geology) ; Shear flow ; Thermal ; Nonlinear system Material Dynamics and Properties ; Theoretical and Computational Physics ; Lattice Boltzmann Simulation Studies
Authors: Danies Seda Yuseva | Muchammad Muchammad | Sulistyo Sulistyo | Syaiful Syaiful | Reza Abdu Rahman
Source: Revue des composites et des matériaux avancés (article, 2025-08-31)
Field: Materials Science — Biomaterials

Investigating the Energy Intake/Discharge Behavior of Xylitol-Based PCM with Polymer as Thermal Storage Material Improving xylitol (XYL) phase change behavior is essential to maximize the energy rating in positive-coefficient thermal energy storage (PC-TES).The XYL requires activation to release the stored latent heat during solidification, which necessitates some modifications to the TES unit.This work solves the issue by introducing binder material from polymer to improve the operability aspect of XYL as TES material.Various highdensity (HD) polyethylene ratios (5%, 10%, 15% and 20%) are prepared using direct mixture method to form XYL-HD mixture (XYH).Thermal properties assessment indicates that the HD content has a substantial effect on the melt behavior, particularly for ratios of 15% and 20%, resulting in a two-step melt process between 99.8/110.1and 98.3/113.9.The microscope profile indicates that the XYL and HD are physically mixed.It confirms the FT-IR profile for the mixture, which has similar chemical identity as the base material.All synthesized XYH systems exhibit a peak during the cooling process, indicating that the system can solidify within the range of 104.7-116.9.It contributes significantly to the improvement of energy intake/discharge behavior.The XYH system able to achieve maximum charge and discharge efficiency around 84.6% and 74.1%, which is higher than XYL (53.9% and 42.6%).Thus, using HD contributes positively to initiating crystallization and eventually improves the operability level of XYL for PC-TES system. Polymer ; Thermal ; Energy storage ; Energy (signal processing) ; Thermal energy storage ; Work (physics) Advanced Cellulose Research Studies ; Phase Change Materials Research ; Korean Urban and Social Studies
Authors: Laxman Mishra | Garima Singh | Anshu Singh
Source: International Journal of Innovations in Science Engineering and Management. (article, 2025-06-19)
Field: Materials Science — Materials Chemistry

Deep Learning and Graph Neural Networks for Mathematical Pattern Recognition: Techniques, Challenges, and Advances Complex systems are often modelled using graphs, and one of the key tasks in complex system analysis is identifying anomalies in a graph. A graph anomaly is a pattern that does not follow the typical patterns predicted by the graph's structures and/or properties. The present article provides a comprehensive review of the techniques, challenges, and advancements in the field of Deep Learning and Graph Neural Networks for Mathematical Pattern Recognition. This review highlights the effectiveness of Deep Learning (DL) and Graph Neural Networks (GNNs) in mathematical pattern recognition. Graph-based models, particularly GraphMR built on Graph2Seq, demonstrate superior performance in model accuracy and efficiency over traditional Seq2Seq methods. GNNs effectively handle structured data like ASTs and DAGs, preserving semantic and syntactic information. The integration of encoder–decoder architectures and graph-based reasoning shows significant advancements in recognizing mathematical structures. The evolution from structural methods to DL and GNN approaches underscores the progress in recognition accuracy. As ML adoption grows, the need for large, high-quality datasets becomes critical for training next-generation models. Computer science ; Deep learning ; Artificial intelligence ; Graph ; Artificial neural network ; Machine learning ; Theoretical computer science Machine Learning in Materials Science ; Advanced Graph Neural Networks ; Graph Theory and Algorithms
Authors: Sailaja Pulaganti | Yerikala Ramesh | Venugopalaiah Penabaka | Prapurna Chandra Yadala
Source: International Journal of Pharmaceutics and Drug Analysis (article, 2025-11-04)
Field: Chemistry — Organic Chemistry

Enhancing prodrug development, strategies and challenges To enhance their pharmacokinetic and pharmacodynamic characteristics, prodrugs are bio reversible derivatives of active medicinal ingredients. Prodrug creation, despite its potential, is a complicated process that involves factors like membrane permeability, enzymatic activation, and chemical stability. Different prodrug development approaches, such as mutual prodrugs, bio precursor prodrugs, and carrier-linked prodrugs, are covered in this review. We also draw attention to the difficulties in prodrug development, including addressing formulation problems, guaranteeing safety and efficacy, and forecasting metabolic destiny. Through comprehension of these tactics and obstacles, scientists can create more potent prodrugs that improve the therapeutic effectiveness and safety of medications. A viable approach to overcoming the drawbacks of drug delivery, such as low bioavailability, toxicity, and lack of selectivity, is prodrug creation. Researchers can enhance the pharmacokinetic and pharmacodynamic characteristics of medicinal medicines by creating prodrugs that can be activated in vivo. Recent developments in prodrug development, such as creative activation mechanisms, targeted delivery methods, and revolutionary prodrug design tactics, are highlighted in this abstract. We'll talk about the prospects and difficulties in prodrug development, with an emphasis on how prodrugs could improve the safety and effectiveness of a variety of medicinal medicines. Prodrug ; Adept ; Drug ; Pharmacokinetics ; Pharmacodynamics ; Process (computing) Click Chemistry and Applications ; HIV/AIDS drug development and treatment ; Biochemical and Molecular Research