The development of materials with tailored functionalities and with continuously shrinking linear dimensions towards (and below) the nanoscale is not only going to revolutionize state of the art fabrication technologies, but also the computational methodologies used to model the materials properties. Specifically, atomistic methodologies are becoming increasingly relevant in the field of materials science as a fundamental tool in gaining understanding on as well as for pre-designing (in silico material design) the behavior of nanoscale materials in response to external stimuli. The major long-term goal of atomistic modelling is to obtain structure-function relationships at the nanoscale, i.e. to correlate a definite response of a given physical system with its specific atomic conformation and ultimately, with its chemical composition and electronic structure. This has clearly its pendant in the development of bottom-up fabrication technologies, which also require a detailed control and fine tuning of physical and chemical properties at sub-nanometer and nanometer length scales. The current work provides an overview of different applications of atomistic approaches to the study of nanoscale materials. We illustrate how the use of first-principle based electronic structure methodologies, quantum mechanical based molecular dynamics, and appropriate methods to model the electrical and thermal response of nanoscale materials, provides a solid starting point to shed light on the way such systems can be manipulated to control their electrical, mechanical, or thermal behavior. Thus, some typical topics addressed here include the interplay between mechanical and electronic degrees of freedom in carbon based nanoscale materials with potential relevance for designing nanoscale switches, thermoelectric properties at the single-molecule level and their control via specific chemical functionalization, and electrical and spin-dependent properties in biomaterials. We will further show how phenomenological models can be efficiently applied to get a first insight in the behavior of complex nanoscale systems, for which first principle electronic structure calculations become computationally expensive. This will become especially clear in the case of biomolecular systems and organic semiconductors.

The development of materials with tailored functionalities and with continuously shrinking linear dimensions towards (and below) the nanoscale is not only going to revolutionize state of the art fabrication technologies, but also the computational methodologies used to model the materials properties. Specifically, atomistic methodologies are becoming increasingly relevant in the field of materials science as a fundamental tool in gaining understanding on as well as for pre-designing (in silico material design) the behavior of nanoscale materials in response to external stimuli. The major long-term goal of atomistic modelling is to obtain structure-function relationships at the nanoscale, i.e. to correlate a definite response of a given physical system with its specific atomic conformation and ultimately, with its chemical composition and electronic structure. This has clearly its pendant in the development of bottom-up fabrication technologies, which also require a detailed control and fine tuning of physical and chemical properties at sub-nanometer and nanometer length scales. The current work provides an overview of different applications of atomistic approaches to the study of nanoscale materials. We illustrate how the use of first-principle based electronic structure methodologies, quantum mechanical based molecular dynamics, and appropriate methods to model the electrical and thermal response of nanoscale materials, provides a solid starting point to shed light on the way such systems can be manipulated to control their electrical, mechanical, or thermal behavior. Thus, some typical topics addressed here include the interplay between mechanical and electronic degrees of freedom in carbon based nanoscale materials with potential relevance for designing nanoscale switches, thermoelectric properties at the single-molecule level and their control via specific chemical functionalization, and electrical and spin-dependent properties in biomaterials. We will further show how phenomenological models can be efficiently applied to get a first insight in the behavior of complex nanoscale systems, for which first principle electronic structure calculations become computationally expensive. This will become especially clear in the case of biomolecular systems and organic semiconductors.

The report contains an account of a development project done during 10 weeks of the spring semester at Luleå University of Technology 2021. The project is done as a final thesis for the program Bachelor of Science with a focus in industrial design. The development project resulted in a prototype lamp. The functioning prototype is an embodied union of the perspectives environment and living environment. Through smart lighting of the home, the living environment, a room can become more flexible and adaptable. It is easier to install new lighting than it is to move a wall. The lamp is created to improve lighting and spaciousness. A light source's use of contrasts and illumination in all directions can make a room feel more comfortable to be in and larger than it is. The environmental perspective is based on materials science. When designing new products, a factor that controls the product's climate footprint and environmental impact is the choice of material. Greater and greater value is placed in the environmental impact of products and consumers have actively begun to influence their buying behaviors based on striving for a better relationship with the environment, this work has taken advantage of. A biocomposite has therefore been created consisting of a matrix material of potato plastic combined with fiber reinforcement made from dried fruit residues from juice production. Especially potatoes and carrots. This gives a result of a 100% bio-based material. The work has followed an iterative process and used creative methods to stimulate innovation and solutions. A great focus has been placed on the prototype's material and the production of samples of biocomposites. Which has given rise to a lamp whose aesthetics are governed by the material. The lamp has a function of giving off two completely different looks when it is on and off. In an off position, the hardness of the material is emphasized, and when it is lit, it comes to life. Like a sun hanging from the ceiling, the lamp extends the days into the night. / Rapporten innehåller en redogörelse av ett utvecklingsprojekt gjort under 10 veckor av vårterminen på Luleå Tekniska Universitet 2021. Projektet är gjort som ett avslutande examensarbete för programmet Teknologiekandidat med inriktning Teknisk design. Utvecklingsprojektet resulterade i en prototyp-lampa. Den fungerande protypen är en förkroppsligad förening av perspektiven miljö och livsmiljö. Genom smart ljussättning av hemmet, livsmiljön kan ett rum bli mer flexibelt och anpassningsbart. Det är lättar att installera ny belysning än vad det är att flytta en vägg. Lampan är skapt för att förbättra ljussättning och rumslighet. En ljuskällas användning av kontraster och upplysning åt alla håll kan få ett rum att upplevas bekvämare att vara i och större än det är. Miljöperspektivet grundat sig i materiallära. Vid utformning av nya produkter är en faktor som styr produktens klimatavtryck och miljöpåverkan valet av materialet. Ett större och större värde läggs i produkters miljöpåverkan och konsumenter har aktivt börjat påverka sina köpbeteenden utifrån att sträva efter ett bättre förhållande med miljön detta har arbetet tagit vara på. En biokomposit har därför skapats bestående av ett matrismaterial av potatisplast kombinerat med fiberarmering gjort av torkade fruktrester från juiceproduktion. Framförallt potatis och morot. Detta ger ett resultat av ett 100 % biobaserat material. Arbetet har följt en iterativ process och använt kreativa metoder för att stimulera innovation och lösningar. Ett stort fokus har lagts på protypens material och framtagning av prover på biokompositer. Vilket har get ett resultat av en lampa vars estetik styrs av materialet. Lampan har en funktion av att ge ifrån sig två helt skilda utseenden när den är tänd och släckt. I ett släckt läge framhävs materialets hårdhet med när det sedan tänds kommer den till liv. Likt en sol hängande från taket förlänger lampan dagarna in i natten.

Solar-thermochemische Redoxzyklen stellen eine vielversprechende Technologieoption zur Nutzung und Umwandlung von erneuerbaren Energiequellen dar. Durch Reduktion von Metalloxiden bei hoher Temperatur und/oder niedrigem Sauerstoffpartialdruck kann ein Material in einen Zustand überführt werden, der dazu geeignet ist, Sauerstoff aus einem Gasstrom zu entfernen oder Wasser bzw. Kohlenstoffdioxid zu spalten. Dadurch ist es möglich, Luft zu zerlegen oder Sauerstoff zu pumpen, sowie sogenannte solare Brennstoffe zu erzeugen. Eine besonders vielversprechende Materialklasse stellen dabei die Perowskite dar. Diese Materialien bilden stabile Phasen mit sehr unterschiedlichen Zusammensetzungen. In dieser Arbeit wird gezeigt, wie diese Perowskit-Oxide in thermochemischen Redoxzyklen verwendet werden können und die Mechanismen hinter diesen Redoxreaktionen werden mit in-situ-Röntgenuntersuchungen aufgeklärt. Es wird auch gezeigt, dass die kinetischen Parameter der Oxidationsreaktion sehr vielversprechend sind. Zudem wird demonstriert, wie feste Lösungen aus Perowskiten in einem weiten Bereich verschiedener Zusammensetzungen hergestellt werden können und wie die Zusammensetzung der Perowskite die Phasenbildung und Stabilität beinflusst. Mit diesem Wissen wird ein Schwerpunkt dieser Arbeit auf die thermodynamischen Eigenschaften dieser Perowskite gelegt. Eine neue Methode der gezielten Materialentwicklung wird demonstriert, welche darauf basiert, den Toleranzfaktor und die thermodynamischen Eigenschaften der Perowskite gezielt einzustellen. Sowohl experimentelle, als auch theoretische Untersuchungen werden durchgeführt, letzere basierend auf Dichtefunktionaltheorie (DFT) im Rahmen von „Materials Project“. Über 240 Perowskit-Brownmillerit-Paare wurden untersucht. Detaillierte Modelle wurden entwickelt, um die thermodynamischen Eigenschaften solcher fester Lösungen aus Perowskiten als eine Funktion der Temperatur, des Sauerstoffpartialdrucks, und der Sauerstoff-Fehlstellenkonzentration 𝛿 zu beschreiben. Mit Hilfe dieser Funktionen wurde ein interaktiver Beitrag im Rahmen von Materials Project entwickelt, mit dem Materialeigenschaften in einem weiten Bereich verschiedener Bedingungen untersucht werden können. Darin ist auch eine Perowskit-Suchmaschine enthalten. Diese verwendet ein vereinfachtes Prozessmodell, um den materialspezifischen Energiebedarf von Redoxzyklen auszuwerten und ermöglicht es so, das effizienteste Material basierend auf den Prozessbedingungen auszuwählen. Es konnten neue Redoxmaterialien zur Anwendung in thermochemischen Kreisprozessen identifiziert werden und es wurde festgestellt, dass Perowskite die Effizienz der solaren Brennstofferzeugung bei vergleichsweise niedrigen Reduktionstemperaturen von 1300-1400 °C erhöhen können. So soll eine höhere Reaktorlebensdauer erreicht werden. Es wird auch diskutiert, welche Faktoren die Prozesseffizienz beeinflussen und es werden Ideen präsentiert, welche Schritte nötig sind, um eine kommerzielle Nutzung zu ermöglichen. Der wichtigste Faktor ist dabei die Wärmerückgewinnungseffizienz zwischen Feststoffen. Durch die Veröffentlichung aller Daten im Rahmen von MPContribs/Materials Project durch das Erstellen von interaktiven Graphen wird eine wertvolle Ressource zur schnelleren und zielgerichteten Materialentwicklung bereitgestellt. / Solar-thermochemical redox cycles are a promising technological option in the framework of utilization and conversion of renewable energy. By reducing metal oxides at high temperature and/or low oxygen partial pressure, one can generate a material in a state which can be used to capture oxygen from a gas stream or split water or carbon dioxide. By this means, air can be separated, oxygen can be pumped, or so-called solar fuels can be generated. One especially attractive materials class for application in such redox cycles is constituted by perovskites. These materials form stable phases over a large compositional range. Within this work, we show how these perovskite oxides can be applied in thermochemical redox cycles and study the mechanisms behind these redox reactions using in-situ X-Ray techniques. We also show that the kinetic properties of the oxidation reaction are very appealing. It is furthermore presented how perovskite solid solutions can be formed over a large compositional range and how phase formation and stability are affected by the perovskite composition. Based on this knowledge, the focus of this work is set on the materials thermodynamics. A new method of rational perovskite materials design is developed by adjusting the tolerance factor of the perovskites and their thermodynamics. Both experimental and theoretical materials development are conducted, the latter based on density functional theory (DFT) within the framework of the online resource “Materials Project”. Over 240 perovsite-brownmillerite pairs are included in the search. Detailed models describing the thermodynamics of such perovskite solid solutions are established which allow describing the perovskite redox properties as a function of the temperature, oxygen partial pressure, and oxygen non-stoichiometry 𝛿. Using these functions, we developed an interactive tool within the framework of Materials Project, which can be used to model materials properties for a large range of conditions and also serves as a perovskite search engine. This search engine uses a simplified process model to evaluate the material-specific energy demand of a thermochemical redox process and allows finding the most efficient materials choice for a large range of different operational parameters. We could identify new redox materials for application in such processes and found that perovskites can lead to more efficient thermochemical fuels production than the state of the art, especially if the reduction temperature is lowered to 1300-1400 °C to reach higher reactor longevity. It is also discussed which factors affect the overall process efficiency to which extent, and suggestions are given which steps are necessary for a commercialization of such redox processes. The most important factor is the solid-solid heat recovery efficiency. By making all this data publicly available in the framework of MPContribs/Materials Project through providing user-controlled interactive graphs, we are providing a valuable resource for accelerating the discovery and use of new redox materials.

Addressing the urgent need for innovative energy solutions amidst increasing environmental concerns, the focus on photovoltaic solar cells is intensifying. Currently limited by the Shockley-Queisser limit, conventional silicon-based solar cells offer a maximum power conversion efficiency of 32%. This limitation has inspired exploration into alternative materials such as two-dimensional multi-junction heterogeneous structures, notably two-dimensional molybdenum disulfide (2D-MoS2). With a 1.86 eV bandgap and remarkable mechanical strength, 2D-MoS2 presents a potential for higher power conversion efficiency and flexibility, with an exceptional ability to accept doping atoms. This study uses the Vienna ab initio Simulation Package to predict the performance of alloyed 2D-MoS2. Transition metals are added into the structure, with specific pairs showing a promising ability to optimize the bandgap. Hybrid density functional theory methods are used to investigate the effects of alloying on the electronic structure and optical absorption. Niobium-technetium, zirconium-ruthenium, and yttrium-rhodium alloyed 2D-MoS2 show potential for greater light absorption under natural light. The bandgap is tunable between 0.51 eV and 2.13 eV through varying alloying elements and concentrations. All structures demonstrate satisfactory thermal stability. Consequently, this alloying strategy holds potential for next-generation solar cells, though experimental testing is needed. / Att adressera det brådskande behovet av innovativa energilösningar i ljuset av ökande miljöproblem, intensifieras fokus på fotovoltaiska solceller. För närvarande begränsade av Shockley-Queisser gränsen, erbjuder konventionella kiselbaserade solceller en maximal omvandlingseffektivitet på 32%. Denna begränsning har inspirerat till utforskning av alternativa material som tvådimensionella flerleds-heterogena strukturer, framför allt 2D-MoS2. Med ett bandgap på 1.86 eV och märkbar mekanisk styrka, presenterar 2D-MoS2 en potential för högre omvandlingseffektivitet och flexibilitet, med en exceptionell förmåga att acceptera dopningsatomer. Denna studie använder Vienna ab initio Simulation Package för att förutsäga prestanda hos legerad 2D-MoS2. Övergångsmetaller läggs till i strukturen, med specifika par som visar en lovande förmåga att optimera bandgapet. Hybrid densitetsfunktionell teori metoder används för att undersöka effekterna av legering på den elektroniska strukturen och optiska absorptionen. Niobium-teknecium, zirkonium-ruthenium och yttrium-rhodium legerade 2D-MoS2 visar potential för större ljusabsorption under naturligt ljus. Bandgapet kan justeras mellan 0.51 eV och 2.13 eV genom att variera legeringselement och koncentration. Alla strukturer demonstrerar tillfredsställande termisk stabilitet. Följaktligen håller denna legeringsstrategi potential för nästa generations solceller, även om experimentell testning behövs.

Machine Learning has become more important for materials engineering in the last decade. Globally, automated machine learning (AutoML) is growing in popularity with the increasing demand for data analysis solutions. Yet, it is not frequently used for small tabular data. Comparisons and benchmarks already exist to assess the qualities of AutoML tools in general, but none of them elaborates on the surrounding conditions of materials engineers working with experimental data: small datasets with less than 1000 samples. This benchmark addresses these conditions and draws special attention to the overall competitiveness with manual data analysis. Four representative AutoML frameworks are used to evaluate twelve domain-specific datasets to provide orientation on the promises of AutoML in the field of materials engineering. Performance, robustness and usability are discussed in particular. The results lead to two main conclusions: First, AutoML is highly competitive with manual model optimization, even with little training time. Second, the data sampling for train and test data is of crucial importance for reliable results.

In this project machine learning (ML) interatomic potentials are trained and used in molecular dynamics (MD) simulations to predict the physical properties of total energy, mean squared displacement (MSD) and specific heat capacity for systems of bulk Aluminium and Silicon. The interatomic potentials investigated are potentials trained using the ML models kernel ridge regression (KRR) and moment tensor potentials (MTPs). The simulations using these ML potentials are then compared with results obtained from ab-initio simulations using the gold standard method of density functional theory (DFT), as implemented in the Vienna ab-intio simulation package (VASP). The results show that the MTP simulations reach comparable accuracy compared to the DFT simulations for the properties total energy and MSD for Aluminium, with errors in the orders of magnitudes of meV and 10-5 Å2. Specific heat capacity is not reasonably replicated for Aluminium. The MTP simulations do not reasonably replicate the studied properties for the system of Silicon. The KRR models are implemented in the most direct way, and do not yield reasonably low errors even when trained on all available 10000 time steps of DFT training data. On the other hand, the MTPs require only to be trained on approximately 100 time steps to replicate the physical properties of Aluminium with accuracy comparable to DFT. After being trained on 100 time steps, the trained MTPs achieve mean absolute errors in the orders of magnitudes for the energy per atom and force magnitude predictions of 10-3 and 10-1 respectively for Aluminium, and 10-3 and 10-2 respectively for Silicon. At the same time, the MTP simulations require less core hours to simulate the same amount of time steps as the DFT simulations. In conclusion, MTPs could very likely play a role in accelerating both materials simulations themselves and subsequently the emergence of the data-driven materials design and informatics paradigm.

In diesem Beitrag wird ein Vergleich zwischen indirekten Testmethoden zur Bewertung der Verbaubarkeit von 3D-gedruckten Mörteln und Betonen vorgestellt. Die Untersuchungen erfolgten an extrudierten Proben von acht zementbasierten Mischungen mit unterschiedlichem rheologischen Verhalten. Auf der Basis der erzielten Ergebnisse werden Vorhersagen zum Material- bzw. Stabilitätsversagen getroffen und mit den Ergebnissen des Direktdruckversuchs verglichen. Anschließend werden die Vor- und Nachteile unterschiedlicher Prüfmethoden diskutiert. Zu diesen zählen die Techniken der Rotationsrheometrie mit konstanter Rotationsgeschwindigkeit (engl.: constant rotational velocity, CRV), ein schneller Penetrationstest sowie einaxiale Druckversuche mit und ohne Querdehnungsbehinderung.