An implicit simplified unified gas-kinetic solver is developed and incorporated into the open-source CFD platform OpenFOAM for efficient steady-state simulation of multiscale nonequilibrium gas flows. The solver adopts an implicit macro-microscopic coupled evolution framework with dual time scales: fluxes are evaluated over a physical time step, while the governing equations are advanced with a larger numerical time step to accelerate convergence. A matrix-free formulation combined with point-relaxation symmetric Gauss–Seidel (PR-SGS) iterations is employed to reduce computational overhead. The implementation supports both structured and unstructured velocity discretizations, offering flexibility to balance simulation accuracy and computational cost. Benchmark tests covering a wide range of Knudsen numbers are conducted to validate the accuracy and efficiency of the proposed solver. Furthermore, a hybrid X-space parallelization strategy, which operates in both physical and velocity spaces, is adopted to further enhance the efficiency of large-scale simulations.
Accurate electrochemical-thermal simulation of lithium-ion batteries (LIBs) is critical for improving performance, ensuring safety, and extending service life. However, conventional pseudo-two-dimensional (P2D) models often fail to capture in-plane inhomogeneities, particularly in large-format pouch cells, due to geometric simplifications. While pseudo-four-dimensional (P4D) models can resolve such effects, their practical use is limited by the high computational cost associated with nonlinear iterative solution procedures. This study introduces a non-iterative electrochemical–thermal solution framework based on a pseudo-four-dimensional (P4D) modeling approach, which incorporates full three-dimensional (3D) spatial resolution alongside a pseudo-dimension representing intra-particle lithium diffusion, enabling high-fidelity analysis of internal gradients in large-format LIBs. To mitigate the computational burden of P4D simulations, an efficient non-iterative numerical scheme is developed by combining staggered time integration, Taylor-series-based linearization, and an adaptive time-stepping strategy guided by output gradients. The governing equations are reformulated into a sequence of linear subsystems, allowing the coupled system to be solved without nonlinear iterations. Validation against experimental discharge data and commercial finite element simulations demonstrates that the proposed method achieves comparable accuracy while reducing computational time by up to 5-fold. The proposed method is further applied to analyze spatial inhomogeneities in large-format pouch cells under varying aspect ratios and charging conditions. Results show that spatial gradients in electrolyte concentration, electrode overpotential, and interfacial reaction rates become increasingly pronounced with larger cell geometries and higher C-rates. These in-plane non-uniformities significantly influence voltage dynamics and remain unresolved in lower-dimensional models such as the P2D model. In particular, the P4D framework enables precise identification of localized regions susceptible to lithium plating–insights inaccessible in conventional modeling approaches. Overall, the results demonstrate that the proposed non-iterative framework enables efficient and scalable high-fidelity P4D simulations, providing a practical pathway for the design and analysis of large-format lithium-ion batteries. PROGRAM SUMMARYProgram Title: VOLTA_PXD: Variation of Optimized & Lightweight Toolkits for Advanced Batteries – Pseudo-X-Dimensional electrochemical-thermal model CPC Library link to program files: (to be added by Technical Editor) Developer’s repository link: https://github.com/MPMC-Lab/VOLTA_PXD Licensing provisions: MIT Programming language: MATLAB (R2020 or later recommended) Supplementary material: Sample input files, benchmark cases, and plotting scripts are available in the GitHub repository. Journal reference of previous version: N/A Does the new version supersede the previous version?: N/A Reasons for the new version: N/A Summary of revisions: N/A Nature of problem (approx. 50-250 words):Modeling large-format lithium-ion batteries (LIBs) requires resolving strongly coupled multi-physics processes, including three-dimensional mass and charge transport, nonlinear electrochemical kinetics, and heat generation. Conventional pseudo-two-dimensional (P2D) models often neglect in-plane gradients, while fully resolved 3D or P4D models become computationally expensive due to the need for nonlinear iterative solvers at each time step. These iterative procedures constitute the primary computational bottleneck, limiting the practical use of high-fidelity models for large-scale simulations and parametric studies. Accurately predicting voltage response, thermal behavior, and spatial degradation risks–especially under high C-rates and varying geometries–remains a key challenge in battery modeling. Solution method (approx. 50-250 words):VOLTA_PXD implements a pseudo-four-dimensional (P4D) modeling framework, combining full 3D spatial resolution with a pseudo-dimension to capture intra-particle diffusion. The solver introduces a fully non-iterative electrochemical–thermal solution strategy, in which the governing equations are reformulated into a sequence of linear subsystems that can be solved without nonlinear iterations. The method employs finite-difference discretization on structured grids and solves the mass, charge, and energy conservation equations in a decoupled manner. Nonlinearities are handled using Taylor-series-based linearization, while staggered time integration decouples the electrochemical and thermal subsystems. As a result, each time step requires only a single linear solve per subsystem, significantly reducing computational cost compared to conventional iterative methods. An adaptive time-stepping scheme based on voltage gradient control further enhances efficiency without sacrificing accuracy. The method is validated against experimental data and commercial FEM tools (COMSOL), demonstrating comparable accuracy with up to a fivefold speedup. Additional comments including restrictions and unusual features (approx. 50-250 words):VOLTA_PXD is designed for efficient simulation of large-format pouch cells under various geometric configurations, including fixed-width and fixed-area designs. The solver includes a built-in uniformity index to quantify spatial inhomogeneities in electrochemical and thermal fields. The MATLAB-based implementation is modular, extensible, and does not require commercial toolboxes or third-party libraries. Current limitations include support for structured Cartesian grids and the assumption of spherical, isotropic active material particles. The code is released under the MIT license and is suitable for both academic and industrial research applications.
The stationary Gross–Pitaevskii equation (GPE) offers the mean-field description of quantized vortices in Bose–Einstein condensates. However, its nonlinear structure and singular behaviour make accurate numerical solutions challenging. In this work, we present a hybrid exponential collocation–Genetic Algorithm (GA) framework to solve the stationary radial GPE in the absence of an external trapping potential. The condensate wavefunction has been approximated using a compact exponential basis, while the unknown coefficients are determined through derivative-free global optimization. The proposed formulation transforms the nonlinear boundary-value problem into a global optimization problem without requiring analytical Jacobians or initial guesses. A systematic study was done to find minimum number of independent functions in basis. Results show that six exponential terms can be the best compromise between solution accuracy, residual minimization, and computational efficiency. Numerical solutions were then obtained for vortex winding numbers (ω=1−−10) and were validated against a high-accuracy adaptive collocation benchmark as well as Chebyshev–Gauss–Lobatto collocation, Newton, Shooting (LSODA), and Relaxation methods. The proposed method accurately reproduced stationary vortex profiles and the maximum absolute errors remained less than 6×10−3and competitive RMSE values were found for various winding numbers. The convergence and statistical analyses demonstrate stable optimization behaviour, good repeatability, and robust performance despite the stochastic nature of the GAs. The computed density profiles revealed the expected broadening of vortex cores when the winding number was increased. Also, the threshold-defined vortex-core radius followed a quadratic dependence on winding number. It reflected an increasing influence of the centrifugal kinetic-energy term. Although deterministic methods such as LSODA achieve slightly higher numerical accuracy, the proposed framework provides an attractive balance between accuracy, robustness, and computational flexibility. The method offers a promising optimization-based alternative to solve nonlinear Gross–Pitaevskii boundary-value problems and can be extended to more complex quantum fluid systems.
We present BCA_modern, an open-source Python code for simulating low-energy ion scattering (LEIS) from crystalline surfaces using the binary collision approximation. The code implements pair-specific NLH interatomic potentials [1] for 70 ion–atom combinations (He+, Ne+, Ar+, Kr+, Xe+ on 14 target elements), position-dependent electronic stopping Se(v, ρ), thermal lattice vibrations, and Hagstrum ion neutralisation. A universal crystal structure module supports 35 built-in structures (zincblende, wurtzite, rocksalt, corundum, cristobalite, FCC metals, BCC metals, diamond cubic), disordered alloys via partial site occupation, and CIF file input. A simulation with automatically generated material and model parameters can be initialised from three required inputs—ion atomic number, crystal name and beam energy—while the beam geometry, temperature, trajectory count and detector acceptance remain user-configurable and must be set to reproduce a specific experiment. We validate the code through: (i) kinematic factor verification yielding machine-precision agreement for 54 ion–target pairs; (ii) backscattering spectra for He+→CaSiO3 under the normal-incidence, 145∘-detector geometry of a recent BCA/experiment study, recovering spectral features at the single-collision kinematic energies of Ca, Si, and O; (iii) statistical convergence analysis demonstrating ∼ 1% precision at 5000 trajectories; and (iv) comparison with published experimental LEIS conditions for He+→Au and Cu at normal incidence, showing peak position agreement within 1% of the kinematic prediction. Applications to GaP, CdTe, GaAs, and Al2O3 are presented; a companion study applies the same code to detector-induced distortions in low-energy ion scattering [1], [2].
We present the Multiscale Universal Interface 2.0 library, the next major release of the lightweight, header-only C++ library for scalable multiphysics or multiscale code coupling. Designed to lower barriers to integration, this release introduces key enhancements in non-conformal data mapping, coupling algorithms, performance scalability, and language interoperability. A new Radial Basis Function spatial sampler enables conservative data transfer across non-conformal interfaces, while built-in modules support robust relaxation schemes for strongly coupled systems with dynamic interfaces. The addition of a dedicated linear algebra subsystem eliminates previous external dependencies and provides a foundation for advanced interpolation and solver acceleration. Accessibility is further expanded through redesigned wrappers for C, Fortran, and Python, and smart communication strategy improves High-Performance Computing scalability via refined communication strategies. Benchmarks on supercomputers demonstrate near-linear scalability under heavy communication loads. This release represents a significant step toward enabling flexible, high-performance multiphysics simulations across diverse platforms and disciplines. * NEW VERSION PROGRAM SUMMARYProgram Title: Multiscale Universal InterfaceCPC Library link to program files: (to be added by Technical Editor)Developer’s repository link: https://github.com/MxUI/MUILicensing provisions: Apache-2.0/GPLProgramming language: C++Supplementary material: MUI-demo https://github.com/MxUI/MUI-demo and MUI-testing benchmark framework https://github.com/MxUI/MUI-Testing repositoriesNature of problem(approx. 50-250 words):Coupling heterogeneous solvers in multiphysics simulations is challenging due to differences in discretisation, solver structure, time-stepping schemes, and parallel execution models. These differences often lead to complex integration efforts, fragile workflows, and scalability bottlenecks on modern high-performance computing systems. Achieving stable and conservative data exchange across non-conformal interfaces, especially in partitioned coupling scenarios, remains a significant challenge. Strong coupling workflows, where solvers iterate within each time step, demand robust relaxation schemes and consistent interface handling, particularly when the interface topology evolves dynamically. There is a need for a lightweight, flexible, and scalable solution that enables solver independence, supports both strong and weak coupling, and provides built-in tools for interpolation, convergence acceleration, and performant parallel computing. To be truly cross-method, the solution should also accommodate meshless data transfer, dynamic point sets, and multi-language integration, while maintaining high performance and minimal overhead. MUI-v2.0 addresses these challenges by offering a modular, header-only C++ library with MPI-based multiple programs multiple data (MPMD) communication, advanced spatial samplers, built-in coupling algorithm modules, and a dedicated linear algebra subsystem. These are designed to lower the barriers to multiphysics coupling in real-world applications.Solution method(approx. 50-250 words):MUI adopts a modular, header-only C++ design with MPI-based multiple programs multiple data (MPMD) communication to enable scalable and minimally intrusive coupling between heterogeneous solvers. It treats exchanged data as Point Cloud and applies spatial and temporal samplers as part of the receiving workload to interpret and interpolate data across solver boundaries. MUI-v2.0 introduces a meshless Radial Basis Function (RBF) sampler, enabling conservative and consistent data transfer across non-conformal interfaces. To support strong coupling workflows, MUI embeds built-in coupling algorithm modules, including Fixed-Relaxation and Aitken schemes, which operate directly on exchanged data streams. A new linear algebra subsystem provides sparse matrix and vector operations without external dependencies, supporting interpolation setup and solver acceleration. Communication efficiency is improved through performance optimisation and Smart Send, which dynamically maps active regions and minimises unnecessary data exchange. MUI supports multiple interfaces per domain, dynamic point sets, and asynchronous execution. Wrappers for C, Fortran, and Python allow integration with a wide range of scientific codes. Together, these features enable MUI to serve as a robust and extensible framework for partitioned multiphysics simulations.Additional comments including restrictions and unusual features (approx. 50-250 words):MUI-v2.0 is designed as a header-only C++ library with a single dependency on MPI, making it highly portable and easy to integrate into existing solvers. It supports both synchronous and asynchronous execution, and is compatible with grid-based and particle-based solvers. A key feature is its ability to operate on dynamic point sets, enabling robust coupling even when interface topology changes during runtime. MUI supports multiple interfaces per domain and provides built-in monitoring of residuals and relaxation factors for convergence diagnostics. The library includes wrappers for C, Fortran, and Python, each offering dimensional flexibility and full access to core features. MUI’s Smart Send mechanism optimises communication by automatically determining relevant MPI ranks based on geometric overlap, significantly reducing message traffic in large-scale simulations. The RBF sampler supports conservative interpolation with localised computation and parallel scalability, and requires a one-time setup phase involving sparse matrix assembly and conjugate gradient solve. MUI is actively maintained and includes extensive demos and testing infrastructure to support adoption and reproducibility.
Understanding the spatial character of electronic excitations, in particular the distinction between local and charge-transfer. (CT) contributions, is essential in the analysis of excited-state phenomena. However, commonly used approaches often rely on method-specific representations or implicit partitioning schemes, limiting their reproducibility and transferability across electronic-structure frameworks.Domain Assignment and Interface Solution in pYthon (DAISpY, pronounced ”daisy”) presents a standalone and format-agnostic tool for domain-based charge-transfer. (CT) analysis of excited states. The method builds on a general representation of excited states in terms of configuration interaction CI-like amplitudes and aggregates their contributions into domain → domain CT matrices. Orbital contributions are assigned to user-defined spatial domains, enabling a direct and intuitive mapping of electron-hole redistribution between molecular fragments. The formalism consistently treats singles, pairs, and doubles excitations while preserving normalization and avoiding double counting.DAISpY is designed as a modular and reproducible analysis framework, supporting multiple input routes, including electronic-structure checkpoint files and portable data representations. The implementation is independent of any specific quantum chemistry package, ensuring broad applicability. PROGRAM SUMMARY Program title: DAISpY (Domain Assignment & Interface Solution in pYthon)CPC Library link to program files: https://doi.org/10.17632/mhpghs4jck.1Developer’s repository link: https://gitlab.com/pybest-edev/ct-analysisLicensing provisions: GNU General Public License 3Programming language: Python (3.10+) with a C++17 backendSupplementary material: Example datasets, tutorial notebooks, and user documentationNature of problem:The interpretation of electronic excited states in terms of spatial charge redistribution remains non-trivial, particularly when distinguishing local excitations from inter-fragment charge transfer. Standard approaches, such as orbital inspection, density differences, or population analyses, often depend on specific electronic-structure implementations and may lack a reproducible and transferable definition of CT character. Moreover, excited states expressed as configuration interaction CI-like expansions contain contributions from multiple excitation ranks, making it difficult to quantify how electron density moves between molecular fragments in a consistent and fragment-resolved manner across different computational workflows.Solution method:DAISpY provides a standalone framework for domain-based CT analysis by mapping CI-like excitation amplitudes onto user-defined spatial domains. Molecular orbitals are assigned to domains based on their atomic contributions, and excitation weights are accumulated into CT matrices. The method supports singles, pairs, and doubles excitations, with higher-order contributions consistently decomposed into effective one-electron channels to preserve normalization and avoid double counting. The implementation is modular and format-agnostic, supporting multiple input routes (HDF5 checkpoints or portable data directories) and offering CLI & Python API and a graphical interface for domain definition and analysis.Additional comments including restrictions and unusual features: DAISpY is independent of any specific quantum chemistry package and can process data from compatible electronic-structure workflows. Domain definitions are user-controlled and can be created interactively via a graphical interface or provided as labeled coordinate files, ensuring reproducibility. The results depend on the chosen orbital representation, active space, and domain partitioning, and should be interpreted in the context of the underlying electronic-structure method. A native C++ backend is used for performance-critical operations, while the Python layer provides flexibility and integration into automated workflows. The software supports both human-readable reports and spreadsheet-oriented outputs for further analysis.References:Interactive environment for testing the code without installation: https://mybinder.org/v2/gl/pybest-edev%2Fct-analysis/notebook?urlpath=%2Fdoc%2Ftree%2Ftutorial.ipynbS. Jahani, K. Boguslawski, P. Tecmer, The relationship between structure and excited-state properties in polyanilines from geminal-based methods, RSC advances. 13 (40) (2023) 27898–27911.L. Szczuczko, M. Gałyńska, M. H. Kriebel, P. Tecmer, K. Boguslawski, Domain-Based Charge-Transfer Decomposition and Its Application to Explore the Charge-Transfer Character in Prototypical Dyes, J. Chem. Theory Comput. 21 (9) (2025) 4506–4519.L. Szczuczko, J. Szczuczko, M. Gałyńska, K. Boguslawski, A Flexible, Automated, and Basis-Set-Insensitive Domain-Based Charge-Transfer Decomposition for Correlated Wave Functions and Its Application to Inter- and Intramolecular Cases, J. Phys. Chem. Lett. 17 (22) (2026) 6245–6255. PROGRAM SUMMARY Program title: DAISpY (Domain Assignment & Interface Solution in pYthon)CPC Library link to program files: https://doi.org/10.17632/mhpghs4jck.1Developer’s repository link: https://gitlab.com/pybest-edev/ct-analysisLicensing provisions: GNU General Public License 3Programming language: Python (3.10+) with a C++17 backendSupplementary material: Example datasets, tutorial notebooks, and user documentationNature of problem:The interpretation of electronic excited states in terms of spatial charge redistribution remains non-trivial, particularly when distinguishing local excitations from inter-fragment charge transfer. Standard approaches, such as orbital inspection, density differences, or population analyses, often depend on specific electronic-structure implementations and may lack a reproducible and transferable definition of CT character. Moreover, excited states expressed as configuration interaction CI-like expansions contain contributions from multiple excitation ranks, making it difficult to quantify how electron density moves between molecular fragments in a consistent and fragment-resolved manner across different computational workflows.Solution method:DAISpY provides a standalone framework for domain-based CT analysis by mapping CI-like excitation amplitudes onto user-defined spatial domains. Molecular orbitals are assigned to domains based on their atomic contributions, and excitation weights are accumulated into CT matrices. The method supports singles, pairs, and doubles excitations, with higher-order contributions consistently decomposed into effective one-electron channels to preserve normalization and avoid double counting. The implementation is modular and format-agnostic, supporting multiple input routes (HDF5 checkpoints or portable data directories) and offering CLI & Python API and a graphical interface for domain definition and analysis.Additional comments including restrictions and unusual features: DAISpY is independent of any specific quantum chemistry package and can process data from compatible electronic-structure workflows. Domain definitions are user-controlled and can be created interactively via a graphical interface or provided as labeled coordinate files, ensuring reproducibility. The results depend on the chosen orbital representation, active space, and domain partitioning, and should be interpreted in the context of the underlying electronic-structure method. A native C++ backend is used for performance-critical operations, while the Python layer provides flexibility and integration into automated workflows. The software supports both human-readable reports and spreadsheet-oriented outputs for further analysis.References:Interactive environment for testing the code without installation: https://mybinder.org/v2/gl/pybest-edev%2Fct-analysis/notebook?urlpath=%2Fdoc%2Ftree%2Ftutorial.ipynbS. Jahani, K. Boguslawski, P. Tecmer, The relationship between structure and excited-state properties in polyanilines from geminal-based methods, RSC advances. 13 (40) (2023) 27898–27911.L. Szczuczko, M. Gałyńska, M. H. Kriebel, P. Tecmer, K. Boguslawski, Domain-Based Charge-Transfer Decomposition and Its Application to Explore the Charge-Transfer Character in Prototypical Dyes, J. Chem. Theory Comput. 21 (9) (2025) 4506–4519.L. Szczuczko, J. Szczuczko, M. Gałyńska, K. Boguslawski, A Flexible, Automated, and Basis-Set-Insensitive Domain-Based Charge-Transfer Decomposition for Correlated Wave Functions and Its Application to Inter- and Intramolecular Cases, J. Phys. Chem. Lett. 17 (22) (2026) 6245–6255.
We present Version 9 of the freeware MAN (Modal Analysis of Nanoresonators) [Comput Phys Commun 284, 108627 (2023)], a software package for computing, normalizing, and exploiting quasinormal modes (QNMs) to analyze the optical response of electromagnetic resonators. This release substantially extends the capabilities of the original software through three major developments. First, it introduces dedicated models and numerical tools for resonators incorporating two-dimensional materials, including graphene, using a surface-conductivity formulation. Second, it implements a coupled-QNM formalism that computes the complex coupling coefficients between resonator modes directly from the QNMs of the individual resonators. Unlike conventional coupled-mode theory, where these coefficients are often introduced phenomenologically or determined by fitting, MAN evaluates them rigorously from first principles. Third, it provides post-processing tools that determine the Fano parameters governing extinction spectra directly from the computed QNM field distributions. Together, these advances broaden the range of nanophotonic systems accessible to MAN while providing new tools for the quantitative interpretation of complex resonant phenomena.
We present a GPU-accelerated finite-difference frequency-domain (FDFD) eigenmode solver for coaxial half-wave resonator (HWR) cavities in cylindrical coordinates. The solver applies a matrix-free curl–curl operator on a staggered Yee grid, treats curved beam-pipe boundaries with the Dey–Mittra conformal subcell method, and incorporates wall losses through a Leontovich impedance boundary condition (IBC) that yields a complex eigenvalue from which the resonant frequency and unloaded quality factor are obtained directly. The resulting complex, non-Hermitian eigenvalue problem is solved by Rayleigh Quotient Iteration with an inner restarted GMRES solver, implemented entirely in CUDA C. We describe the GPU implementation in detail: the structure-of-arrays data layout, the cylindrical curl kernels, the conformal subcell kernels and their additional memory traffic, the complex IBC arithmetic, and the warp-level reductions for the volume-weighted inner products. A roofline characterization shows the curl–curl operator is memory-bandwidth-bound (arithmetic intensity ≈ 0.72 floating-point operations (FLOPs) per byte); the GPU sustains up to 35% of peak bandwidth and achieves a matrix–vector product (matvec) speedup of up to 26 × over a single CPU thread and 8 × over a 16-thread CPU, consistent with the architectural bandwidth ratio. A grid convergence study confirms second-order accuracy, and validation against CST Microwave Studio® and COMSOL Multiphysics® shows agreement within 0.01% in frequency. A three-step solution strategy isolates the perturbative effects of radial and endcap pipes on a fixed grid. Finally, a single-pass beam dynamics demonstration confirms that the structured cylindrical field maps are used directly by a GPU particle tracker without interpolation, with the computed energy gain matching the expected radial gap voltage.
Trigonal solid-state defects are often subjects of spontaneous symmetry breaking driven by the E⊗e Jahn-Teller effect, reflecting strong electron-phonon coupling. These systems, particularly paramagnetic defect qubits in solids are central for quantum technology applications, where accurate knowledge of their fine-structure parameters – shaped by the complex interplay of spin-orbit and electron-phonon interactions – is essential. We introduce the jahn−teller−dynamics package, a Python code that implements the first-principles approach of [Phys. Rev. X 8, {021063} (2018)] to accurately compute the spin-orbit-phonon entanglement in trigonal defects utilizing the output from density functional theory calculations (DFT) to predict fine-structure parameters of zero-phonon lines (ZPLs), including Zeeman shifts under external magnetic fields. We demonstrate its capabilities on negatively charged Group-IV–vacancy (G4V) defects in diamond: SiV−, GeV−, SnV−, PbV− and the neutral N3V0 defect in diamond, and the CH3O0 methoxy radical. Additionally, we implement a generic electron-phonon code that is capable entangling an arbitrary amount of (i) vibration modes and (ii) electronic levels by (iii) arbitrarily high order of vibronic interaction terms. Exemplarily, we demonstrate the Jahn-Teller multimode problem on the CH3O0 methoxy radical and the Pseudo Jahn-Teller case on the C4H4+ butatrien cation.PROGRAM SUMMARY/NEW VERSION PROGRAM SUMMARYProgram Title: jahn-teller-dynamicsCPC Library link to program files: https://doi.org/10.17632/czcdhwry8v.1Developer's repository link:https://github.com/tbalu98/Jahn-Teller-Dynamicshttps://pypi.org/project/jahn-teller-dynamicsLicensing provisions(please choose one): GPLv3Programming language: Python 3.11Data availability: https://doi.org/21.15109/ARP/EXJKGLNature of problem(approx. 50-250 words): Electron states that have close or degenerate or degenerate energy levels are susceptible to atomic vibrations caused by atomic nuclei that causes the dynamic Jahn-Teller and pseudo Jahn-Teller interaction. Indeed, density functional theory (DFT) and multiconfigurational Hartree-Foch calculations within the Born-Oppenheimer approximation can be employed to determine the electronic structure in different geometrical configurations or determine the spin-orbit coupling strength. However, in order to solve Jahn-Teller problem one has to go beyond the Born-Oppenheimer approximation that is usually well beyond the capabilities of current state-of-art codes. Therefore, a first-principles approach is necessary to accurately determine the fine-structure parameters such as the spin-orbit splitting visible in optical measurements utilizing trigonal color centers and molecules. Solution method(approx. 50-250 words): In jahn−teller−dynamics library we implemented a general formulation of dynamic Jahn-Teller theory, where arbitrary number of electron states and phonon modes interact with each other up to any order. Therefore, the user can freely customize the Hamilton operator of the electron-phonon interaction. We dedicated extra care to the E⊗e dynamic Jahn-Teller interaction, that is very common among point defects. We implemented methodology developed in Refs. [1], [2]. It utilizes the results directly obtained from the VASP[3] density functional theory (DFT) code to formulate the Hamiltonian of the E⊗e Jahn-Teller case. Our solution includes the non-perturbative effect of spin-orbit coupling and the dynamic Jahn-Teller interaction simultaneously, where we observe that these two interactions non-trivially entangle with each other. Our methodology determines the damping of experimentally visible spin-orbit splitting known as Ham [4], [5], [6] reduction factor p that can be identified as electron-phonon renormalization of physical observables such as the renormalization of spin-orbit coupling strength [7], [8], [9], [10] that of trigonal defects. Our code provides a framework that automatically reads and post-processes the DFT results to compute fine-structure parameters and it includes the effect of external magnetic fields.
One major shortcoming of classical and mixed quantum-classical approaches devoted to large helium nanodroplets (HNDs) is the lack of superfluidity. A method, recently published in Chemical Physics Letters, is implemented in DynHeMat to enable the user to take into account helium superfluidity on a phenomenological manner by imposing projectiles colliding with HNDs to maintain their velocity at the critical Landau velocity when they move within the HND. Projectiles can thus enter deeply inside the droplet and, for instance, the stability of weakly-bound complexes in helium can be investigated. Moreover, the database provided with DynHeMat, called ZPAD_DB, contains a new file with the positions and velocities of He70000 equilibrated at T=0.37K for 1.5 ns with the mPL He-He pseudopotential. Output files collecting the HND center-of-mass position and linear momentum as well as the HND total angular momentum are supplied for each trajectory and output files gathering energetic data are somewhat changed. Finally, a few error messages displayed at DynHeMat execution are slightly modified. NEW VERSION PROGRAM SUMMARY Program Title: DynHeMatCPC Library link to program files: https://doi.org/10.17632/3hrfykstvr.2Licensing provisions: GPLv3Programming language: Fortran 90Journal reference of previous version: David A. Bonhommeau, Comput. Phys. Commun. 321 (2026) 110014.Does the new version supersede the previous version?: Yes.Reasons for the new version:The original DynHeMat program [1] enables zero-point averaged dynamics (ZPAD) simulations of pure and doped HNDs but superfluidity cannot be taken into account. The main reason for the new version is the implementation of a phenomenological approach that allows a system embedded in helium to maintain a velocity equal to the critical Landau velocity when it moves within the HND, then mimicking the superfluid nature of helium while maintaining the total energy of the HND constant [2]. This upgrade of the program is supplemented by additional adjustments: some error messages are modified and the content of some output files is altered to make it in better adequacy with the file names.Summary of revisions:The algorithm to include superfluidity on a phenomenological manner in ZPAD simulations [2] is written in the file called lib_Landau.f90. In the DynHeMat source code, this algorithm is sometimes referred as PSLVM algorithm (ie, Phenomenological Superfluidity with Landau Velocity Maintenance) although this name was not introduced in the original paper that presented the method. Some parameters needed by this algorithm are collected in the LANDAU_params module added in lib_modules.f90. The activation or deactivation of the algorithm by the user is made possible by adding in the setup file the keyword SUPERFLUIDITY supplemented by a batch of subkeywords that reflect available options related to the algorithm. Minor changes have also been brought to the main file (main.f90), the makefile (Makefile) and the file that contains the velocity Verlet integrator (lib_vvi.f90) to enable the algorithm to be compiled and run every Landau_every time steps.Information provided in output files has been somewhat altered:•In energ-eq_AAA.dat and energ-prod_AAA.dat files (AAA is an integer corresponding to the trajectory number, which can range from 001 to 999), the total angular momentum is removed from column 5 and the temperature of the HND is added in column 2. Therefore, energ-eq_AAA.dat files are 5-column files in ASCII format that display energies as a function of time for equilibration runs and have the following file structure:Line 1: Comments describing the content of the columns.Lines displayed every print_every_eq time steps: Time (column 1), temperature (column 2), total energy (column 3), kinetic energy (column 4) and potential energy (column 5).energ-prod_AAA.dat files have the same file structure as energ-eq_AAA.dat files but for production runs.•COM_AAA.dat files are created to store the norm and components of the center-of-mass position vector, total linear momentum vector, and total angular momentum vector. They are 13-column files in ASCII format that display HND center-of-mass properties and total angular momentum as a function of time for production runs and have the following file structure:Line 1: Comments describing the content of the columns.Line displayed every print_every_prod time steps: Time (column 1), norm of the center-of-mass position vector (column 2), (x,y,z) components of the center-of-mass position vector (columns 3 to 5), norm of the total linear momentum vector (column 6), (x,y,z) components of the total linear momentum vector (columns 7 to 9), norm of the total angular momentum vector (column 10), (x,y,z) components of the total angular momentum vector (columns 11 to 13).The content of some error messages has been partially modified in lib_Rg-pot.f90 and lib_config.f90, and a configuration file of He70000 equilibrated at 0.37 K for 1.5 ns is supplied in ZPAD_DB, the databank of HND configurations available in the DynHeMat package. In order to reflect all these changes, the five test cases available in the original version of DynHeMat [1] are rerun and a sixth test case, dedicated to a short ZPAD simulation to model the collision Ar + Ar4He70007 with phenomenological inclusion of superfluidity, is added.Nature of problem:Superfluidity should be taken into account to model the coagulation of rare-gas atoms or the submersion of alkali clusters in large HNDs (N ≳ 104) [2], [3]. In the contrary case, the impurity (rare-gas atoms or an alkali cluster in aforementioned examples) might remain at the vicinity of the droplet surface. However, classical methods cannot intrinsically take into account superfluidity because this property is essentially a manifestation of the bosonic character of 4He atoms. Therefore, altenate strategies have to be devised to circumvent this difficulty while trying to preserve some physical properties of the HND, such as its total energy.Solution method:Superfluidity is included on a phenomenological manner by imposing a projectile that penetrates inside a given HND to maintain its velocity at the critical Landau velocity (vL≈60ms−1) and head toward the center of the HND, where a dopant may be located. Such a procedure should violate conservation laws of classical mechanics (eg, conservation of total energy and linear momentum) because the projectile is not expected to maintain its velocity at a constant value and should rather exchange energy with surrounding He atoms. However, the conservation of total energy can be ensured by reducing the energy of He atoms to compensate for the increase of the projectile speed to vL. Moreover, the motion of the HND center of mass was found to be small ( ≲ 0.5 Å) upon typical ZPAD simulations carried out on HNDs composed of about 7 × 104 He atoms [2]. This phenomenological approach is a first step through the inclusion of superfluidity in classical and mixed quantum-classical simulations dedicated to large HNDs (N ≳ 104) and its implementation in DynHeMat could be a valuable asset to the community.Additional comments including restrictions and unusual features:The main unsual feature of this new version of DynHeMat is the implementation of the algorithm for phenomenological inclusion of superfluidity in ZPAD simulations [2]. Since total energy is maintained by construction, the first restriction of this method is the non-conservation of linear and angular momenta even if the former seems to have limited influence on the dynamics at the low temperature of HNDs (T=0.37K) [4], [5]. Moreover, the maintenance of the projectile speed at vL compels the velocity of He atoms to be decreased and this cooling of the HND can lead to a slight underestimation of He evaporation. Finally, when the formation of weakly-bound complexes is investigated in large HNDs, the algorithm for phenomenological inclusion of superfluidity should be deactivated when the projectile reaches the vicinity of the dopant to avoid unphysical behaviors and the distance criterion for this deactivation may need to be adjusted [2]. Examples of distance criteria for rare gases are provided in the source code (see also the user manual).
Phonon calculations are pivotal for understanding the thermodynamic and dynamical properties of materials, yet density functional theory (DFT) approaches often incur prohibitive computational costs for large-scale systems such as moiré superlattices. We introduce NEPHONON, an open-source high-performance package designed to quickly calculate phonon properties of extended systems with near-DFT accuracy. By leveraging the computational efficiency of machine-learned Neuroevolution potentials, NEPHONON enables the rapid generation of second-order force constants even in systems with thousands of atoms. Beyond standard phonon band structures, density of states, and group velocity, NEPHONON implements the simulation of isofrequency phonon surfaces and inelastic neutron scattering spectra S(Q,E). Furthermore, the code provides access to full phonon eigenvectors, facilitating advanced analyses of topological chiral phonons and visualization of vibrational modes. Through benchmarks on twisted bilayer phosphorene, graphene, and copper, we demonstrate the package's capabilities, confirming that NEPHONON is a powerful tool for rapidly exploring complex phononic phenomena in materials.
The ability to achieve controlled distributions of precipitates is one of the cornerstones of alloy optimization, in which small-angle scattering (SAS) serves as a powerful technique to characterize these distributions. One method of analyzing SAS data involves form factor intensity models, where modeled distribution parameters are obtained by solving a nonlinear least-squares (NLS) problem. However, the NLS method with a simultaneous search for all model parameters minimizes a very ill-conditioned objective function, which leads to a large number of search iterations and can give inadequate solutions. With the advancement of the 4th generation synchrotron rings and their potentially large datasets, it is increasingly important to find new and efficient numerical strategies for high throughput analysis. As a step in this direction, the purpose of this work is to investigate a pseudo-automatic numerical solution strategy based on the separable NLS method. The strategy is assessed in terms of correlation and precision of the model parameters, as well as convergence of the solution, using both synthetic and experimental scattering datasets. The decoupled fitting approach favors efficient parallelized batch fitting, which provides linear speedup for appropriate workloads. To support further development, the compounded features of the proposed solution strategy are packed into an easily accessible modular framework named python Small Angle Scattering Analysis (pySASA), which is openly available.
The Chord Length Sampling (CLS) method is an efficient implicit geometric modeling approach for particle transport simulation in stochastic media. In conventional implementations, however, each particle independently samples chord lengths, causing the material distribution at a given spatial position to vary from particle to particle. In this work, a CLS transport method for stochastic media is developed and implemented in OpenMC, where position-dependent deterministic seeds are employed to endow chord length sampling with both spatial consistency and reproducibility. A physically consistent boundary treatment further eliminates the need for conventional packing fraction correction parameters. The method is systematically evaluated through a three-tier progressive validation strategy using neutron criticality calculations. For four sets of white-boundary spherical benchmark cases, the keff deviations all fall within 100 pcm. A PWR single-pin benchmark with 28 parameter combinations and an MTR single-plate benchmark with multiple thicknesses reveal that CLS deviations are primarily governed by geometric parameters, with the deviation direction depending on the relative neutronic properties of the sphere and matrix materials. The parameter β, defined as the ratio of the mean chord segment period to the characteristic size D of the stochastic medium, is identified as the governing parameter for CLS applicability in finite-geometry dispersion fuels, representing the inverse of the expected number of complete chord segment cycles traversed by a particle through the stochastic medium. The systematic bias scales as Δkeff∝β. Both rod-type and plate-type data exhibit a consistent decay trend in the β-deviation plane, with deviations remaining on the order of 100 pcm for β < 0.1. Notably, the computational throughput of the CLS method does not degrade with increasing dispersion sphere count, and the geometric storage requirement at the million-sphere scale amounts to less than one hundred-thousandth of that required by the explicit method. The geometric acceleration framework of the method is independent of the transported particle type and can be extended to broader radiation transport scenarios.
Efficient simulation of photon propagation in highly scattering, fluorescent multi-layer media remains challenging due to the need to simultaneously model scattering, absorption, and emission. Existing open-source codes, developed primarily for biomedical and sensing applications, cannot handle multi-layer configurations with multiple fluorescent and non-fluorescent (e.g., white filler) inclusions. There is a need for user-friendly open-source tools capable of modeling such complex structures, with applications in radiative cooling, energy harvesting, and solid-state lighting. Additionally, accommodating uncertainty in optical properties is a valuable feature currently lacking in existing codes. In this paper, we present an open-source code utilizing a Python-based, parallelized Monte Carlo algorithm that handles photon propagation in multi-layer media with fluorescent and non-fluorescent inclusions, simulating the following spectral radiative properties: reflectance, spectral fluorescence, absolute and normalized radiosity, total and different types of absorptances, and transmittance. This work serves as a built function on FOS, a previous open-source code developed by our group for non-fluorescent media. The Fluor-FOS open-source code enables efficient simulation of spectral radiative properties for fluorescent media in radiative cooling applications, LED packages, and energy harvesting systems. The proposed software has been validated against an open-source code and two experimental cases with different configurations and light sources, ensuring the fidelity of the proposed modified Monte Carlo algorithm. PROGRAM SUMMARY Program Title: Fluor-FOS: Fluorescent FOS for optical modeling of nancomposite media with fluorescent inclusion.Developer’s repository link: https://github.com/khalidmeshari/fluor-fos.gitLicensing provisions: GNU General Public License version 3Programming language: Python 3.10Nature of problem: Calculation of the solar-weighted and spectral radiative properties (normalized radiosity, transmittance and different types of absorptances) in fluorescent nanoparticle media. The calculation of scattering and absorption coefficient for spherical inclusion.Solution method: The simulated spectral radiative properties is accomplished by modified Monte Carlo algorithm solving the radiative transport equation (RTE). The calculation of attenuation properties for spherical inclusion is done by modified Mie theory.Additional comments including restrictions and unusual features: The program files are attached written with python programming language and can be run on different operation systems (Mac and Linux).
