arXiv subjects

Christian Thomsen

Publications and source records attributed to Christian Thomsen.

14 recordsLinked to original sources

arXiv2026

Microscopic Origin of Temperature-Dependent Anisotropic Heat Transport in Ultrawide-Bandgap Rutile GeO2

Ultrawide-bandgap rutile GeO2 is emerging as a promising semiconductor for power electronics, where efficient heat dissipation is essential to suppress self-heating and ensure device reliability. However, the temperature dependence and microscopic origin of its anisotropic heat transport have remained experimentally unresolved. Here, temperature-dependent time-domain thermoreflectance measurements combined with first-principles phonon transport calculations are used to quantify the thermal conductivity of single-crystal rutile GeO2 from 80 to 350 K along [001] and [110]. At 295 K, the thermal conductivity reaches 47.5 W m^-1 K^-1 along [001] and 32.5 W m^-1 K^-1 along [110], corresponding to an anisotropy ratio of 1.46, in good agreement with theory. Rather than following a simple T^(-1) law, the thermal conductivity exhibits an approximate T^(-1.4) dependence, indicating additional scattering beyond purely three-phonon-limited transport. Mode-resolved analysis reveals that the room-temperature anisotropy originates from the combined effect of larger phonon group velocities along [001] and direction-dependent phonon lifetimes. Upon cooling, depopulation of high-frequency phonons progressively suppresses their contribution to heat transport and reduces the anisotropy. The temperature-dependent thermal boundary conductance of Al/rutile GeO2 interfaces is further resolved, and the scaled conductance indicates predominantly elastic interfacial transport. These findings establish the microscopic basis of bulk and interfacial heat transport in rutile GeO2 and position this material as a promising thermally robust platform for ultrawide-bandgap electronics.

cond-mat.mtrl-sci↗

arXiv2025

Extending the SAREF4ENER Ontology with Flexibility Based on FlexOffers

A key element to support the increased amounts of renewable energy in the energy system is flexibility, i.e., the possibility of changing energy loads in time and amount. Many flexibility models have been designed; however, exact models fail to scale for long time horizons or many devices. Because of this, the FlexOffers model has been designed, to provide device-independent approximations of flexibility with good accuracy, and much better scaling for long time horizons and many devices. An important aspect of the real-life implementation of energy flexibility is enabling flexible data exchange with many smart energy appliances and market systems, e.g., in smart buildings. For this, ontologies standardizing data formats are required. However, the current industry standard ontology for integrating smart devices for energy purposes, SAREF for Energy Flexibility (SAREF4ENER), only has limited support for flexibility and thus cannot support important use cases. In this paper, we propose an extension of SAREF4ENER that integrates full support for the complete FlexOffer model, including advanced use cases, while maintaining backward compatibility. This novel ontology module can accurately describe flexibility for advanced devices such as electric vehicles, batteries, and heat pumps. It can also capture the inherent uncertainty associated with many flexible load types.

cs.CL↗

arXiv2024

Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems

Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will necessarily have to encompass both the radio and the fiber-optical domain. This paper introduces the Decentralized Multi-Party, Multi-Network AI (DMMAI) framework for integrating AI into 6G networks deployed at scale. DMMAI harmonizes AI-driven controls across diverse network platforms and thus facilitates networks that autonomously configure, monitor, and repair themselves. This is particularly crucial at the network edge, where advanced applications meet heightened functionality and security demands. The radio/optical integration is vital due to the current compartmentalization of AI research within these domains, which lacks a comprehensive understanding of their interaction. Our approach explores multi-network orchestration and AI control integration, filling a critical gap in standardized frameworks for AI-driven coordination in 6G networks. The DMMAI framework is a step towards a global standard for AI in 6G, aiming to establish reference use cases, data and model management methods, and benchmarking platforms for future AI/ML solutions.

cs.NI↗

arXiv2024

Creating and Querying Data Cubes in Python using pyCube

Data cubes are used for analyzing large data sets usually contained in data warehouses. The most popular data cube tools use graphical user interfaces (GUI) to do the data analysis. Traditionally this was fine since data analysts were not expected to be technical people. However, in the subsequent decades the data landscape changed dramatically requiring companies to employ large teams of highly technical data scientists in order to manage and use the ever increasing amount of data. These data scientists generally use tools like Python, interactive notebooks, pandas, etc. while modern data cube tools are still GUI based. This paper proposes a Python-based data cube tool called pyCube. pyCube is able to semi-automatically create data cubes for data stored in an RDBMS and manages the data cube metadata. pyCube's programmatic interface enables data scientist to query data cubes by specifying the expected metadata of the result. pyCube is experimentally evaluated on Star Schema Benchmark (SSB). The results show that pyCube vastly outperforms different implementations of SSB queries in pandas in both runtime and memory while being easier to read and write.

cs.DB↗

arXiv2021

Scalable Model-Based Management of Correlated Dimensional Time Series in ModelarDB+

To monitor critical infrastructure, high quality sensors sampled at a high frequency are increasingly used. However, as they produce huge amounts of data, only simple aggregates are stored. This removes outliers and fluctuations that could indicate problems. As a remedy, we present a model-based approach for managing time series with dimensions that exploits correlation in and among time series. Specifically, we propose compressing groups of correlated time series using an extensible set of model types within a user-defined error bound (possibly zero). We name this new category of model-based compression methods for time series Multi-Model Group Compression (MMGC). We present the first MMGC method GOLEMM and extend model types to compress time series groups. We propose primitives for users to effectively define groups for differently sized data sets, and based on these, an automated grouping method using only the time series dimensions. We propose algorithms for executing simple and multi-dimensional aggregate queries on models. Last, we implement our methods in the Time Series Management System (TSMS) ModelarDB (ModelarDB+). Our evaluation shows that compared to widely used formats, ModelarDB+ provides up to 13.7 times faster ingestion due to high compression, 113 times better compression due to the adaptivity of GOLEMM, 630 times faster aggregates by using models, and close to linear scalability. It is also extensible and supports online query processing.

cs.DB↗

arXiv2017

Time Series Management Systems: A Survey

The collection of time series data increases as more monitoring and automation are being deployed. These deployments range in scale from an Internet of things (IoT) device located in a household to enormous distributed Cyber-Physical Systems (CPSs) producing large volumes of data at high velocity. To store and analyze these vast amounts of data, specialized Time Series Management Systems (TSMSs) have been developed to overcome the limitations of general purpose Database Management Systems (DBMSs) for times series management. In this paper, we present a thorough analysis and classification of TSMSs developed through academic or industrial research and documented through publications. Our classification is organized into categories based on the architectures observed during our analysis. In addition, we provide an overview of each system with a focus on the motivational use case that drove the development of the system, the functionality for storage and querying of time series a system implements, the components the system is composed of, and the capabilities of each system with regard to Stream Processing and Approximate Query Processing (AQP). Last, we provide a summary of research directions proposed by other researchers in the field and present our vision for a next generation TSMS.

cs.DB↗

arXiv2015

Splitting of the monolayer out-of-plane A'1 Raman mode in few-layer WS2

We present Raman measurements of mono- and few-layer WS2. We study the monolayer A'1 mode around 420 cm(-1) and its evolution with the number of layers. We show that with increasing layer number there is an increasing number of possible vibrational patterns for the out-of-plane Raman mode: in N-layer WS2 there are N Gamma-point phonons evolving from the A'1 monolayer mode. For an excitation energy close to resonance with the excitonic transition energy we were able to observe all of these N components, irrespective of their Raman activity. Density functional theory calculations support the experimental findings and make it possible to attribute the modes to their respective symmetries. The findings described here are of general importance for all other phonon modes in WS2 and other layered transition metal dichalcogenide systems in the few layer regime.

cond-mat.mes-hall↗

arXiv2012

Index assignment of a carbon nanotube rope using tip-enhanced Raman spectroscopy

We used tip-enhanced Raman spectroscopy to study the diameter-dependent Raman modes in a contacted carbon nanotube rope. We show that with the near-field tip enhancement a large number of nanotubes within a rope can be identified, even if the nanotube modes can not be distinguished in the far-field signal. Several metallic and semiconducting nanotubes can be identified and assigned to nanotube families. Additionally, we provide a tentative chiral index assignment.

cond-mat.mes-hall↗

arXiv2011

Ab initio calculations of edge-functionalized armchair graphene nanoribbons: Structural, electronic, and vibrational effects

We present a theoretical study on narrow armchair graphene nanoribbons (AGNRs) with hydroxyl functionalized edges. Although this kind of passivation strongly affects the structure of the ribbon, a high degree of edge functionalization proves to be particularly stable. An important consequence of the geometric deviations is a severe reduction of the band-gap of the investigated 7-AGNR. This shift follows a linear dependence on the number of added hydroxyl groups per unit cell and thus offers the prospect of a tunable band-gap by edge functionalization. We furthermore cover the behavior of characteristic phonons for the ribbon itself as well as fingerprint modes of the hydroxyl groups. A large down-shift of prominent Raman active modes allows the experimental determination of the degree of edge functionalization.

cond-mat.mes-hall↗

arXiv2011

Raman 2D-Band Splitting in Graphene: Theory and Experiment

We present a systematic experimental and theoretical study of the two-phonon (2D) Raman scattering in graphene under uniaxial tension. The external perturbation unveils that the 2D mode excited with 785nm has a complex line-shape mainly due to the contribution of two distinct double resonance scattering processes (inner and outer) in the Raman signal. The splitting depends on the direction of the applied strain and the polarization of the incident light. The results give new insight into the nature of the 2D band and have significant implications for the use of graphene as reinforcement in composites since the 2D mode is crucial to assess how effectively graphene uptakes an applied stress or strain.

cond-mat.mes-hall↗

arXiv2010

Splitting of the Raman $2D$ band of graphene subjected to strain

The Raman $2D$-band -important for the analysis of graphene- shows a splitting for uniaxial strain. The splitting depends on the strength and direction of the applied strain and on the polarization of the incident and outgoing light. We expand the double-resonance Raman model in order to explain the strain direction dependence and the polarization dependence of the splitting. The analysis of this splitting gives new insight into the origin of the $2D$-band. Our prediction of the strain direction and polarization dependence agrees well with recent experiments.

cond-mat.mtrl-sci↗

arXiv2009

The two-dimensional Brillouin zone of uniaxially strained graphene

We present an in-depth analysis of the electronic and vibrational band structure of uniaxially strained graphene by ab-initio calculations. Depending on the direction and amount of strain, the Fermi crossing moves away from the $K$-point. However, graphene remains semimetallic under small strains. The deformation of the Dirac cone near the $K$-point gives rise to a broadening of the 2D Raman mode. In spite of specific changes in the electronic and vibrational band structure the strain-induced frequency shifts of the Raman active E2g and 2D modes are independent of the direction of strain. Thus, the amount of strain can be directly determined from a single Raman measurement.

cond-mat.mes-hall↗

arXiv2009

Vibrational properties of graphene nanoribbons by first-principles calculations

We investigated the vibrational properties of graphene nanoribbons by means of first-principles calculations on the basis of density functional theory. We confirm that the phonon modes of graphene nanoribbons with armchair and zigzag type edges can be interpreted as fundamental oscillations and their overtones. These show a characteristic dependence on the nanoribbon width. Furthermore, we demonstrate that a mapping of the calculated Gamma-point phonon frequencies of nanoribbons onto the phonon dispersion of graphene corresponds to an "unfolding" of nanoribbons' Brillouin zone onto that of graphene. We consider the influence of spin states with respect to the phonon spectra of zigzag nanoribbons and provide comparisons of our results with past studies.

cond-mat.mtrl-sci↗

arXiv2005

Exciton resonances quench the photoluminescence of zigzag carbon nanotubes

We show that the photoluminescence intensity of single-walled carbon nanotubes is much stronger in tubes with large chiral angles - armchair tubes - because exciton resonances make the luminescence of zigzag tubes intrinsically weak. This exciton-exciton resonance depends on the electronic structure of the tubes and is found more often in nanotubes of the +1 family. Armchair tubes do not necessarily grow preferentially with present growth techniques; they just have stronger luminescence. Our analysis allows to normalize photoluminescence intensities and find the abundance of nanotube chiralities in macroscopic samples.

cond-mat.mtrl-sci↗