diff --git a/.github/workflows/build_and_test.yaml b/.github/workflows/build_and_test.yaml
index f4be766..a1042b2 100644
--- a/.github/workflows/build_and_test.yaml
+++ b/.github/workflows/build_and_test.yaml
@@ -33,7 +33,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up pixi
-        uses: prefix-dev/setup-pixi@v0.8.8
+        uses: prefix-dev/setup-pixi@v0.8.10
 
       - name: Generate build directory
         run: mkdir -p ${{ env.FANS_BUILD_DIR }}
diff --git a/.github/workflows/build_and_test_mac.yaml b/.github/workflows/build_and_test_mac.yaml
index b917d18..c6d9107 100644
--- a/.github/workflows/build_and_test_mac.yaml
+++ b/.github/workflows/build_and_test_mac.yaml
@@ -33,7 +33,7 @@ jobs:
           brew install fftw eigen
 
       - name: Set up pixi
-        uses: prefix-dev/setup-pixi@v0.8.8
+        uses: prefix-dev/setup-pixi@v0.8.10
 
       - name: Generate build directory
         run: mkdir -p ${{ env.FANS_BUILD_DIR }}
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5f62666..9e00faa 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,11 @@
 # FANS Changelog
 
+## v0.4.2
+
+- Reduce dependencies of dashboard for cf-package https://github.com/DataAnalyticsEngineering/FANS/pull/71
+- Add pixi task `h52xdmf` to generate XDMF from H5 files directly as `pixi run h52xdmf {h5filepath}`
+- Add logo of FANS to the README https://github.com/DataAnalyticsEngineering/FANS/pull/70
+
 ## v0.4.1
 
 - remove std::sqrt from constexpr - failed on Clang https://github.com/DataAnalyticsEngineering/FANS/pull/64
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 4294bfd..45a23c3 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -5,7 +5,7 @@ cmake_minimum_required(VERSION 3.21)
 # ##############################################################################
 
 project(FANS
-        VERSION 0.4.1
+        VERSION 0.4.2
         LANGUAGES C CXX
 )
 
diff --git a/FANS_Dashboard/pyproject.toml b/FANS_Dashboard/pyproject.toml
index c9f5287..e1ef4c8 100644
--- a/FANS_Dashboard/pyproject.toml
+++ b/FANS_Dashboard/pyproject.toml
@@ -4,19 +4,15 @@ build-backend = "hatchling.build"
 
 [project]
 name            = "fans-dashboard"
-version         = "0.4.1"
-requires-python = ">=3.13"
+version         = "0.4.2"
+requires-python = ">=3.9"
 dependencies = [
-  "numpy>=2.2.5,<3",
-  "h5py>=3.13.0,<4",
-  "plotly>=6.0.1,<7",
-  "lxml>=5.4.0,<6",
-  "nbformat>=5.10.4,<6",
-  "matplotlib>=3.10.1,<4",
-  "scipy>=1.15.2,<2",
-  "meshio>=5.3.5,<6",
-  "ipykernel>=6.29.5,<7",
-  "nbclient>=0.10.2,<0.11",
+  "numpy",
+  "h5py",
+  "plotly",
+  "lxml",
+  "scipy",
+  "meshio",
 ]
 
 [tool.hatch.build.targets.wheel]
diff --git a/README.md b/README.md
index e900a83..94884a3 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@
 Fourier-Accelerated Nodal Solver (FANS) is an FFT-based homogenization solver for microscale multiphysics problems. FANS is written in C++, built using CMake, and it has MPI parallelization.
 
 <p align="center">
-  <img src="docs/images/FANS_example.png" alt="Example Image" width="400" height="300">
+  <img src="docs/images/FANS_logo.png" alt="Example Image" width="300" height="300">
 </p>
 
 ## Table of contents
@@ -17,7 +17,7 @@ Fourier-Accelerated Nodal Solver (FANS) is an FFT-based homogenization solver fo
 
 FANS has the following dependencies:
 
-- A C++ compiler (e.g. GCC, Clang, etc.)
+- A C++ compiler (e.g., GCC, Clang, etc.)
 - CMake (version 3.21 or higher)
 - Git (for cloning this repo)
 - MPI (mpicc and mpic++)
@@ -27,7 +27,7 @@ FANS has the following dependencies:
 
 ### Installing dependencies
 
-- On Debian based systems, we recommend installing the dependencies using using `apt`,
+- On Debian-based systems, we recommend installing the dependencies using `apt`,
 
   ```bash
   apt-get install \
@@ -51,10 +51,10 @@ FANS has the following dependencies:
 
 ### Setting up a Python environment
 
-Also, we recommend to set up a Python virtual environment for the [`FANS_Dashboard.ipynb`](FANS_Dashboard/FANS_Dashboard.ipynb) via [pixi](https://pixi.sh/) with all required Python dependencies in an isolated environment:
+Also, we recommend setting up a Python virtual environment for the [`FANS_Dashboard.ipynb`](FANS_Dashboard/FANS_Dashboard.ipynb) via [pixi](https://pixi.sh/) with all required Python dependencies in an isolated environment:
 
 ```bash
-# Install pixi if not done already
+# Install Pixi if not done already,
 curl -fsSL https://pixi.sh/install.sh | sh
 
 # Create and activate the environment
@@ -79,7 +79,7 @@ Spack is a package manager designed for high-performance computing environments.
     spack install fftw +mpi
     ```
 
-    Additionally, optimized FFTW implementations can be used depending on your system's architecture, for example `amdfftw` (For AMD systems) or `cray-fftw` (For Cray systems) or `fujitsu-fftw` (For Fujitsu systems).
+    Additionally, optimized FFTW implementations can be used depending on your system's architecture, for example `amdfftw` (For AMD systems) or `cray-fftw` (For Cray systems), or `fujitsu-fftw` (For Fujitsu systems).
 
 3. **Load Dependencies** Once dependencies are installed, load them before building:
 
@@ -142,7 +142,7 @@ Install FANS (system-wide) using the following options:
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/fans/badges/platforms.svg)](https://anaconda.org/conda-forge/fans)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/fans/badges/downloads.svg)](https://anaconda.org/conda-forge/fans)
 
-FANS is also available as a conda-package on [conda-forge/fans](https://anaconda.org/conda-forge/fans). No dependencies have to be manually installed for it to work.
+FANS is also available as a conda package on [conda-forge/fans](https://anaconda.org/conda-forge/fans). No dependencies have to be manually installed for it to work.
 It can be installed via
 
 ```bash
@@ -153,7 +153,7 @@ exposing the executable `FANS`.
 
 ## Input File Format
 
-FANS requires a JSON input file specifying the problem parameters. Example input files can be found in the [`test/input_files`](test/input_files) directory. It is recommended to use these files as a reference to create your own input file.
+FANS requires a JSON input file specifying the problem parameters. Example input files can be found in the [`test/input_files`](test/input_files) directory. It is recommended to use these files as a reference to create your input file.
 
 ### Microstructure Definition
 
@@ -167,7 +167,7 @@ FANS requires a JSON input file specifying the problem parameters. Example input
 
 - `filepath`: This specifies the path to the HDF5 file that contains the microstructure data.
 - `datasetname`: This is the path within the HDF5 file to the specific dataset that represents the microstructure.
-- `L`: Microstructure length defines the physical dimensions of the microstructure in the x, y, and z directions.
+- `L`: Microstructure length defines the physical dimensions of the microstructure in the $x$, $y$, and $z$ directions.
 
 ### Problem Type and Material Model
 
@@ -189,7 +189,7 @@ FANS requires a JSON input file specifying the problem parameters. Example input
   - `LinearElasticIsotropic` for linear isotropic elastic material model
   - `LinearElasticTriclinic` for linear triclinic elastic material model
   - `PseudoPlasticLinearHardening` / `PseudoPlasticNonLinearHardening` for plasticity mimicking model with linear/nonlinear hardening
-  - `J2ViscoPlastic_LinearIsotropicHardening` / `J2ViscoPlastic_NonLinearIsotropicHardening` for rate independent / dependent J2 plasticity model with kinematic and linear/nonlinear isotropic hardening.
+  - `J2ViscoPlastic_LinearIsotropicHardening` / `J2ViscoPlastic_NonLinearIsotropicHardening` for rate-independent / dependent J2 plasticity model with kinematic and linear/nonlinear isotropic hardening.
 
 - `material_properties`: This provides the necessary material parameters for the chosen material model. For thermal problems, you might specify `conductivity`, while mechanical problems might require `bulk_modulus`, `shear_modulus`, and more properties for advanced material models. These properties can be defined as arrays to represent multiple phases within the microstructure.
 
@@ -206,7 +206,7 @@ FANS requires a JSON input file specifying the problem parameters. Example input
 ```
 
 - `method`: This indicates the numerical method to be used for solving the system of equations. `cg` stands for the Conjugate Gradient method, and `fp` stands for the Fixed Point method.
-- `error_parameters`: This section defines the error parameters for the solver. Error control is applied on the finite element nodal residual of the problem.
+- `error_parameters`: This section defines the error parameters for the solver. Error control is applied to the finite element nodal residual of the problem.
   - `measure`: Specifies the norm used to measure the error. Options include `Linfinity`, `L1`, or `L2`.
   - `type`: Defines the type of error measurement. Options are `absolute` or `relative`.
   - `tolerance`: Sets the tolerance level for the solver, defining the convergence criterion based on the chosen error measure. The solver iterates until the solution meets this tolerance.
@@ -235,7 +235,7 @@ FANS requires a JSON input file specifying the problem parameters. Example input
 - For `thermal` problems, the array typically has 3 components, representing the temperature gradients in the $x$, $y$, and $z$ directions.
 - For `mechanical` problems, the array must have 6 components, corresponding to the components of the strain tensor in Mandel notation (e.g., $[\varepsilon_{11}, \varepsilon_{22}, \varepsilon_{33}, \sqrt{2}\varepsilon_{12}, \sqrt{2}\varepsilon_{13}, \sqrt{2}\varepsilon_{23}]$).
 
-In the case of path/time-dependent loading as shown, for example as in plasticity problems, the `macroscale_loading` array can include multiple steps with corresponding loading conditions.
+In the case of path/time-dependent loading, as shown, for example, in plasticity problems, the `macroscale_loading` array can include multiple steps with corresponding loading conditions.
 
 FANS also supports mixed boundary conditions, where some components can be strain-controlled while others are stress-controlled:
 
@@ -257,26 +257,26 @@ FANS also supports mixed boundary conditions, where some components can be strai
             "microstructure", "displacement", "displacement_fluctuation", "stress", "strain"]
 ```
 
-- `results`: This array lists the quantities that should be stored into the results HDF5 file during the simulation. Each string in the array corresponds to a specific result:
+- `results`: This array lists the quantities that should be stored in the results HDF5 file during the simulation. Each string in the array corresponds to a specific result:
 
   - `stress_average` and `strain_average`: Volume averaged- homogenized stress and strain over the entire microstructure.
-  - `absolute_error`: The L-infinity error of finite element nodal residual at each iteration.
+  - `absolute_error`: The L-infinity error of the finite element nodal residual at each iteration.
   - `phase_stress_average` and `phase_strain_average`: Volume averaged- homogenized stress and strain for each phase within the microstructure.
   - `microstructure`: The original microstructure data.
   - `displacement`: The displacement field (for mechanical problems) and temperature field (for thermal problems) at each voxel in the microstructure.
   - `displacement_fluctuation`: The periodic displacement fluctuation field (for mechanical problems) and periodic temperature fluctuation field (for thermal problems at each voxel in the microstructure).
   - `stress` and `strain`: The stress and strain fields at each voxel in the microstructure.
 
-- Additional material model specific results can be included depending on the problem type and material model.
+- Additional material model-specific results can be included depending on the problem type and material model.
 
 ## Acknowledgements
 
-Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2075 – 390740016. Contributions by Felix Fritzen are funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the Heisenberg program - DFG-FR2702/8 - 406068690; DFG-FR2702/10 - 517847245 and through NFDI-MatWerk - NFDI 38/1 - 460247524. We acknowledge the support by the Stuttgart Center for Simulation Science ([SimTech](https://www.simtech.uni-stuttgart.de/)).
+Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2075 – 390740016. Contributions by Felix Fritzen are funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the Heisenberg program - DFG-FR2702/8 - 406068690; DFG-FR2702/10 - 517847245 and through NFDI-MatWerk - NFDI 38/1 - 460247524. We acknowledge the support of the Stuttgart Center for Simulation Science ([SimTech](https://www.simtech.uni-stuttgart.de/)).
 
 ## Contributors
 
 - [Sanath Keshav](https://github.com/sanathkeshav)
-- [Florian Rieg](about:blank)
+- [Florian Rieg](https://github.com/scylent)
 - [Ishaan Desai](https://github.com/IshaanDesai)
 - [Moritz Sigg](https://github.com/siggmo)
 - [Claudius Haag](https://github.com/claudiushaag)
diff --git a/docs/images/FANS_example.png b/docs/images/FANS_example.png
deleted file mode 100644
index 3e49c99..0000000
Binary files a/docs/images/FANS_example.png and /dev/null differ
diff --git a/docs/images/FANS_logo.png b/docs/images/FANS_logo.png
new file mode 100644
index 0000000..f01b935
Binary files /dev/null and b/docs/images/FANS_logo.png differ
diff --git a/pixi.lock b/pixi.lock
index 822be9d..bf7ba4b 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -9,449 +9,418 @@ environments:
       linux-64:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/beartype-0.20.2-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/asttokens-3.0.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/beartype-0.21.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h4bc722e_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.4.26-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.6.15-hbd8a1cb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cffi-1.17.1-py313hfab6e84_0.conda
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-  - blas =2.131=openblas
+  - blas 2.132   openblas
+  - liblapack  3.9.0   32*_openblas
   - mkl <2025
-  - liblapack =3.9.0=31*_openblas
+  - libcblas   3.9.0   32*_openblas
+  - liblapacke 3.9.0   32*_openblas
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 17123
-  timestamp: 1740088119350
-- conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-31_h641d27c_mkl.conda
-  build_number: 31
-  sha256: 7bb4d5b591e98fe607279520ee78e3571a297b5720aa789a2536041ad5540de8
-  md5: d05563c577fe2f37693a554b3f271e8f
+  size: 17520
+  timestamp: 1750388963178
+- conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-32_h641d27c_mkl.conda
+  build_number: 32
+  sha256: 809d78b096e70fed7ebb17c867dd5dde2f9f4ed8564967a6e10c65b3513b0c31
+  md5: 49b36a01450e96c516bbc5486d4a0ea0
   depends:
   - mkl 2024.2.2 h66d3029_15
   constrains:
-  - libcblas =3.9.0=31*_mkl
-  - blas =2.131=mkl
-  - liblapacke =3.9.0=31*_mkl
-  - liblapack =3.9.0=31*_mkl
+  - libcblas   3.9.0   32*_mkl
+  - liblapack  3.9.0   32*_mkl
+  - liblapacke 3.9.0   32*_mkl
+  - blas 2.132   mkl
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 3733728
-  timestamp: 1740088452830
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-31_he106b2a_openblas.conda
-  build_number: 31
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-  md5: abb32c727da370c481a1c206f5159ce9
+  size: 3735390
+  timestamp: 1750389080409
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-32_he106b2a_openblas.conda
+  build_number: 32
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+  md5: 3d3f9355e52f269cd8bc2c440d8a5263
   depends:
-  - libblas 3.9.0 31_h59b9bed_openblas
+  - libblas 3.9.0 32_h59b9bed_openblas
   constrains:
-  - liblapacke =3.9.0=31*_openblas
-  - liblapack =3.9.0=31*_openblas
-  - blas =2.131=openblas
+  - blas 2.132   openblas
+  - liblapack  3.9.0   32*_openblas
+  - liblapacke 3.9.0   32*_openblas
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 16796
-  timestamp: 1740087984429
-- conda: https://conda.anaconda.org/conda-forge/osx-64/libcblas-3.9.0-31_hff6cab4_openblas.conda
-  build_number: 31
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-  md5: c655cc2b0c48ec454f7a4db92415d012
+  size: 17308
+  timestamp: 1750388809353
+- conda: https://conda.anaconda.org/conda-forge/osx-64/libcblas-3.9.0-32_hff6cab4_openblas.conda
+  build_number: 32
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+  md5: 2c1e774d4546cf542eaee5781eb8940b
   depends:
-  - libblas 3.9.0 31_h7f60823_openblas
+  - libblas 3.9.0 32_h7f60823_openblas
   constrains:
-  - liblapacke =3.9.0=31*_openblas
-  - blas =2.131=openblas
-  - liblapack =3.9.0=31*_openblas
+  - blas 2.132   openblas
+  - liblapack  3.9.0   32*_openblas
+  - liblapacke 3.9.0   32*_openblas
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 17006
-  timestamp: 1740087955460
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-31_hb3479ef_openblas.conda
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-  md5: 7353c2bf0e90834cb70545671996d871
+  size: 17574
+  timestamp: 1750389040732
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-32_hb3479ef_openblas.conda
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+  md5: d8e8ba717ae863b13a7495221f2b5a71
   depends:
-  - libblas 3.9.0 31_h10e41b3_openblas
+  - libblas 3.9.0 32_h10e41b3_openblas
   constrains:
-  - liblapacke =3.9.0=31*_openblas
-  - blas =2.131=openblas
-  - liblapack =3.9.0=31*_openblas
+  - blas 2.132   openblas
+  - liblapack  3.9.0   32*_openblas
+  - liblapacke 3.9.0   32*_openblas
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 17032
-  timestamp: 1740088127097
-- conda: https://conda.anaconda.org/conda-forge/win-64/libcblas-3.9.0-31_h5e41251_mkl.conda
-  build_number: 31
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-  md5: 43c100b94ad2607382b0cf0f3a6b0bf3
+  size: 17485
+  timestamp: 1750388970626
+- conda: https://conda.anaconda.org/conda-forge/win-64/libcblas-3.9.0-32_h5e41251_mkl.conda
+  build_number: 32
+  sha256: d0f81145ae795592f3f3b5d7ff641c1019a99d6b308bfaf2a4cc5ba24b067bb0
+  md5: 054b9b4b48296e4413cf93e6ece7b27d
   depends:
-  - libblas 3.9.0 31_h641d27c_mkl
+  - libblas 3.9.0 32_h641d27c_mkl
   constrains:
-  - blas =2.131=mkl
-  - liblapacke =3.9.0=31*_mkl
-  - liblapack =3.9.0=31*_mkl
+  - liblapack  3.9.0   32*_mkl
+  - liblapacke 3.9.0   32*_mkl
+  - blas 2.132   mkl
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 3733549
-  timestamp: 1740088502127
-- conda: https://conda.anaconda.org/conda-forge/osx-64/libcxx-20.1.5-hf95d169_0.conda
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-  md5: 9dde68cee0a231b19e189954ac29027b
+  size: 3735392
+  timestamp: 1750389122586
+- conda: https://conda.anaconda.org/conda-forge/osx-64/libcxx-20.1.7-hf95d169_0.conda
+  sha256: f6e088a2e0e702a4908d1fc9f1a17b080bdcf63e1f8a9cb35dd158fc1d1eb2f5
+  md5: 8b47ade37d4e75417b4e993179c09f5d
   depends:
   - __osx >=10.13
   license: Apache-2.0 WITH LLVM-exception
   license_family: Apache
   purls: []
-  size: 562408
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcxx-20.1.5-ha82da77_0.conda
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-  md5: 4ef1bdb94d42055f511bb358f2048c58
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcxx-20.1.7-ha82da77_0.conda
+  sha256: a3fd34773f1252a4f089e74a075ff5f0f6b878aede097e83a405f35687c36f24
+  md5: 881de227abdddbe596239fa9e82eb3ab
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   - __osx >=11.0
   license: Apache-2.0 WITH LLVM-exception
   license_family: Apache
   purls: []
-  size: 568010
-  timestamp: 1747262879889
+  size: 567189
+  timestamp: 1749847129529
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20250104-pl5321h7949ede_0.conda
+  sha256: d789471216e7aba3c184cd054ed61ce3f6dac6f87a50ec69291b9297f8c18724
+  md5: c277e0a4d549b03ac1e9d6cbbe3d017b
+  depends:
+  - ncurses
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=13
+  - ncurses >=6.5,<7.0a0
+  license: BSD-2-Clause
+  license_family: BSD
+  purls: []
+  size: 134676
+  timestamp: 1738479519902
+- conda: https://conda.anaconda.org/conda-forge/osx-64/libedit-3.1.20250104-pl5321ha958ccf_0.conda
+  sha256: 6cc49785940a99e6a6b8c6edbb15f44c2dd6c789d9c283e5ee7bdfedd50b4cd6
+  md5: 1f4ed31220402fcddc083b4bff406868
+  depends:
+  - ncurses
+  - __osx >=10.13
+  - ncurses >=6.5,<7.0a0
+  license: BSD-2-Clause
+  license_family: BSD
+  purls: []
+  size: 115563
+  timestamp: 1738479554273
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libedit-3.1.20250104-pl5321hafb1f1b_0.conda
+  sha256: 66aa216a403de0bb0c1340a88d1a06adaff66bae2cfd196731aa24db9859d631
+  md5: 44083d2d2c2025afca315c7a172eab2b
+  depends:
+  - ncurses
+  - __osx >=11.0
+  - ncurses >=6.5,<7.0a0
+  license: BSD-2-Clause
+  license_family: BSD
+  purls: []
+  size: 107691
+  timestamp: 1738479560845
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.0-h5888daf_0.conda
   sha256: 33ab03438aee65d6aa667cf7d90c91e5e7d734c19a67aa4c7040742c0a13d505
   md5: db0bfbe7dd197b68ad5f30333bae6ce0
@@ -1695,65 +1476,65 @@ packages:
   purls: []
   size: 44978
   timestamp: 1743435053850
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.1.0-h767d61c_2.conda
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-  md5: ea8ac52380885ed41c1baa8f1d6d2b93
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.1.0-h767d61c_3.conda
+  sha256: 59a87161212abe8acc57d318b0cc8636eb834cdfdfddcf1f588b5493644b39a3
+  md5: 9e60c55e725c20d23125a5f0dd69af5d
   depends:
   - __glibc >=2.17,<3.0.a0
   - _openmp_mutex >=4.5
   constrains:
-  - libgcc-ng ==15.1.0=*_2
-  - libgomp 15.1.0 h767d61c_2
+  - libgcc-ng ==15.1.0=*_3
+  - libgomp 15.1.0 h767d61c_3
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
-  size: 829108
-  timestamp: 1746642191935
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.1.0-h69a702a_2.conda
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-  md5: ddca86c7040dd0e73b2b69bd7833d225
+  size: 824921
+  timestamp: 1750808216066
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.1.0-h69a702a_3.conda
+  sha256: b0b0a5ee6ce645a09578fc1cb70c180723346f8a45fdb6d23b3520591c6d6996
+  md5: e66f2b8ad787e7beb0f846e4bd7e8493
   depends:
-  - libgcc 15.1.0 h767d61c_2
+  - libgcc 15.1.0 h767d61c_3
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
-  size: 34586
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.1.0-h69a702a_2.conda
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-  md5: f92e6e0a3c0c0c85561ef61aa59d555d
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+  md5: bfbca721fd33188ef923dfe9ba172f29
   depends:
-  - libgfortran5 15.1.0 hcea5267_2
+  - libgfortran5 15.1.0 hcea5267_3
   constrains:
-  - libgfortran-ng ==15.1.0=*_2
+  - libgfortran-ng ==15.1.0=*_3
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/libgfortran-14.2.0-hef36b68_105.conda
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-  md5: 6b27baf030f5d6603713c7e72d3f6b9a
+  size: 29057
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+- conda: https://conda.anaconda.org/conda-forge/osx-64/libgfortran-5.0.0-14_2_0_h51e75f0_103.conda
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+  md5: 090b3c9ae1282c8f9b394ac9e4773b10
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-  - libgfortran5 14.2.0 h58528f3_105
+  - libgfortran5 14.2.0 h51e75f0_103
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   license_family: GPL
   purls: []
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran-14.2.0-heb5dd2a_105.conda
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-  md5: ad35937216e65cfeecd828979ee5e9e6
+  size: 156202
+  timestamp: 1743862427451
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran-5.0.0-14_2_0_h6c33f7e_103.conda
+  sha256: 8628746a8ecd311f1c0d14bb4f527c18686251538f7164982ccbe3b772de58b5
+  md5: 044a210bc1d5b8367857755665157413
   depends:
-  - libgfortran5 14.2.0 h2c44a93_105
+  - libgfortran5 14.2.0 h6c33f7e_103
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
-  size: 155474
-  timestamp: 1743913530958
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.1.0-hcea5267_2.conda
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-  md5: 01de444988ed960031dbe84cf4f9b1fc
+  size: 156291
+  timestamp: 1743863532821
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.1.0-hcea5267_3.conda
+  sha256: eea6c3cf22ad739c279b4d665e6cf20f8081f483b26a96ddd67d4df3c88dfa0a
+  md5: 530566b68c3b8ce7eec4cd047eae19fe
   depends:
   - __glibc >=2.17,<3.0.a0
   - libgcc >=15.1.0
@@ -1762,42 +1543,42 @@ packages:
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   license_family: GPL
   purls: []
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/libgfortran5-14.2.0-h58528f3_105.conda
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-  md5: 94560312ff3c78225bed62ab59854c31
+  size: 1565627
+  timestamp: 1750808236464
+- conda: https://conda.anaconda.org/conda-forge/osx-64/libgfortran5-14.2.0-h51e75f0_103.conda
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+  md5: 6183f7e9cd1e7ba20118ff0ca20a05e5
   depends:
   - llvm-openmp >=8.0.0
   constrains:
-  - libgfortran 14.2.0
+  - libgfortran 5.0.0 14_2_0_*_103
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
-  size: 1224385
-  timestamp: 1743911552203
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran5-14.2.0-h2c44a93_105.conda
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-  md5: 06f35a3b1479ec55036e1c9872f97f2c
+  size: 1225013
+  timestamp: 1743862382377
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran5-14.2.0-h6c33f7e_103.conda
+  sha256: 8599453990bd3a449013f5fa3d72302f1c68f0680622d419c3f751ff49f01f17
+  md5: 69806c1e957069f1d515830dcc9f6cbb
   depends:
   - llvm-openmp >=8.0.0
   constrains:
-  - libgfortran 14.2.0
+  - libgfortran 5.0.0 14_2_0_*_103
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
-  size: 806283
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.1.0-h767d61c_2.conda
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-  md5: fbe7d535ff9d3a168c148e07358cd5b1
+  size: 806566
+  timestamp: 1743863491726
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.1.0-h767d61c_3.conda
+  sha256: 43710ab4de0cd7ff8467abff8d11e7bb0e36569df04ce1c099d48601818f11d1
+  md5: 3cd1a7238a0dd3d0860fdefc496cc854
   depends:
   - __glibc >=2.17,<3.0.a0
   license: GPL-3.0-only WITH GCC-exception-3.1
   license_family: GPL
   purls: []
-  size: 452635
-  timestamp: 1746642113092
+  size: 447068
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 - conda: https://conda.anaconda.org/conda-forge/win-64/libhwloc-2.11.2-default_ha69328c_1001.conda
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   size: 638142
   timestamp: 1740128665984
-- conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-31_h7ac8fdf_openblas.conda
-  build_number: 31
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-  md5: 452b98eafe050ecff932f0ec832dd03f
+- conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-32_h7ac8fdf_openblas.conda
+  build_number: 32
+  sha256: 5b55a30ed1b3f8195dad9020fe1c6d0f514829bfaaf0cf5e393e93682af009f2
+  md5: 6c3f04ccb6c578138e9f9899da0bd714
   depends:
-  - libblas 3.9.0 31_h59b9bed_openblas
+  - libblas 3.9.0 32_h59b9bed_openblas
   constrains:
-  - libcblas =3.9.0=31*_openblas
-  - liblapacke =3.9.0=31*_openblas
-  - blas =2.131=openblas
+  - libcblas   3.9.0   32*_openblas
+  - blas 2.132   openblas
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   license: BSD-3-Clause
   license_family: BSD
   purls: []
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-  - blas =2.131=openblas
-  - liblapacke =3.9.0=31*_openblas
+  - blas 2.132   openblas
+  - liblapacke 3.9.0   32*_openblas
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   license_family: BSD
   purls: []
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-  - libcblas =3.9.0=31*_openblas
-  - blas =2.131=openblas
+  - blas 2.132   openblas
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-  - blas =2.131=mkl
-  - liblapacke =3.9.0=31*_mkl
+  - libcblas   3.9.0   32*_mkl
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   constrains:
-  - openblas >=0.3.29,<0.3.30.0a0
+  - openblas >=0.3.30,<0.3.31.0a0
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+  - libsodium >=1.0.20,<1.0.21.0a0
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  license: MPL-2.0
+  license_family: MOZILLA
+  purls: []
+  size: 2527503
+  timestamp: 1731585151036
+- conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhd8ed1ab_0.conda
+  sha256: 7560d21e1b021fd40b65bfb72f67945a3fcb83d78ad7ccf37b8b3165ec3b68ad
+  md5: df5e78d904988eb55042c0c97446079f
+  depends:
+  - python >=3.9
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/zipp?source=hash-mapping
+  size: 22963
+  timestamp: 1749421737203
diff --git a/pixi.toml b/pixi.toml
index 5d065c1..2ba4ca8 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -4,12 +4,13 @@ name = "FANS"
 platforms = ["linux-64", "win-64", "osx-64", "osx-arm64"]
 
 [dependencies]
-python = ">=3.13.3,<3.14"
-pytest = ">=8.3.5,<9"
+python = ">=3.13.5,<3.14"
+pytest = ">=8.4.1,<9"
 pre-commit = ">=4.2.0,<5"
 sympy = ">=1.14.0,<2"
 quaternion = ">=2024.0.8,<2025"
-beartype = ">=0.20.2,<0.21"
+beartype = ">=0.21.0,<0.22"
+ipykernel = ">=6.29.5,<7"
 
 
 [pypi-dependencies]
@@ -21,3 +22,4 @@ pyrecest = {git = "https://github.com/FlorianPfaff/pyRecEst.git"}
 [tasks]
 test = "pytest -v -s"
 precommit = "pre-commit run --all-files"
+h52xdmf = { args = ["file"], cmd = "cd \"$INIT_CWD\" && python -m fans_dashboard.plotting.h52xdmf -t -v {{file}}" }
diff --git a/test/README.md b/test/README.md
index 147e323..c2dbaac 100644
--- a/test/README.md
+++ b/test/README.md
@@ -51,3 +51,9 @@ Each test case has corresponding input JSON files in the `input_files/` director
 ```bash
 mpiexec -n 2 ./FANS input_files/test_LinearElastic.json test_results.h5
 ```
+
+To quickly visualize the test results, and accompanying XDMF for the HDF5 output can be generated which can be directly opened in ParaView for 3D visualization and analysis:
+
+```bash
+pixi run h52xdmf test_results.h5
+```