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Molecular chemical physics and sensorics
Doctoral Programme,
Faculty of Chemical Engineering
--- Careers--- Programme Details
Ph.D. topics for study year 2026/27Ab initio modeling of charge-carrier mobility in polymorphic of organic semiconductors
AnnotationLarge structural and chemical variability of organic semiconductors raises the need for computational screening of the electronic structure of the bulk phase and related material properties, such as the band gap or the charge-carrier mobility. The latter property remains rather low for most existing organic semi-conductive materials when compared to the traditional inorganic crystalline platforms of the optoelectronic devices. Understanding relationships among the bulk structure, non-covalent interactions therein, electronic properties, conductivity, and the response of all such properties to temperature and pressure variation will greatly fasten the material research in the field of organic semiconductors. This thesis will employ the established electronic structure methods with periodic boundary conditions, as well as fragment-based ab initio methods to map the cohesion of bulk organic semiconductors with the charge-carrier mobility is both crystalline and amorphous structures of these materials. Ab initio calculations and the Marcus theory will be used as the starting point for a detailed investigation of the impact of local structure variations, due to chemical substitution, thermal motion, or polymorphism on the conductivity of target materials. Ab initio refinement of cocrystal screening methods for active pharmaceutical ingredients
AnnotationModern formulations of drugs often rely on cocrystalline forms the crystal lattice of which is built from multiple chemical species, mainly an active pharmaceutical ingredient and another biocompatible compound being called a coformer in this context. These cocrystalline drug forms often exhibit higher solubility, stability or other beneficial properties when compared to crystals of pure active pharmaceutical ingredients. Since molecular materials tend to crystallize in single-component crystals rather than in cocrystals, the task of finding a suitable coformer for a given active pharmaceutical ingredient may be very tedious and labor demaning. To circumvent the costly experimental trial-and-error attempts, in silico methods can help to preselect a list of possible coformers offering a high probability of forming the cocrystal. Currently available methods focus on screening the electrostatic potential around the assessed molecules and empiric pairing of its maxima and minima for the individual molecules, which enables coformer screening with a fair accuracy for predominantly hydrogen-bonded molecules. This thesis will aim at incorporation of ab initio calculations of molecular interactions that will bring further improvements also for cocrystal screening of larger molecules with prevailing dispersion components of their interactions. Also the impacts of stechiometry variations and of the spatial packing of the molecules in the cocrystal lattice will be newly considered, greatly enlarging the applicability range of the current cocrystal screening procedures. All-atom and Coarse-Grained Simulations of Thermoresponsive Biopolymers in Aqueous Media
AnnotationThermoresponsive behavior of bio-inspired biopolymers, such as poly-N-isopropylacrylamide, elastin-like polypeptides or intrinsically-disordered-protein like polypeptides (PNIPAM, ELPs, IDPs), is a central feature enabling their applications in drug delivery, biosensing, and molecular separation. These systems exhibit reversible phase transitions (LCST or UCST), which are strongly influenced by temperature, solute concentration, and cosolute identity. Understanding these transitions at the molecular level requires a combination of atomistic insight and mesoscopic modeling approaches. This project aims to characterize the structural and thermodynamic behavior of model thermoresponsive biopolymers in aqueous solutions using a multiscale simulation approach. Atomistic molecular dynamics (MD) simulations will provide detailed insights into solute hydration, solute-cosolute interactions and induced structural and conformational changes of the biopolymer. These results will be used to parameterize and validate coarse-grained (CG) models (e.g., CALVADOS, developed at Uni. Malmo with prof. Tesei) capable of efficiently exploring concentration-dependent aggregation and phase behavior. Specific attention will be paid to: Solute–solute and solute–cosolute interactions influencing LCST/UCST transitions, Chain collapse and aggregation phenomena, Sequence and composition dependence of the transition behavior, Transition thermodynamic quantities (e.g., enthalpy, entropy) derived via enhanced sampling methods. The project will involve collaboration with experimental teams to cross-validate simulation predictions using calorimetry, osmometry, and phase equilibrium measurements (in-house), and spectroscopy and scattering techniques (collaboration with foreign laboratories, prof. Cremer). This synergy ensures that the simulations not only reproduce but also explain the underlying mechanisms of experimentally observed transitions. Bacterial resistance in the context of the antimicrobial effect of non-thermal plasma
AnnotationThis dissertation focuses on studying the potential for the emergence and mechanisms of development of bacterial resistance to non-thermal plasma. The experimental part will monitor the effect of repeated exposure to non-thermal plasma on selected bacterial strains in order to determine whether and how adaptive changes occur that may affect the long-term effectiveness of this technology. The thesis also includes an assessment of the practical implications of these findings for the future use of non-thermal plasma in decontamination and antimicrobial applications. Biobased Polymer Gel Electrolytes for All-Solid-State Flexible Supercapacitors
AnnotationThis thesis focuses on the design and development of biobased polymer gel electrolytes for all-solid-state flexible supercapacitors, aiming to combine high electrochemical performance with mechanical flexibility and environmental sustainability. The research explores renewable polymer matrices as solid electrolytes, investigating their ionic conductivity, mechanical compliance, and chemical stability under repeated bending, folding, and stretching. Hybrid electrode–electrolyte architectures will be evaluated to optimize interfacial adhesion, charge transport, and overall device durability. Both aqueous and organic electrolyte systems will be considered to expand the operational window and adaptability of the devices. Multiscale characterization—including structural, chemical, and electrochemical analyses—will be complemented by mechanical testing to understand the relationship between electrolyte composition, mechanical behavior, and electrochemical performance. This work aims to establish a general framework for the rational design of flexible, sustainable, and high-performance all-solid-state supercapacitors, paving the way for their application in next-generation wearable, portable, and soft electronic devices. Hybrid Electrode–Electrolyte Architectures for Flexible and Durable Supercapacitors
AnnotationThe rapid growth of wearable, portable, and soft electronic devices has created a pressing need for energy-storage systems that combine high performance with mechanical flexibility and durability. This project focuses on the development of flexible supercapacitors capable of maintaining efficient charge storage and delivery under bending, folding, and stretching. By exploring a range of hybrid electrode–electrolyte architectures and both aqueous and organic electrolytes, the study aims to identify general relationships between material design, interfacial interactions, and electrochemical performance. The work emphasizes versatile, mechanically resilient energy-storage solutions that can adapt to emerging applications in wearable and portable technologies, providing a foundation for the next generation of flexible, high-performance supercapacitors. Chiral spectroscopy and dynamics in the X-ray regime
AnnotationChirality is a central concept for understanding life processes, the mechanisms of drug action, and many modern technologies. Over the years, a wide range of chiral-sensitive experimental techniques has been developed. However, only recently—driven by advances in light sources and detection—have X-ray spectroscopic approaches begun to be applied systematically, in particular to measurements in solution and to the study of dynamical phenomena. The goal of this PhD project is to explore, both theoretically and experimentally, the practical limits of chiral X-ray spectroscopy, including its sensitivity, selectivity, time resolution, and the robustness of signal interpretation in realistic molecular systems. A second, broader objective is to investigate chirality in a dynamical environment—for example, how a chiral solute can imprint chiral order or orientational preferences onto its surrounding liquid, how long such chiral information persists, and how these effects manifest in measurable spectroscopic observables. The project will combine state-of-the-art quantum chemistry and time-dependent electronic structure methods with molecular simulations (e.g., classical and ab initio molecular dynamics) and computational modeling of spectroscopic signals. The experimental component will employ suitable chiral-sensitive X-ray spectroscopic approaches and will be closely linked to theoretical predictions, with the aim of establishing a reliable interpretative framework for solution-phase measurements and ultrafast chiral dynamics. Advancing Dynamic Methods for Spectroscopic Simulations with Machine Learning
AnnotationThis dissertation focuses on advancing dynamic methods for spectroscopic simulations through machine learning. Traditional static approaches often rely on harmonic and other approximations, often neglecting anharmonic and temperature effects or interference phenomena. In contrast, dynamic methods employ molecular dynamics and autocorrelation functions to compute vibrational (IR, Raman) and electronic (UV/Vis) spectra, offering higher accuracy but at significant computational cost. This work proposes integrating state-of-the-art machine learning architectures, such as equivariant neural networks and kernel methods, to accelerate these simulations while preserving or improving accuracy. Methodological innovations include ML-driven prediction of forces, dipole moments, polarizabilities, and electronically excited states along semiclassical trajectories. These enhancements should allow for the employment of otherwise infeasible or very costly spectroscopic methods, such as dephasing representation. These approaches will be applied to complex systems like rhodamine dyes or carbon-based materials, enabling exceptional insight into anharmonic effects and spectral features at a fraction of the computational expense. Modelling Extremely Concentrated Electrolytes
AnnotationExtremely concentrated electrolytes (e.g., water-in-salt concepts) are becoming integral to next-generation energy storage and conversion technologies, as they can strongly affect interfacial stability, transport properties, and the electrochemical stability window. Despite their importance, our molecular-level understanding of these liquids remains incomplete: in the ultra-concentrated regime, strong ion–ion and ion–solvent correlations, complex solvation, and local heterogeneity dominate, complicating both experimental interpretation and rational formulation design. This PhD aims to close this gap by developing advanced computational approaches to model the structure, dynamics, and electronic properties of extremely concentrated electrolytes. A central challenge is that most widely used classical force fields were parameterized for dilute solutions and may fail in the ultra-concentrated regime, leading to inaccurate thermodynamics and transport. The project will therefore focus on developing and re-parameterizing specialized force fields (including options such as polarizable and/or many-body descriptions) and systematically validating them against ab initio reference data and key experiments. Nuclear quantum effects are expected to play an important role, so the models will be designed to remain consistent with PIMD simulations that explicitly capture these effects. Where appropriate, machine learning (e.g., ML potentials and/or ML-based corrections) will be explored to enhance accuracy while maintaining computational efficiency. The research will combine classical and quantum simulation methods with statistical mechanics and modern quantum-chemistry tools, and it is expected to involve close collaboration with experimental teams to complement and validate the theoretical insights. The outcome will be predictive models and design principles for next-generation electrolyte formulations relevant to energy applications. Inhibition of β-amyloid fibril formation using modified cyclodextrins
AnnotationCyclodextrins (CDs) are native macrocyclic compounds composed of glucopyranoside units with orientation to hydrophobic cavity and hydrophilic surface and are able to form inclusion complexes with various guest molecules. Due to their low price modified CDs are a compound of choice to increase the bioavailability of low soluble active pharmaceutical ingredient (API) or inhibit undesirable aggregation reactions of proteins. The aim of the proposed PhD project is to gain detailed information on the equilibrium quantities and kinetic mechanisms of CDs acting as inhibitor of β-amyloid fibrillar structure formation. Using set of complementary equilibrium, kinetic, spectral and scattering solution experimental techniques the key driving factors will be identified on commercial modified CDs and proteins as model structures of peptide fibrils. Analyzing the results from the view of experimental conditions, cyclodextrins’ and proteins’ structure, should provide sufficient information for modeling of CD inhibition effect on β-amyloid formation. Study of molecule–metal interactions at micrometer and nanometer resolution
AnnotationInterakce molekul s kovovými povrchy hrají klíčovou roli v katalýze, povrchové chemii, senzorice i v oblasti nanotechnologií. Cílem doktorského tématu je studium těchto interakcí s využitím pokročilých experimentálních metod umožňujících prostorové rozlišení v mikrometrovém a nanometrovém měřítku. Práce bude zaměřena na sledování způsobů adsorpce nízkomelekulárních látek na plasmonické kovy za různých experimentálních podmínek. K řešení budou využity moderní spektroskopické a mikroskopické techniky (SERS, SEIRA, AFM, STM, SEM) v kombinaci s elektrochemií (EC-SERS) a metody kombinující vysoké prostorové rozlišení s chemickou selektivitou (např. s-SNOM nebo TERS). Doktorand/ka získá hluboké znalosti v oblasti charakterizace povrchů a rozhraní a přispěje k porozumění mechanismům interakcí na rozhraní molekula–kov, které jsou zásadní pro návrh nových funkčních materiálů a zařízení. Thermodynamic and Spectroscopic Characterization of Phase Behavior in Thermoresponsive Biopolymers
AnnotationThermoresponsive biopolymers, such as poly-N-isopropylacrylamide (PNIPAM), elastin-like polypeptides (ELPs), and intrinsically disordered protein-like polymers (IDPs), exhibit reversible phase transitions in aqueous media. These transitions — including lower (LCST) or upper (UCST) critical solution temperatures — depend sensitively on temperature, pH, ionic strength, and the presence of osmolytes or salts. Understanding these transitions from both thermodynamic and molecular perspectives is crucial for the rational design of smart biomaterials for applications such as drug delivery, molecular separation, and biosensing. This PhD project focuses on the experimental characterization of phase behavior and solute–solute / solute–additive interactions in such thermoresponsive systems. Calorimetric techniques (DSC, ITC), membrane and vapor pressure osmometry, and dialysis will be used to quantify enthalpies, chemical potentials, and partitioning in coexisting aqueous phases. Structural changes will be probed using spectroscopy (UV-Vis, FTIR, Raman) and scattering techniques (DLS, SAXS). The project will aim to: Map LCST/UCST phase behavior under varying environmental conditions, Quantify preferential interactions with salts and osmolytes, Analyze partitioning and exclusion effects in aqueous two-phase systems (ATPS), Provide thermodynamic reference data to support and validate molecular simulations (e.g., all-atom MD and CG models). The research will be conducted in close collaboration with simulation teams (in house and at Malmo Uni., Prof. Tesei) and external spectroscopy/scattering experts (e.g., Cremer group at PennState, Prof. Lund, Lund University). Data interpretation will be supported by statistical thermodynamics frameworks, especially Kirkwood–Buff theory. Computational Chemistry for EUV Lithography: Nonadiabatic Dynamics, Electron-Induced Chemistry, and Molecular Design
AnnotationEUV lithography is developing very rapidly, and its further progress depends on understanding materials at the molecular level. However, a number of key mechanistic aspects remain unclear, especially how the absorption of high-energy radiation leads to cascades of secondary electrons, excited states, and ionization, and how these processes translate into subsequent chemical reactions. The goal of this dissertation is to develop and apply computational methods that will elucidate these processes and enable their targeted control. The project will focus on nonadiabatic dynamics and electron-induced chemistry in EUV-relevant materials. It will integrate quantum mechanics (time-dependent and, where appropriate, multireference electronic-structure methods), quantum/semi-classical dynamics (nonadiabatic dynamics), and statistical physics (reaction networks, coarse-graining, kinetic and Monte Carlo approaches). The expected outcome is mechanistic insight, predictive models, and design rules for the molecular design of chemistries for EUV lithography. Utilisation of aerogels for gas sensors
AnnotationSignificant development of technology of nanomaterials in the last two decades has enabled the preparation of a wide range of materials for sensoric applications with unique structure and properties. Relatively simple supercritical drying technique, can be used to prepare active layers from the materials used for gas sensors in the form of aerogels. From the point of view of chemical sensors, such nanostructured materials show unique properties in many ways (high sensitivity and selectivity, large active surface). The aim of the work will be the design and implementation of sensors based on aerogels formed by inorganic oxides and their possible chemical (selective organic receptors, surface tension modifiers) and physical modification (laser annealing, incorporation of catalytically active nanoparticles). Impedance spectroscopy and UV-VIS-NIR spectrometry will be used to evaluate the sensor response. Probing and Transforming Molecules with High-Energy Photons
AnnotationHigh-energy photons in the XUV/EUV range provide an efficient tool for probing molecules and their transformations, while also offering a relatively new route to initiate chemical reactions. The project is driven by the rapid development of modern experiments, in particular EUV pump–EUV probe schemes enabled by HHG technologies, as well as more recent X-ray pump–X-ray probe measurements performed at X-FEL sources. These processes are of interest not only for fundamental studies, but also from technological and astrochemical perspectives. Modeling such dynamics requires the development of new computational techniques, ranging from the simulation of spectroscopic signals to the efficient adaptation of trajectory-based approaches. Quantum dynamics and time-dependent electronic structure methods will play a central role throughout the project. |
Updated: 20.1.2022 16:26, Author: Jan Kříž