jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhiguang Jia | Allen Chen | Shanlong Li | S. Thayumanavan
Source: Biophysical Journal (article, 2025-11-14)
Field: Materials Science — Biomaterials

Stepwise disassembly of supramolecular structures triggered by specific protein binding Supramolecular assemblies that can spontaneously disassemble in response to specific protein binding provide a powerful platform for sensing and targeted delivery. This concept has been previously demonstrated using a peptide-based amphiphilic polymer (P1) that consists of both hydrophobic M1 and hydrophilic M2 and M3 side chains and presents a specific ligand for protein bovine carbonic anhydrase II (bCA-II). To further understand the molecular forces and mechanism of the assembly and disassembly of P1, we developed a coarse-grained modeling framework for direct simulation of the dynamic polymer-unimer equilibrium of amphiphilic peptide nanoassembly. The results show that P1 unimers initially self-assemble into small micelles, which are capable of encapsulating hydrophobic cargos such as the dye molecule DiI. The micelles subsequently aggregate into larger multicore nanostructures. Notably, the micelle architecture persists within the larger aggregates, with the hydrophobic M1 side chains forming distinct cores. The simulations further show that introduction and binding of bCA-II to the M3 side chains, which contain the specific ligand, lead to a disassembly process. Our simulations revealed that bCA-II binding causes a stepwise disassembly of the aggregates. First, the micelle-micelle interfaces are replaced by micelle-water interfaces, with minimal exposure of individual M1-concentrated hydrophobic cores. Complete disassembly occurs only when multiple bCA-II molecules bind to a single micelle, leading to the breakdown of the hydrophobic core and the subsequent release of encapsulated DiI molecules. This stepwise disassembly mechanism underscores the intricate balance between structural stability and responsiveness in these supramolecular assemblies. Our findings provide new insights into the design of smart materials for biomedical applications, where controlled release mechanisms are essential. The ability to fine-tune the assembly and disassembly processes through specific molecular interactions opens many new possibilities for the development of responsive drug delivery systems and biosensors. Amphiphile ; Supramolecular chemistry ; Hydrophobic effect ; Micelle ; Side chain ; Peptide ; Molecule ; Molecular dynamics ; Plasma protein binding Supramolecular Self-Assembly in Materials ; Polymer Surface Interaction Studies ; Diatoms and Algae Research
Authors: Mustafa Yegin | Aytekin Çelik | Umay Halisdemir | Halil Hasar
Source: Journal of Inorganic and Organometallic Polymers and Materials (article, 2025-10-31)
Field: Materials Science — Materials Chemistry

Synthesis and Detailed Physicochemical Characterization of Ti3C2Tx MXene via Optimized HF-Based Etching of Ti3AlC2 MXenes ; Etching (microfabrication) ; Hydrofluoric acid ; Characterization (materials science) ; Thermal stability ; Surface modification ; Thermal ; MAX phases MXene and MAX Phase Materials ; 2D Materials and Applications ; Electromagnetic wave absorption materials
Authors: Riya Singh | Aryan Amit Barsainyan | Rida Irfan | Connor Joseph Amorin | Stewart He | Tony Davis | Arun Thiagarajan | Shiva Sankaran | Seyone Chithrananda | Walid Ahmad | Derek Jones | Kevin McLoughlin | Hyojin Kim | Anoushka Bhutani | Shreyas Vinaya Sathyanarayana | Venkat Viswanathan | Jonathan Allen | Bharath Ramsundar
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2025-08-04)
Field: Materials Science — Materials Chemistry

ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models.Repo link: https://github.com/deepforestsci/chemberta3 Training (meteorology) ; Foundation (evidence) ; Open source ; Data source ; Work (physics) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemistry and Chemical Engineering
Authors: Beatrice Zurletti | Ilaria Andreana | Iris C. Salaroglio | Valeria Bincoletto | Maela Manzoli | Barbara Rolando | Paola Milla | Chiara Riganti | Barbara Stella | Silvia Arpicco
Source: Molecules (article, 2025-03-17)
Field: Materials Science — Biomaterials

Tailoring the Composition of HA/PEG Mixed Nano-Assemblies for Anticancer Drug Delivery Self-assembling amphiphilic polymers represent highly promising materials with emerging applications across various fields. In these polymers, the presence of hydrophilic and hydrophobic segments within their structure drives the self-assembly process in aqueous environments, leading to organized structures capable of incorporating lipophilic drugs. Their high chemical versatility enables the design of tailored structures to meet specific requirements, such as the active targeting ability, thereby broadening their potential applications. In this work, a polyethylene glycol-phospholipid conjugate was employed to form nanocarriers loaded with a lipophilic derivative of gemcitabine. To achieve nano-assemblies actively targeted towards cancer cells overexpressing the hyaluronic acid (HA) receptor CD44, a HA-phospholipid conjugate was co-formulated in various molar ratios (1%, 10%, and 20%). All formulations exhibited a mean diameter below 130 nm, a negative zeta potential (approximately -30 mV), and a high encapsulation efficiency (above 90%). These nano-assemblies demonstrated stability during storage and effectively released the encapsulated drug in a cell culture medium. Upon incubation with cancer cells, the nano-assemblies were internalized via a CD44 endocytosis-mediated mechanism, with the extent of internalization depending on the HA conjugate content. Consistently, cell viability studies revealed that the nanocarriers decorated with higher amounts of HA exerted a higher cytotoxicity, enabling a fine tuning of the nano-assembly properties. Nanocarriers ; Zeta potential ; Conjugate ; Polyethylene glycol ; Nanotechnology ; Drug delivery ; Chemistry ; PEG ratio ; Nanoparticle ; Phospholipid ; Amphiphile ; Polymer ; Endocytosis ; Biophysics ; Materials science ; Chemical engineering ; Copolymer ; Organic chemistry ; Biochemistry ; Membrane ; Cell Nanoparticle-Based Drug Delivery ; Lipid Membrane Structure and Behavior ; RNA Interference and Gene Delivery
Authors: Elizabeth S. Thrall | Olivia M. Vanden Assem | Julia Schneider | Joshua Schrier | Sebastian Tassoti
Source: ChemRxiv (article, 2025-12-02)
Field: Materials Science — Materials Chemistry

Can you help ChatGPT get an ‘A’ in organic chemistry? Teaching effective prompting of large language models for reaction prediction Context (archaeology) ; Digitization ; Chemistry education ; Disadvantage ; Best practice Machine Learning in Materials Science ; Artificial Intelligence in Healthcare and Education ; Various Chemistry Research Topics
Authors: Revista, Zen | CHEMISTRY, 10
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2025-11-27)
Field: Chemistry — Organic Chemistry

Jahn-Teller Engineering of Ligand Fields for Tunable Olefin Metathesis Catalysis Olefin metathesis is a powerful catalytic reaction for carbon-carbon bond formation, enabling the synthesis of diverse organic molecules, polymers, and pharmaceuticals. The efficiency and selectivity of these transformations are critically dependent on the design of transition metal catalysts, where the ligand environment profoundly influences the metal's electronic structure and reactivity. This paper explores the concept of Jahn-Teller engineering as a novel strategy to precisely tune the ligand field of metathesis catalysts, thereby controlling their performance. The Jahn-Teller effect, a geometric distortion that arises in non-linear molecules with degenerate electronic ground states, leads to significant structural and electronic alterations in transition metal complexes. By carefully designing ligands that induce or exploit specific Jahn-Teller distortions, it is hypothesized that the d-orbital energies and populations of the active metal center can be manipulated. This manipulation can fine-tune key steps in the catalytic cycle, such as olefin coordination, metallacyclobutane formation, and cycloreversion, ultimately leading to enhanced activity, selectivity (e.g., E/Z stereoselectivity), and stability. This review summarizes the fundamental principles of olefin metathesis, the Jahn-Teller effect, and ligand field theory, proposing a theoretical and computational framework to investigate and predict the impact of Jahn-Teller active metal centers in tunable metathesis catalysis. Potential target metal centers and ligand motifs susceptible to controlled Jahn-Teller distortions are discussed, along with a proposed methodology encompassing density functional theory calculations and experimental validation through catalyst synthesis and kinetic studies. The ultimate goal is to establish design principles for new generations of metathesis catalysts with unprecedented control over their catalytic properties. Ligand (biochemistry) ; Metathesis ; Catalysis ; Olefin metathesis ; Olefin fiber ; Selectivity ; Transition metal ; Density functional theory Synthetic Organic Chemistry Methods ; Organometallic Complex Synthesis and Catalysis ; Catalysis and Hydrodesulfurization Studies
Authors: Qiqi Zhu | You Wu | Haitao Fu | Zhi Li
Source:  (article, 2025-12-15)
Field: Materials Science — Materials Chemistry

MLPET: a Multi-Level Prompt-Enhanced Transformer for Unified Molecular Property and Drug-Drug Interaction Event Prediction Accurate prediction of molecular properties and drug-drug interaction (DDI) events is crucial for drug discovery and pharmacological safety assessment. However, existing approaches typically focus on single-level molecular representation and lack generalizable strategies for multi-task knowledge transfer. In this work, we propose a unified Multi-Level PromptEnhanced Transformer framework (MLPET), jointly modeling both multi-level molecular features and inter-drug relational semantics. To capture multi-level structural knowledge, we design three complementary self-supervised pretraining tasks: (1) atom prediction, which predicts randomly masked atom types to learn local chemical context; (2) bond prediction, which infers the existence of chemical bonds between atom pairs to capture topological dependencies; and (3) distance prediction, which regresses the 3D spatial distance between atoms to encode molecular geometry. In the downstream stage, we introduce a lightweight prompt fusion mechanism that integrates task-specific prompts into a unified vector to guide fine-tuning. This enables flexible and efficient knowledge transfer to multiple tasks, including molecular property prediction and multi-class DDI event classification. Extensive experiments on MoleculeNet, Ryu, and Deng benchmarks demonstrate that MLPET consistently outperforms state-of-the-art baselines, particularly in low-resource and longtail scenarios. Our results highlight the potential of promptguided multi-task pretraining as a generalizable paradigm for molecular representation learning. The source code of MLPET is available at https://github.com/fuhaitao95/MLPET. ENCODE ; Property (philosophy) ; Representation (politics) ; Transformer ; Event (particle physics) ; Topology (electrical circuits) ; Code (set theory) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
Authors: D. O. Oriekhov | T. T. Osterholt | R. A. Duine | V. P. Gusynin
Source: Physical review. B./Physical review. B (article, 2025-07-08)
Field: Materials Science — Materials Chemistry

RKKY quadratic and biquadratic spin-spin interactions in twisted bilayer graphene We study the competition between the Ruderman-Kittel-Kasuya-Yosida (RKKY) quadratic and biquadratic spin-spin interactions of two magnetic impurities in twisted bilayer graphene away from the magic angle. We apply the Bistritzer-MacDonald model of two graphene layers twisted with respect to each other by a small angle. By reducing the model to the Dirac-type one with modified Fermi velocity, we derive expressions for the RKKY quadratic and biquadratic spin interactions using perturbation theory for the free energy. The biquadratic interaction is suppressed by a larger power of the interaction constant and decreases faster with the distance between impurities compared to the quadratic one. Nevertheless, due to the different period of the oscillations with the impurity separation distance, chemical potential, twist angle, and temperature, it is possible to fine-tune the system to the regime of dominating biquadratic interaction. The existence of such a fine-tuned regime might provide a promising opportunity to observe nonconventional spin ordering. Condensed matter physics ; Bilayer graphene ; Spin (aerodynamics) ; RKKY interaction ; Bilayer ; Graphene ; Physics ; Quadratic equation ; Ferromagnetism ; Quantum mechanics ; Mathematics ; Chemistry ; Membrane ; Geometry Graphene research and applications ; Quantum and electron transport phenomena ; Advanced NMR Techniques and Applications
Authors: Krishnan, Nandana S. | Sundramoorthy, Ashok K.
Source: Figshare (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Recent Advances on Green Synthesis and Application of Carbon Dots for Cancer Cell Detection: A Review The lack of effective early cancer detection methods continues to contribute significantly to the global cancer mortality rate. This has intensified the pursuit of innovative nanotheranostic platforms that can integrate early diagnosis with cost-effective therapy. Among these, carbon dots (CDs) synthesized through green methods have emerged as a sustainable and highly promising solution. Derived from natural and renewable sources such as medicinal plants, biomass waste, microorganisms, and animal-derived materials, green-synthesized CDs exhibit the exceptional properties including strong photoluminescence, excellent biocompatibility, and minimal toxicity. Green synthesis approaches are environmentally friendly, aligning with the principles of sustainability by reducing reliance on hazardous chemicals and energy-intensive processes. These methods also allow fine-tuning of the optical and chemical properties of CDs for specific biomedical applications. This review highlights the synthesis techniques, improved characteristics, and biomedical potential of green CDs, particularly in cancer-related applications such as biosensing, bioimaging, and targeted drug delivery. Special attention is given to their role in early cancer detection, where biofunctionalized green CDs enable sensitive electrochemical and fluorescence-based identification of cancer biomarkers. Furthermore, their integration with surface-enhanced Raman spectroscopy (SERS) opens up avenues for ultra-sensitive detection of tumor markers. The review also addresses the current challenges in clinical translation and large-scale production, while emphasizing the transformative potential of green synthesized carbon dots in advancing precision oncology. Cancer ; Renewable energy ; Sustainability ; Cancer treatment ; Identification (biology) ; Cancer cell Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Advanced Nanomaterials in Catalysis
Authors: Suraj Aswale | Hyerin Kang | Aruna Kumar Mohanty | Hanyoung Kim | Yoon Jung Jang | Minsung Kim | Heung Bae Jeon | Hong Y. Cho | Hyun‐jong Paik
Source: Macromolecular Rapid Communications (article, 2025-03-17)
Field: Chemistry — Organic Chemistry

Various Topological Poly( <i>tert</i> ‐butyl acrylate)s and Their Impacts on Thermal and Solution Properties This study reports the synthesis of acrylate-based polymers with diverse topologies, including cyclic and 8-shaped structures, using a combination of atom transfer radical polymerization (ATRP) and click coupling reactions. The linear and tetra-arm poly(tert-butyl acrylate) (PtBA) polymers with similar molar masses are synthesized via the activators regenerated by electron transfer atom transfer radical polymerization. These polymers are further transformed into cyclic and 8-shaped topologies, respectively, through a click reaction. All topologies possessed similar molar mass are confirmed using <sup>1</sup>H NMR, FT-IR, SEC, and MALDI-TOF mass spectrometry. The influence of macromolecular topology on intrinsic viscosity and glass transition temperature (T<sub>g</sub>) is systematically investigated. The findings show that within the PtBA topology series, T<sub>g</sub> increases with structural compactness, with cyclic polymers exhibiting higher T<sub>g</sub> than their precursors. Additionally, intrinsic viscosity decreases as compactness increases across the various topological macromolecules. These observations highlight the potential of topology as a tool for fine-tuning polymer properties, facilitating the development of advanced materials with specific behaviors in solution and bulk properties. Atom-transfer radical-polymerization ; Acrylate ; Molar mass ; Polymer ; Topology (electrical circuits) ; Materials science ; Polymer chemistry ; Glass transition ; Polymerization ; Macromolecule ; Intrinsic viscosity ; Radical polymerization ; Methyl acrylate ; Chemical engineering ; Monomer ; Chemistry ; Composite material Advanced Polymer Synthesis and Characterization ; Photopolymerization techniques and applications ; Polymer composites and self-healing
Authors: Leone Bacciu | Matteo Grazioso | Silvia Multari | Francesca Grisoni | Angelica Mazzolari | Marco S. Nobile
Source:  (article, 2025-08-20)
Field: Chemistry — Electrochemistry

Improving the Efficiency and the Validity of Molecular Transformers Since their advent, Transformer models have been applied across a wide range of fields, including cheminformatics. In this context, drug discovery has benefited from using Molecular Transformers by leveraging diverse string representations of molecules, such as the Simplified Molecular Input Line Entry Systems (SMILES), for a variety of tasks. In this study, we present a model focused on the optimization of a formerly developed Molecular Transformer specifically dedicated to metabolism prediction. Metabolism refers to all the biotransformations a drug undergoes once inside the human body, directly influencing its therapeutic effect and potential toxicity, and therefore represents a key topic in medicinal chemistry. Framing molecular transformation prediction as a sequence-to-sequence translation task has shown promise, but suffers from limitations such as low validity of generated molecules and high computational cost. To address this limitation, we here propose an optimized model that integrates pre-training, transfer learning, and fine-tuning techniques, already improving validity and reducing computation time. Finally, by separating the metabolism prediction task from the SMILES syntax learning, we ensure broader applicability of the proposed model across diverse datasets and a variety of SMILES-based tasks beyond metabolic transformations, expanding its potential utility. Transformer ; Computation ; Variety (cybernetics) ; Computational model ; Drug discovery Electrochemical Analysis and Applications ; Machine Learning in Materials Science ; Inorganic and Organometallic Chemistry
Authors: Min Zeng | William H. Parsons | Yixuan Chen | David K. Chalmers | S. Perrier
Source: Angewandte Chemie (article, 2025-03-31)
Field: Materials Science — Biomaterials

Hydrophobicity‐Controlled Self‐Assembly of Supramolecular Peptide Nanotubes in Water Abstract Polymer‐conjugated peptides are attractive building blocks for the construction of new nanomaterials. However, the ability to control the self‐assembly of these materials remains a major limitation to their wider utilization. Herein, we report a facile strategy to fine‐tune the assembly of water‐soluble hydrophilic polymer‐conjugated cyclic peptides by incorporating a defined, short hydrocarbon linker between the polymer and peptide. This addition creates a well‐defined hydrophobic “inner shell” that suppresses water from disrupting the organized peptide hydrogen bond network. Our approach is demonstrated using a series of cyclic peptide‐linker‐PDMA conjugates that were evaluated by asymmetric flow field flow fractionation, small angle neutron scattering and transmission electron microscopy. Molecular dynamics simulations were also used to show how the polymer and the peptide stacks interact and illustrate the impact of this hydrophobic inner shell approach. This strategy provides a modular approach to fine control the nanotube self‐assembling behavior. We expect that this technique will improve the versatility of peptide nanotubes for the engineering of advanced nanomaterials. Supramolecular chemistry ; Self-assembly ; Peptide ; Chemistry ; Nanotechnology ; Self-assembling peptide ; Materials science ; Crystallography ; Biochemistry ; Crystal structure Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Chemical Synthesis and Analysis
Authors: Mirko Vanzan | Susanna Bertuletti | Begoña Bazán | Minze T. Rispens | Shaogui Wan | Michel Leeman | Willem L. Noorduin | Francesca Baletto
Source: ArXiv.org (preprint, 2025-01-14)
Field: Chemistry — Spectroscopy

A rational framework to estimate the chiroptical activity of [6]Helicene Derivatives Helicenes are a class of molecules potentially suitable in several technological applications with intrinsic structural chirality which makes them interesting scaffolds for chiroptical properties. As desirable is tuning chiroptical property by synthesis, we combine experimental optical characterization and ab-initio calculations to study how different substituents influence the optical properties of [6]helicene. We explore anchoring groups presenting a variety of sizes and chemical nature, finding that both electron withdrawing and donating groups redshift and dwindle the optical activity of the molecule. We suggest the observed dumping in transitions energy and intensity is connected to the strength of the perturbation induced by the substituent on the pi-conjugation of the aromatic rings. Such observations demonstrate how helicenes' chiroptical properties can be fine-tuned via stereochemical control of the substituents and validates a simple yet effective computational setup to model the optics of those systems. Helicene ; Chemistry ; Stereochemistry ; Organic chemistry ; Molecule Molecular spectroscopy and chirality ; Synthesis and Properties of Aromatic Compounds ; Photoreceptor and optogenetics research
Authors: Bogdan C. Enache | Adela F. Simene | Anamaria Hanganu | Cristina Tablet | Augustin M. Mădălan | Codruța C. Popescu | Mihaela Matache
Source: Synthesis (article, 2025-08-03)
Field: Materials Science — Materials Chemistry

Light-Responsive Oxadiazole-Based (Hetero)aryl-azobenzenes Abstract Switching molecules under light irradiation has become a very popular topic to attain interconvertible states with different properties. Fine-tuning of molecular structures can lead to very interesting compounds and by combining various motifs, novel light-responsive molecules can be prepared. We describe herein the design and synthesis of novel (hetero)aryl-azo derivatives in the form of oxadiazole-decorated azobenzenes and oxadiazole-based aryl-azopyrazoles. We studied the behavior of the synthesized compounds under light irradiation, both in terms of photoswitching and emissive properties. Chemistry ; Oxadiazole ; Aryl ; Combinatorial chemistry ; Organic chemistry Photochromic and Fluorescence Chemistry ; Luminescence and Fluorescent Materials ; Radical Photochemical Reactions