Investigation of the electronic structure and composition of the surfaces of multicomponent semiconductors Cd(Zn)1xMn(Fe)xTe1y(Se,S)y

Познавање површинске структуре вишекомпонентних II–VI полупроводника и утицаја дуготрајног излагања ваздуху на њу значајно је у технолошком и научном смислу. Резултати добијени у овом раду омогућавају боље разумевање процеса на површини испитиваних система (оксидација, сегрегација и миграција елемената), који су уско повезани са њиховим површинским својствима. Метода фотоелектронске спектроскопије рендгенским зрачењем (XPS) је указала на различит састав испитиваних површина, одступање од стехиометријског састава, али и неуниформност састава по дубини узорака на бази CdTe и ZnTe. Због слабо израженог хемијског помераја линија Cd и Zn у XPS спектру, за одређивање хемијских веза које ови елементи граде, у Тези је успешно примењен нови приступ за моделовање Ожеових линија. Одступање од стехиометријског састава може бити последица површинске морфологије, те је овај утицај детаљно размотрен, али је пре свега последица неуниформности састава испитиваних површина по дубини. Површинске концентрације елемената добијене рутинским приступом квантитативној анализи XPS резултата (коришћењем фактора осетљивости) послужиле су за праћење њихове међузависности и једноставну процену површинског састава, а показано је и да постоји компетиција процеса оксидације и адсорпције угљоводоника на површини. Ипак, да би се одредио састав специфичне површинске структуре узорака, која није униформна по дубини те примена фактора осетљивости није могућа, у оквиру ове Тезе је развијен модел који полази од „првих принципа“. Применом модела, уз сазнања која је пружила опсежна анализа XPS и Ожеових спектара, утврђен је тачан састав узорака. Одређене су хемијске фазе присутне у свакој од уочене три површинске области – запреминска област, оксидни слој и слој нечистоћа, и процењена је дебљина површинских слојева узорака.Understanding of the multicomponent II–VI semiconductors surface structure and influence of long term air exposure on it, is a very important question in both, scientific and technological manner. Results presented in this dissertation offers better insight into surface processes of investigated systems (oxydation, segregation and migration of elements), which are closely related to their surface properties. X–ray photoelectron spectroscopy (XPS) reveals different surface structures, variations in stoichiometry and in–depth non–uniform structure of examined samples based on CdTe and ZnTe. Due to poor chemical peak shifts of Cd and Zn lines in XPS spectrum, for chemical bond identification of these elements, the new approach for modeling Auger lines was successfully applied here. Deviation from stoichiometry composition can be a consequence of surface morphology and this influence was considered in detail, but is certainly attributed to non–uniform structure of surfaces in depth. Relative concentrations of elements detected at the surfaces of investigated samples obtained using standard quantitative analysis approach in XPS (using atomic sensitivity factors) served to monitor their correlation and evaluation of surface structure. Furthermore, competiton of two surface processes, oxydation and hydrocarbons adsorption, is established. The model based on first principles is developed in this dissertation, in order to determine the specific surface structure of samples, where using of atomic sensitivity factors is not possible. Application of this model, followed by additional results provided by XPS and Auger spectrum analysis, enables determination of exact in–depth sample structures. Chemical bonds present in each of the three surface areas – bulk, oxide and contamination layer, were determined. Samples surface layers thicknesses were also evaluated

High-throughput screening of novel hydrogen storage materials – ML approach

Hydride formation in metals is a widely studied and applied phenomenon necessary to transition to clean energy solutions and various technological applications. We focus on three perspective applications of these materials, namely near-ambient hydrogen storage, hydrogen storage compressor materials, and alkali metal conversion electrodes, to demonstrate acceleration in the research achieved by utilizing a data-driven approach. Graph neural network was developed using a transfer learning approach from the MEGNet model and data related to the thermodynamics of hydride formation obtained in experimental work. Based on the crystal structure and composition as input features, we apply the MetalHydrideEnth model developed in our previous work to predict hydride formation enthalpy in intermetallic compounds. In this work, we focus on demonstrating how this approach, combined with available crystal information obtained from density functional theory calculations, can be applied for fast and extensive searches of novel metal hydride materials, having in mind the above-listed applications.ICCBIKG 2023 : 2nd International Conference on Chemo and Bioinformatics, 28-29 September 2023, Kragujevac, Serbi

Razvoj materijala za litijum-jonske baterije korišćenjem mašinskog učenja

The development of novel materials is seen as the key approach to improvements in the performance of Li-ion batteries. Recently, conversion-type electrodes have been demonstrated to improve battery capacity and energy density. Metal hydrides are considered promising anode materials, while some hydride materials are also considered solid ionic conductors. In this research, we rely on the machine learning approach to predict the properties of novel anode materials depending on hydride conversion reactions. We limit our search to Mg-containing intermetallic compounds and screen a vast database of optimized crystal structures obtained using density functional theory calculations. The composition and crystal structure of selected metals/intermetallics are input for a graph neural network-based machine learning model to predict hydride formation enthalpy and equilibrium electrode potential vs. Li+ /Li0 . Among 245 intermetallic compounds found to be satisfactory as anode materials, we particularly discuss La-Mg-X intermetallics. The work demonstrates the advantages of combining artificial intelligence tools and theoretical approaches with experimental results for property prediction and fast screening of vast combinatorial space.Brojna istraživanja usmerena su na razvoj novih materijala kao ključnog pristupa u poboljšanju performansi litijum-jonskih baterija. Poslednjih godina posebno se ispituju konverzione elektrode koje omogućavaju veće kapacitete i gustine energija. Posebno, metalni hidridi se ispituju kao pogodni materijali za anode konverzionog tipa, dok se takođe neki hidridi ispituju i kao pogodni jonski provodnici. U ovom radu koristimo modele mašinskog učenja za predviđanje osobina novih anodnih materijala, oslanjajući se na reakcije konverzije hidrida. Pretraga novih intermetalnih jedinjenja ograničana je na one koji sadrže magnezijum, a kao izvor podataka korišćene su dostupne baze kristalnih struktura oprimizovanih proračunima zasnovanim na teoriji funkcionala gustine. Sastav i kristalna struktura odabranih metala/intermetalnih jedinjenja korišćeni su kao ulazni podaci za model mašinskog učenja zasnovan na graf neuronskim mrežama. Na taj način predviđene su entalpije formiranja hidrida i ravnotežni elektrodni potencijali u odnosu na Li+/Li0. Od 245 intermetalnih jedinjenja koja zadovoljavaju uslov za anodni materijal izdvojena su i diskutovana ternarna jedinjenja La-Mg-X. Ovaj rad pokazuje prednost kombinovanja alata veštačke inteligencije i teorijskih pristupa sa eksperimentalnim radom u cilju predviđanja osobina novih materijala i brze pretrage velikog prostora mogućih intermetalnih jedinjenja

Metal Hydride Conversion Anodes for Alkali-Ion Batteries – A Machine Learning Perspective

Aiming for the increased utilization of renewable energy and a decrease in carbon footprint, electrochemical energy conversion plays a vital role in many applications. Improvements in battery materials aim for cheaper and safer systems, including all-solid-state batteries. Due to the high theoretical capacity and suitable working potential, the conversion reaction of metal hydrides is demonstrated as a valuable solution for negative electrodes in both standard and all-solid-state Li-ion batteries. Relying on the same principle of conversion reaction, applicability for Na-ion batteries is in the early stage of the investigation. In this work, we demonstrate the relevance of the developed deep-learning model for the fast screening of potential anode materials based on the stability of the metal hydrides. Relying on the structural features of various metal alloys obtained using density functional theory calculations, we predict equilibrium electrode potential for both Li-ion and Na-ion batteries. From the initial dataset of over 5000 intermetallic compounds, we discuss ten selected compositions for both applications, focusing on the stability of alloys and additional criteria (such as weight, price, etc.). In addition to proposing promising compositions for future experimental investigation, this work demonstrates the advantages of developing and utilizing artificial intelligence tools for property prediction and fast assessment of the vast combinatorial space of metal alloys.TICMET23 : the 5th international conference of materials and engineering technology, November 13-16, 2023, Trabzon, Turkiy

Ispitivanje promena na površini nakon dugotrajnog izlaganja vazduhu polazeći od prvih principa-XPS

Within the scope of this paper, a potential impact of noble metal particles on the surface of N-TiO2 and its catalytic properties is observed through correlation with contamination layer thickness. Owing to 'first principle' approach study, without additional experimental measurements or permanent damage to the surface of the samples, it is possible to obtain significant novel information based on a single measurement of the XPS spectra. Presented research demonstrated how the surface contamination layer in the case of samples based on N-TiO2 is related to the nature of two studied noble metals, indicating that Pd might serve as an important co-modifier to suppress surface contamination.Kroz ovaj rad će biti sagledan uticaj čestica plemenitih metala na strukturu površine titanijum dioksida dopiranog azotom i katalitička svojstva kroz uticaj na debljinu sloja nečistoća. U ovakvom pristupu koji polazi od „prvih principa“ je bez dodatnih eksperimentalnih merenja i trajnog oštećenja površine uzoraka moguće dobiti značajne nove informacije korišćenjem rezultata jednom izvedenog merenja rendgenskog fotoelektronskog spektra. Dobijeni rezultati ukazuju na to da promene na površini uzoraka na bazi N-TiO2, do kojih dolazi zbog prisustva Pd, utiču na suzbijanje površinskih organskih nečistoća

Metal hydrides by design – insights from DFT and data science

Clean energy solutions rely on various hydride materials, for both hydrogen storage and hydrogen production. In our work, we address the possibility of tuning the properties of the most attractive hydrides: Mg-based hydrides, AlH3, and NaBH4, by doping. [...]mESC-IS 2022 : 6th International Symposium on Materials for Energy Storage and Conversion ; July 5-8 2022 ; Brač, Croati

Data-driven Design of New Mg-based Hydride Materials – A Synergy of Experiments and DFT

Hydrogen absorption/desorption is one of the key processes underlying many clean energy applications, such as thermal energy storage, hydrogen storage, hydrogen compression, and nickel-metal hydride batteries. For all those applications fast and reliable characterization of new materials, and in particular, information regarding energetics of hydride formation reaction is of main interest. In the last decades, DFT (density functional theory) approach showed good predictive potential for the ground state properties and calculation of hydride formation energies. Recently, MEGNet implementation of graph neural networks showed promising results for fast and reliable prediction of formation energies for molecules and crystals. Here, we consider the development of a machine learning model based on the available DFT predicted structures and experimentally measured hydride formation enthalpies. The proposed model is capable to predict hydride formation behavior for a wide variety of intermetallic compounds and distinguish the behavior of the polymorphs. In particular, based only on the crystal structure of the starting intermetallic compound, we were able to predict hydride formation enthalpy with accuracy comparable to DFT calculated values. Further, we demonstrate the application of this model for proposing new materials in Mg-Ni-M compound space with the desired enthalpy for hydrogen storage.COIN2022 - Contemporary Batteries and Supercapacitors - International Symposium ; June 1-2, 2022 ; Belgrade, Serbi

Al-ions Charge Storage Ability of the Conductive Polyaniline Emeraldine Salt

Development of new and attractive generation of polymer devices for application in the field of energy storage that meets the requirements of safety and environmental sustainability is an ongoing challenge. The majority of previous scientific results reported that polyaniline-based supercapacitors use only aqueous acid solutions as electrolyte. [1] The aim of this work is to examine the redox activity of polyaniline emeraldine salt (PANI-ES) in an aqueous electrolyte of aluminum salt, that have been studied to a lesser extent and lacking the characterization of charge storage behavior. The advantage of employing aluminum among various post-lithium rechargeable systems has the advantage in the fact that it is the most abundant metal element in the Earth’s crust with one of the highest gravimetrical and volumetric energy densities. By combining experimental (cyclic voltammetry, chronopotentiometry, galvanic charge/discharge, AFM - Atomic Force Microscopy) and theoretical approaches (density functional theory - DFT), the redox mechanism of polyaniline in the aqueous Al-salt solution is explained. [2] Polyaniline has been shown to have higher Coulombic capacitance at the same charge and discharge current in aqueous aluminum nitrate solution (1M Al(NO3)3) than in hydrogen chloride electrolyte solution (1M HCl), which makes it a suitable electrode for supercapacitors. From a practical point of view, a supercapacitor based on polyaniline and an aqueous solution of Al(NO3)3 was constructed and tested in terms of capacitance, cycle time, and self-discharge. The capacitor shows high charge and discharge capacity (≈269 F g-1 at a current density of 10 A g-1) and relatively good capacity retention after 1000 charge and discharge cycles.COIN2022 - Contemporary Batteries and Supercapacitors - International Symposium ; June 1-2, 2022 ; Belgrade, Serbi

DFT studija MgH2 i AlH3 hidrida dopiranih 3d prelaznim metalima

The electronic structures of lightweight binary hydrides MgH2 and AlH3 doped with 3d transition metals (TM=Sc, Ti, Mn, and Cu) were investigated using first-principles calculations. The influence of 3d states of TM was clearly visible from electronic structure calculations. Doping of these systems has a favorable influence on hydrogen desorption energies of both systems, decreasing it in the case of MgH2 for all TM and increasing it in metastable AlH3 when doped with Sc and Ti.Elektronske strukture lakih binarnih hidrida MgH2 i AlH3 dopiranih 3d prelaznim metalima (PM=Sc, Ti, Mn i Cu ) su ispitane primenom proračuna iz prvih principa. Na osnovu proračuna elektronske strukture jasno je vidljiv uticaj 3d stanja PM. Dopiranje ovih sistema ima povoljan uticaj na energije desorpcije vodonika oba sistema, smanjujući je u slučaju MgH2 za sve PM i povećavajući je u metastabilnom AlH3 kada se dopira sa Sc i Ti

Uticaj nanočestica brukit/anatas TiO2 na strukturna i elektrohemijska svojstva provodne forme polianilina

The emeraldine salt polyaniline/TiO2 composite (PANI_ES@TiO2_BA) was prepared by in situ chemical oxidation of aniline in the presence of the TiO2 brookite(74%)/anatase(26%) nanoparticles. Raman spectroscopy and Cyclic Voltammetry were used to examine the properties of the obtained composites and their charge storage performances. A significant decrease of the composite charging/discharging capacity indicates that the incorporation of 33 wt% of the brookite/anatase TiO2 nanoparticles into the PANI_ES matrix deteriorates the charge storage possibilities of the composite in comparison with the pure PANI_ES at a common scan rate of 20 mVs-1.Kompozit polianilina u formi emeraldin soli/TiO2 (PANI_ES@TiO2_BA) je sintetisan in situ hemijskom oksidativnom polimerizacijom anilina u prisustvu nanočestica TiO2 brukit(74%)/anatas(26%). Za ispitivanje svojstava dobijenog kompozita i njegovih performansi za skladištenje naelektrisanja korišćena je metoda Ramanske spektroskopije i ciklična voltametrija. Značajno smanjenje kapaciteta punjenja/pražnjenja kompozita ukazuje na to da ugradnja 33 težinskih procenata (wt%) nanočestica brukit/anatas TiO2 u PANI_ES matricu smanjuje sposobnost skladištenja naelektrisanja u kompozitu u poređenju sa čistim PANI_ES, pri brzini polarizacije od 20 mVs-1.Meeting point of the science and practice in the fields of corrosion, materials and environmental protection : proceedings = Stecište nauke i prakse u oblastima korozije, zaštite materijala i životne sredine : knjiga radova / XXIV YuCorr International Conference, May 28-31, 2023, Divčibare, Serbi