Raihana belkacem2026-08-20Zenodo (CERN European Organization for Nuclear Research)
This work introduces a Physics-Informed Neural Network (PINN) framework tailored for solving the Schrödinger equation in quantum mechanical systems. By incorporating the fundamental physical laws governed by the Schrödinger equation directly into the loss function, the model accurately predicts quantum wave functions…
Model Reduction and Neural NetworksMachine Learning in Materials ScienceQuantum many-body systems
Олег Ивченко、Iryna Ivchenko2026-08-20Zenodo (CERN European Organization for Nuclear Research)
Research article: Multimodal AI in Scientific Discovery: 2025 Benchmarks in Drug Discovery and Materials Science (Draft)
Artificial Intelligence in Healthcare and EducationComputational Drug Discovery MethodsMachine Learning in Materials Science
Jincheng Zhang2026-08-20Zenodo (CERN European Organization for Nuclear Research)
This paper explores the concept of computational plasticity, focusing on the development and analysis of algorithms designed to mimic and potentially surpass the adaptive capabilities observed in biological systems. The core premise is that complex adaptive behaviors, particularly those associated with recovery from d…
Machine Learning in Materials ScienceModel Reduction and Neural NetworksGene Regulatory Network Analysis
Jyothi M Girisankar M*2026-08-20Zenodo (CERN European Organization for Nuclear Research)
Delivering protein and peptide therapeutics through the oral route continues to be a difficult problem, mainly because these molecules break down so readily in the gastrointestinal tract and struggle to cross biological membranes. Their fragility and fast enzymatic turnover typically translate into poor bioavailabilit…
Silk-based biomaterials and applicationsRNA Interference and Gene DeliverySurface Modification and Superhydrophobicity
Tapas Bar、David Pesquera、Timm Swoboda 等 8 位作者2026-08-20arXiv (Cornell University)
We report asymmetric kinetics in thermally driven metal-insulator transitions (MITs) in 1T-TaS$_2$. Using combined transport, calorimetric, and Raman measurements, we show that the transition proceeds via burst-like avalanches during cooling, while remaining continuous during heating. Although bulk transport is masked…
Organic and Molecular Conductors ResearchMaterial Dynamics and PropertiesThermal properties of materials
Jincheng Zhang2026-08-20Zenodo (CERN European Organization for Nuclear Research)
The concept of symmetry has long served as a cornerstone in the formulation of physical laws and mathematical structures. Classical symmetry refers to transformations that leave a system's observable configuration unchanged. In this work we introduce a complementary notion, which we call deep symmetry, defined as the…
Neural Networks and Reservoir ComputingMachine Learning in Materials ScienceModel Reduction and Neural Networks
Jeremiah Lipp、Ismail Paykar、Ritubarna Banerjee 等 8 位作者2026-08-20ACS Omega
Abstract High sensitivity powder X-ray diffraction has been employed to investigate the room temperature oxidation of a series of noble metals supported on an amorphous silica, using a recently developed Rietveld analysis for ultrasmall (<2 nm) supported nanoparticles. It is found that Pt, Pd, Ir, and Rh are mostly ox…
X-ray Diffraction in CrystallographyX-ray Spectroscopy and Fluorescence AnalysisMesoporous Materials and Catalysis
Xin Fu、Xiao-Ke Qiao、Huang Hai-fei 等 9 位作者2026-08-20ACS Applied Electronic Materials
Abstract Room-temperature mid- and far-infrared photodetectors are critical for next-generation sensing and communication, yet their development is severely hindered by the prohibitive cooling requirements of conventional state-of-the-art materials and the restricted 1200 nm cut-off wavelength of emerging earth-abunda…
Advanced Thermoelectric Materials and DevicesChalcogenide Semiconductor Thin Films2D Materials and Applications
Anthony SANTANA2026-08-20Zenodo (CERN European Organization for Nuclear Research)
AbstractSimulating electronic transport properties and scattering networks within continuous condensed matter physicspresents an intractable computational barrier due to the factorial scaling of infinite continuum path permutations.This paper introduces a unified framework that utilizes Ewin Tang’s dequantization matr…
Advanced Physical and Chemical Molecular InteractionsNanopore and Nanochannel Transport StudiesBlock Copolymer Self-Assembly
A. Cano2026-08-20arXiv (Cornell University)
Whether a quantum system with a double-well effective potential undergoes spontaneous symmetry breaking depends not only on the potential landscape but also on the kinetics and the coupling with additional degrees of freedom. Here we introduce a quasi-exactly solvable model to study this problem in the context of ferr…
Organic and Molecular Conductors ResearchFerroelectric and Negative Capacitance DevicesFerroelectric and Piezoelectric Materials
Devshankar Dwivedi*1, Sunil Kumar Shah1, B. K. Dubey2, Deepak Basedia22026-08-20Zenodo (CERN European Organization for Nuclear Research)
Background: Green synthesis of metal nanoparticles using plant extracts has gained considerable attention due to its eco-friendly nature, cost effectiveness, and enhanced biocompatibility. Copper nanoparticles exhibit promising antimicrobial and physicochemical properties, making them suitable for pharmaceutical and b…
Pharmacology and Nanomedicine ResearchMedicinal Plant ResearchNanoparticles: synthesis and applications
Khanh Duy Nguyen、Gabriele Berruto、Yunhe Bai 等 10 位作者2026-08-20arXiv (Cornell University)
Exciton condensates provide a platform to study quasiparticle pairing, Bose-Einstein condensation-Bardeen-Cooper-Schrieffer (BEC-BCS) crossover, and excitonic topological phenomena. Achieving a nonequilibrium exciton condensate allows the ultimate tunability of these emergent phenomena. Yet, evidence of a light-induce…
Topological Materials and Phenomena2D Materials and ApplicationsOrganic and Molecular Conductors Research
Martin Noirmont2026-08-20Zenodo (CERN European Organization for Nuclear Research)
Large language models generate fluent text by collapsing a high-dimensional representation onto a next-token distribution. That collapse is computationally convenient and theoretically dangerous. If one treats the residual set of linguistically compatible worlds as an uncollapsed phase space - the space of what langua…
Big Data and Digital EconomyMachine Learning in Materials ScienceQuantum many-body systems
Yuxuan Tang、Keith T. Butler2026-08-20arXiv (Cornell University)
Heterogeneous interfaces underpin technologies from microelectronics to energy conversion and storage, but their configurational complexity precludes exhaustive first-principles screening of interface registries. Although data-driven approaches can alleviate this burden, they remain limited by sparse interface dataset…
Advanced Chemical Physics StudiesMachine Learning in Materials ScienceElectronic and Structural Properties of Oxides
和行 河盛、GoogleAI2026-08-20Zenodo (CERN European Organization for Nuclear Research)
This paper provides a novel reinterpretation of the inherent imbalance between additive and multiplicative structureswithin the ABC Conjecture (Oesterl´e–Masser Conjecture) through the lens of 2-Dimensional Square Symmetry. We proposethat the continuous scale transformation via the “Theta-link” (Θ-link) in Shinichi Mo…
Advanced Combinatorial MathematicsQuasicrystal Structures and PropertiesFinite Group Theory Research
Jincheng Zhang2026-08-20Zenodo (CERN European Organization for Nuclear Research)
This paper explores the fundamental question of how much historical information is necessary for accurate prediction. We investigate whether predicting future states solely based on the current state [P(x_t)] is sufficient, or if incorporating past states [P(x_t, x_{t-1}, ..., x_0)] is required. We introduce a key con…
Parallel Computing and Optimization TechniquesGaussian Processes and Bayesian InferenceMachine Learning in Materials Science
Jincheng Zhang2026-08-20Zenodo (CERN European Organization for Nuclear Research)
This paper investigates the algorithmic prediction of phase transitions, focusing on a simplified model where resource availability dictates the likelihood of a phase transition occurring. We posit a scenario where a resource, denoted as *r*, is available, and a probability *P(r)* represents the likelihood of a phase…
Stochastic Gradient Optimization TechniquesMachine Learning in Materials ScienceFerroelectric and Negative Capacitance Devices
R. Srinivasan、N. Karthikeyan、P. Thiruramanathan 等 5 位作者2026-08-20International Journal of Nanoscience
Cerium oxide (CeO 2 ) nanoparticles synthesized through a co-precipitation route were characterized by X-ray powder diffraction (XRD), where peak broadening analysis was employed to estimate crystallite size, microstrain, stress, and deformation energy density. The Williamson-Hall (W-H) and Scherrer methods were emplo…
Microstructure and mechanical propertiesBoron and Carbon Nanomaterials ResearchX-ray Diffraction in Crystallography
Sangay Wangdi, Sonam Dendup, Sonam Dorji2026-08-20Zenodo (CERN European Organization for Nuclear Research)
In this study we have performed first principle calculations to study the electronic and its resulting thermoelectric properties of SnSb alloy within the framework of density functional theory (DFT). Generalized Gradient Approximation (GGA) is employed to model the exchange and correlation of KohnSham Eigen states. Th…
Thermal properties of materialsHeusler alloys: electronic and magnetic propertiesAdvanced Thermoelectric Materials and Devices
Balwant Singh Chauhan、Priyanka Sharma、Rie Y. Umetsu 等 4 位作者2026-08-20arXiv (Cornell University)
Magnetoelectric (ME) phenomena in emerging material classes, such as two-dimensional van der Waals (vdW) magnets and Single-Molecule Magnets (SMMs), hold immense promise for next-generation cryogenic memory and quantum technologies. However, ME coupling in these systems predominantly manifests at low temperatures, mak…
2D Materials and ApplicationsMultiferroics and related materialsMagnetism in coordination complexes