相关论文: Computational nanoplasmonics in the quasistatic li…
Interactions between surfaces and proteins occur in many vital processes and are crucial in biotechnology: the ability to control specific interactions is essential in fields like biomaterials, biomedical implants and biosensors. In the…
A near-field optical detection method and its theoretical model are developed, which follow from an algebra-based conclusion: in the localized surface plasmon resonance (LSPR) region, the extinction coefficient of a metal nanosphere is the…
The continuum theory applied to bimolecular electrostatics leads to an implicit-solvent model governed by the Poisson-Boltzmann equation. Solvers relying on a boundary integral representation typically do not consider features like…
Credibility building activities in computational research include verification and validation, reproducibility and replication, and uncertainty quantification. Though orthogonal to each other, they are related. This paper presents…
Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density…
The Poisson-Boltzmann equation (PBE) is a relevant partial differential equation commonly used in biophysical applications to estimate the electrostatic energy of biomolecular systems immersed in electrolytic solutions. A conventional mean…
Radiomics enables the extraction of quantitative biomarkers from medical images for precision modeling, but reproducibility and scalability remain limited due to heterogeneous software implementations and incomplete adherence to standards.…
We present the latest version of micromegas, a code that calculates the relic density of the lightest supersymmetric particle in the MSSM. All tree-level processes for the annihilation of the LSP are included as well as all possible…
Real-time remote sensing applications like search and rescue missions, military target detection, environmental monitoring, hazard prevention and other time-critical applications require onboard real time processing capabilities or…
Stellar abundance analysis relies on flexible, high-performance spectral synthesis. To meet these needs, we present PySME v1.0, an updated Python implementation of Spectroscopy Made Easy (SME) designed for precise and survey-scale modelling…
We report on measurements of visible extinction spectra of semicontinuous silver nanoshells grown on colloidal silica spheres. We find that thin, fractal shells below the percolation threshold exhibit geometrically tunable plasmon…
Subwavelength resonators, ranging from single atoms to metallic nanoparticles, typically exhibit a narrow-bandwidth response to optical excitations. We computationally design and experimentally synthesize tailored distributions of silver…
Subwavelength resonators, ranging from single atoms to metallic nanoparticles, typically exhibit a narrow-bandwidth response to optical excitations. We computationally design and experimentally synthesize tailored distributions of silver…
Nano-composite films of Tin Sulfide (SnS) and silver (Ag) fabricated by thermal evaporation showed two prominent peaks in the visible region of their extinction spectra. Theoretical modeling of the extinction spectra suggest that these two…
Experimental and theoretical studies of colloidal nanoparticles have primarily focused on accurate characterization and simulation of observable characteristics, such as resonant wavelength. In this Letter, we tackle the optimal design of…
Two-dimensional transition metal dichalcogenides (TMDCs), as promising alternative plasmonics supporting materials to graphene, exhibit potential applications in sensing. Here, we propose an ultrasensitive, accurate long-range surface…
NIT is a super fine-grained nuclear emulsion which has a detection capability for ionizing particle with nanometric resolution and record the track by a line of silver nanograin with a various of shape and size. The particle tracks need to…
Despite tremendous potential of highly sensitive electronic detection of bio-molecules by nanoscale biosensors for genomics and proteomic applications, many aspects of experimentally observed sensor response (S) are unexplained within…
The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to enhance physics sensitivity while still meeting data processing time constraints. In…
PySR is an open-source library for practical symbolic regression, a type of machine learning which aims to discover human-interpretable symbolic models. PySR was developed to democratize and popularize symbolic regression for the sciences,…