jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Walter A. Henne | Adil Iqbal
Source: OPUS - Open Portal to University Scholarship (Governors State University) (article, 2026-04-10)
Field: Chemistry — Physical and Theoretical Chemistry

Development of an AI-Coded Protein Quantitation Analyzer for Biochemistry Research and Instruction Colorimetric protein quantitation is a fundamental technique used in analytical, biochemistry and molecular biology labs across the globe. Although sophisticated and expensive software is available with advanced instruments, flexible computational tools for standard curve analysis and unknown concentration determination remain limited for academic research and educational settings, mostly relegated to spreadsheet and graphing programs like Excel. To address this gap, we developed a “Protein Quantitation Analyzer” application using AI-assisted coding (Claude, Anthropic), for both research-grade analysis and classroom instruction without the need for specialized software or hardware. The software, moreover, can run on virtually any operating system, including the tablets commonly used in laboratory environments. The application was built using natural-language prompts and is freely accessible as a web application through the Henne Lab at Governors State University, along with numerous other applications. The tool supports five widely used colorimetric assay types: Bradford (595 nm); Lowry (750 nm); BCA (562 nm); Biuret (540 nm); and A₂₈₀ (280 nm), as well as a custom wavelength option. Data entry is performed through an interactive interface with individually labeled wells, supporting flexible experimental designs including triplicates and mixed-plate layouts. Key features include automated blank subtraction, standard curve generation using linear or nonlinear regression, error bar display, percent coefficient of variation (% CV) reporting, and back-calculation of unknown protein concentrations. Absorbance is modeled according to the Beer-Lambert Law (A = εlc), and results can be exported in CSV format for analysis in other software packages. Customizable axis labels, plot titles, and color schemes are provided to support publication-ready figure generation. This protein quantitation tool has been successfully integrated into both undergraduate and graduate biochemistry laboratory courses (in addition to research to projects). Our report illustrates how AI-assisted software development can rapidly create open-access scientific tools for research laboratories worldwide. Biuret test ; Software ; Spectrum analyzer ; Bicinchoninic acid assay ; Bradford protein assay ; Standard curve ; Interface (matter) ; Plot (graphics) Various Chemistry Research Topics ; Genetics, Bioinformatics, and Biomedical Research ; Advanced Proteomics Techniques and Applications
Authors: Sören Arlt | Haonan Duan | Felix Li | Sang Michael Xie | Yuhuai Wu | Mario Krenn
Source: Nature Machine Intelligence (article, 2026-02-19)
Field: Materials Science — Materials Chemistry

Meta-designing quantum experiments with language models Abstract Artificial intelligence can solve complex scientific problems beyond human capabilities, but the resulting solutions offer little insight into the underlying physical principles. One prominent example is quantum physics, where computers can discover experiments for the generation of specific quantum states, but it is unclear how finding general design concepts can be automated. Here we address this challenge by training a transformer-based language model to create human-readable Python code that generates entire families of experiments. The model is trained on millions of synthetic examples of quantum states and their corresponding experimental blueprints, enabling it to infer general construction rules rather than isolated solutions. This strategy, which we call meta-design, enables scientists to gain a deeper understanding and to extrapolate to larger experiments without additional optimization. We demonstrate that the approach can rediscover known design principles and uncover previously unknown generalizations of important quantum states, such as those from condensed-matter physics. Beyond quantum optics, the methodology provides a blueprint for applying language models to interpretable, generalizable scientific discovery across disciplines such as materials science and engineering. Quantum ; Blueprint ; Language model ; Human language ; Python (programming language) ; Scientific discovery ; Quantization (signal processing) Machine Learning in Materials Science ; Quantum many-body systems ; Quantum Computing Algorithms and Architecture
Authors: Jiaxin Zhao | Xinxin Xiao | Shasha Wei | Q. Wang | Qiao Ding | Yuqin Lei | Hongchao Zhang
Source: Trends in Food Science & Technology (article, 2026-01-20)
Field: Materials Science — Biomaterials

Advances in light-responsive food packaging: Mechanisms, applications, and challenges Commercialization ; Active packaging ; Food packaging ; Quality (philosophy) ; Food safety ; Food industry ; Emerging technologies ; Food products Nanocomposite Films for Food Packaging ; Advanced Cellulose Research Studies ; Biopolymer Synthesis and Applications
Authors: dong zhang
Source: Zenodo (CERN European Organization for Nuclear Research) (preprint, 2026-01-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Discrete Electromagnetic Interaction Theory for Slit Experiments: Material Boundaries, Accumulation, and AI-Compatible Reasoning This work presents a discrete, interaction-centered reinterpretation of slit-based interference experiments, treating slit boundaries as finite atomic structures with active electromagnetic properties rather than as geometrical, interaction-free constraints. Interference phenomena in slit experiments are traditionally described using continuous wave superposition, with slit boundaries treated as geometrical and electromagnetically neutral. In this work, we present a discrete, interaction-centered framework in which slit boundaries are modeled as finite atomic structures with incomplete electromagnetic cancellation. Photons and electrons are treated as finite entities undergoing localized, time-dependent electromagnetic interactions during slit transit. Interference patterns are shown to arise as accumulated statistical distributions of exit directions produced by many discrete events, rather than as instantaneous self-interference of single particles. A complete step-by-step mathematical formulation is provided, compatible with finite reasoning and artificial intelligence modeling. The framework predicts material-dependent and surface-dependent interference effects and motivates experimental tests using asymmetric and material-specific slits. DIY experimental photographs are included as an appendix to illustrate practical realizations of electromagnetically active boundaries. This document combines all conceptual sections and all mathematical steps into a single, unified exposition. It presents a discrete, interaction-centered reinterpretation of slit-based interference experiments, integrating physical reasoning, logical structure, and explicit equations. Continuous wave superposition is replaced throughout by finite electromagnetic interactions between passers (photons or electrons) and electromagnetically active atomic boundaries. Superposition principle ; Interference (communication) ; Double-slit experiment ; Electromagnetic radiation ; Electromagnetism ; Electromagnetic field ; Reinterpretation ; Photon Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Electromagnetic Scattering and Analysis
Authors: Roberto Ribeiro Faria | Fernando Freitas Siqueira Silva | Odonírio Abrahão Júnior
Source: Orbital - The Electronic Journal of Chemistry (article, 2026-02-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Evaluating Norbornadiene/Quadricyclane for Solar Thermal Energy Storage: A Systematic Review Using Methodi Ordinatio This work presents a comprehensive systematic review of the potential of Norbornadiene/Quadricyclane (NBD/QC) as a promising molecular system for solar thermal energy storage (MOST). Utilizing the Methodi Ordinatio methodology, this study aims to identify, classify, and rank the most impactful research articles based on a weighted combination of their citation count, impact factor, and year of publication. A complete literature search was performed across the Scopus, ScienceDirect, and Web of Science databases using targeted keywords such as "Norbornadiene," "Quadricyclane," and "solar thermal energy storage." A complete literature search across Scopus, ScienceDirect, and Web of Science using targeted keywords initially identified 567 studies; after applying relevance criteria, 341 articles published between 2014 and 2024 were selected for detailed analysis. The saved studies were then ranked using the InOrdinatio index, ensuring a data-driven prioritization of the most relevant contributions to the field. The analysis highlights recent technological advancements in NBD/QC-based solar energy systems, focusing on photoconversion efficiencies exceeding 90%, energy densities reaching up to 966 kJ/kg, improvements in isomerization kinetics, and enhanced thermodynamic stability of their metastable states. This systematic review not only contributes to the growing body of knowledge on molecular solar thermal systems but also offers strategic reflections for advancing sustainable and efficient solar energy technologies. Solar energy ; Work (physics) ; Web of science ; Energy (signal processing) ; Relevance (law) ; Thermal energy ; Energy landscape Magnetism in coordination complexes ; Thermal Expansion and Ionic Conductivity ; Organic Electronics and Photovoltaics
Authors: Robert Otieno | Edward V. Odhong | Alex Munyasia Muumbo
Source: Next Materials (article, 2026-03-17)
Field: Materials Science — Biomaterials

Systematic review of wettability enhancement, interface engineering and fabrication of magnesium oxide-coated graphene nanoplatelets in AZ91 matrix composites The future calls for smart, sustainable, high‑performance, biodegradable materials that integrate seamlessly into biomedical and engineering applications. Magnesium oxide (MgO)-coated graphene nanoplatelet (GNP) reinforced AZ91 matrix composites have emerged as a promising candidate. However, persistent challenges of poor wettability and unstable interfacial bonding hinder their potential. These shortcomings restrict efficient load transfer and uniform dispersion. This systematic review of transformative, cutting-edge research provides a consolidated foundation for future experimental and computational breakthroughs that unlocks new horizons in biomedical and engineering applications. It uniquely synthesizes advances in wettability enhancement, interface engineering, and fabrication approaches, identifying critical challenges and charting pathways for sustainable performance. Methodological robustness was ensured using validation technique that relied on multiple databases of Scopus and Web of Science. Strong thematic consistency across databases was found through comparative analysis of keywords, sources, and authors. Structured literature search and eligibility evaluation was done using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Peer-reviewed articles of 106 articles of 388 authors in the period of 2010–2025 were analysed and organized into four refined thematic clusters: (1) wettability enhancement of MgO-coated GNPs, (2) interface engineering, (3) fabrication and dispersion routes, and (4) biomedical applications. The evidence highlights their unique ability to enhance wettability, suppress detrimental interfacial reactions, and achieve strength–ductility synergy through semi‑coherent interfaces. Looking ahead, this review identifies new frontiers in adaptive interfaces, real‑time diagnostics, AI‑guided optimization, and multifunctional surface engineering, providing a roadmap for scalable and sustainable design of next‑generation MgO‑coated GNP reinforced AZ91 composites. • Profound systematic review consolidating advances in engineering of MgO-coated GNP/AZ91 composites. • Confirms that MgO coatings enable semi-coherent interfaces that achieve the rare strength-ductility synergy. • Provides consolidated foundation for future breakthroughs in new generation reinforced MgO@GNP/AZ91 composites. • Uniquely synthesizes advances in MgO@GNP/AZ91 wettability enhancement, interface engineering, and fabrication. • Identifies new frontiers in adaptive interfaces, AI-guided optimization and multifunctional surface engineering. Wetting ; Fabrication ; Graphene ; Interface (matter) ; Systematic review ; Scalability ; Robustness (evolution) Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Magnesium Oxide Properties and Applications
Authors: Yasmine S. Al-Hamdani | Dario Alfè | Andrea Zen
Source: arXiv (Cornell University) (preprint, 2026-04-08)
Field: Materials Science — Materials Chemistry

Towards viable H$_2$ storage in Ca decorated low-dimensional materials with insights from reference quantum Monte Carlo Hydrogen technology is set to be a key energy alternative for mitigating pollution and reducing CO$_2$ emissions. However, the current storage mechanism of hydrogen molecules in carbon fibre tanks detracts from the fuel economy of hydrogen in mobile applications, necessitating the development of alternative storage mechanisms. Adsorbing hydrogen in its molecular form (H$_2$) at typical operating conditions of proton exchange membranes can potentially meet storage requirements. However, H$_2$ is the smallest molecule with only two electrons and therefore it has very limited propensity to physisorb in a material within the binding energy window of $-0.2$ to $-0.4$ eV that is suitable for storage. Calcium atom decorators on graphene have previously shown promise for tunable H$_2$ binding, but the system is thermodynamically unstable toward the formation of calcium hydride. Moreover, the absolute adsorption of H$_2$ is challenging to predict accurately and is typically overestimated with van der Waals inclusive density functional approximations. In this work, we perform state-of-the-art fixed-node diffusion Monte Carlo alongside a selection of density functional approximations for two strategies of anchoring Ca: (i) Ca on boron doped graphene and (ii) Ca inside carbon nanotubes. We predict reliable Ca and H$_2$ binding energies, and establish that Ca is anchored inside carbon nanotubes and on boron doped graphene, while boosting the H$_2$ adsorption energy. Importantly, the H$_2$ adsorption energy is found to be improved by the anchoring strategies, with the energy inside a Ca decorated carbon nanotube reaching the viable storage window. The reference DMC binding energies provide much-needed benchmarks for developing data-driven methods and guiding experiment in the systematic design of hydrogen storage materials. Graphene ; Carbon nanotube ; Hydrogen storage ; van der Waals force ; Adsorption ; Hydrogen ; Density functional theory ; Binding energy ; Monte Carlo method Hydrogen Storage and Materials ; Advanced Physical and Chemical Molecular Interactions ; Chemical and Physical Properties of Materials
Authors: Aishwarya Nanasaheb Babar, Amruta Shashikant Madane, Rutuja Rajaram Katare, Mujawar suhana salim*, Dr. Rahul ishwara jadhav
Source: Open MIND (article, 2026-03-02)
Field: Materials Science — Biomaterials

RECENT ADVANCES IN TARGETED DRUG DELIVERY SYSTEMS FOR CANCER THERAPY: FORMULATION STRATEGIES, PHARMACOLOGICAL MECHANISMS AND CLINICAL APPLICATIONS Cancer continues to represent a major global health burden, necessitating the development of more precise and effective therapeutic strategies. Conventional chemotherapy, although widely used, is associated with significant limitations including systemic toxicity, poor selectivity, unfavorable pharmacokinetics, and the emergence of multidrug resistance. Targeted drug delivery systems (TDDS) have emerged as a transformative approach to address these shortcomings by enhancing tumor-specific drug accumulation while minimizing off-target effects. This review comprehensively discusses recent advances in targeted drug delivery systems for cancer therapy, focusing on formulation strategies, pharmacological mechanisms, and clinical applications. Various nanocarrier platforms—including lipid-based systems, polymeric nanoparticles, inorganic nanomaterials, and biomimetic carriers—are critically analyzed in terms of design principles, drug loading capacity, surface functionalization, and targeting efficiency. Mechanistic insights into cellular uptake pathways, intracellular trafficking, resistance modulation, and tumor microenvironment responsiveness are elaborated to highlight their contribution to improved therapeutic outcomes. Clinically approved targeted formulations such as liposomal chemotherapeutics, albumin-bound nanoparticles, and antibody–drug conjugates demonstrate the translational potential of nanomedicine in oncology. Despite these advancements, challenges including tumor heterogeneity, variability of the enhanced permeability and retention effect in humans, immunogenicity, large-scale manufacturing constraints, and regulatory complexities remain significant barriers. Future perspectives emphasize personalized nanomedicine, artificial intelligence-assisted nanoparticle design, combination therapeutic approaches, and theranostic systems integrating diagnosis and therapy. Continued interdisciplinary innovation and translational research are essential to optimize targeted drug delivery platforms and advance precision oncology. KEYWORDS Targeted drug delivery systems; Cancer therapy; Nanomedicine; Liposomes; Polymeric nanoparticles; Antibody–drug conjugates; Tumor microenvironment; Enhanced permeability and retention effect; Stimuli-responsive systems; Personalized nanomedicine Nanocarriers ; Nanomedicine ; Drug delivery ; Targeted drug delivery ; Cancer ; Drug ; Targeted therapy ; Cancer therapy Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Cancer Research and Treatment
Authors: Santosh Kumar | Shivam Rathaur | Debalina Maity | Parag Varshney | Jiaur R. Gayen
Source: Nanomedicine (article, 2026-03-03)
Field: Materials Science — Biomaterials

Nanotechnology based targeted drug delivery systems for breast cancer: challenges, recent advancement and future perspectives Globally, breast cancer remains a leading causes of cancer-related mortality among women, emphasizing the need for more effective therapies. Nanotechnology-based drug delivery systems have emerged as promising tools for reducing systemic toxicity while enhancing the precision and efficacy of treatments. By engineering nanoparticles to selectively target tumor cells, these systems increase drug accumulation at the tumor site and minimize harm to healthy tissues. This review focuses on the development of nanocarrier systems such as liposomes, polymeric nanoparticles, dendrimers, micelles, metallic nanoparticles, black phosphorus, and protein-based nanoparticles for the targeted delivery of chemotherapeutic agents in breast cancer. Both passive and active targeting mechanisms were explored, including the enhanced permeability and retention (EPR) effect, tumor specific biomarkers to achieve stimuli-responsive drug release. Future directions in research aim to further optimize these nanocarriers to enhance therapeutic efficacy while minimizing toxicity. The integration of personalized medicine with smart nanocarriers, AI-assisted delivery systems, diagnostic tools, and CRISPR/Cas9 gene editing holds great promise for more precise and individualized breast cancer therapies. Despite significant progress, challenges such as regulatory hurdles, tumor heterogeneity, multidrug resistance, issues related to nanoparticle biocompatibility continue to impede clinical translation. This work also addresses these barriers and implementation of nanomedicine in clinical oncology. Nanocarriers ; Nanomedicine ; Drug delivery ; Breast cancer ; Targeted drug delivery ; Personalized medicine ; Drug Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Cancer Research and Treatment
Authors: Omaima Bourzgui | A. El Harrak | El Houcine Lahrar | Othman El Kssiri | I. Nadi | Abdessamad Faik
Source: Journal of Power Sources (article, 2026-02-06)
Field: Materials Science — Materials Chemistry

Toward scalable hydrogen storage in mobility systems: An integrated review of metal hydrides, multiscale modeling, and sustainability assessment Software deployment ; Scalability ; Hydrogen storage ; Life-cycle assessment ; Hydride ; Sustainability ; Public records ; Multiscale modeling ; System integration Hydrogen Storage and Materials ; Hybrid Renewable Energy Systems ; Nuclear Materials and Properties
Authors: Aishwarya Nanasaheb Babar, Amruta Shashikant Madane, Rutuja Rajaram Katare, Mujawar suhana salim*, Dr. Rahul ishwara jadhav
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2026-03-02)
Field: Materials Science — Biomaterials

RECENT ADVANCES IN TARGETED DRUG DELIVERY SYSTEMS FOR CANCER THERAPY: FORMULATION STRATEGIES, PHARMACOLOGICAL MECHANISMS AND CLINICAL APPLICATIONS Cancer continues to represent a major global health burden, necessitating the development of more precise and effective therapeutic strategies. Conventional chemotherapy, although widely used, is associated with significant limitations including systemic toxicity, poor selectivity, unfavorable pharmacokinetics, and the emergence of multidrug resistance. Targeted drug delivery systems (TDDS) have emerged as a transformative approach to address these shortcomings by enhancing tumor-specific drug accumulation while minimizing off-target effects. This review comprehensively discusses recent advances in targeted drug delivery systems for cancer therapy, focusing on formulation strategies, pharmacological mechanisms, and clinical applications. Various nanocarrier platforms—including lipid-based systems, polymeric nanoparticles, inorganic nanomaterials, and biomimetic carriers—are critically analyzed in terms of design principles, drug loading capacity, surface functionalization, and targeting efficiency. Mechanistic insights into cellular uptake pathways, intracellular trafficking, resistance modulation, and tumor microenvironment responsiveness are elaborated to highlight their contribution to improved therapeutic outcomes. Clinically approved targeted formulations such as liposomal chemotherapeutics, albumin-bound nanoparticles, and antibody–drug conjugates demonstrate the translational potential of nanomedicine in oncology. Despite these advancements, challenges including tumor heterogeneity, variability of the enhanced permeability and retention effect in humans, immunogenicity, large-scale manufacturing constraints, and regulatory complexities remain significant barriers. Future perspectives emphasize personalized nanomedicine, artificial intelligence-assisted nanoparticle design, combination therapeutic approaches, and theranostic systems integrating diagnosis and therapy. Continued interdisciplinary innovation and translational research are essential to optimize targeted drug delivery platforms and advance precision oncology. KEYWORDS Targeted drug delivery systems; Cancer therapy; Nanomedicine; Liposomes; Polymeric nanoparticles; Antibody–drug conjugates; Tumor microenvironment; Enhanced permeability and retention effect; Stimuli-responsive systems; Personalized nanomedicine Nanocarriers ; Nanomedicine ; Drug delivery ; Targeted drug delivery ; Cancer ; Drug ; Targeted therapy ; Cancer therapy Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Cancer Research and Treatment