First principles study of the atomic layer deposition of alumina by TMA-H2O-process

Atomic layer deposition (ALD) is a coating technology used to produce highly uniform thin films. Aluminiumoxide, Al2O3, is mainly deposited using trimethylaluminium (TMA) and water as precursors and is the most studied ALD-process to date. However, only few theoretical studies have been reported in the literature. The surface reaction mechanisms and energetics previously reported focus on a gibbsite-like surface model but a more realistic description of the surface can be achieved when the hydroxylation of the surface is taken into account using dissociatively adsorbed water molecules. The adsorbed water changes the structure of the surface and reaction energetics change considerably when compared to previously studied surface model. Here we have studied the TMA/H2O process using density functional theory on a hydroxylated alumina surface and reproduced the previous results for comparison. Mechanisms and energetics during both the TMA and the subsequent water pulse are presented. TMA is found to adsorb exothermically onto the surface. The reaction barriers for the ligand-exchange reactions between the TMA and the surface hydroxyl groups were found to be much lower compared to previously presented results. TMA dissociation on the surface is predicted to saturate at monomethylaluminium. Barriers for proton diffusion between surface sites are observed to be low. TMA adsorption was also found to be cooperative with the formation of methyl bridges between the adsorbants. The water pulse was studied using single water molecules reacting with the DMA and MMA surface species. Barriers for these reactions were found to reasonable in the process conditions. However, stabilizing interactions amongst water molecules were found to lower the reaction barriers and the dynamical nature of water is predicted to be of importance. It is expected that these calculations can only set an upper limit for the barriers during the water pulse.Peer reviewe

Mining Cell Transition Data

Cell transition data is obtained from a cellular phone that switches its current serving cell tower. The data consists of a sequence of transition events, which are pairs of cell identifiers and transition times. The focus of this thesis is applying data mining methods to such data, developing new algorithms, and extracting knowledge that will be a solid foundation on which to build location-aware applications. In addition to a thorough exploration of the features of the data, the tools and methods developed in this thesis provide solutions to three distinct research problems. First, we develop clustering algorithms that produce a reliable mapping between cell transitions and physical locations observed by users of mobile devices. The main clustering algorithm operates in online fashion, and we consider also a number of offline clustering methods for comparison. Second, we define the concept of significant locations, known as bases, and give an online algorithm for determining them. Finally, we consider the task of predicting the movement of the user, based on historical data. We develop a prediction algorithm that considers paths of movement in their entirety, instead of just the most recent movement history. All of the presented methods are evaluated with a significant body of real cell transition data, collected from about one hundred different individuals. The algorithms developed in this thesis are designed to be implemented on a mobile device, and require no extra hardware sensors or network infrastructure. By not relying on external services and keeping the user information as much as possible on the user s own personal device, we avoid privacy issues and let the users control the disclosure of their location information.Matkapuhelinverkoissa tukiasemat palvelevat tietyllä alueella olevia puhelimia. Tukiaseman radiosignaalin kattamaa aluetta kutsutaan soluksi. Vaihtaessaan käyttämäänsä tukiasemaa puhelin tuottaa solusiirtymädataa, joka koostuu sarjasta solutunnisteita ja siirtymisaikoja. Vaikka data ei sisälläkään paikkojen koordinaatteja, siitä voidaan silti oppia tunnistamaan puhelimen käyttäjälle tärkeitä paikkoja sekä ennustamaan hänen liikkumistaan paikkojen välillä. Väitöskirjatyössä sovelletaan tiedonlouhinnan menetelmiä solusiirtymädataan ja tavoitteena on tuottaa työkaluja paikkatietoisten sovellusten kehittämiseen. Saatuja tuloksia testataan aineistolla, joka on kerätty noin sadalta matkapuhelimen käyttäjältä. Datassa on erityispiirteitä, jotka tekevät sen käsittelystä haastavaa. Yksi keskeinen ongelma on se, että solun vaihtuminen ei aina johdu käyttäjän liikkumisesta, vaan puhelin voi vaihtaa käyttämäänsä tukiasemaa myös muista syistä. Ja kääntäen: yksittäisen solun sisällä on mahdollista liikkua jonkin matkaa ennen solun vaihtumista. Solujen ja fyysisten paikkojen vastaavuuksien löytämiseksi työssä esitellään klusterointimenetelmä, joka yhdistää samaan paikkaan todennäköisesti liittyviä soluja suuremmiksi kokonaisuuksiksi. Kyseessä on ns. online-algoritmi, joka analysoi solusiirtymävirtaa ja päivittää klusterien joukkoa reaaliaikaisesti. Työn tuloksena syntyneet algoritmit voidaan toteuttaa käytännössä kaikilla mobiililaitealustoilla, eikä niiden käyttö vaadi toimenpiteitä puhelinoperaattorilta tai -valmistajalta. Koska menetelmät vaativat vain vähän puhelimen laskenta- ja tallennuskapasiteettia, käyttäjän paikkatietoja ei tarvitse lähettää puhelimesta eteenpäin jatkokäsittelyä varten. Tämä turvaa puhelimen käyttäjän yksityisyyttä, sillä käyttäjä voi päättää itse, kenelle ja kuinka paljon tietoja luovutetaan

Structure of CAl12

The structures of an isolated CAl12 cluster and a solid composed of CAl12 clusters have been studied using the Car–Parrinello method, based on the density functional theory and the local density approximation. We have compared the results of using the ultrasoft Vanderbilt pseudopotential with those of both a traditional pseudopotential and a linear combination of atomic orbitals method. We have confirmed the high stability of the cluster in its icosahedral structure. However, we show that the cluster‐assembled solid is unstable against melting of the clusters, as previously found for SiAl12.Peer reviewe

Charge distribution and Fermi level in bimetallic nanoparticles

Upon metal-metal contact, a transfer of electrons will occur between the metals until the Fermi levels in both phases are equal, resulting in a net charge difference across the metal-metal interface. Here, we have examined this contact electrification in bimetallic model systems composed of mixed Au-Ag nanoparticles containing ca. 600 atoms using density functional theory calculations. We present a new model to explain this charge transfer by considering the bimetallic system as a nanocapacitor with a potential difference equal to the work function difference, and with most of the transferred charge located directly at the contact interface. Identical results were obtained by considering surface contacts as well as by employing a continuum model, confirming that this model is general and can be applied to any multimetallic structure regardless of size or geometry. Furthermore, the equilibrium Fermi level was found to be strongly dependent on the surface coverage of different metals, enabling the construction of scaling relations. We believe that the charge transfer due to Fermi level equilibration has a profound effect on the catalytic, electrocatalytic and other properties of bimetallic particles. Additionally, bimetallic nanoparticles are expected to have very interesting self-assembly for large superstructures due to the surface charge anisotropy between the two metals

Active site manipulation in MoS2 cluster electrocatalysts by transition metal doping

The development of non-platinum group metal catalysts for the hydrogen evolution reaction (HER) in water electrolyser devices is essential for their widespread and sustainable deployment. In recent years, molybdenum disulfide (MoS2) catalysts have received significant attention as they not only exhibit good electrocatalytic HER activity but also, crucially, acid-stability. However, further performance enhancement is required for these materials to be competitive with Pt and to that end transition metal doping of MoS2 has been explored as a route to further increasing its catalytic activity. In this work, cluster beam deposition was employed to produce controlled cobalt-doped MoS2 clusters (MoS2–Co). We demonstrate that, in contrast to previous observations of performance enhancement in MoS2 resulting from nickel doping (MoS2–Ni), the introduction of Co has a detrimental effect on HER activity. The contrasting behaviours of Ni and Co doping are rationalized by density functional theory (DFT) calculations, which suggest that HER-active surface vacancies are deactivated by combination with Co dopant atoms, whilst their activity is retained, or even partially enhanced, by combination with Ni dopant atoms. Furthermore, the adatom dopant–vacancy combination kinetics appear to be more than three orders of magnitude faster in MoS2–Co than for MoS2–Ni. These findings highlight a fundamental difference in the influence of transition metal dopants on the HER performance of MoS2 electrocatalysts and stress the importance of considering surface atomic defects when predicting their behaviour

Composition-Tuned Pt-Skinned PtNi Bimetallic Clusters as Highly Efficient Methanol Dehydrogenation Catalysts

Platinum is the most active anode and cathode catalyst in next-generation fuel cells using methanol as liquid source of hydrogen. Its catalytic activity can be significantly improved by alloying with 3d metals, although a precise tuning of its surface architecture is still required. Herein, we report the design of a highly active low-temperature (below 0 °C) methanol dehydrogenation anode catalyst with reduced CO poisoning based on ultralow amount of precisely defined PtxNi1–x (x = 0 to 1) bimetallic clusters (BCs) deposited on inert flat oxides by cluster beam deposition. These BCs feature clear composition-dependent atomic arrangements and electronic structures stemming from their nucleation mechanism, which are responsible for a volcano-type activity trend peaking at the Pt0.7Ni0.3 composition. Our calculations reveal that at this composition, a cluster skin of Pt atoms with d-band centers downshifted by subsurface Ni atoms weakens the CO interaction that in turn triggers a significant increase in the methanol dehydrogenation activity

Biomimetic Oxygen Reduction by Cofacial Porphyrins at a Liquid-Liquid Interface

Oxygen reduction catalyzed by cofacial metalloporphyrins at the 1,2-dichlorobenzene-water interface was studied with two lipophilic electron donors of similar driving force, 1,1'-dimethylferrocene (DMFc) and tetrathiafulvalene (TTF). The reaction produces mainly water and some hydrogen peroxide, but the mediator has a significant effect on the selectivity, as DMFc and the porphyrins themselves catalyze the decomposition and the further reduction of hydrogen peroxide. Density functional theory calculations indicate that the biscobaltporphyrin, 4,5-bis[5-(2,8,13,17-tetraethyl-3,7,12,18-tetramethylporphyrinyl)]-9,9-dimethylxanthene, Co-2(DPX), actually catalyzes oxygen reduction to hydrogen peroxide when oxygen is bound on the "exo" side ("dock-on") of the catalyst, while four-electron reduction takes place with oxygen bound on the "endo" side ("dock-in") of the molecule. These results can be explained by a "dock-on/dock-in" mechanism. The next step for improving bioinspired oxygen reduction catalysts would be blocking the "dock-on" path to achieve selective four-electron reduction of molecular oxygen