jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rohit Goswami | H. Jónsson
Source: ChemPhysChem (article, 2026-02-23)
Field: Materials Science — Materials Chemistry

Adaptive Pruning for Increased Robustness and Reduced Computational Overhead in Gaussian Process Accelerated Saddle Point Searches Gaussian process (GP) regression provides a strategy for accelerating saddle point searches on high-dimensional energy surfaces by reducing the number of times the energy and its derivatives with respect to atomic coordinates need to be evaluated. The computational overhead in the hyperparameter optimization can, however, be large and make the approach inefficient. Failures can also occur if the search ventures too far into regions that are not represented well enough by the GP model. Here, these challenges are resolved by using geometry-aware optimal transport measures and an active pruning strategy using a summation over Wasserstein-1 distances for each atom-type in farthest-point sampling, selecting a fixed-size subset of geometrically diverse configurations to avoid rapidly increasing cost of GP updates as more observations are made. Stability is enhanced by a permutation-invariant metric that provides a reliable trust radius for early-stopping and a logarithmic barrier penalty for the growth of the signal variance. These physically motivated algorithmic changes prove their efficacy by reducing to less than a half the mean computational time on a set of 238 challenging configurations from a previously published data set of chemical reactions. With these improvements, the GP approach is established as a robust and scalable algorithm for accelerating saddle point searches when the evaluation of the energy and atomic forces requires significant computational effort. Maxima and minima ; Gaussian process ; Robustness (evolution) ; Logarithm ; Saddle point ; Computational complexity theory ; Parametric statistics ; Correctness ; Hessian matrix Machine Learning in Materials Science ; Gaussian Processes and Bayesian Inference ; Computational Drug Discovery Methods
Authors: Tomas Aidukas | Ilnura Usmanova | Benjamín Béjar Haro | Maarten Nachtegaal | Adam H. Clark
Source: Journal of Synchrotron Radiation (article, 2026-03-17)
Field: Materials Science — Materials Chemistry

Denoising framework for X-ray absorption spectroscopy data X-ray absorption spectroscopy (XAS) is a powerful tool for probing the structural and electronic properties of materials, but its analysis is often challenging due to the low signal-to-noise ratio of the XAS spectra. Denoising of XAS spectra is particularly challenging because the measured spectral features span a broad range of feature widths. Such spectral feature variability is called non-stationarity. XAS spectra also suffer from energy-dependent noise and are often acquired using non-uniform energy sampling. While a broad range of denoising methods exists, they underperform when dealing with non-stationary and non-uniformly sampled signals. We introduce a novel stationarity warping approach, which transforms XAS spectra into a domain where they appear stationary, resulting in greatly improved denoising performance. This warping approach can be combined with any denoising method. We also implemented advanced denoisers based on Gaussian process regression and a convolutional autoencoder. All of the denoising and stationarity warping methods are packaged into a Python-based denoising software called XASDenoise, which provides a modular, easy-to-use denoising functionality of XAS measurements. Our benchmarking shows that stationarity warping consistently enhances spectral feature preservation and noise suppression across a diverse range of XAS datasets and is applicable to any denoising method. Noise reduction ; Image warping ; Noise (video) ; Pattern recognition (psychology) ; X-ray absorption spectroscopy ; Feature (linguistics) ; Spectral line Machine Learning in Materials Science ; X-ray Spectroscopy and Fluorescence Analysis ; Advanced X-ray and CT Imaging
Authors: G Zhang | Shilin Dong | Lin Guo | Chenghao Li | Xinyu Wang | Gongming Xin
Source: International Journal of Heat and Mass Transfer (article, 2026-03-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Interfacial thermal transport investigation of β-Ga2O3/4H-SiC power devices via active-learning-driven neuroevolution potential Thermal ; Thermal conductivity ; Phonon ; Work (physics) ; Robustness (evolution) ; Coupling (piping) ; Thermal resistance ; Range (aeronautics) ; Atmospheric temperature range Ga2O3 and related materials ; GaN-based semiconductor devices and materials ; High Entropy Alloys Studies
Authors: Jinyu Zhao | Jikai Zhou | Hanyu Zhang
Source: Applied Radiation and Isotopes (article, 2026-03-24)
Field: Materials Science — Materials Chemistry

Enhanced mechanical and shielding properties of heavy concrete: A machine learning approach to mix proportion optimization Bayesian optimization ; Electromagnetic shielding ; Sorting ; Support vector machine ; Monte Carlo method ; Boron carbide ; Attenuation ; Genetic algorithm ; Software ; Linear regression Radiation Shielding Materials Analysis ; Graphite, nuclear technology, radiation studies ; Effects of Radiation Exposure
Authors: Beomgu Kang | Munendra Singh | Hyunseok Seo | Hyun Wook Park | Hye-Young Heo
Source: Physics in Medicine and Biology (article, 2026-02-05)
Field: Materials Science — Materials Chemistry

Physics-informed optimization of saturation-transfer MRI protocols using non-differentiable Bloch models Saturation transfer MR fingerprinting (ST-MRF) is a quantitative molecular MRI method that simultaneously estimates parameters of free water, solute, and semisolid macromolecule protons. The accuracy of these quantification is highly dependent on the choice of acquisition parameters, and thus, the optimization of the data acquisition schedule is crucial to improve acquisition efficiency and quantification accuracy. Herein, we developed a learning-based optimization framework for ST-MRF, incorporating a deep Bloch equation simulator as a surrogate model for the forward Bloch equation solver to enable rapid simulations. Notably, the deep Bloch equation simulator overcomes the non-differentiability of the original model by enabling gradient computation during backpropagation within the physics-informed optimization framework, thereby allowing iterative updates of the acquisition schedule to minimize quantification error. In addition, the proposed method estimated an accurate ΔB<sub>0</sub>map with the inclusion of a minimal number of scans to address B<sub>0</sub>inhomogeneity. B<sub>1</sub>inhomogeneity was corrected by providing a relative<i>B</i><sub>1</sub>map as an input to the quantification network. We validated our approach using Bloch-McConnell equation-based digital phantoms and further evaluated the performance of the proposed optimized ST-MRF framework in<i>in vivo</i>experiments. Our results showed that the optimal ST-MRF schedule outperformed other data acquisition schedules with regard to quantification accuracy. In addition, we enhanced the<i>in vivo</i>quantitative maps by correcting motion artifacts and suppressing noise using self-supervised learning techniques. The optimal ST-MRF approach could generate accurate and reliable multi-tissue parameter maps within a clinically acceptable time. Bloch equations ; Data acquisition ; Solver ; Computation ; Schedule ; Backpropagation ; Noise (video) ; Deep learning Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: Aleksandr Avdoshin | Nikita A. Matsokin | Thanh-Nam Huynh | Dmitry I. Sharapa | Karin Fink | Felix Studt | Wolfgang Wenzel | Mariana Kozlowska
Source: npj Computational Materials (article, 2026-03-24)
Field: Chemistry — Inorganic Chemistry

Multiscale kinetic model of ethylene oligomerization in Ni-NU-1000 metal-organic framework Abstract Single-atom catalysts (SACs) provide isolated, well-defined metal sites that are suited for mechanistic modeling in porous materials such as metal-organic frameworks (MOFs). However, the influence of framework topology and mass transport on catalytic outcomes remains poorly understood. Here we develop a multiscale kinetic model for ethylene oligomerization in Ni-grafted NU-1000 that combines density functional theory (DFT)-derived free-energy barriers with adsorption and diffusion descriptors. The framework predicts product distributions under realistic reaction conditions. The simulations show that flow -mode operation favors selective C 4 H 8 formation across a temperature range. This selectivity window progressively narrows with increasing effective diffusion length and catalytic-site density, as longer residence times enhance chain growth beyond dimerization. In contrast, batch -mode operation shifts the product distribution toward heavier olefins. These trends provide practical guidance for tuning operating conditions and material properties to achieve desired selective Ni-MOF catalysts. Catalysis ; Diffusion ; Ethylene ; Product (mathematics) ; Kinetic energy ; Adsorption ; Work (physics) ; Mass transport ; Density functional theory Metal-Organic Frameworks: Synthesis and Applications ; Zeolite Catalysis and Synthesis ; Catalysts for Methane Reforming
Authors: Yongsheng Zhao
Source: ChemRxiv (article, 2026-02-09)
Field: Materials Science — Polymers and Plastics

Phase-Locked Dynamics: Decoupling Mechanical Stability and Reprocessability in Vitrimer Elastomers Vitrimers have emerged as a powerful class of dynamic polymer networks, yet their design has been largely governed by chemical exchange kinetics. This chemistrycentric view, however, falls short of rationalizing the persistent trade-off between mechanical stability and reprocessability in vitrimer elastomers. Here, we introduce Phase-Locked Dynamics (PLD) as a physics-based framework in which dynamic covalent bond exchange is hierarchically confined by multiphase architectures, including crystalline domains, supramolecular clusters, entanglement networks, and filler-induced physical locks. In PLD systems, relaxation processes are deliberately separated across length and time scales, enabling dynamic bonds to remain chemically active while mechanically latent under service conditions. We further discuss how nonequilibrium processing fields selectively activate exchange pathways by coupling multiscale relaxation modes, offering a route to program vitrimer topology and anisotropy without altering intrinsic bond chemistry. By integrating polymer physics, simulation-guided insights, and emerging experimental evidence, this Perspective establishes Phase-Locked Dynamics as a general design principle for vitrimer elastomers with decoupled mechanical stability and processability. Elastomer ; Decoupling (probability) ; Supramolecular chemistry ; Stress relaxation ; Molecular dynamics ; Polymer ; Relaxation (psychology) ; Anisotropy ; Non-equilibrium thermodynamics Polymer composites and self-healing ; Advanced Materials and Mechanics ; Hydrogels: synthesis, properties, applications
Authors: Manoharan Karthik | S. Sathishkumar | Rajendran Sridevi | Raj Boopathiraja | S. Nirmaladevi
Source: Energy Storage (article, 2026-01-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Design of Polypyrrole‐Induced Nickel Disulfide ( <scp> NiS <sub>2</sub> </scp> ) Based Positive Electrode for Asymmetric Supercapacitor Applications ABSTRACT Polypyrrole composited NiS 2 composite was easily synthesized using a hydrothermal and chemical polymerization technique. Two distinct composites (NS@P1 and NS@P3) were created by varying the polymer precursors stoichiometric ratio. The NS@P3 electrode exhibits a high surface area of 68 m 2 g 1 compared to other NS (46.4 m 2 g −1 ) and NS@P1 (59.3 m 2 g −1 ). The polypyrrole composited electrode exhibits excellent performance in electrochemical behavior. The NS@P3 electrode gives a huge specific capacitance of 1356 Fg −1 at 0.5 Ag −1 compared to other electrode of NS (452 g −1 ) and NS@P1 (874 g −1 ). The NS@P3 electrode's capacitive and diffusive mechanism were analyzed by using the Trasatti method. The assembled ASC‐NS@P3//AC exhibits a high energy density of 68 Wh/kg and a power density of 646 W/kg. The prospective utilization of the NS@P3 composite as energy storage electrode materials for supercapacitor applications is confirmed by the enormous specific capacitance, energy and power delivered by the built ASC device. Supercapacitor ; Electrode ; Polypyrrole ; Capacitance ; Composite number ; Power density ; Electrochemistry ; Polymerization Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Electrochemical sensors and biosensors
Authors: Peter Serles | Alianna Maguire | Thomas Butruille | Jet Lem | S Yang | Pedro Guerra Demingos | Sahar Choukir | Michel J.R. Haché | Boran Kumral | Katherine Min Jia | Charles Jia | Yu Zou | Chandra Veer Singh | Carlos M. Portela | Jun Lou | P. M. Ajayan | Tobin Filleter
Source: Advanced Functional Materials (article, 2026-02-22)
Field: Materials Science — Materials Chemistry

Quasi‐Static to Supersonic Energy Absorption of Nanoarchitected Tubulanes and Schwarzites ABSTRACT Nanoarchitected metamaterials exhibit exceptional specific strength and energy absorption under quasi‐static conditions, but their performance scaling toward high strain rates is critical for their adoption in dynamic loading applications. Using energy absorptive carbon nanoarchitectures of Tubulanes and Schwarzites, we demonstrate their mechanical resilience for strain rates spanning twelve orders of magnitude from = 10 −3 to 10 8 s −1 . Quasi‐static testing reveals specific strengths approaching the Suquet limit for Tubulane architectures with failure strain exceeding ε = 26%, the combination of which produces the highest quasi‐static specific energy absorption of any architected material at Ω/ρ = 321 ± 38 J g −1 . Distinct from bulk ceramics, these carbon nanoarchitectures show strain rate‐independent mechanical properties under uniaxial compression from = 10 −3 to 10 2 s −1 . Molecular dynamics simulations of complete unit cells highlight atomic reconfiguration to enable high failure strain and energy absorption. Micro‐ballistics testing at impact velocities up to 900 m s −1 demonstrate exceptional resilience to impact with shielding up to 687 m s −1 for 12 µm thick Tubulanes and ultrahigh specific inelastic energy absorption of 865 J g −1 at = 10 8 s −1 . Collectively, this study highlights the marked promise of pyrolytic carbon and its nanoarchitecture for translation beyond quasi‐static conditions toward supersonic mechanical resilience with pressing impacts in ballistics defence, protective equipment, and micro‐asteroid shielding. Supersonic speed ; Resilience (materials science) ; Absorption (acoustics) ; Strain (injury) ; Carbon fibers ; Strain rate ; Plasticity ; Energy (signal processing) Boron and Carbon Nanomaterials Research ; Cellular and Composite Structures ; High-Velocity Impact and Material Behavior
Authors: Abdul Jarami | Youssef El Amrani | Khadija Benjelloun
Source: Open Access Research Journal of Engineering and Technology (article, 2026-01-27)
Field: Materials Science — Materials Chemistry

Metal-Ion Batteries with MXene Electrodes: State of the Art and Perspectives MXenes are an emerging family of two-dimensional layered materials composed of transition-metal carbides, nitrides, and carbonitrides that have attracted broad attention because of their unusual combination of properties. Since their discovery, their metallic-level electrical conductivity, high accessible surface area, adjustable surface terminations, and lamellar architecture have made them strong candidates for electrochemical energy storage. Across a wide range of battery chemistries, including lithium-ion, sodium-ion, lithium sulfur, and zinc-ion systems, MXenes have been explored as fast-charging electrodes, conductive frameworks that improve electron transport, building blocks in performance-boosting composites, and even as current-collector modifications. Among these functions, one of the most central is their direct participation as charge-storing host materials. In this review, I summarize recent advances in the synthesis and characterization of MXenes and critically assess their use as active materials in divalent metal-ion batteries, with a focus on strategies that improve electrochemical performance. I also examine the dominant charge-storage pathways and how they evolve in pure MXenes versus MXene-based composites within these multivalent systems. Finally, I highlight key limitations and open challenges and outline future directions, emphasizing microstructure engineering as a practical route to designing MXenes that deliver stronger divalent-ion storage performance. MXenes ; Battery (electricity) ; Characterization (materials science) ; SPARK (programming language) ; Key (lock) ; Electrical conductor MXene and MAX Phase Materials ; Advancements in Battery Materials ; Advanced Battery Materials and Technologies
Authors: Nicholas O. Ongwen | Adel Bandar Alruqi
Source: Inorganics (article, 2026-04-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Structural, Electronic, and Thermoelectric Insights into the Novel K2OsCl3Ag3 and Rb2OsCl3Ag3 Perovskites The field of perovskites continues to advance each day, with new materials being discovered in order to eliminate the toxic and less efficient ones. Some of the challenges currently facing the perovskite industry include coming up with materials with higher electrical conductivity and lower thermal conductivity, as well as p-type semiconductors. In an attempt to address these challenges, this study modeled two novel perovskites from potassium hexachloroosmate (VI) (K2OsCl6) by replacing some of the chlorine atoms with those of silver, then characterized their structural, electronic (using both conventional and hybrid functionals), and thermoelectric properties using Quantum Espresso and BoltzTrap2 codes. The calculations were performed within the framework of density functional theory. The results showed that the novel materials exhibited higher density, lower thermal conductivity, lower band gaps, and positive Hall coefficient, unlike the K2OsCl6 sample. These materials can thus be used in areas such as in p–n junctions, thermoelectric devices, and optoelectronic devices. However, since this study was purely computational, the properties need to be verified through an experimental study. Thermoelectric effect ; Perovskite (structure) ; Thermoelectric materials ; Thermal conductivity ; Thermal ; Field (mathematics) ; Electrical resistivity and conductivity ; Density functional theory Heusler alloys: electronic and magnetic properties ; Perovskite Materials and Applications ; Thermal Expansion and Ionic Conductivity
Authors: Rajendra Kumar Challa | M. S. S. Bharathi | Rahul Murali | Venugopal Rao Soma | Sai Santosh Kumar Raavi
Source: arXiv (Cornell University) (article, 2026-03-05)
Field: Materials Science — Materials Chemistry

Beam Geometry-Controlled Nonequilibrium Formation of WS2/CsPbBr3 Hybrids and Interfacial Carrier Dynamics Perovskite based nanocomposites provide a versatile platform for tailoring light matter coupling and carrier injection in low dimensional optoelectronics. In particular hybrid structures incorporating transition metal dichalcogenides (TMDCs) enable tunable band alignment and excitonic dynamics. However, the central challenge lies in the scalable synthesis of defect controlled layered TMDCs suitable for coherent interfacial coupling. Here we demonstrate geometry dependent femtosecond (fs) laser ablation in liquid as a scalable strategy for defect controlled exfoliation of WS2 and in situ formation of WS2/CsPbBr3 nanocomposite. Using 50 fs pulses at identical fluence, we directly compare Gaussian and Bessel beam profiles to elucidate how spatial energy distribution governs nonlinear carrier generation, Coulomb stress and electron-lattice energy transfer. Multiphysics modeling combining nonlinear absorption, Coulomb instability criteria and two temperature dynamics reveals that the axially extended, weakly diffracting Bessel profile excites carrier densities above the electronic destabilization threshold while reducing the peak lattice heating. In contrast, Gaussian excitation concentrates energy within the focal volume, promoting rapid thermalization and defect formation. Spectroscopic analysis reveals reduced trap assisted recombination and enhanced excitonic stability in Bessel processed samples. Transient absorption spectroscopy (TAS) further demonstrates prolonged carrier lifetime. Extending this approach, single step ablation yields WS2/CsPbBr3 hybrids exhibiting Type-I band alignment and geometry dependent interfacial carrier injection, evidenced by photoluminescence quenching and modified ultrafast decay dynamics. Femtosecond ; Exciton ; Photoexcitation ; Filamentation ; Photoluminescence ; Bessel beam ; Picosecond ; Plasmon ; Excitation ; Ultrafast laser spectroscopy 2D Materials and Applications ; Perovskite Materials and Applications ; Advanced Fiber Laser Technologies
Authors: H. M. Ragab | N. S. Diab | Rosilah Ab Aziz | Shimaa Mohammed Aboelnaga | A. Al Ojeery | Tahani M. Alresheedi | M. O. Farea
Source: RSC Advances (article, 2026-01-01)
Field: Materials Science — Polymers and Plastics

Tuning the electrical and optical performance of PVA/PANI films <i>via</i> Fe <sub>2</sub> O <sub>3</sub> nanorods for advanced energy storage and optoelectronic devices PVA/PANI-Fe<sub>2</sub>O<sub>3</sub> nanocomposite films were successfully fabricated <i>via</i> a solution casting method with Fe<sub>2</sub>O<sub>3</sub> nanorod loadings ranging from 1.0 to 4.5 wt% to tailor their structural, optical, and electrical properties for optoelectronic applications. XRD analysis revealed a progressive reduction in crystallite size (from ∼4.2 to ∼3.0 nm) and enhanced amorphous character, attributed to the disruption of the native hydrogen-bonding network in the polymer matrix by Fe<sub>2</sub>O<sub>3</sub> nanorods. FTIR results confirmed strong interfacial interactions through hydrogen bonding between Fe<sub>2</sub>O<sub>3</sub> and PVA/PANI chains. Optical measurements demonstrated a red shift in absorption edges and a significant narrowing of both direct and indirect band gaps, accompanied by an increase in Urbach energy, indicating the formation of localized states and increased structural disorder. These changes are associated with the modified electronic structure induced by Fe<sub>2</sub>O<sub>3</sub> incorporation. Furthermore, dielectric analysis revealed multiple conduction regimes, with electrical conductivity improving by nearly two orders of magnitude due to the formation of interconnected charge transport pathways facilitated by the nanorods. Overall, the incorporation of Fe<sub>2</sub>O<sub>3</sub> nanorods effectively tunes the physicochemical properties of PVA/PANI films, making them promising candidates for flexible optoelectronic and energy-related applications. Nanorod ; Nanocomposite ; Casting ; Ranging ; Energy storage ; Nanowire Polymer Nanocomposite Synthesis and Irradiation ; Conducting polymers and applications ; Electrospun Nanofibers in Biomedical Applications