| 1. |
- Borysov, Stanislav S., et al.
(författare)
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Online search tool for graphical patterns in electronic band structures
- 2018
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Ingår i: npj Computational Materials. - : Springer Science and Business Media LLC. - 2057-3960. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- Many functional materials can be characterized by a specific pattern in their electronic band structure, for example, Dirac materials, characterized by a linear crossing of bands; topological insulators, characterized by a Mexican hat pattern or an effectively free electron gas, characterized by a parabolic dispersion. To find material realizations of these features, manual inspection of electronic band structures represents a relatively easy task for a small number of materials. However, the growing amount of data contained within modern electronic band structure databases makes this approach impracticable. To address this problem, we present an automatic graphical pattern search tool implemented for the electronic band structures contained within the Organic Materials Database. The tool is capable of finding user-specified graphical patterns in the collection of thousands of band structures from high-throughput calculations in the online regime. Using this tool, it only takes a few seconds to find an arbitrary graphical pattern within the ten electronic bands near the Fermi level for 26,739 organic crystals. The source code of the developed tool is freely available and can be adapted to any other electronic band structure database.
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| 2. |
- Finizio, Simone, et al.
(författare)
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Periodogram-Based Detection of Unknown Frequencies in Time-Resolved Scanning Transmission X-ray Microscopy
- 2022
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Ingår i: ACS Nano. - : American Chemical Society (ACS). - 1936-0851 .- 1936-086X. ; 16:12, s. 21071-21078
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Tidskriftsartikel (refereegranskat)abstract
- Pump–probe time-resolved imaging is a powerful technique that enables the investigation of dynamical processes. Signal-to-noise and sampling rate restrictions normally require that cycles of an excitation are repeated many times with the final signal reconstructed using a reference. However, this approach imposes restrictions on the types of dynamical processes that can be measured, namely, that they are phase locked to a known external signal (e.g., a driven oscillation or impulse). This rules out many interesting processes such as auto-oscillations and spontaneously forming populations, e.g., condensates. In this work we present a method for time-resolved imaging, based on the Schuster periodogram, that allows for the reconstruction of dynamical processes where the intrinsic frequency is not known. In our case we use time of arrival detection of X-ray photons to reconstruct magnetic dynamics without using a priori information on the dynamical frequency. This proof-of-principle demonstration will allow for the extension of pump–probe time-resolved imaging to the important class of processes where the dynamics are not locked to a known external signal and in its presented formulation can be readily adopted for X-ray imaging and also adapted for wider use.
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| 3. |
- Geilhufe, R. Matthias, et al.
(författare)
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Identification of strongly interacting organic semimetals
- 2020
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Ingår i: Physical Review B. - : AMER PHYSICAL SOC. - 2469-9950 .- 2469-9969. ; 102:20
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Tidskriftsartikel (refereegranskat)abstract
- Dirac and Weyl point- and line-node semimetals are characterized by a zero band gap with simultaneously vanishing density of states. Given a sufficient interaction strength, such materials can undergo an interaction instability, e.g., into an excitonic insulator phase. Due to generically flatbands, organic crystals represent a promising materials class in this regard. We combine machine learning, density functional theory, and effective models to identify specific example materials. Without taking into account the effect of many-body interactions, we found the organic charge transfer salts [bis(3,4-diiodo-3',4'-ethyleneditio-tetrathiafulvalene), 2,3-dichloro-5,6-dicyanobenzoquinone, acetenitrile] [(EDT-TTF-I-2)(2)](DDQ)center dot(CH3CN) and 2, 2', 5, 5'-tetraselenafulvalene-7, 7, 8, 8-tetracyano-p-quinodimethane (TSeF-TCNQ) and a bis-1,2,3-dithiazolyl radical conductor to exhibit a semimetallic phase in our ab initio calculations. Adding the effect of strong particle-hole interactions for (EDT-TTF-I-2)(2)(DDQ)center dot(CH3CN) and TSeF-TCNQ opens an excitonic gap on the order of 60 and 100 meV, which is in good agreement with previous experiments on these materials.
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| 4. |
- Geilhufe, R. Matthias, et al.
(författare)
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Materials Informatics for Dark Matter Detection
- 2018
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Ingår i: Physica Status Solidi. Rapid Research Letters. - : Wiley. - 1862-6254 .- 1862-6270. ; 12:11
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Tidskriftsartikel (refereegranskat)abstract
- Dark Matter particles are commonly assumed to be weakly interacting massive particles (WIMPs) with a mass in the GeV to TeV range. However, recent interest has shifted toward lighter WIMPs, which are more difficult to probe experimentally. A detection of sub-GeV WIMPs will require the use of small gap materials in sensors. Using recent estimates of the WIMP mass, we identify the relevant target space toward small gap materials (100 to 10 meV). Dirac Materials, a class of small- or zero-gap materials, emerge as natural candidates for sensors for Dark Matter detection. We propose the use of informatics tools to rapidly assay materials band structures to search for small gap semiconductors and semimetals, rather than focusing on a few preselected compounds. As a specific example of the proposed strategy, we use the organic materials database () to identify organic candidates for sensors: the narrow band gap semiconductors BNQ-TTF and DEBTTT with gaps of 40 and 38 meV, and the Dirac-line semimetal (BEDT-TTF)center dot Br which exhibits a tiny gap of approximate to 50 meV when spin-orbit coupling is included. We outline a novel and powerful approach to search for dark matter detection sensor materials by means of a rapid assay of materials using informatics tools.
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| 5. |
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| 6. |
- Olsthoorn, Bart, et al.
(författare)
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Band Gap Prediction for Large Organic Crystal Structures with Machine Learning
- 2019
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Ingår i: Advanced Quantum Technologies. - : Wiley. - 2511-9044. ; 2:7-8
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Tidskriftsartikel (refereegranskat)abstract
- Machine‐learning models are capable of capturing the structure–property relationship from a dataset of computationally demanding ab initio calculations. Over the past two years, the Organic Materials Database (OMDB) has hosted a growing number of calculated electronic properties of previously synthesized organic crystal structures. The complexity of the organic crystals contained within the OMDB, which have on average 82 atoms per unit cell, makes this database a challenging platform for machine learning applications. In this paper, the focus is on predicting the band gap which represents one of the basic properties of a crystalline material. With this aim, a consistent dataset of 12 500 crystal structures and their corresponding DFT band gap are released, freely available for download at https://omdb.mathub.io/dataset. An ensemble of two state‐of‐the‐art models reach a mean absolute error (MAE) of 0.388 eV, which corresponds to a percentage error of 13% for an average band gap of 3.05 eV. Finally, the trained models are employed to predict the band gap for 260 092 materials contained within the Crystallography Open Database (COD) and made available online so that the predictions can be obtained for any arbitrary crystal structure uploaded by a user.
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| 7. |
- Olsthoorn, Bart, et al.
(författare)
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Finding hidden order in spin models with persistent homology
- 2020
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Ingår i: Physical Review Research. - : American Physical Society (APS). - 2643-1564. ; 2:4
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Tidskriftsartikel (refereegranskat)abstract
- Persistent homology (PH) is a relatively new field in applied mathematics that studies the components and shapes of discrete data. In this paper, we demonstrate that PH can be used as a universal framework to identify phases of classical spins on a lattice. This demonstration includes hidden order such as spin-nematic ordering and spin liquids. By converting a small number of spin configurations to barcodes we obtain a descriptive picture of configuration space. Using dimensionality reduction to reduce the barcode space to color space leads to a visualization of the phase diagram.
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| 8. |
- Olsthoorn, Bart
(författare)
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Homology and machine learning for materials informatics
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Materials informatics is the field of study where materials science is combined with modern data science. This data-driven approach is powered by the growing availability of computational power and storage capability. The development and application of these methods accelerates materials science and represents an effective way to study and model material properties. This thesis is a compilation of theoretical and computational works that can be divided into three key areas: materials databases, machine learning for materials, and homology for materials.Machine learning and data mining rely on the availability of materials databases to test methods and models. The Organic Materials Database (OMDB), for example, contains a large number of organic crystals and their corresponding electronic structures. The electronic properties of the organic crystals are computed using atomic scale materials modelling, which is computationally expensive because organic crystals typically contain many atoms in the unit cell. However, the resulting data can be used in a variety of materials informatics applications. We demonstrate data mining for dark matter sensors as an example application.Accurate machine learning models can capture the structure-property relationship of materials and accelerate the discovery of new materials with desired properties. This is explored by investigating the properties of the organic crystals in the OMDB. For example, we employ supervised learning on the electronic band gap, an important material property for technological applications. Unsupervised learning is used to construct a dimensionality-reduced chemical space that reveals interesting clusters of materials.Finally, persistent homology is a relatively new method from the field of algebraic topology that studies the shapes that are present in data at different length scales. In this thesis, the method is used to study magnetic materials and their phase transitions. More specifically, in the case of classical models, we use persistent homology to detect the phase transition directly from sampled spin configurations. For quantum spin models, the shapes in the entanglement structure are captured and a sudden change reveals a quantum phase transition.In summary, these three topics provide an overview on how to study material properties with modern data science methods. The tools can be used in combination with the traditional methods in materials science and accelerate materials design.
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| 9. |
- Olsthoorn, Bart, et al.
(författare)
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Indoor radon exposure and its correlation with the radiometric map of uranium in Sweden
- 2022
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 811
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Tidskriftsartikel (refereegranskat)abstract
- Indoor radon concentrations are controlled by both human factors and geological factors. It is important to separate the anthropogenic and geogenic contributions. We show that there is a positive correlation between the radiometric map of uranium in the ground and the measured radon in the household in Sweden. A map of gamma radiation is used to obtain an equivalent uranium concentration (ppm eU) for each postcode area. The aggregated uranium content is compared to the yearly average indoor radon concentration for different types of houses. Interestingly, modern households show reduced radon concentrations even in postcode areas with high average uranium concentrations. This shows that modern construction is effective at reducing the correlation with background uranium concentrations and minimizing the health risk associated with radon exposure. These correlations and predictive housing parameters could assist in monitoring higher risk areas.
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| 10. |
- Olsthoorn, Bart, et al.
(författare)
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Mass fluctuations and absorption rates in dark-matter sensors based on Dirac materials
- 2020
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Ingår i: Physical Review B. - : AMER PHYSICAL SOC. - 2469-9950 .- 2469-9969. ; 101:4
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Tidskriftsartikel (refereegranskat)abstract
- We study the mass fluctuations in gapped Dirac materials by treating the mass term as both a continuous and discrete random variable. Gapped Dirac materials were proposed to be used as materials for dark-matter sensors. One thus would need to estimate the role of disorder and fluctuations on the interband absorption of dark matter. We find that both continuous and discrete fluctuations across the sample introduce tails (e.g., Dirac-Lifshitz tails) in the density of states and the interband absorption rate. We estimate the strength of the gap filling and discuss implications of these fluctuations on the performance as sensors for dark matter detection. The approach used in this work provides a basic framework to model the disorder by any arbitrary mechanism on the interband absorption of Dirac material sensors.
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| 11. |
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| 12. |
- Olsthoorn, Bart
(författare)
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Persistent homology of quantum entanglement
- 2023
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Ingår i: Physical Review B. - : American Physical Society (APS). - 2469-9950 .- 2469-9969. ; 107:11
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Tidskriftsartikel (refereegranskat)abstract
- Structure in quantum entanglement entropy is often leveraged to focus on a small corner of the exponentially large Hilbert space and efficiently parametrize the problem of finding ground states. A typical example is the use of matrix product states for local and gapped Hamiltonians. We study the structure of entanglement entropy using persistent homology, a relatively new method from the field of topological data analysis. The inverse quantum mutual information between pairs of sites is used as a distance metric to form a filtered simplicial complex. Both ground states and excited states of common spin models are analyzed as an example. Furthermore, the effect of homology with different coefficients and boundary conditions is also explored. Beyond these basic examples, we also discuss the promising future applications of this modern computational approach, including its connection to the question of how space-time could emerge from entanglement.
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| 13. |
- Rocha, W. R. M., et al.
(författare)
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LIDA : The Leiden Ice Database for Astrochemistry
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 668
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Tidskriftsartikel (refereegranskat)abstract
- Context. High-quality vibrational spectra of solid-phase molecules in ice mixtures and for temperatures of astrophysical relevance are needed to interpret infrared observations toward protostars and background stars. Such data are collected worldwide by several laboratory groups in support of existing and upcoming astronomical observations. Over the last 25 yr, the Laboratory for Astrophysics at Leiden Observatory has provided more than 1100 (high-resolution) spectra of diverse ice samples.Aims. In time with the recent launch of the James Webb Space Telescope, we have fully upgraded the Leiden Ice Database for Astrochemistry (LIDA) adding recently measured spectra. The goal of this paper is to describe what options exist regarding accessing and working with a large collection of infrared (IR) spectra, and the ultraviolet-visible (UV/vis) to the mid-infrared refractive index of H2O ice. This also includes astronomy-oriented online tools to support the interpretation of IR ice observations.Methods. This ice database is based on open-source Python software, such as Flask and Bokeh, used to generate the web pages and graph visualization, respectively. Structured Query Language (SQL) is used for searching ice analogs within the database and Jmol allows for three-dimensional molecule visualization. The database provides the vibrational modes of molecules known and expected to exist as ice in space. These modes are characterized using density functional theory with the orca software. The IR data in the database are recorded via transmission spectroscopy of ice films condensed on cryogenic substrates. The real UV/vis refractive indices of H2O ice are derived from interference fringes created from the simultaneous use of a monochromatic HeNe laser beam and a broadband Xe-arc lamp, whereas the real and imaginary mid-IR values are theoretically calculated. LIDA not only provides information on fundamental ice properties, but it also offers online tools. The first tool, SPECFY, is directly linked to the data in the database to create a synthetic spectrum of ices towards protostars. The second tool allows the uploading of external files and the calculation of mid-infrared refractive index values.Results. LIDA provides an open-access and user-friendly platform to search, download, and visualize experimental data of astrophysically relevant molecules in the solid phase. It also provides the means to support astronomical observations; in particular, those that will be obtained with the James Webb Space Telescope. As an example, we analysed the Infrared Space Observatory spectrum of the protostar AFGL 989 using the resources available in LIDA and derived the column densities of H2O, CO and CO2 ices.
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| 14. |
- Rocha, W. R.M., et al.
(författare)
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SPECFY - an important tool of the Leiden Ice Database for Astrochemistry in the era of the James Webb Space Telescope
- 2022
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Ingår i: Honoring Charlotte Moore Sitterly: Astronomical Spectroscopy in the 21st Century. - : Cambridge University Press (CUP). ; , s. 67-71
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Molecular data obtained from laboratory studies are crucial for deriving chemical abundances in astrophysical environments. The Leiden Ice Database for Astrochemistry (LIDA; https://icedb.strw.leidenuniv.nl/) has supported these studies for years in the context of astrophysical ices. For the era of the James Webb Space Telescope - JWST, LIDA hosts more than 1100 infrared spectra of pure and mixed ices that mimic different astrophysical conditions and UV-vis optical constants of water ice. Additionally, LIDA has an online tool - SPECFY, that allows the creation of protostar synthetic spectra. In this paper, we create a synthetic spectrum including OCS ice to check the detection feasibility of this molecule with a 3σ significance using JWST. The calculations are made with the exposure time calculator (ETC). LIDA is a prime deliverable of Ice Age, an Early Release Science JWST program. The collected data and online tools are also accessible for other programs collecting ice data.
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