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Anhang für "Selbstassoziierende frustrierte Lewis-Paare und mechanistische Untersuchungen zu Piers‘ Boran induzierten Umlagerungen und Carboborierungen"
(2023-05-08) Müller, Tizian Jürgen
Rohdaten zur Dissertation „Selbstassoziierende frustrierte Lewis-Paare und mechanistische Untersuchungen zu Piers‘ Boran induzierten Umlagerungen und Carboborierungen“ vorgelegt von Tizian Jürgen Müller. Diese Sammlung enthält: - NMR-Spektren der charakterisierten Verbindungen und durchgeführten Kinetiken. - SC-XRC Rohdaten und cif-Dateien. - Auswertung der durchgeführten Kinetiken als xlsx-Datei - Rohdaten der diskutierten quantenmechanischen Rechnungen als out-Dateien.
Code and Data for "S100Z is expressed in a lateral subpopulation of olfactory receptor neurons in the main olfactory system of Xenopus laevis"
(2024-02-05) Kahl, Melina; Hassenklöver, Thomas
This repository contains Python scripts that were used to analyze the distribution of manually identified cells in the olfactory system. Multiphoton microscopy image stacks of immunohistochemically labeled olfactory system tissue were manually annotated using the ImageJ ROI Manager tool. Regions of interest were exported from ImageJ as roi-files (provided as zip-archive). We include two datasets that were analyzed using these scripts. The datasets comprise of the imported ROI informations, experiment metadata, and results of calculations performed with the Python scripts. code.py: Script collection to analyze regions of interest drawn using the ImageJ ROI Manager tool. rois_from_imagej.zip: Roi-files exported from ImageJ. Subfolders contain s100z/biocytin labeled cells in different samples. biocytin_cell_counts.csv: Dataset of biocytin-backfilled olfactory receptor neurons s100z_cell_counts.csv: Dataset of human S100Z antibody labeled cells
Data and Code for "Contrasting Historical and Physical Perspectives in Asymmetric Catalysis: ∆∆G‡ versus enantiomeric excess"
(2023-10-13) Ruth, Marcel
This repository contains all datasets that were used to evaluate the difference between ee and ΔΔG‡ modeling in enantioselective organocatalytic reactions. The scripts and notebooks used are also included to elucidate our modeling process. All descriptor and fingerprint-based models are included in "descriptorbased_parametric_models-repeated.ipynb". The evaluations and hyperparameter optimizations by our graph neural network are split into several small scripts and helper functions (basically all Python files). Article abstract: The modeling of catalytic, enantioselective reactions is pivotal for chiral drug development, green chemistry, and industrial applications. While ligand-based and quantitative structure-activity relationships have a long history, the limitations of these methods, including inadequate representation of reaction dynamics and physical constraints, have become increasingly evident. With the rise of machine learning due to increased computational power, the modeling of chemical systems has reached a new era and has the potential to revolutionize how we understand and predict reactions. Here we probe the historic dependence on utilizing enantiomeric excess (ee) as a target variable and discuss the benefits of using instead physically grounded differences Gibbs free activation energies (ΔΔG‡). We outline key benefits, such as enhanced modeling performance using ΔΔG‡, escaping physical limitations, addressing temperature effects, managing non-linear error propagation, adjusting for data distributions, and how to deal with unphysical predictions. For this endeavor, we gathered ten datasets from the literature covering very different reaction types, e.g., hydrogenation, Suzuki-, and Heck-reactions for 2761 data points. We evaluated fingerprint, descriptor, and graph neural network based models. Our results highlight the distinction in performance among varying model complexities and emphasize the importance of choosing suitable metrics for accurate and robust chemical modeling.
Data and Code for "Designing the Next Better Catalyst Utilizing Machine Learning with a Key-Intermediate Graph: Differentiating a Methyl from an Ethyl Group"
(2023-11-15) Pereira, Oliver; Ruth, Marcel
# Dataset and Scripts Overview ## General Overview This dataset includes a series of Python scripts and Jupyter notebooks that are primarily focused on the analysis, modeling, and visualization of chemical data. The scripts encompass various aspects of data preprocessing, including graph-based transformations, model definitions for Graph Neural Networks (GNNs) and Feedforward Neural Networks (FFNNs), training utilities like early stopping, and comprehensive workflows for training, evaluating, and visualizing model performance. ## File Descriptions ### Python Scripts 1. **CV_cat-subs.py**: Script for training and evaluating a machine learning model using cross-validation. 2. **LOOCV_CV.py**: Similar to CV_cat-subs.py but employs Leave-One-Out Cross-Validation for model evaluation. 3. **config.py**: Configuration file containing optimal parameters for the models. 4. **eval_mol_representation.py**: Evaluates molecular representations using various machine learning models. 5. **hpo_cbs.py**: Hyperparameter optimization script for tuning Graph Neural Network models. 6. **models.py**: Defines neural network models, including Graph Neural Networks. 7. **preprocessing_data_new.py**: Preprocesses the dataset, preparing it for analysis and modeling. 8. **preprocessing_graph_new.py**: Prepares graph-based data representations, essential for GNNs. 9. **screening_models.py**: Provides additional model definitions for various machine learning tasks. 10. **training.py**: Contains utilities for model training, including an early stopping mechanism. ### Jupyter Notebooks 1. **CV_plots.ipynb**: Focuses on data visualization, particularly for cross-validation results. 2. **main.ipynb**: A comprehensive notebook covering data preprocessing, model training, evaluation, and visualization. ## Dataset Structure: "CBS_10-04-2023.csv" The dataset "CBS_10-04-2023.csv" is a key component of this collection. It includes various chemical properties and molecular structures relevant to the domain of cheminformatics. The structure of the dataset comprises columns that detail different chemical entities (catalyst, substrate, product), reaction conditions, and results. This dataset is used extensively throughout the scripts and notebooks for preprocessing, analysis, and model training. Understanding its structure is crucial for interpreting the results and for any further modification or analysis. ## Usage Instructions To use these scripts and notebooks, ensure you have Python installed along with necessary libraries like Pandas, NumPy, Torch, Torch Geometric, and RDKit. Each script can be executed independently, provided the required data files are available in the specified paths. The Jupyter notebooks can be run in a sequence for a complete end-to-end workflow. ## Variable and Function Explanations - Variables and functions within the scripts and notebooks are named to reflect their purpose in data processing, modeling, or visualization tasks. Specific domain-related variables, such as those handling chemical properties or molecular structures, are used in accordance with standard practices in cheminformatics. ## Additional Notes - These scripts and notebooks are tailored for chemical data analysis and may require domain-specific understanding for optimal usage and interpretation of results.
Data and Code for "Machine Learning for Bridging the Gap between Density Functional Theory and Coupled Cluster Energies"
(2023-02-02) Ruth, Marcel
The datasets, models, and scripts were created to achieve an accurate prediction of the increment of single-point energies between density functional theory (DFT) and wavefunction-based methods, which led to our submitted article: 'A Machine Learning Approach for Bridging the Gap between Density Functional Theory and Coupled Cluster Energies'. We used the ORCA quantum chemical package to compute the geometries of each species at the B3LYP-D3(BJ)/cc-pVTZ level of theory. The optimized structure was subsequently employed for single-point (SP) computations at the DLPNO-CCSD(T)/cc-pVTZ and CCSD(T)/cc-pVTZ levels of theory. All data were extracted from the calculations and compiled in the provided .csv files. With the datasets and prediction scripts, it is possible to forecast the differences in single-point (SP) energies between the B3LYP-D3(BJ)/cc-pVTZ and DLPNO-CCSD(T)/cc-pVTZ (for monomers and dimers) levels of theory, as well as to the CCSD(T)/cc-pVTZ level of theory for monomers. The datasets can be opened and read with any text editor. The Pytorch models can be loaded and manipulated as usual (https://pytorch.org/tutorials/beginner/saving_loading_models.html). The prediction can be made by installing a suitable Python environment and setting the code line: test_database = f'TestDatabase_{mode}.csv' to the desired dataset for prediction. The format and column names of the file should match the uploaded dataset files. Once the line is modified, a prediction can be generated using the following command, for example, “python gen_predictions_CCSDt.py”.
Data for "1,1,2-Ethenetriol: The Enol of Glycolic Acid, a High-Energy Prebiotic Molecule"
(2021) Schreiner, Peter
Raw IR , UV/is and NMR spectra for the publication A. Mardyukov, F. Keul, and P. R. Schreiner "1,1,2-Ethenetriol: The Enol of Glycolic Acid, a High-Energy Prebiotic Molecule" . File format is the Bruker vibrational spectroscopy software OPUS for visualization, processing, analysis IR and UV/Vis data. File format is MestReNova NMR software for visualization, processing, analysis NMR data.
Data for "Current extinction rate in European freshwater gastropods greatly exceeds that of the late Cretaceous mass extinction"
(2021-03-24) Neubauer, Thomas A.
The dataset contains the primary data underyling the diversification analyses in Neubauer et al. (2021), as well as the results of the iucn_sim analyses on current species extinction rates.
Data for "Development of a multi‐step screening procedure for redox active molecules in organic radical polymer anodes and as redox flow anolytes"
(2024-01) Achazi, Andreas J.; Mollenhauer, Doreen
Calculated structural data of organic redox compounds for the publication: Andreas J. Achazi, Xhesilda Fataj, Philip Rohland, Martin D. Hager, Ulrich S. Schubert, Doreen Mollenhauer. "Development of a multi‐step screening procedure for redox active molecules in organic radical polymer anodes and as redox flow anolytes". The structures were optimized at different levels of theory. After downloading and unpacking the *zip-file you will find a file named "Readme.pdf" which contains all details on how to use the dataset and additional computational information to recalculate all data from the dataset (information about software etc.).
Data for "Development of novel redox-active organic materials based on benzimidazole, benzoxazole, and benzothiazole – a combined theoretical and experimental screening approach"
(2023-12) Achazi, Andreas J.; Pohl, K. Linus H.; Mollenhauer, Doreen
Calculated structural data of organic redox moieties for the publication: Xhesilda Fataj, Andreas J. Achazi, Philip Rohland, Erik Schröter, Simon Muench, René Burges, K. Linus H. Pohl, Doreen Mollenhauer, Martin D. Hager, Ulrich S. Schubert. "Development of Novel Redox-Active Organic Materials Based on Benzimidazole, Benzoxazole, and Benzothiazole: A Combined Theoretical and Experimental Screening Approach". All structures were optimized at the BP86D3(BJ)/def2-TZVP (DCOSMO-RS) level of theory. The file format is xyz. In the folders are usually subfolders. "n" stands for neutral molecules, "p" stands for plus which means the molecules have a charge of +1, "pp" stands for plusplus which means the molecules have a charge of +2, and "m" stands for minus which means the molecules have a charge of -1. The rotated folder has only the molecules with a charge of +1. It contains the structures calculated with COSMO and in that folder with DCOSMO-RS. The number in front stands for the degree of rotation. You can find the same information in the ReadMe-file included in the zip-archive.
Data for "Diversity, biogeography, and evolution of European freshwater gastropods through time: a voyage across scales"
(2023-01-31) Neubauer, Thomas A.
The dataset contains the taxonomic, geographic, and stratigraphic data on freshwater mollusks used in the habilitation thesis of T. A. Neubauer at JLU (2023). The dataset is divided into four parts: 1. species occurrence data for fossil European and North American freshwater gastropods from the Triassic to the Pleistocene. This includes information on geography, taxonomy/systematics, stratigraphy, and literature sources. The information was acquired over the past 10 years from the primary literature and constantly updated. Parts were published in previous papers by the author. 2. A species list of all fossil and extant fresh- and brackish-water Mollusca stored in the online database MolluscaBase (https://molluscabase.org/), as of 3 January 2023. 3. Distribution data in the form of geographic polygon names for all taxa in (2), as of 19 December 2022. 4. Fossil age data for all taxa in (2), as of 19 December 2022. Disclaimer: Data from MolluscaBase are used and stored with kind permission. MolluscaBase and its parent, the World Register of Marine Species (WoRMS, https://www.marinespecies.org/), is constantly updated and thus contain the most recent available information on the species and associated distribution and age information.
Data for "Evolution of JAGGED-like genes functions"
(2023-08-28) Siwei, Pang
This is the supplementary material for the master's thesis "Evolution of JAGGED-like genes functions", including vector maps, vector sequences, and sequencing files. Please see the file "Description of dataset.xlsx" for more information about every file in this dataset and how to use them.
Data for "Extinction risk is linked to lifestyle in freshwater gastropods"
(2021-08-17) Neubauer, Thomas A.
The dataset contains the primary species distribution data for Miocene to extant European freshwater gastropods, as well as the presence-absence data for 130 lakes, used in the analyses in Neubauer & Georgopoulou (2021).
Data for "Imaging the microstructure of lithium and sodium metal in anode-free solid-state batteries using electron backscatter diffraction"
(2024-08-28) Fuchs, Till; Ortmann, Till
Dataset Description: The data set consists of series of measurements of electrochemical impedance spectroscopy, scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD) to characterize the microstructure of lithium and sodium metal as well as electrochemically depositied alkali metals at a solid|solid interfaces. A detailed description of the data set and supplementary information related to the data file formats is provided in the "README" file. The data set presented serves as the basis for the following publication and is structured in accordance with the figures presented in this manuscript: Title: Imaging the Microstructure of Lithium and Sodium Metal in “Anode-Free” Solid-State Batteries using EBSD Authors: Till Fuchs, Till Ortmann, Juri Becker, Catherine G. Haslam, Maya Ziegler, Vipin Kumar Singh, Marcus Rohnke, Boris Mogwitz, Klaus Peppler, Linda F. Nazar, Jeff Sakamoto and Jürgen Janek DOI: Publication Abstract (English): “Anode-free” or more fittingly, metal reservoir-free cells (RFCs) have the potential of drastically improving current solid-state battery technology by achieving higher energy density, improving safety and simplifying the manufacturing process. Various strategies have been reported so far to control the morphology of electrodeposited alkali metal films to be homogeneous and dense, for example, by utilizing planar interfaces with seed interlayers or three-dimensional host structures. To date, the microstructure of such electrodeposited alkali metal, i.e., its grain size distribution, shape and orientation is unknown, and a suitable characterization route is yet to be identified. At the same time, the influence of the alkali metal microstructure on the electrochemical performance of the anode, including the available discharge capacity, is expected to be substantial. Hence, analysis of the microstructure and its influence on the performance of electrochemically deposited alkali metal layers is a key require-ment to improving cell performance. This work establishes first a highly reproducible protocol for characterizing the size and orientation of metal grains in differently processed lithium and sodium samples by a combination of focused-ion beam (FIB) techniques and electron-backscatter diffraction (EBSD) with high spatial resolution. After ruling out grain growth in lithium or sodium during room temperature storage or induced by FIB, electrodeposited films at Cu|LLZO, Steel|LPSCl and Al|NZSP interfaces were then characterized. The analyses show very large grain sizes (>100 µm) within these films and a clear preferential orientation of grain boundaries. Furthermore, metal growth and dissolution were investigated using in situ SEM analyses, showing a dynamic grain coarsening during electrodeposition and pore formation within grains during dissolution. Our methodology and results open up a new research field for the improvement of solid-state battery performance through first characteriza-tion of the deposited alkali metal microstructure and subsequently suggesting methods to control it.
Data for "Insight into the Li/LiPON Interface at the Molecular Level: Interfacial Decomposition and Reconfiguration"
(2024-05) Wang, Kangli; Mollenhauer, Doreen
This dataset contains the calculated structures involving the surface and interface for the publication: Kangli Wang, Jürgen Janek, Doreen Mollenhauer. "Insight into the Li/LiPON Interface at the Molecular Level: Interfacial Decomposition and Reconfiguration". Further information relevant to the reuse of the dataset can be found in the included readme file.
Data for "Matrix Isolation and Photorearrangement of Cis- and Trans- 1,2-Ethenediol to Glycolaldehyde"
(2022) Mardyukov, Artur
Raw IR , UV/is and NMR spectra for the publication A. Mardyukov, R. C. Wende, and P. R. Schreiner "Matrix Isolation and Photorearrangement of Cis- and Trans- 1,2-Ethenediol to Glycolaldehyde". File format is the Bruker vibrational spectroscopy software OPUS for visualization, processing and analysis of IR and UV/Vis data. File format is MestReNova NMR software for visualization, processing and analysis of NMR data.
Data for "Short-term paleogeographic reorganizations and climate events shaped diversification of North American freshwater gastropods over deep time"
(2022-01-03) Neubauer, Thomas A.
The dataset contains species occurrence data for fossil North American freshwater gastropods from the Late Triassic to the Pleistocene. This includes information on geography, taxonomy/systematics, stratigraphy and literature sources.
Data for "The Enol of Isobutyric Acid"
(2024) Danho, Akkad
Spectra for deuterated and non-deuterated enols, along with density functional theory computations IR and UVVis-spectra. A Sumitomo cryostat system consisting of an RDK 408D2 closed-cycle refrigerator cold head and an F-70 compressor unit was used for matrix isolation experiments. A polished CsI window was mounted in the cold head sample holder. The sample holder, connected with silicon diodes for temperature measurements, was covered by a vacuum shroud, which was equipped with KBr windows to allow for IR measurements. In some experiments BaF2 windows were used due to their higher transparency when measuring UV/vis spectra. The sample and the host gas (Ar, purity of 99.999%) were co-deposited at 3.5 K. All spectral data were collected at 3.5 K. The pyrolysis zone was equipped with a heatable 90 mm long quartz tube (inner diameter 7 mm), controlled by a Ni/CrNi thermocouple. The travel distance of the sample from the pyrolysis zone to the matrix was ∼45 mm. Ar was stored in a 2 L gas balloon, which was evacuated and filled three times before every experiment. The sample was evaporated from a Schlenk tube at 80 °C (water) and reduced pressure (∼3 × 10–6 mbar) and co-deposited with a high excess of argon on both sides of the matrix window in the dark (preventing unwanted photochemistry) at a rate of ∼1 mbar min–1, based on the pressure inside the Ar balloon. Pyrolyses were carried out at 750 °C. IR spectra were recorded between 7000 and 350 cm–1 with a resolution of 0.7 cm–1 with a Bruker Vertex 70 FTIR spectrometer. A spectrum of the cold matrix window before deposition was used as background spectrum for the subsequent IR measurements. UV/vis spectra were recorded between 190 and 800 nm with a resolution of 1 nm with a Jasco V-760 spectrophotometer. A high-pressure-mercury lamp equipped with a monochromator (LOT Quantum Design) or a low-pressure-mercury lamp (Gräntzel) fitted with a Vycor filter were used for irradiation of the matrix during photochemical experiments. Spectra were saved as "X-files" and can be opened with "OPUS". Computations. All DFT computations were performed with the Gaussian 16,1 Revision C.01 (full citations for electronic structure codes are given at the end of this document) at the B3LYP/def2-TZVP2-3 level of theory. The keywords Opt and Freq=NoRaman were used for the characterization of minima on the PES. For transition structures the keyword Opt=(ts,tight,calcfc,noeigen) was used. UV/Vis absorptions were computed by using the keyword td(50-50,nstates=10). The results of the calculations were saved as "out" files and can be opened with the editor and graphically with 'ChemCraft'.
Data for "The enol of propionic acid"
(2023-08-25) Danho, Akkad
IR and UVVis-spectra. A Sumitomo cryostat system consisting of an RDK 408D2 closed-cycle refrigerator cold head and an F-70 compressor unit was used for matrix isolation experiments. A polished CsI window was mounted in the cold head sample holder. The sample holder, connected with silicon diodes for temperature measurements, was covered by a vacuum shroud, which was equipped with KBr windows to allow for IR measurements. In some experiments BaF2 windows were used due to their higher transparency when measuring UV/vis spectra. The sample and the host gas (Ar, purity of 99.999%) were co-deposited at 3.5 K. All spectral data were collected at 3.5 K. The pyrolysis zone was equipped with a heatable 90 mm long quartz tube (inner diameter 7 mm), controlled by a Ni/CrNi thermocouple. The travel distance of the sample from the pyrolysis zone to the matrix was ∼45 mm. Ar was stored in a 2 L gas balloon, which was evacuated and filled three times before every experiment. The sample was evaporated from a Schlenk tube at 70 °C (water) and reduced pressure (∼3 × 10–6 mbar) and co-deposited with a high excess of argon on both sides of the matrix window in the dark (preventing unwanted photochemistry) at a rate of ∼1 mbar min–1, based on the pressure inside the Ar balloon. Pyrolyses were carried out at 500 °C. IR spectra were recorded between 7000 and 350 cm–1 with a resolution of 0.7 cm–1 with a Bruker Vertex 70 FTIR spectrometer. A spectrum of the cold matrix window before deposition was used as background spectrum for the subsequent IR measurements. UV/vis spectra were recorded between 190 and 800 nm with a resolution of 1 nm with a Jasco V-760 spectrophotometer. A high-pressure-mercury lamp equipped with a monochromator (LOT Quantum Design) or a low-pressure-mercury lamp (Gräntzel) fitted with a Vycor filter were used for irradiation of the matrix during photochemical experiments. Spectra were saved as "X-files" and can be opened with "OPUS". Computations. All DFT computations were performed with the Gaussian 16,1 Revision C.01 (full citations for electronic structure codes are given at the end of this document) at the B3LYP/def2-TZVP2-3 level of theory. The keywords Opt and Freq=NoRaman were used for the characterization of minima on the PES. For transition structures the keyword Opt=(ts,tight,calcfc,noeigen) was used. UV/Vis absorptions were computed by using the keyword td(50-50,nstates=10). The results of the calculations were saved as "out" files and can be opened with the editor and graphically with 'ChemCraft'.
Data for "The Intrinsic Barrier Width and Its Role in Chemical Reactivity"
(2023-03-07) Qiu, Guanqi
Raw IR spectra for the publication G. Qiu and P. R. Schreiner "The Intrinsic Barrier Width and its Role in Chemical Reactivity". File format is the Bruker vibrational spectroscopy software OPUS and MestReNova for visualization, processing, and analysis of IR data. The integrals of the relevant peaks were collected in the Excel file. Geometry optimizations and non-projected IRCs were computed at the MP2/cc-pVDZ level of theory using the Gaussian 16 package. All output files are provided. Tunneling half-lives and projected IRCs were determined at the CVT/SCT//MP2/cc-pVDZ level of theory using Polyrate Version 2017-c. Both the Polyrate code and the output files are provided.
Electrochemical data for "Enhancing the Electrochemical Performance of LiNi0.70Co0.15Mn0.15O2 Cathodes Using a Practical Solution-Based Al2O3 Coating"
(2020-06-05) Negi, Rajendra S.
Raw cycling data and electrochemical impedance spectroscopy (EIS) data of the cells investigated in the publication Negi, R.S, Culver, S.P., Mazilkin, A., Brezesinski, T., Elm, M.T. “Enhancing the Electrochemical Performance of LiNi0.70Co0.15Mn0.15O2Cathodes Using a Practical Solution-Based Al2O3Coating” ACS Appl. Mater. Interfaces 2020, 12, 31392-31400; https://doi.org/10.1021/acsami.0c06484. File format is the standard .txt format. Cycling data of the three pristine (uncoated) NCM cathodes (P-NCM) and the three investigated, coated NCM cathodes (C-NCM) are stored in three blocks: 1. Cycle number, 2. Discharge capacity cell1 (mAh g-1), 3. Discharge capacity cell2 (mAh g-1), 4. Discharge capacity cell3 (mAh g-1). Experimental impedance data after the first cycle and the 100th cycle for one pristine (P-NCM) and coated cathode (C-NCM) are stored in 3 blocks: 1. Frequency (Hz), 2. Real part (Ohm), 3. Imaginary Part (Ohm). In each file, blocks 4 and 5 give the results of the fitting according to the equivalent circuit discussed in the publication. Block 4: Fitted real part (Ohm), block 5: Fitted imaginary part (Ohm).

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