jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ercan Yıldız | Ahmet Sümbül
Source: Horticultural Studies (article, 2025-08-02)
Field: Materials Science — Biomaterials

Effect of Some Colloidal Coating Treatments on the Shelf Life and Quality Characteristics of Strawberry Fruits Short shelf life after harvest is one of the biggest problems for fresh strawberries. In this study, the effects of next generation edible colloidal coating agents formed from combinations of chitosan, selenium and thyme essential oil obtained by ionic gelation method on the post-harvest quality criteria of strawberries were investigated. The quality parameters (weight loss, decay rate, respiration rate, fruit color, firmness, total soluble solids: TSS, titratable acid: TA, ascorbic acid content, total phenolic content, antioxidant capacity and total anthocyanin content) of fruits of Albion strawberry variety kept at 21°C (room temperature conditions, relative humidity) were measured on days on 0th, 3rd, 5th, 7th and 10th. All coating treatments showed positive effects on quality parameters during shelf life. Edible colloidal coating treatments showed positive effects on the reduction of weight loss, reduction of decay, respiration rate, color values, fruit firmness, titratable acid content, ascorbic acid content, total phenolic content, total anthocyanin content and total antioxidant capacity values during shelf life compared to the control group. Among all the treatments, the most effective treatments in preserving quality properties were Chitosan + Selenium and Chitosan + Selenium + Thyme essential oil treatments. The research of results will provide information on the development of edible colloidal coating materials in related future studies planned on similar topics. Shelf life ; Coating ; Quality (philosophy) ; Food science ; Materials science ; Chemistry ; Nanotechnology ; Physics Nanocomposite Films for Food Packaging ; Postharvest Quality and Shelf Life Management ; Phytochemicals and Antioxidant Activities
Authors: Ao Zhang | Y Liu | Chao Yu | Mengting Yu | Yang Xu | Bingning Gao | Chenyu Yang | Jianye Xia | Yu Zheng | Jia Song | M. R. Wang
Source: Fermentation (article, 2025-12-20)
Field: Chemistry — Analytical Chemistry

A Review on the Application of Near-Infrared Technology for Monitoring and Control of Food Fermentation Process The optimization and control of the food fermentation process, which are vital for consistent product quality, are often hindered by the limitations of conventional analytical methods. Conventional wet-chemistry methods for food fermentation process analysis are slow, expensive, and require significant reagents and skilled personnel. Near-infrared (NIR) spectroscopy is a powerful tool for non-destructive analysis of fermentation processes, with key advantages of speed, cost-effectiveness, minimal sample preparation, and reagent-free operation. This review provides an overview of the fundamental principles of NIR, the importance of chemometrics for building robust calibration models, and its application in the food fermentation process. Furthermore, this review also critically evaluates the challenges and opportunities of using NIR spectroscopy for fermentation process analysis and control. This review aims to provide novel insights into the application of NIR spectroscopy in the food fermentation industry, improving the process control and quality assurance for the intelligent transformation (from empirical control to AI-based control) of fermented foods. Fermentation ; Process (computing) ; Process control ; Fermentation in food processing ; Process analytical technology ; Chemometrics ; Food industry ; Bioprocess Spectroscopy and Chemometric Analyses ; Biopolymer Synthesis and Applications ; Viral Infectious Diseases and Gene Expression in Insects
Authors: Andres Pirolo
Source: Research Square (preprint, 2025-12-19)
Field: Materials Science — Materials Chemistry

Room-Temperature Micro-SMES via Acoustically Stabilized YHf2H24 Multilayer Stacks: A Solid-State Infinite Storage Solution Energy storage ; Dissipation ; Power (physics) ; Energy (signal processing) ; Stress (linguistics) ; Standby power ; Battery (electricity) ; Magnetic storage ; Phonon Hydrogen Storage and Materials ; Superconductivity in MgB2 and Alloys ; MXene and MAX Phase Materials
Authors: Boudjemaa Mehimmedetsi | Abdellah Draidi | Billel Smaani
Source: Indonesian Journal of Electrical Engineering and Computer Science (article, 2025-10-01)
Field: Materials Science — Materials Chemistry

Analysis of solid oxide fuel cell systems for off-grid energy production &lt;p&gt;This work presents a simulation study of a 50-kW solid oxide fuel cell (SOFC) power supply system that provides electricity to residential users. Indeed, many decentralized applications rely on renewable energy sources not connected to the primary power grid. Moreover, fuel cell modelling and simulation are critical for promoting renewable energy as they eliminate the need for physical prototypes, saving time and money. We have also developed a reliable model for simulating self-contained SOFC fuel cells. The elaborated model includes the kinetics of electrochemical processes and accounts for voltage losses in SOFCs. Our fuel cells produce the necessary electrical current to charge the device. Also, our system has fuel cells, a DC/DC converter, and an inverter with LCL filters. These components connect the fuel cell system to other power electronics and the electrical load. Furthermore, a mathematical model of a dual inverter system describes its control method, including the proportional and integral parameters in the voltage and current loops has been derived. The proposed model and system could be helpful for a standalone load.&lt;/p&gt; Solid oxide fuel cell ; Renewable energy ; Inverter ; Electricity ; Electric potential energy ; Work (physics) ; Voltage ; Electric power system ; Electricity generation Advancements in Solid Oxide Fuel Cells
Authors: Junqi Yin | Marc Mauermann
Source:  (article, 2025-01-01)
Field: Materials Science — Biomaterials

Predictive fouling detection in dairy industry heat exchangers using sequence-to-sequence deep learning models Fouling in heat exchangers challenges heat transfer efficiency, making its predictive detection crucial for the dairy industry.Despite numerous sensors integrated into production facilities, valuable data relevant to fouling prediction often remains underutilized.This study evaluates three Sequence-to-Sequence deep learning models-Long Short-Term Memory (LSTM), Encoder-Decoder LSTM, and Convolutional Neural Network LSTM (CNN-LSTM) to predict sensor profiles several minutes into the future and to estimate fouling based on a dataset from a full-scale dairy heat exchanger.Sensor data such as inlet hot water temperature, outlet product pressure, and pump power were treated as indicator for fouling and analyzed to estimate it.Evaluation metrics include mean squared error and mean absolute scaled error.Of the models tested, CNN-LSTM showed the lowest prediction error 12.3 for estimating the outlet product pressure, offering potential for early fouling detection in industrial applications.These findings demonstrate the feasibility of deep learning for improving heat exchanger maintenance strategies. Fouling ; Sequence (biology) ; Heat exchanger ; Deep learning ; Computer science ; Artificial intelligence ; Dairy industry ; Process engineering ; Machine learning ; Engineering ; Chemistry ; Mechanical engineering Calcium Carbonate Crystallization and Inhibition
Authors: Onur Boyar
Source: Proceedings of the AAAI Conference on Artificial Intelligence (article, 2025-04-11)
Field: Materials Science — Materials Chemistry

De Novo Molecular and Crystal Design with Latent Space Bayesian Optimization This thesis explores Latent Space Bayesian Optimization (LSBO) for the generation and optimization of de novo molecules and crystal materials. Our goal is to develop practical, sample-efficient de novo discovery algorithms with a focus on real-world applicability, and our results so far demonstrate significant progress toward practical implementation. Bayesian optimization ; Bayesian probability ; Space (punctuation) ; Crystal (programming language) ; Computer science ; Computational biology ; Artificial intelligence ; Biology ; Programming language Machine Learning in Materials Science
Authors: Huaisong Yong | Holger Merlitz
Source: Langmuir (article, 2025-07-22)
Field: Chemistry — Physical and Theoretical Chemistry

An Analytical Understanding of Reentrant Condensation of a Polyelectrolyte in the Presence of an Oppositely Charged Surfactant We explore the phase-transition mechanism of the reentrant condensation of a polyelectrolyte in the presence of an oppositely charged surfactant, which is of fundamental importance to the understanding of liquid-liquid phase separation (LLPS) in soft materials and biological systems. We focus on the adsorption and attraction effects of surfactants near/on polymer chains and ignore their own nonessential mixing effects if surfactant molecules are far away from polymer chains. This novel approach allows us to construct a simple mean-field equilibrium theory with closed-form analytical solutions, which can rationalize the essential features of the emergent "egg shape"-like phase diagram. The theory addresses that a strong electrostatic adsorption between the ionic monomers and surfactant ions is critical to understand the peculiar phenomenon that both the collapse and re-entry transitions of polyelectrolytes can occur when the concentration of the surfactant is lower than its bulk critical micelle concentration (CMC). Our theory also indicates that a minimum coupling energy for the nonlinear hydrophobic-aggregation effect of the adsorbed surfactant is essential for a phase transition to occur, which explains why polyelectrolytes show such a phase transition only if the surfactant chain length is beyond a minimum value. This work provides insight into the understanding of liquid-liquid phase separation in biological systems if proteins and/or peptides bound to DNAs and/or RNAs play an important role. Polyelectrolyte ; Reentrancy ; Pulmonary surfactant ; Condensation ; Chemistry ; Polymer science ; Polymer chemistry ; Chemical physics ; Chemical engineering ; Materials science ; Thermodynamics ; Physics ; Organic chemistry ; Condensed matter physics ; Polymer ; Engineering Electrostatics and Colloid Interactions ; Surfactants and Colloidal Systems ; Electrowetting and Microfluidic Technologies
Authors: Dr DEVIDUTTA MAURYA
Source: JOURNAL OF ADVANCE AND FUTURE RESEARCH (article, 2025-12-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Computational Study Of Molecular and Electronic Structure Geometrical Optimization and IR Spectra Of The Molecule 385D The present work reports a comprehensive computational investigation of the molecular and electronic structure of the molecule 385D using density functional theory (DFT). Geometry optimization was carried out to obtain the most stable conformation of the molecule, and detailed structural parameters such as bond lengths, bond angles, and dihedral angles were analyzed to understand its three-dimensional arrangement and conformational stability. The optimized geometry confirms the absence of imaginary frequencies, indicating that the structure corresponds to a true minimum on the potential energy surface. Electronic properties were evaluated through frontier molecular orbital (HOMO–LUMO) analysis to gain insight into charge distribution, chemical reactivity, and electronic transitions within the molecule. The calculated HOMO–LUMO energy gap provides valuable information regarding the stability and possible biological or electronic activity of 385D.Vibrational frequency calculations were performed to simulate the infrared (IR) spectrum of the molecule. The characteristic vibrational modes corresponding to functional groups such as C–H, C=O, N–H, S=O, and C–F were assigned and analyzed. The simulated IR spectrum shows good consistency with expected theoretical frequencies, supporting the optimized structural model.Overall, this computational study offers a detailed understanding of the molecular geometry, electronic structure, and vibrational behavior of molecule 385D, which may be useful for interpreting experimental data and for further theoretical and applied studies involving this compound. Dihedral angle ; Electronic structure ; Molecular geometry ; Density functional theory ; Molecule ; Bond length ; Molecular orbital ; Molecular vibration ; Energy minimization Nonlinear Optical Materials Research ; Cancer Research and Treatment ; Advanced Physical and Chemical Molecular Interactions
Authors: Jiaoyan Dai | Guoqiang Liu
Source: Metals (article, 2025-06-30)
Field: Materials Science — Materials Chemistry

The Mechanism of High Electrical Conductivity in Copper–Chromium Alloy Cr alloyed Cu exhibits puzzlingly high electrical conductivity compared with other 3d elements alloying. Here, we present a theoretical understanding based on standard electronic band structure calculations. The influence of local spin-polarization on electrical conductivity was first investigated. It is found that the non-magnetic calculation produces a high density of states peak at the Fermi level, and then it fails to explain the high electrical conductivity of Cu-Cr alloy. When spin polarization is taken into account, the density of states is significantly reduced, and the results are in good agreement with experimental measurements. Meanwhile, the calculation results can explain the increase in strength and also lead to some interesting deductions. Finally, a computational program is proposed to select a high electrical conductivity Cu alloy based on a simple calculation model. Electrical resistivity and conductivity ; Alloy ; Copper ; Conductivity ; Materials science ; Condensed matter physics ; Fermi level ; Polarization (electrochemistry) ; Chromium ; Spin polarization ; Electronic structure ; Density of states ; Metallurgy ; Chemistry ; Electron ; Physics ; Physical chemistry Microstructure and mechanical properties ; Surface and Thin Film Phenomena ; Semiconductor materials and interfaces
Authors: Yunji Pei | Zhongyao Liang | Xuexue Chen | Xinran Wang | Wenlin Zhou | Wen Lu | Li Jiang
Source: Processes (article, 2025-10-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Bio-Solid Fuel from Wheat Straw via Microwave Torrefaction: Process Optimization and Environmental Assessment There is a need to address the limitations of wheat straw (WS) as a raw biomass fuel, promote its valorisation into a high-quality renewable solid fuel, and enable this fuel to replace fossil fuels in applications such as power plants and industrial boilers. This study focused on optimizing microwave torrefaction parameters to enhance key fuel properties. Optimal conditions were determined via the Box–Behnken design (BBD) within Response Surface Methodology (RSM) as 422.32 W of microwave power, 14.95 min of irradiation time, and a 15 g microwave absorber, resulting in a 69.12% mass yield, an 18.44 MJ/kg higher heating value (HHV) surpassing lignite at 16.76 MJ/kg, and a 25.50% Energy-Mass Co-efficiency Index (EMCI). Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis/derivative thermogravimetric analysis (TG/DTG) were conducted to gain insights about chemical composition and thermal stability variations due to torrefaction. LCA showed that electricity produced from 1 ton of torrefied WS reduces CO2 emissions by 259.26 kg CO2eq compared to electricity generated from bituminous coal. From an economic perspective, the usage of torrefied WS for power generation lead to a net profit of CNY 435.19/ton. This scalable technology, by valorising agricultural waste for fuel production, delivers dual environmental and economic benefits, laying the groundwork for industrial deployment. Valorisation ; Torrefaction ; Thermogravimetric analysis ; Fossil fuel ; Renewable energy ; Raw material ; Biomass (ecology) ; Electricity generation ; Life-cycle assessment Electromagnetic wave absorption materials ; Thermochemical Biomass Conversion Processes ; Flame retardant materials and properties
Authors: M. Nazari | Farhad Khoeini | M. Amir Bazrafshan | B. Szafran
Source: Journal of Applied Physics (article, 2025-12-03)
Field: Materials Science — Materials Chemistry

Spin-selective thermoelectric properties and field-induced band engineering in bilayer zigzag silicene nanoribbons Silicene, a two-dimensional allotrope of silicon, has attracted significant attention due to its unique electronic properties and potential for diverse applications. Unlike its bulk counterpart, silicene exhibits remarkable quantum phenomena due to its low-dimensional structure and strong spin–orbit coupling. In this study, we investigate the spin and charge transport, as well as the thermoelectric properties, of zigzag bilayer silicene nanoribbons in nonmagnetic (NM), ferromagnetic (FM), and antiferromagnetic (AFM) configurations under perpendicular electric fields. The analysis is carried out using tight-binding and non-equilibrium Green’s function methods. Numerical simulations reveal that half-metallic behavior can be induced in the FM and AFM configurations by tuning the electric field. We demonstrate spin-resolved thermoelectric figures of merit reaching ZeTS = 1.85 (FM) and 1.2 (AFM), induced by electric-field-tuned half-metallicity and spin-dependent bandgaps. These enhancements are attributed to the electric-field-induced bandgap modulation and improved transport coefficients. The unique properties of silicene make it a promising candidate for applications in next-generation spintronic devices, such as spin transistors and magnetic memory storage technologies. Silicene ; Thermoelectric effect ; Spintronics ; Zigzag ; Ferromagnetism ; Antiferromagnetism ; Band gap ; Bilayer Graphene research and applications ; Topological Materials and Phenomena ; 2D Materials and Applications
Authors: Tatsuya Yamamoto | Tomoki Sugiura | Tomoyuki Hiroyasu | Satoru Hiwa
Source: Network Neuroscience (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Task-guided generative adversarial networks for synthesizing and augmenting structural connectivity matrices for connectivity-based prediction Recent machine learning techniques have improved connectome-based predictions by modeling complex dependencies between brain connectivity and cognitive traits. However, they typically require large datasets that are costly and time-consuming to collect. To address this, we propose Task-guided generative adversarial network (GAN) II, a novel data augmentation method that uses GANs to expand sample sizes in connectome-based prediction tasks. Our method incorporates a task-guided branch within the Wasserstein GAN framework, specifically designed to synthesize structural connectivity matrices and improve prediction accuracy by capturing task-relevant features. We evaluated Task-guided GAN II on the prediction of fluid intelligence using the NIMH Health Research Volunteer Dataset. Results showed that data augmentation improved prediction accuracy. To further assess whether augmentation can substitute for increasing actual collected sample sizes, we conducted additional validation using the Human Connectome Project WU-Minn S1200 dataset. Task-guided GAN II improved prediction performance with limited real data, with gains of up to twofold augmentation observed. However, excessive augmentation did not result in further improvements, suggesting that augmentation complements, but does not fully replace, real data augmentation. These results suggest that Task-guided GAN II is a promising tool for harnessing small datasets in human connectomics research, improving predictive modeling where large-scale data collection is impractical. Generative grammar ; Adversarial system ; Task (project management) ; Computer science ; Artificial intelligence ; Engineering Machine Learning in Materials Science
Authors: Pei-Tzu Chen | J. Andrew Yeh | Jui–Hsia Weng | Kuen‐Phon Wu
Source:  (preprint, 2025-03-11)
Field: Chemistry — Inorganic Chemistry

Elucidating the Mechanism Underlying UBA7•UBE2L6 Disulfide Complex Formation Abstract We elucidate cryo-EM structure and formation of the ubiquitin-associated bovine UBA7•UBE2L6 disulfide complex, shedding light on a highly specific and evolutionarily conserved mechanism governing ISG15 conjugation, a pivotal process in the immune response. UBA7 displays a unique capacity to recognize UBE2L6, distinct from this latter’s homolog UBE2L3, highlighting the intricacies of cellular regulation. Inter-species interactions of the resulting complex further underscore its significance. We characterize three crucial factors that influence UBA7•UBE2L6 disulfide complex formation: (1) strong binding affinity and specificity; (2) conformational differences in the catalytic cysteine capping loop (CCL); and (3) increased thiolate/thiol ratios at catalytic cysteines. Modification of any of these factors profoundly impacts complex activation and the ISG15 transfer cascade. This redox-sensitive complex implies a link between oxidative stress and regulation of the immune response, highlighting a potential therapeutic target for modulating immune reactions arising from infections and inflammatory conditions. Mechanism (biology) ; Disulfide bond ; Chemistry ; Biophysics ; Biochemistry ; Biology ; Philosophy ; Epistemology Inorganic Chemistry and Materials ; Boron Compounds in Chemistry ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Kristoffer Vorm | Chrysoula Stathaki | Pedro Leonidas Oseliero Filho | Hery Mitsutake | Tereza S. Martins | Nikolay Kardjilov | Luis C. Cides-da-Silva | Márcia Carvalho de Abreu Fantini | François Lauze | Heloisa N. Bordallo
Source: Microporous and Mesoporous Materials (article, 2025-11-16)
Field: Materials Science — Materials Chemistry

Protein distribution in SBA-15: Insights from thermal decomposition and advanced imaging Ordered Mesoporous Silica (OMS) materials, particularly SBA-15, are widely used in drug delivery due to their structural stability and high porosity. However, the role of macroporosity (pores >50 nm) in influencing protein adsorption and spatial distribution remains poorly understood. In this study, three SBA-15 variants were produced by changing the synthesis temperature and stirring speed, and combined evolved gas analysis (EGA), Raman imaging, and X-ray micro-computed tomography (micro-CT) were used to investigate the adsorption and distribution of lysozyme, a model protein, in the samples. While thermal analysis showed comparable overall protein uptake across all variants, Raman imaging and micro-CT demonstrated that SBA-15 with the larger macropore distribution exhibited a less uniform lysozyme distribution. These observations suggest that macroporosity affects protein localization within SBA-15, which is critical for optimizing antigen delivery and release. Our results advance understanding of how OMS morphology impacts biomolecule encapsulation, offering insights valuable for the design of advanced drug delivery systems and oral vaccines. • Protein distribution across morphologies is key to controlling drug delivery efficiency. • Lysozyme fits mesopores; adsorption remained stable despite changes in SBA-15 synthesis. • Raman images reveal lysozyme’s local environment in SBA‑15 morphologies. • Different SBA-15 morphologies influence the distribution of proteins within the mesoporous material. • Micro‑CT segmentation successfully identified calcination inclusions. Drug delivery ; Biomolecule ; Raman spectroscopy ; Mesoporous material ; Adsorption ; Macropore ; Calcination ; Protein adsorption Mesoporous Materials and Catalysis ; Advanced Drug Delivery Systems ; Aerogels and thermal insulation