jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nannan Li | Xiaotong Han | Ho Seok Park | Jin Yong Lee
Source: Physical Chemistry Chemical Physics (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

MXenes enhance electrocatalytic water electrolysis of NiFe layered double hydroxides through bifunctional heterostructuring Transition metal-based layered double hydroxides (TM-LDHs) are among the most promising catalytic materials for the electrochemical reactions involved in energy conversion and storage technology. We systematically investigate NiFe-LDH-based electrocatalysts toward application in water electrolysis. We start with the highly accurate advanced density functional theory description of NiFe-LDH's fundamental properties, and demonstrate that coupling a spin-polarized p-band or d-band center model with the Gibbs free energy calculations explains NiFe-LDH's oxygen evolution reaction (OER) mechanism. By involving the related transient states, a reversible oxygen vacancy assisted reaction mechanism has been directly observed and motivated by the high spin transition metal impurity which is further confirmed by the time-consuming hybrid functional method. To further facilitate the electrocatalytic activity of NiFe-LDH, we study NiFe-LDH/MXene heterostructures where the essential semiconductor-to-metallic transition takes place by the additional Ti-3d orbitals and the interfacial non-covalent interaction between the two catalysts. On the basis of calculated results, we propose a link between microscopic properties and macroscopic electrocatalytic kinetics of heterogenous electrocatalysts. Accurately describing the electronic and magnetic structures of electrocatalysts leads us to a step-by-step process for tailoring desired electrocatalytic properties, especially for the high spin state contained TM-LDHs. A descriptor based on combination of the calculated d-band center of transition metal and p-band center of oxygen is the key to predicting electrochemical activity and stability of oxide electrocatalysts. From our results, we establish a design strategy for NiFe-LDH-based bifunctional electrocatalyst fabrication. Layered double hydroxides ; Oxygen evolution ; Bifunctional ; MXenes ; Materials science ; Transition metal ; Electrochemistry ; Electrolysis ; Water splitting ; Oxide ; Density functional theory ; Catalysis ; Gibbs free energy ; Electrolysis of water ; Graphene ; Inorganic chemistry ; Chemistry ; Chemical physics ; Nanotechnology ; Physical chemistry ; Computational chemistry ; Hydroxide ; Electrode ; Electrolyte ; Thermodynamics MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; Nanomaterials for catalytic reactions
Authors: Gopal Chandra Debnath | B. Vasu | Rama Subba Reddy Gorla
Source: Cancer Nanotechnology (article, 2025-10-16)
Field: Materials Science — Materials Chemistry

Current state-of-the-art in multi-scale modeling in nano-cancer drug delivery: role of AI and machine learning Nanomedicine has transformed cancer therapy by enabling targeted drug delivery through nanoparticle-based systems. However, challenges such as inefficient tumor accumulation, poor tissue penetration, and limited cellular uptake hinder therapeutic efficacy. This review explores computational modeling approaches to optimize nanodrug delivery, focusing on multi-scale and stochastic frameworks. Mathematical models have been developed to simulate nanoparticle transport across systemic, tissue, and cellular levels, addressing key processes such as transvascular extravasation, interstitial distribution, and drug release. Additionally, studies integrating artificial intelligence (AI) and machine learning (ML) into in silico models have demonstrated improved predictive accuracy, optimized patient-specific treatments, and refined nanoparticle design. Computational tools for simulating nanoparticle transport, model validation strategies, and the challenges of merging AI with traditional modeling paradigms are discussed. Furthermore, environmental and manufacturing sustainability concerns in nanomedicine production are addressed. By bridging gaps in current research, this work provides a comprehensive overview of computational methodologies, emphasizing their potential to advance precision oncology and accelerate the clinical translation of AI-driven nano-cancer drug delivery systems. Nanomedicine ; Computational model ; Bridging (networking) ; Drug delivery ; In silico ; Targeted drug delivery ; Computational simulation ; Predictive modelling Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Nanoparticle-Based Drug Delivery
Authors: Satoshi Migita | Masaki Satō
Source: Adhesives (article, 2025-12-18)
Field: Materials Science — Surfaces, Coatings and Films

Protein Adsorption and Cell Adhesion on Metallic Biomaterial Surfaces Metallic biomaterials play essential roles in modern medical devices, but their long-term performance depends critically on protein adsorption and subsequent cellular responses at material interfaces. This review examines the molecular mechanisms governing these interactions and discusses surface modification strategies for controlling biocompatibility. The physicochemical properties of oxide layers formed on metal surfaces—including Lewis acid-base chemistry, surface charge, surface free energy, and permittivity—collectively determine protein adsorption behavior. Titanium surfaces promote stable protein adsorption through strong coordination bonds with carboxylate groups, while stainless steel surfaces show complex formation with proteins that can lead to metal ion release. Surface modification strategies can be systematically categorized based on two key parameters: effective ligand density (σ_eff) and effective mechanical response (E_eff). Direct control approaches include protein immobilization, self-assembled monolayers, and ionic modifications. The most promising strategies involve coupled control of both parameters through hierarchical surface architectures and three-dimensional modifications. Despite advances in understanding molecular-level interactions, substantial challenges remain in bridging the gap between surface chemistry and tissue-level biological performance. Future developments must address three-dimensional interfacial interactions and develop systems-level approaches integrating multiple scales of biological organization to enable rational design of next-generation metallic biomaterials. Protein adsorption ; Adsorption ; Surface modification ; Biomaterial ; Metal ; Ionic bonding ; Cell adhesion ; Adhesion Polymer Surface Interaction Studies ; Graphene and Nanomaterials Applications ; Molecular Junctions and Nanostructures
Authors: Sibel Büyüktiryaki
Source: Polymers (review, 2025-08-23)
Field: Chemistry — Analytical Chemistry

Molecularly Imprinted Polymer Nanoparticles for Pharmaceutical Applications: Sample Preparation, Sensor-Based Detection, and Controlled Drug Release Molecularly imprinted polymer nanoparticles (MIP NPs) are synthetic receptors with selective recognition sites for target molecules. They are employed instead of biorecognition elements in many applications due to their high affinity and selectivity, stability, easy preparation, and low cost. Their nanoscale size provides enhanced surface interactions, faster response times, improved biocompatibility, and effective cellular penetration, particularly in complex biological environments. MIP NPs provide high selectivity and structural versatility in the sample preparation, sensor-based detection, and controlled drug delivery, serving as promising alternatives to conventional methods. This review highlights the recent advancements in the synthesis and application of MIP NPs in three critical areas: sample preparation, sensor-based detection, and controlled drug release. Additionally, recent developments in green synthesis approaches, biocompatible materials, and surface functionalization strategies that are effective in the performance of MIP NPs are mentioned. Molecularly imprinted polymer ; Nanotechnology ; Nanoparticle ; Materials science ; Drug ; Polymer ; Drug detection ; Molecular imprinting ; Chromatography ; Chemistry ; Organic chemistry ; Pharmacology ; Selectivity ; Medicine ; Catalysis Analytical chemistry methods development ; Analytical Chemistry and Chromatography ; Analytical Chemistry and Sensors
Authors: Xiuyan Cheng | Di Liang | Miao Jiang | Yufei Sha | Xiaonan Liu | Jinlai Liu | Qingchen Cao | Jiangliu Shi
Source: Micromachines (review, 2025-05-31)
Field: Materials Science — Materials Chemistry

Review of Directed Self-Assembly Material, Processing, and Application in Advanced Lithography and Patterning Directed self-assembly (DSA) lithography, a cutting-edge technology based on the self-assembly of block copolymers (BCPs), has received significant attention in recent years. Combining DSA with established lithography technologies, such as extreme ultraviolet (EUV), deep ultraviolet (DUV), electron beam lithography, and nanoimprint lithography, significantly enhances the resolution of target patterns and device density. Currently, there are two commonly used methods in DSA: graphoepitaxy, employing lithographically defined topographic templates to guide BCP assembly, and chemoepitaxy, utilizing chemically patterned surfaces with precisely controlled interfacial energies to direct nanoscale phase segregation. Through novel DSA lithography technology, nanoscale patterns with smaller feature sizes and higher densities can be obtained, realizing the miniaturization of hole and line patterns and pitch multiplication and improving the roughness and local critical dimension uniformity (LCDU). It is gradually becoming one of the most promising and advanced lithography techniques. DSA lithography technology has been applied in logic, memory, and optoelectronic device fabrications. Extreme ultraviolet lithography ; Lithography ; Multiple patterning ; Next-generation lithography ; Materials science ; Nanoimprint lithography ; Computational lithography ; Stencil lithography ; Nanotechnology ; Miniaturization ; X-ray lithography ; Electron-beam lithography ; Critical dimension ; Immersion lithography ; Nanoscopic scale ; Resist ; Photolithography ; Template ; Optoelectronics ; Optics ; Physics Block Copolymer Self-Assembly ; Advancements in Photolithography Techniques ; Nanofabrication and Lithography Techniques
Authors: Mohammad Awwal Adeshina | Hyunmin Kim
Source: Nanophotonics (review, 2025-03-08)
Field: Materials Science — Materials Chemistry

Exploring the frontier: nonlinear optics in low dimensional materials Nonlinear optics, the study of intense light-matter interactions, traditionally uses bulk materials like LiNbO<sub>3</sub> for device fabrication. However, these materials face challenges such as limited nonlinear susceptibility, large dimensions, and phase matching issues, limiting compact and integrated devices. Recent research has illuminated that a variety of low-dimensional materials exhibit markedly stronger nonlinear optical responses than their bulk counterparts. This has made nonlinear optics in low-dimensional materials a dynamic area of study, allowing for rapid light-matter interactions and advancing nonlinear nanophotonic and optoelectronic applications. These applications span diverse areas, from wavelength conversion and the generation of ultrashort laser pulses to advancements in quantum photonics and integrated photonic technologies. This review covers two-dimensional materials such as graphene and transition metal dichalcogenides to one-dimensional forms like carbon nanotubes and nanowires, and further to zero-dimensional structures including nanoparticles and quantum dots. By providing a comprehensive overview of the current state of non-linear optics in the context of low-dimensional materials, this review not only encapsulates the existing knowledge base but also charts a course for future explorations in this rapidly progressing domain. Nanophotonics ; Nonlinear optics ; Photonics ; Materials science ; Context (archaeology) ; Nanotechnology ; Nonlinear system ; Quantum optics ; Graphene ; Optoelectronics ; Quantum dot ; Laser ; Physics ; Optics ; Quantum mechanics 2D Materials and Applications ; Advanced Fiber Laser Technologies ; Nonlinear Optical Materials Studies
Authors: Tong Wu | Song Bi | Hao Li | Ruizhe Xing | Jun Yang | Xuanyu Liu | Zhuoxun Li
Source: Discover Nano (review, 2025-07-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multiscale construction of wave-absorbing carbon nanomaterials With the gradual improvement of electromagnetic protection of equipment and electromagnetic pollution prevention requirements, carbon heterostructured wave-absorbing nanomaterials have become a research hotspot due to their tunable electromagnetic properties, high stability, and lightweight advantages. In this paper, we comprehensively and deeply discuss the multi-scale construction of carbon nano-absorbent materials, and elaborate on the design strategy and research progress from the micro-, meso- and macro-levels. At the microscopic level, the structure of carbon materials is controlled at the nanoscale by means of intrinsic structural design, elemental doping and interfacial modulation to introduce more microstructural defects to enhance the polarisation and scattering of electromagnetic waves, thereby improving the wave-absorbing performance. The mesoscopic level focuses on the modulation of the micro-nano multilevel structure of carbon absorbers, such as the in situ multilevel assembly of MXene, MOFs and heterogeneous continuous fibers at the mesoscopic scale, which is conducive to the enhancement of the absorber's conductivity and interfacial loss to enhance its wave-absorbing ability. The macroscopic level focuses on structure-function integrated design, such as 3D porous structures, sandwich honeycomb structures, and surface superstructures, which enable the materials to possess excellent mechanical properties along with good wave-absorbing properties. The comprehensive use of these design strategies to optimize the whole design chain of wave-absorbing materials is conducive to maximizing the performance and application value of the materials. The aim of this paper is to elucidate the effect of multiscale heterostructures on carbon-based wave-absorbing materials, which provides a reference for the precise design of their wave-absorbing properties. Nanomaterials ; Carbon fibers ; Nanotechnology ; Materials science ; Environmental science ; Composite material ; Composite number Electromagnetic wave absorption materials ; Carbon Nanotubes in Composites ; Graphene research and applications
Authors: Mikhail P. Egorov | Vladimir Ya. Lee | Igor V. Alabugin
Source: Chemistry (article, 2025-06-26)
Field: Materials Science — Materials Chemistry

Cocktail of Catalysts: A Dynamic Advance in Modern Catalysis Cocktail-type catalysis represents a significant shift in the understanding of catalytic processes, recognizing that multiple interconverting species—such as metal complexes, clusters, and nanoparticles—can coexist and cooperate within a single reaction environment. Originating from mechanistic studies on palladium-catalyzed systems, this concept challenges the classical division between homogeneous and heterogeneous catalysis. Instead, it introduces a dynamic framework where catalysts adapt and evolve under reaction conditions, often enhancing efficiency, selectivity, and durability. Using advanced spectroscopic, microscopic, and computational techniques, researchers have visualized the formation and transformation of catalytic species in real time. The cocktail-type approach has since been extended to platinum, nickel, copper, and other transition metals, revealing a general principle in catalysis. This approach not only resolves long-standing mechanistic inconsistencies, but also opens new directions for catalyst design, green chemistry, and sustainable industrial applications. Embracing the complexity of catalytic systems may redefine future strategies in both fundamental research and applied catalysis. Catalysis ; Chemistry ; Organic chemistry Machine Learning in Materials Science
Authors: N. Segal | Aviv Netanyahu | Kevin P. Greenman | Pulkit Agrawal | Rafael Gómez‐Bombarelli
Source: npj Computational Materials (article, 2025-11-20)
Field: Materials Science — Materials Chemistry

Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules Abstract Discovery of high-performance materials and molecules requires identifying extremes with property values that fall outside the known distribution. Therefore, the ability to extrapolate to out-of-distribution (OOD) property values is critical for both solid-state materials and molecular design. Our objective is to train predictor models that extrapolate zero-shot to higher ranges than in the training data, given the chemical compositions of solids or molecular graphs and their property values. We propose using a transductive approach to OOD property prediction, achieving improvements in prediction accuracy. In particular, our method improves extrapolative precision by 1.8× for materials and 1.5× for molecules, and boosts recall of high-performing candidates by up to 3×. Our method leverages analogical input-target relations in the training and test sets, enabling generalization beyond the training target support, and can be applied to any other material and molecular tasks. Property (philosophy) ; Generalization ; Training set ; Training (meteorology) ; Recall ; Property value Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Machine Learning in Bioinformatics
Authors: Christian R. Zwick | Maike Eckhoff | Jeremy Henle | Anna V. Bay | Rafal Swiatowiec | Shashank Shekhar | Cassie Yang | Yong Zhou | Amanda L. Wall | Rodger F. Henry | Jessica N. Hoskins | Matthew S. Sigman
Source: Journal of the American Chemical Society (article, 2025-02-13)
Field: Chemistry — Organic Chemistry

Development of a Thioetherification of Heteroarene Electrophiles with Broad Scope via a Proton Transfer Dual Ionization Mechanism Sulfur-derived functional groups represent prevalent motifs in highly sought-after small molecules, such as active pharmaceutical ingredients (APIs). Thioethers are one such example, being commonly encountered in APIs, prodrugs, and as valuable synthetic "linchpins" to access an array of sulfur-derived functional groups. While nucleophilic aromatic substitution (S<sub>N</sub>Ar) has traditionally been used to synthesize aryl thioethers, modern approaches leverage transition metals to catalyze thermal or photochemical cross-coupling. While studying photochemical thioetherification reactions, we uncovered a remarkably mild condition that does not require light, transition metals, or exogenous bases. An array of thiols and halogenated heterocycles were coupled to produce >70 diverse products. Reaction progress kinetic analysis (RPKA) and computational studies support a unique mechanism termed proton transfer dual ionization (PTDI) S<sub>N</sub>Ar. Finally, a predictive statistical model was constructed aided by high-throughput experimentation (HTE) to understand when the PTDI processes are successful, resulting in the completion of ten target-oriented syntheses. This transformation complements modern approaches to thioether synthesis and motivates additional research evaluating PTDI as a general activation mode between reaction partners. Chemistry ; Electrophile ; Mechanism (biology) ; Scope (computer science) ; Proton ; Dual (grammatical number) ; Transferability ; Ionization ; Computational chemistry ; Photochemistry ; Organic chemistry ; Nuclear physics ; Ion ; Epistemology ; Physics Sulfur-Based Synthesis Techniques ; Radical Photochemical Reactions ; Synthesis and Catalytic Reactions
Authors: M. Hjiri | Sonia Soltani | Anouar Jbeli | Nazir Mustapha | Nouf Ahmed Althumairi | Majdi Benamara | M.A. Valente
Source: Nanomaterials (article, 2025-04-01)
Field: Materials Science — Materials Chemistry

Tunable Electrical Properties of Cobalt-Doped Maghemite Nanoparticles for Advanced Resistive and Thermistor Applications Maghemite (γ-Fe<sub>2</sub>O<sub>3</sub>) nanoparticles have attracted considerable interest for electronic applications due to their tunable electrical properties. Doping strategies offer an effective way to optimize their resistive behavior for use in electronic devices. In this study, cobalt (Co) was incorporated into γ-Fe<sub>2</sub>O<sub>3</sub> to enhance its resistive properties. X-ray diffraction (XRD) confirmed the retention of the cubic P4<sub>3</sub>32 phase, with Co doping inducing subtle lattice distortions due to ionic substitution. Scanning and transmission electron microscopy (SEM/TEM) revealed morphological changes, where Co incorporation influenced particle shape and size distribution. Electrical conductivity analysis demonstrated a decrease in both AC and DC conductivity with the increase in Co content, indicating enhanced resistive behavior. The increase in activation energy suggests a reduction in charge carrier mobility, leading to higher resistivity. Impedance spectroscopy further confirmed increased real and imaginary impedance values, reinforcing the role of Co in suppressing charge transport. These results position cobalt-doped maghemite as a promising material for electronic resistive devices, such as tunable resistors and negative temperature coefficient (NTC) thermistors, where controlled conductivity and stable resistive behavior are essential. Materials science ; Dielectric spectroscopy ; Resistive touchscreen ; Doping ; Electrical resistivity and conductivity ; Nanoparticle ; Cobalt ; Maghemite ; Analytical Chemistry (journal) ; Nanotechnology ; Optoelectronics ; Electrode ; Electrochemistry ; Chemistry ; Electrical engineering Dielectric properties of ceramics ; Electrical and Thermal Properties of Materials ; Ferroelectric and Piezoelectric Materials
Authors: Yun-Kyu Choi | Takayuki Katoh | Adam T. Beattie | Hiroaki Suga
Source: Nature Communications (article, 2025-05-20)
Field: Materials Science — Materials Chemistry

A super versatile flexizyme system with phenol esters for genetic code reprogramming Genetic code reprogramming enables ribosomal incorporation of multiple nonproteinogenic amino acids (npAAs), supporting bioactive peptide development. Flexizyme technology with npAA-benzyl(thio)esters (BZEs) as acyl-donors has been crucial for preparing diverse npAA-tRNAs. However, low acylation yields for some npAAs hinder peptide library construction. Here we report a versatile flexizyme system using phenol esters as alternative acyl-donors. Computational pK<sub>a</sub> predictions guided the synthesis of five phenol esters, which are mild enough to prevent random aminoacylation yet reactive with tRNA 3'-hydroxy groups. Among them, 3-nitrophenol (3NP) was chosen to prepare 18 structurally distinct npAA-3NPs, demonstrating direct tRNAs aminoacylation in 15-41% yields. Moreover, the flexizyme eFx drastically enhances aminoacylation efficiency, yielding near-quantitative conversion for some npAAs, e.g. cyclic β-npAAs. This eFx/npAA-3NP system facilitates access to diverse npAA-tRNAs, expanding ribosomal synthesis of nonstandard peptides, including macrocyclic structures. Thus, our approach provides an efficient tool for constructing peptide libraries with multiple npAA building blocks. Reprogramming ; Genetic code ; Phenol ; Code (set theory) ; Computational biology ; Computer science ; Biology ; Chemistry ; Genetics ; Programming language ; DNA ; Organic chemistry ; Gene Photochromic and Fluorescence Chemistry ; DNA and Nucleic Acid Chemistry ; Photosynthetic Processes and Mechanisms