jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Manabu Machida | Koichi Mayumi
Source: arXiv (Cornell University) (article, 2026-02-09)
Field: Materials Science — Materials Chemistry

Tikhonov regularization-based reconstruction of partial scattering functions obtained from contrast variation small-angle neutron scattering Contrast variation small-angle neutron scattering (CV-SANS) has been widely employed for nano structural analysis of multicomponent systems. In CV-SANS experiments, scattering intensities of samples with different scattering co\ ntrasts are decomposed into partial scattering functions, corresponding to structure of each component and cross-correlation between different components, by singular value decomposition (SVD). However, the estimation of partial scattering functions with small absolute values often suffers from instability due to the significant differences in the singular values. In this paper, we propose a remedy for this instability by introducing the Tikhonov regularization, which ensures more stable reconstruction of the partial scattering functions. Scattering ; Tikhonov regularization ; Neutron scattering ; Small-angle neutron scattering ; Biological small-angle scattering ; Instability ; Scattering theory ; X-ray scattering techniques X-ray Diffraction in Crystallography ; Crystallography and Radiation Phenomena ; Microstructure and mechanical properties
Authors: Orestis Kanaris | Lydia-Yasmin Sobisch | Annett Gödt | Frank Schreiber | Niclas Nordholt
Source: npj Antimicrobials and Resistance (article, 2026-01-08)
Field: Chemistry — Organic Chemistry

Consequences of benzalkonium chloride tolerance for selection dynamics and de novo resistance evolution driven by antibiotics Biocides are used in large amounts in industrial, medical, and domestic settings. Benzalkonium chloride (BAC) is a commonly used biocide, for which previous research revealed that Escherichia coli can rapidly adapt to tolerate BAC-disinfection, with consequences for antibiotic susceptibility. However, the consequences of BAC tolerance for selection dynamics and resistance evolution to antibiotics remain unknown. Here, we investigated the effect of BAC tolerance in E. coli on its response upon challenge with different antibiotics. Competition assays showed that subinhibitory concentrations of ciprofloxacin-but not ampicillin, colistin and gentamicin-select for the BAC-tolerant strain over the BAC-sensitive ancestor at a minimal selective concentration of 0.0013-0.0022 µg∙mL<sup>-</sup><sup>1</sup>. In contrast, the BAC-sensitive ancestor was more likely to evolve resistance to ciprofloxacin, colistin and gentamicin than the BAC-tolerant strain when adapted to higher concentrations of antibiotics in a serial transfer laboratory evolution experiment. The observed difference in the evolvability of resistance to ciprofloxacin was partly explained by an epistatic interaction between the mutations conferring BAC tolerance and a knockout mutation in ompF encoding for the outer membrane porin F. Taken together, these findings suggest that BAC tolerance can be stabilized in environments containing low concentrations of ciprofloxacin, while it also constrains evolutionary pathways towards antibiotic resistance. Benzalkonium chloride ; Colistin ; Antibiotics ; Escherichia coli ; Experimental evolution ; Antibiotic resistance ; Multidrug tolerance ; Evolvability ; Mutation ; Strain (injury) Antimicrobial agents and applications ; Environmental Chemistry and Analysis ; Antibiotic Resistance in Bacteria
Authors: Natasha M. Bourgeois | Satchel Bell | Jean Olivier | Michael Rout | John Aitchison | Fred Mast
Source: BIO-PROTOCOL (article, 2026-01-01)
Field: Materials Science — Materials Chemistry

High-Resolution Quantification of Two-Way Nanobody Synergy Using Automated Liquid Handling and Computational Modeling Evaluating single-domain antibody cooperativity is essential for developing potent, escape-resistant antiviral biologics. Here, we present a protocol that reproducibly quantifies functional synergy between neutralizing nanobody pairs in standardized viral infectivity assays. Controlled automated liquid handling prepares two-dimensional concentration matrices, minimizing pipetting variance and systematic error. Neutralization data are fitted using quantitative models that independently estimate potency, cooperativity, and efficacy to distinguish additive, synergistic, and antagonistic effects between nanobody pairs. Replicated measurements enable statistically interpretable parameter estimates, supporting robust evaluation of combinatorial nanobody therapeutics with commonly available equipment and open-source analysis tools. This framework is broadly applicable to assessing cooperative effects among other classes of binding or inhibitory molecules, facilitating systematic discovery of synergistic combinations. Key features • Understanding functional synergistic effects between antiviral nanobodies advances their rational therapeutic design. • Performing nanobody synergy experiments with an automated liquid handling workflow enables high-throughput and highly reproducible analysis of nanobody cooperativity. • Evaluating a two-dimensional matrix of nanobody concentrations using the MuSyC model provides the resolution needed to understand how one nanobody can be influenced by another. • This protocol integrates experimental, computational, and visualization procedures into a unified framework to identify and characterize synergistic antiviral nanobody combinations. Automation ; Key (lock) ; Automated method ; Noise (video) Block Copolymer Self-Assembly ; Nanopore and Nanochannel Transport Studies ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Saumya Suvarna | Prabhat K. Jaiswal | Madhu Priya
Source: ArXiv.org (article, 2026-03-03)
Field: Materials Science — Materials Chemistry

Disorder induced melting and glass formation in a one-component Lennard-Jones system Identifying the conditions under which glass formation occurs is crucial for a fundamental understanding of the glass transition mechanism. Pure liquids devoid of any frustration avoid glass transition and undergo crystallization. In this work, we investigate a one-component liquid interacting via the Lennard-Jones potential in two dimensions, where disorder is introduced through pinning, a protocol in which a fixed fraction of particles is immobilized at positions selected from an equilibrium configuration. By employing molecular dynamics simulation, we systematically study the influence of pinning concentration on both structural and dynamical properties. Structural properties quantified by radial distribution function and hexatic-order parameter display a systematic decrease with a rise in pinning concentration. However, the dynamical properties such as the fragility index and the late-time mean squared displacement exhibit a non-monotonic trend as the concentration of pinned particles increases. A moderate concentration of pinned particles helps prevent crystallization and facilitates particle motion. A further rise in the number of pinned particles suppresses particle mobility, leading to a reduction in the overall dynamics of the system. These simulation results are in good agreement with experimental observations on colloidal suspensions confined between glass coverslips, where particles are immobilized. Our findings demonstrate the pivotal role of pinning in controlling the phase behavior of simple liquids and validate the unique dynamical features of two-dimensional liquids with pinned particles. Fragility ; Dynamical heterogeneity ; Mean squared displacement ; Particle (ecology) ; Glass transition ; Colloidal particle ; Crystallization ; Colloid ; Frustration ; Atomic packing factor Material Dynamics and Properties ; Advanced Physical and Chemical Molecular Interactions ; Liquid Crystal Research Advancements
Authors: Sinan Gündoğdu | Lea M. Rektorschek | Marco E. Stucki | Maarten H. van der Hoeven | Tim Kolbe | Sylvia Hagedorn | Markus Weyers | Tommaso Pregnolato | Julian M. Bopp | Tim Schröder
Source: npj Nanophotonics (article, 2026-02-02)
Field: Materials Science — Materials Chemistry

Hetero-integrated diamond-on-AlGaN/AlN waveguides for optical color center interfacing Abstract Quantum photonic devices require efficient access to solid-state spin qubits serving as quantum memories or single-photon sources and nonlinearities. Additionally, they demand nonlinear and electro-optic components for frequency converters and phase shifters. The serial production of quantum devices needs the on-chip integration of all these photonic components. These requirements motivate the hetero-integration of materials with complementary properties. Diamond color centers provide access to spin registers, long coherence times, and suitability for quantum networking. In contrast, aluminum gallium nitride-on-aluminum nitride (AlGaN/AlN) photonics features second-order nonlinear and first-order electro-optic effects. Here, we demonstrate the accurate integration of diamond waveguides containing nitrogen-vacancy (NV) centers into AlGaN/AlN waveguides using a pick-and-place method. Both waveguides possess tapered sections for adiabatic mode transfer. We model the tapered diamond-AlGaN/AlN interface with finite element simulations, implementing fabrication constraints and placement uncertainties. Measured coupling efficiencies coincide closely with simulation model predictions. Photonics ; Interfacing ; Qubit ; Diamond ; Quantum dot ; Coherence (philosophical gambling strategy) ; Waveguide ; Fabrication ; Coupling (piping) ; Quantum Diamond and Carbon-based Materials Research ; Photonic and Optical Devices ; Advanced Fiber Laser Technologies
Authors: Siavash Mirzaei-Ghormish | Jeddy Bennett | Ryan M. Camacho
Source: Quantum (article, 2026-03-20)
Field: Materials Science — Materials Chemistry

High-efficiency vertical emission spin-photon interface for scalable quantum memories We present an efficient spin-photon interface for free-space vertical emission coupling. Using a dipole model, we show that our design achieves a far-field collection efficiency of 96% at the numerical aperture of 0.7 with a 95% overlap to a Gaussian mode. Our approach is based on a dual perturbation layer design. The first perturbation layer extracts and redirects the resonant mode of a diamond microdisk resonator around the optical axis. The second perturbation layer suppresses side lobes and concentrates most of the light intensity near the center. This dual-layer design enhances control over the farfield pattern and also reduces alignment sensitivity. Additionally, the implemented dipole model performs calculations <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mn>3.2</mml:mn> </mml:math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>&amp;#x00D7;</mml:mo> </mml:mrow> </mml:math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mn>6</mml:mn> </mml:msup> </mml:math> times faster than full-wave FDTD simulations. These features make the design promising for quantum information applications. Quantum ; Perturbation (astronomy) ; Resonator ; Dipole ; Gaussian ; Scalability ; Numerical aperture ; Quantum efficiency ; Light-emitting diode Diamond and Carbon-based Materials Research ; Quantum and electron transport phenomena ; Quantum optics and atomic interactions
Authors: Siyuan Chen | Jonathan P.H. Belnoue | Dmitry Ivanov
Source: Materials science forum (article, 2026-04-10)
Field: Materials Science — Polymers and Plastics

Fabric Patching: A Simple Approach to Mitigate Defects Forming of dry textile preforms for liquid moulding processes becomes increasingly challenging for geometries exhibiting strong double curvature and aggressive tapering. While sequential draping can mitigate defects, it is often impractical for high-rate manufacturing and lacks robustness for dry fabrics with limited inter-ply tack. This paper investigates an alternative approach in which locally printed and cured or semi-cured resin patches are used to steer deformation during forming and suppress shear localisation. A numerical framework is developed to model patched preforms using a superposition-based material representation and is applied to an extreme “bow-tie” benchmark geometry. Initial simulations reveal severe shear-strain localisation leading to fibre-path instability. Various patching strategies are explored to identify the dominant drivers governing defect mitigation. The results demonstrate that appropriately placed and sufficiently stiff patches can significantly delocalise shear and eliminate multi-stripe deformation patterns. Based on these findings, key optimisation parameters and practical guidelines for patch placement and stiffness selection are formulated, providing a foundation for future automated optimisation of patch-assisted preform forming. Robustness (evolution) ; Curvature ; Stiffness ; Shear (geology) ; Benchmark (surveying) ; Representation (politics) ; Deformation (meteorology) Textile materials and evaluations ; Mechanical Behavior of Composites ; Epoxy Resin Curing Processes
Authors: Nazlee Sharmin | A. Chow
Source: PLoS ONE (article, 2026-04-10)
Field: Chemistry — Physical and Theoretical Chemistry

Featuring the application of biochemistry in dental practice through a self-directed assignment: A descriptive study While the assignment included a limited number of follow-up questions, which restricted our ability to explore student perceptions in detail, it demonstrates the potential of a well-designed, interactive, case-based assignment to stimulate student motivation by highlighting the relevance and application of biochemistry content in the future dental profession. Descriptive statistics ; Descriptive research ; Relevance (law) ; Perception ; MEDLINE ; Oral health ; Class (philosophy) Various Chemistry Research Topics ; Science Education and Pedagogy ; Dental Research and COVID-19
Authors: Youhe Jiang | Ran Yan | You Peng | Wenshuang Li | Taiyi Wang | Fangcheng Fu | Binhang Yuan
Source: arXiv (Cornell University) (article, 2026-04-08)
Field: Materials Science — Materials Chemistry

Autopoiesis: A Self-Evolving System Paradigm for LLM Serving Under Runtime Dynamics Modern Large Language Model (LLM) serving operates in highly volatile environments characterized by severe runtime dynamics, such as workload fluctuations and elastic cluster autoscaling. Traditional serving systems rely on static, human-engineered serving policies (e.g., scheduling algorithms and rescheduling strategies) to manage these dynamics. However, these policies must navigate deeply intertwined runtime trade-offs (e.g., scheduling overhead vs. execution efficiency, rescheduling frequency vs. reconfiguration overhead), whose optimal balance is workload-specific and shifts continuously as runtime conditions evolve, rendering any fixed policy fundamentally unable to adapt. We propose Autopoiesis, a novel online self-evolving system that shifts LLM serving from static policy deployment to continuous online policy evolution. First, Autopoiesis introduces an LLM-driven program synthesis workflow to evolve serving policies with respect to real-time observed dynamics, where the evolved policies reflect the optimal decision in navigating the complex, multi-dimensional trade-off space. Second, Autopoiesis enables this synthesis process to operate continuously during serving, observing real-world system behavior, and rewriting the policy code as runtime trade-offs shift, thereby transforming policy design from a one-time offline endeavor into an ongoing system component, enabling autonomous adaptation to evolving runtime conditions. Together, we establish a new paradigm: Serving policies are no longer static artifacts designed by humans before deployment, but living code that LLMs continuously evolve throughout deployment to navigate runtime trade-offs beyond human design. We evaluate Autopoiesis across diverse runtime dynamics and show up to 53% and on average 34% improvements over state-of-the-art LLM serving systems. Control reconfiguration ; Workflow ; Software deployment ; Scheduling (production processes) ; Runtime system ; Runtime verification ; Compiler ; Workload ; Process (computing) Machine Learning in Materials Science ; Natural Language Processing Techniques ; Big Data and Digital Economy
Authors: Jan Krüger | Sven Dopslaff | Phillip Manley | Detlef Bergmann | Rainer Köning | Gaoliang Dai | Kai Hahm | Philipp‐Immanuel Schneider | Martin Hammerschmidt | Lin Zschiedrich | Harald Bosse | Bernd Bodermann
Source: Measurement Science and Technology (article, 2026-02-11)
Field: Materials Science — Surfaces, Coatings and Films

Photomask linewidth measurement comparison including an improved model-based through-focus measurement approach Abstract We introduce a new method for structure width (critical dimension (CD)) measurements, the ultraviolet through-focus optical microscopy (UV-TFOM). It is based on through-focus measurements, providing additional information about the phase change introduced by the sample and the measurement system for the sophisticated data analysis, which is based on rigorous simulations of the underlying diffraction problem and Bayesian target vector optimization. In addition to the dimensional structure parameters of interest, such as the CD, the method allows to determine and incorporate the most significant aberrations of the imaging system. To test the performance of this new method, line structures on a chromium-on-glass photomask down to nominal widths of 100 nm were measured. The results and the derived measurement uncertainties are compared with the results of a previous comparison using standard CD calibration tools used at the Physikalisch-Technische Bundesanstalt (PTB), including CD atomic force measurement (CD-AFM), CD scanning electron microscopy (CD-SEM) and transmission ultraviolet optical microscopy (UV-OM). The measured values are CD at 50% of the height of the structures. Here, the edge angle of the structures is also taken into account. While some of the results of the old comparison have already been published previously, all the results obtained at PTB are presented here for the first time. The comparison confirms the excellent agreement between PTB’s CD-AFM, and SEM measurements and the good agreement also with the UV-OM results, most of which are well within the combined expanded uncertainties. However, in contrast to UV-OM, the measurement results obtained with UV-TFOM show no significant systematic deviations from the non-optical methods, has an extended range down to 100 nm, and also offers a reduced measurement uncertainty. We present the new method including the setup used, provide all measurement results including the related uncertainty budget and the expanded uncertainties. Photomask ; Calibration ; Critical dimension ; Metrology ; Laser linewidth ; Reticle ; Microscopy ; Phase (matter) ; Measurement uncertainty ; Sample (material) Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Advancements in Photolithography Techniques
Authors: Yuchen Shao | Yongmei Ding
Source: Journal of Physics Conference Series (article, 2026-04-01)
Field: Materials Science — Materials Chemistry

Prediction of Hansen solubility parameters using an ensemble model based on molecular descriptions and fingerprints Abstract Accurate prediction of Hansen solubility parameters (HSPs) is of great significance for elucidating intermolecular interaction mechanisms and guiding solvent selection in chemistry, pharmaceuticals, and materials science. However, experimental determination processes are often time-consuming and costly. Furthermore, traditional prediction models typically rely on small datasets and single features, which leads to issues such as limited accuracy and insufficient interpretability. In this study, using the large 10K dataset from HSPiP software, we develop an ensemble machine learning framework combining molecular descriptors (MDs) and molecular fingerprints for predicting the three HSP components: dispersion component ( δ d ), polar component ( δ p ), and hydrogen bonding component ( δ h ). The stacking ensemble model we built obtained excellent prediction performance by integrating multiple base learners, with the R 2 for δ d , δ p , and δ h reaching 0.946, 0.908, and 0.961. SHapley Additive exPlanations (SHAP) analysis shows the key features that affect HSPs, finding that topological features, electronic properties, and hydrogen bonding-related descriptors play a major role in solubility behaviour. This study shows that the ensemble learning strategy combining molecular descriptors and molecular fingerprints significantly enhances both predictive performance and interpretability of the model, providing an effective computational method for predicting solubility parameters and designing solvents. Interpretability ; Stacking ; Molecular descriptor ; Component (thermodynamics) ; Solubility ; Ensemble forecasting ; Intermolecular force ; Ensemble learning ; Feature selection Crystallization and Solubility Studies ; Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Bryan J. Mathis | Alexander Zaboronok | Ying Shi | Yoshiyuki Nagumo | Hiroyuki Nishiyama | Yuji Hiramatsu
Source: Pharmaceutics (article, 2026-04-13)
Field: Materials Science — Biomaterials

Nanoparticle Clearance and New Horizons in Engineered Drug Delivery Nanomedicine has advanced rapidly as engineered nanoparticles have become increasingly capable of improving drug stability, targeting, controlled release, and biocompatibility. However, nanoparticle clinical utility relies on both delivery efficiency and how they are metabolized, retained, and cleared. This review examines the major biological pathways governing nanoparticle clearance and discusses how engineering parameters can be tuned to influence bioaccumulation, metabolism, excretion, and therapeutic performance with a wide range of available materials. This article is a narrative review of the recent and foundational literature on medically relevant nanoparticles, including lipid-based, polymeric, biopolymer, inorganic, polylactide, and bile-derived systems. All relevant translational, biochemical, chemical, and clinical literature from PubMed was searched from January 1971 to January 2026 to obtain a representative sample of work before information extraction. Nanoparticle clearance is governed by interconnected molecular and organ-level processes that vary according to composition, size, surface chemistry, and route of administration. Surface modifications with PEGylation, zwitterionic coatings, cholesterol, proteins, or responsive linkers can prolong circulation, alter immune recognition, and direct organ-specific handling. While rapid clearance remains desirable for many systemically acting drugs, prolonged intracellular or intratumoral retention may improve outcomes, particularly in boron neutron capture therapy and other activation-dependent treatments. Nanoparticle clearance should be regarded as a context-dependent design parameter rather than a universal limitation. Rational control of clearance kinetics may improve both safety and therapeutic effectiveness in next-generation engineered drug delivery systems. Drug delivery ; Nanoparticle ; Rational design ; Clearance ; Metabolic clearance rate ; Surface modification ; PEGylation ; Drug Nanoparticle-Based Drug Delivery ; Inhalation and Respiratory Drug Delivery ; Graphene and Nanomaterials Applications
Authors: Ziming Yu | Song He | Wenli Du
Source: Computational Materials Science (article, 2026-01-12)
Field: Materials Science — Materials Chemistry

A framework for automated extraction and validation of experimental arguments in zeolite synthesis Correctness ; Automation ; Argument (complex analysis) ; Inference ; Representation (politics) ; Frame (networking) ; Semantics (computer science) ; Information extraction Machine Learning in Materials Science ; Zeolite Catalysis and Synthesis ; Scientific Computing and Data Management