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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. Quantum Sensing Using Optical Bionanosensors
AnnotationQuantum nanosensors offer significant advantages over classical sensors, including high sensitivity and resolution. One type of such quantum nanosensor is photoluminescent nanoparticles, whose detection is based on monitoring luminescence changes in response to external stimuli. The goal of the project is to read optical nanosensors using pulsed optical electron paramagnetic resonance (EPR) detection and tracking spectral changes. The student will design and implement advanced pulse sequences into an existing quantum confocal microscope, conduct measurements, and analyze the results. Furthermore, they will optimize the sensitivity of the nanosensors through chemical surface modifications. The outcome of the project will be time-resolved, localized quantum detection in biologically relevant environments. The expected knowledge of the applicant should be at the level of a completed Master's degree in the field of biophysics, chemical physics or physical chemistry. The work will be carried out by the Synthetic Nanochemistry team at the Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences. Quantum Sensing Using Optical Bionanosensors
AnnotationQuantum nanosensors offer significant advantages over classical sensors, including high sensitivity and resolution. One type of such quantum nanosensor is photoluminescent nanoparticles, whose detection is based on monitoring luminescence changes in response to external stimuli. The goal of the project is to read optical nanosensors using pulsed optical electron paramagnetic resonance (EPR) detection and tracking spectral changes. The student will design and implement advanced pulse sequences into an existing quantum confocal microscope, conduct measurements, and analyze the results. Furthermore, they will optimize the sensitivity of the nanosensors through chemical surface modifications. The outcome of the project will be time-resolved, localized quantum detection in biologically relevant environments. The expected knowledge of the applicant should be at the level of a completed Master's degree in the field of biophysics, chemical physics or physical chemistry. The work will be carried out by the Synthetic Nanochemistry team at the Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences. 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. Molecular Design of New (Metallo- and Xeno-)Peptidic Frameworks for Biocatalysis
AnnotationEnzyme redesign or de novo design, often supported by computational algorithms, has matured over the last few decades and various successful examples can be found in the literature. They include changing a single amino acid in a protein to achieve catalytic activity in previously non-catalytic proteins, designing catalytic activity for established protein folds, cofactor preference redesign, or chemomimetic biocatalysis exploiting the synthetic potential of cofactor-dependent enzymes. We will utilize efficient conformational sampling based on the machine-learned quantum mechanical energies in implicit solvent (ML-QM(DFT)/COSMO energies) for the design of new and unprecedented oligopeptides which, after metal insertion, will mimic catalytic sites in the native scaffolds in metalloenzymes. Using the same methods and approaches, we will also explore the same question for peptides composed of xeno- (non-natural) -amino acids to unravel the unknown catalytic potential of metallo-xeno peptides or their small protein counterparts. With this, we may be able to open new horizons in biocatalysis and in the design of metallo-xeno peptides. Ab Initio Prediction of Protein Structure: Viewing Protein Folding as an Intramolecular Solvation Problem
AnnotationThe research goal is the development and implementation of an ab initio protein structure predictor (tentatively denoted QMLFold). QMLFold will couple an extension of the COSMO-RS solvation theory into 3 D space (this new method is denoted as 3D-COSMO-RS) with ML-based peptide potentials, recently developed in our group, and efficient sampling algorithms. The program should be independent of known protein structures, and as such, it shall be universal and versatile. The machine-learning component inside its algorithm – ‘ML’ in the QMLFold – will only be used to predict the “QM-quality” intramolecular free energies of the short peptide fragments constituting the protein chain. The paradigm-shifting idea behind QMLFold is embodied in the question of whether we can view protein folding as a ‘universal solvation problem’. Or rephrased as: “Can we consider a protein as an ensemble of chemically distinct entities – amino acid side chains, covalently linked by a “poly-glycine” backbone, which are solvated in themselves?” QMLFold may open new horizons in biocatalysis, metal-binding peptides (sensors), and might be a potential game changer in the area that is not amenable to AlphaFold3-like algorithms (medium-sized peptides, intrinsically disordered proteins, or peptides with xeno- amino acids). Preparation and Characterization of Quantum-Optical Bionanosensors
AnnotationPhotoluminescent nanodiamonds represent a novel type of quantum biosensor that exploits changes in luminescent properties in response to external stimuli. Compared to classical sensors, they offer the benefits of high sensitivity and resolution but are often nonspecific. The aim of the project is to chemically functionalize these sensors for specific and sensitive detection in biologically relevant environments. To achieve this, the student will employ covalent surface modifications of nanosensors in a colloidal state and subsequently characterize them. The functionality of the constructed nanosensors will be verified using a quantum confocal microscope with advanced pulse sequences. The outcome of the project will be time-resolved, localized quantum detection of specific molecules. The expected knowledge of the applicant should be at the level of a completed Master's degree in the field of biophysics, chemical physics or physical chemistry. The work will be carried out by the Synthetic Nanochemistry team at the Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences. Radiation damage to DNA, experiment and theory
AnnotationThe project aims to study radiation damage to DNA on individual molecules using DNA origami nanostructures. The methodology developed in our laboratory [Sala et al. J. Phys. Chem. Lett. 2022, 13, 17, 3922] will be used to study the radiosensitization effect of nanoparticles on precisely defined DNA sequences. This basic research is focused on understanding the details of radiation therapy using gold nanoparticles with the potential for better targeting of therapy and development of new theranostic procedures. The student will become familiar with the preparation of DNA origami nanostructures and he/she will participate in experiments with ionizing radiation in collaborating laboratories in the Czech Republic and abroad. A significant part of the project will focus on theoretical modeling of the studied processes, especially using molecular dynamics tools and coarse-grained models. 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. Computational Design of Ligands for Radiotherapy
AnnotationTargeted radiotherapy based on metal radionuclide complexes is an important and rapidly developing approach in modern oncology. A key component of such systems is the chelator, which must provide high thermodynamic stability, kinetic inertness under physiological conditions, and an appropriate coordination environment of the metal center. This thesis focuses on the computational design and characterization of chelators based on peptidic ligands/frameworks for complexation of therapeutically relevant radionuclides, in particular 177Lu, 161Tb, 225Ac, and others. Density functional theory (DFT) calculations will be employed to study geometries, binding energies, and electronic properties of the complexes. In addition, paramagnetic NMR parameters will be calculated to support the interpretation of experimental NMR data, providing detailed insight into the structure and solution dynamics of paramagnetic metal complexes. Based on this analysis, new or modified ligand architectures will be proposed to optimize metal–ligand bonding, coordination geometry, and complex stability. The results will be discussed in the context of structure–property relationships relevant to rational radiopharmaceutical ligand design. Practical realizations will be carried out by our foreign collaborators. 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: 25.3.2022 16:21, Author: Jan Kříž