jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tina Fathalipour Ardabili | Banchamlak Bemerw Kassaun | Hossein Roohollahi | Hossein Kazemian
Source: Materials & Design (article, 2026-01-18)
Field: Materials Science — Biomaterials

Poly (butylene adipate‐co‐terephthalate) (PBAT) and functional blends: Applications, performance tuning, and emerging directions Poly (butylene adipate‐co‐terephthalate) (PBAT) is a flexible, industrially compostable polyester compatible with conventional processing, yet its broader deployment remains constrained by cost, limited barrier/mechanical performance, and uncertain degradation outside industrial composting. While most reviews emphasize synthesis, properties, and conventional blends, significantly less attention has focused on functional PBAT systems (antimicrobial, sensing, self-healing), biomedical uses, natural-fiber reinforcement, additive manufacturing, and real-world environmental persistence. Adopting a structure-processing-property (SPP) perspective, this review synthesizes PBAT fundamentals, scalable processing routes, commercial uptake, and state-of-the-art blends and composites for packaging, agricultural films, and biomedical applications. Evidence-based pathways toward enhanced functionality and scalability are identified, including compatibilizer-assisted multifunctional blends, AI-guided blown-film optimization, and emerging chemical and enzymatic recycling strategies.To strengthen environmental credibility, a unified validation framework distinguishing certified industrial compostability from marine and ambient biodegradation (ASTM D6691/ D7991; ISO standards) is discussed. Finally, prioritized, testable milestones (e.g., ≥80 % elongation retention with ≥ 3-log antibacterial efficacy) are proposed to guide translation from laboratory innovation to industrial deployment. This review links multi-scale structure, processing control, and application-specific performance targets to support the development of functional, scalable, and environmentally credible PBAT technologies. Scalability ; Software deployment ; Biodegradation ; Degradation (telecommunications) ; Polyester ; Certification biodegradable polymer synthesis and properties ; Polymer crystallization and properties ; Microplastics and Plastic Pollution
Authors: Monika Babasaheb Ghodke | Kailas Ganpati Rathod
Source: Journal of international research in medical and pharmaceutical sciences (article, 2026-01-16)
Field: Materials Science — Biomaterials

Navigating the Future of Novel Drug Delivery Systems: Market Dynamics, Technological Innovations, and Translational Challenges Novel Drug Delivery Systems (NDDS) have emerged as pivotal technologies in modern therapeutics, addressing limitations of conventional drug administration such as poor bioavailability, non-specific targeting, and adverse side effects. The growing global market and rapid technological advancements underscore the need for a comprehensive understanding of NDDS development, market dynamics, and translational challenges. This review systematically analyses recent progress in NDDS, focusing on key nanocarriers including liposomes, cubosomes, and solid lipid nanoparticles, alongside emerging multifunctional and stimuli-responsive systems. A thorough literature survey was conducted using databases such as PubMed, Scopus, and Web of Science, complemented by market reports and regulatory guidelines. Emphasis was placed on formulation techniques, material innovations, integration with personalised medicine, and the role of artificial intelligence in optimising design and clinical translation. Results highlight significant advances in scalable manufacturing, green synthesis, and multifunctional hybrid platforms that enhance targeting and controlled release. However, challenges persist in regulatory approval, long-term safety evaluation, and market adoption, particularly due to complex manufacturing and intellectual property landscapes. The integration of digital health tools and real-time monitoring presents promising avenues to improve patient compliance and therapeutic outcomes. In conclusion, NDDS represent a transformative shift toward precision medicine, but their successful clinical translation requires multidisciplinary collaboration, regulatory alignment, and sustainable manufacturing practices. Addressing current research gaps and leveraging emerging technologies will be critical to fully realise the therapeutic and commercial potential of NDDS, ultimately improving patient care worldwide. Translational research ; Multidisciplinary approach ; Emerging technologies ; Transformative learning ; Grand Challenges ; Nanocarriers ; Paradigm shift ; Sustainability ; Biomedical technology Nanoparticle-Based Drug Delivery ; Inhalation and Respiratory Drug Delivery ; Advanced Drug Delivery Systems
Authors: Atul Kumar Srivastava | Pooja Mishra | Simpal Kumari | Nisar Uddin | Songshu Chen | Yudan Zhao | Xin Xie
Source: Journal of Nanobiotechnology (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Post translational modifications as biomarkers of soil microbe responses to nano-pesticides Nano-pesticides represent a significant technology advancement in modern agricultural, offering improved target specificity and reduced chemical load. However, their potential to induce subtle, sub-lethal disturbance in soil microbial function remains poorly resolved and is not adequately capture by conventional indicators such as microbial diversity, abundance, or bulk enzymatic activity. The central novelty of this review lies in proposing post-translational modifications (PTMs) as functional, early-warning biomarkers for nano-pesticide induced microbial stress, providing a molecular resolution that bridges exposure and ecological outcome. This review critically examines the current evidence on nano-pesticides-microbiome interaction and PTM-centric framework to interpret microbial responses at the protein regulation level. We highlight phosphorylation, acetylation, and ubiquitination regulate microbial stress responses, modulating detoxification enzymes, efflux pumps, and cellular signalling pathways under nanoparticle-induced stress. Unlike prior reviews that emphasize toxicity endpoints or gene-level responses, this work integrates metaproteomic evidence demonstrating PTM enrichment within stress-responsive functional protein groups across real environmental datasets, underscoring their relevance as conserved biomarkers of adaptive and maladaptive responses. By integrating metagenomics with metaproteomic and metabolomics, this review illustrates how PTM profiling enables mechanistic insight into microbial adaptation, functional impairment, and resilience under nano-pesticide pressure. Furthermore, we introduce a systems-level perspective that combines PTM data with computational modelling and AI-assisted bioinformatics to predict microbiome shifts and ecological risk, an approach not previously synthesized within the context of nano-pesticide assessment. Collectively, this review bridges nanomaterial design, microbial molecular regulation, and environmental risk evaluation, and proposes PTM-based assessment as a new paradigm for developing microbiome-safe, eco-compatible nano-pesticides and advancing molecular environmental monitoring strategies. Posttranslational modification ; Translational medicine ; Translational research ; Bacterial protein Nanoparticles: synthesis and applications ; Pesticide and Herbicide Environmental Studies ; Arsenic contamination and mitigation
Authors: Mihai Ganciu
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2026-02-08)
Field: Materials Science — Materials Chemistry

Oscillatory Caloric Cooling Below the Curie Temperature in Ordered Materials Solid-state cooling technologies based on caloric effects typically rely on quasi-static field variations near the Curie temperature, where entropy changes are maximized. Here we demonstrate a fundamentally different mechanism: an oscillatory caloric effect operating strictly below the Curie temperature, in the ordered phase of a ferroelectric material. By driving the polarization through controlled oscillations, we induce periodic entropy modulation that extracts heat from the material without requiring proximity to a phase transition. We further show that part of the oscillatory electrical energy can be recovered through a resonant transfer network, enabling cooling efficiencies reaching 20–25% of the Carnot limit without energy recovery and theoretically exceeding 50% with optimized resonant coupling. Finally, we generalize the mechanism to ferromagnetic materials below their magnetic Curie point, suggesting a broader class of oscillatory caloric phenomena in ordered systems. These results open a new direction for high-efficiency, environmentally friendly cooling technologies with applications in microelectronics, artificial intelligence, and solar-powered refrigeration. Curie temperature ; Carnot cycle ; Ferromagnetism ; Caloric theory ; Curie ; Magnetic refrigeration ; Magnetic field ; Entropy (arrow of time) Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advanced Thermoelectric Materials and Devices
Authors: Yannah J. U. Melle | Thanh Cong Nguyen | Jeffrey Lopez | Daniel Schwalbe-Koda
Source: Open MIND (preprint, 2026-02-24)
Field: Chemistry — Analytical Chemistry

Automatic Identification of Compounds in Molecular Mixtures from Liquid-Phase Infrared Spectra Interpreting spectroscopy data is a critical bottleneck in automating chemical research and industrial characterization. Particularly within infrared (IR) spectroscopy, identifying compounds in complex, liquid-phase chemical mixtures largely relies on expert knowledge, as variable peak assignment, broadening, and shifts hinder data-driven methods. Here, we show that an algorithmic approach can identify components in both simulated and experimental mixture spectra with high accuracy despite nonlinearities in liquid-phase IR data. The method is comprehensively benchmarked with a dataset of over 44,000 simulated liquid-phase IR spectra for mixtures and achieves up to 90% accuracy in identifying molecular components across a dataset of binary and ternary liquid mixtures. Our strategy is robust to perturbation of spectra, and its accuracy is capped by near-identical liquid-phase IR spectra that limit the resolution of chemical identification, imposing theoretical limits on achieving perfect accuracy in structure identification. Finally, we apply the method to automatically interpret IR spectra in experimental settings, correctly identifying the components of nearly all samples within a blind study. This work provides tools and data to advance automated chemical laboratories through algorithmic interpretation of liquid-phase IR spectra of mixtures. Spectral line ; Infrared spectroscopy ; Ternary operation ; Bottleneck ; Binary number ; Resolution (logic) ; Identification (biology) ; Infrared Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Spectroscopy and Laser Applications
Authors: Mihai Ganciu
Source: Open MIND (article, 2026-02-08)
Field: Materials Science — Materials Chemistry

Oscillatory Caloric Cooling Below the Curie Temperature in Ordered Materials Solid-state cooling technologies based on caloric effects typically rely on quasi-static field variations near the Curie temperature, where entropy changes are maximized. Here we demonstrate a fundamentally different mechanism: an oscillatory caloric effect operating strictly below the Curie temperature, in the ordered phase of a ferroelectric material. By driving the polarization through controlled oscillations, we induce periodic entropy modulation that extracts heat from the material without requiring proximity to a phase transition. We further show that part of the oscillatory electrical energy can be recovered through a resonant transfer network, enabling cooling efficiencies reaching 20–25% of the Carnot limit without energy recovery and theoretically exceeding 50% with optimized resonant coupling. Finally, we generalize the mechanism to ferromagnetic materials below their magnetic Curie point, suggesting a broader class of oscillatory caloric phenomena in ordered systems. These results open a new direction for high-efficiency, environmentally friendly cooling technologies with applications in microelectronics, artificial intelligence, and solar-powered refrigeration. Curie temperature ; Carnot cycle ; Ferromagnetism ; Caloric theory ; Curie ; Magnetic refrigeration ; Magnetic field ; Entropy (arrow of time) Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advanced Thermoelectric Materials and Devices
Authors: Hongchul Shin | YUJIN PARK | Junbin Yeom | S. Na | Taeyoung Yoon
Source: Journal of Computational Design and Engineering (article, 2026-01-07)
Field: Materials Science — Biomaterials

Systematic evaluation of attention mechanisms in transformer models for De Novo UTS-driven silk protein sequence design Abstract Protein sequence generation has emerged as a central theme in computational biology, with silk proteins receiving attention due to their superior mechanical properties compared to synthetic materials. However, systematic evaluation of transformer architectures for silk protein sequence generation remains limited. In this study, we conducted a comparative analysis of five attention mechanisms in transformer architectures optimized for silk protein crystalline region generation, validated by steered molecular dynamics simulations. Among the tested mechanisms, convolutional attention demonstrated the best performance, achieving a correlation coefficient of 0.91 between target and simulated ultimate tensile strength values. Attention map analysis further revealed that convolutional attention effectively captured local sequence dependencies critical for β-sheet formation. These findings provide a foundation for data-driven design of protein-based materials with tunable mechanical properties across a broad range. Transformer ; SILK ; Sequence (biology) ; Ultimate tensile strength ; Protein design ; Pattern recognition (psychology) Silk-based biomaterials and applications ; Advanced Materials and Mechanics ; Diatoms and Algae Research
Authors: Yannah J. U. Melle | Thanh Cong Nguyen | Jeffrey Lopez | Daniel Schwalbe-Koda
Source: arXiv (Cornell University) (article, 2026-02-24)
Field: Chemistry — Analytical Chemistry

Automatic Identification of Compounds in Molecular Mixtures from Liquid-Phase Infrared Spectra Interpreting spectroscopy data is a critical bottleneck in automating chemical research and industrial characterization. Particularly within infrared (IR) spectroscopy, identifying compounds in complex, liquid-phase chemical mixtures largely relies on expert knowledge, as variable peak assignment, broadening, and shifts hinder data-driven methods. Here, we show that an algorithmic approach can identify components in both simulated and experimental mixture spectra with high accuracy despite nonlinearities in liquid-phase IR data. The method is comprehensively benchmarked with a dataset of over 44,000 simulated liquid-phase IR spectra for mixtures and achieves up to 90% accuracy in identifying molecular components across a dataset of binary and ternary liquid mixtures. Our strategy is robust to perturbation of spectra, and its accuracy is capped by near-identical liquid-phase IR spectra that limit the resolution of chemical identification, imposing theoretical limits on achieving perfect accuracy in structure identification. Finally, we apply the method to automatically interpret IR spectra in experimental settings, correctly identifying the components of nearly all samples within a blind study. This work provides tools and data to advance automated chemical laboratories through algorithmic interpretation of liquid-phase IR spectra of mixtures. Spectral line ; Infrared spectroscopy ; Ternary operation ; Bottleneck ; Binary number ; Resolution (logic) ; Identification (biology) ; Infrared Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Spectroscopy and Laser Applications
Authors: Po‐Sheng Chiu | Y. L. Huang | Fenglin Peng | Ying Geng | Shin‐Tson Wu
Source: Journal of the Society for Information Display (article, 2026-04-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Field‐Sequential‐Color Liquid Crystal Devices for AR and VR Displays ABSTRACT We demonstrate two types of field‐sequential‐color (FSC) liquid crystal devices for augmented reality (AR) and virtual reality (VR) displays, respectively. For AR, we employ a negative dielectric anisotropy liquid crystal mixture in a reflective vertical‐alignment (VA) liquid‐crystal‐on‐silicon (LCoS) and achieve an average 1.48 ms gray‐to‐gray (GTG) response at 35 °C, enabling a 676 Hz FSC field rate with low driving voltage. For VR, we report an optimized transmissive fringe‐field switching (FFS) liquid crystal display (LCD) using a low rotational viscosity ( γ 1 = 38 mPa·s at 20.7 °C) nematic mixture ZOC‐5322. With a two‐step overdrive/undershoot driving scheme, the FFS cell reaches an average 0.74 ms GTG response at 40 °C, supporting FSC operation to suppress image blur and color breakup. This approach simultaneously increases resolution density and optical efficiency by eliminating lossy color filters, helping meet 1‐arcminute visual acuity and low power consumption for next‐generation VR headsets. Overall, these two FSC microdisplays provide promising routes toward compact, high‐resolution‐density, and full‐color AI‐assisted AR glasses, and VR headsets with 60 pixels per degree, 100° field of view, and low power consumption. Liquid-crystal display ; Liquid crystal ; Pixel ; Augmented reality ; Liquid crystal on silicon ; Response time ; Virtual reality ; Power (physics) ; Power consumption Liquid Crystal Research Advancements ; Advanced Optical Imaging Technologies ; Electrowetting and Microfluidic Technologies
Authors: In-Ho Yoon
Source: Economic and Environmental Geology (article, 2026-02-27)
Field: Materials Science — Materials Chemistry

Research Trends in Environmental Remediation Technologies for Domestic and International Nuclear Facility Sites Site remediation of nuclear facilities represents the final stage of decommissioning and is crucial for both environmental safety and economic value creation.This study systematically analyzes radioactive contaminated soil remediation technologies and site remediation strategies.The regulatory framework including Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) methodology and Derived Concentration Guideline Level (DCGL) establishment procedures are examined, comparing unrestricted release and restricted use strategies.Remediation technologies are classified into physical, chemical leaching, and biological methods, each selectively applied based on soil characteristics and contaminating radionuclides.Cesium(Cs)-137 removal is particularly challenging due to its strong binding with clay minerals, prompting development of innovative technologies using cationic polymers and magnetic nanoparticles.International cases including Hanford (USA) and Gundremmingen (Germany) are analyzed alongside domestic cases such as Kori Unit 1. Emerging technologies including digital twin modeling, Artificial Intelligence (AI)based contamination prediction, Unmanned Aerial Vehicle (UAV) surveying, and modular remediation systems are presented.For upcoming domestic nuclear decommissioning projects, securing safe and economical remediation technologies is essential.Key future directions include waste volume reduction and transition to resource circulation models.The study emphasizes the importance of sitespecific technology selection through decision-support models, integrated treatment for complex contamination, and ecological function recovery assessment.Successful site remediation can transform decommissioned nuclear sites into renewable energy hubs or industrial complexes, contributing to regional economic development and social acceptance of nuclear energy. Nuclear decommissioning ; Environmental remediation ; Work (physics) ; Nuclear power Graphite, nuclear technology, radiation studies ; Radioactive contamination and transfer ; Radioactive element chemistry and processing
Authors: Yong Gan | Man Xie | Haiqiang Lian | Hui Wang | Feng Wang
Source: SHILAP Revista de lepidopterología (article, 2026-03-01)
Field: Materials Science — Materials Chemistry

Key Achievements and Future Prospects of China's Innovative Development in New Materials New materials serve as the material foundation for China's efforts to boost its strength in manufacturing development and achieve high-quality development. The level of their research, development, and industrialization is a crucial indicator of a country's socioeconomic progress, technological advancement, and defense capabilities. This study analyzes the significant achievements in the innovative development of new materials in China over the past decade since the implementation of the strategy of building China into a strong manufacturing nation. It reviews landmark achievements and proposes key directions for the development of the new materials sector in China by 2035, along with pathways to accelerate innovation-driven growth. The study concludes that China's new materials industry has continuously expanded in scale, enhanced its technological competitiveness, significantly improved its capacity for independent supply, strengthened its innovation capabilities, and accelerated industrial transformation and upgrading. The industry has transitioned from a phase of scale expansion "primarily focused on solving the problem of availability" to a high-quality development stage aimed at meeting major strategic needs of the country and enhancing international competitiveness. Looking ahead, there is an urgent need to align with the strategic demands of major application scenarios for material development. Priority should be given to developing materials for the next-generation information technology, new energy materials, materials for high-end manufacturing and major projects, as well as next-generation biomedical materials. Additionally, it is essential to accelerate the establishment of a new paradigm for new materials research and development based on artificial intelligence, thereby enhancing China's original innovation capability in new materials. Industrialisation ; China ; Scale (ratio) ; Key (lock) ; Strategic planning ; Phase (matter) ; Advanced manufacturing ; Socioeconomic development Machine Learning in Materials Science ; Research, Science, and Academia ; Big Data and Digital Economy