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Carbon nitride semiconductors: properties and application as photocatalysts in organic synthesis
(2023)
Graphitic carbon nitrides (g-CNs) are represented by melon-type g-CN, poly(heptazine imides) (PHIs), triazine-based g-CN and poly(triazine imide) with intercalated LiCl (PTI/Li+Cl‒). These materials are composed of sp2-hybridized carbon and nitrogen atoms; C:N ratio is close to 3:4; the building unit is 1,3,5-triazine or tri-s-triazine; the building units are interconnected covalently via sp2-hybridized nitrogen atoms or NH-moieties; the layers are assembled into a stack via weak van der Waals forces as in graphite. Due to medium band gap (~2.7 eV) g-CNs, such as melon-type g-CN and PHIs, are excited by photons with wavelength ≤ 460 nm. Since 2009 g-CNs have been actively studied as photocatalysts in evolution of hydrogen and oxygen – two half-reactions of full water splitting, by employing corresponding sacrificial agents. At the same time application of g-CNs as photocatalysts in organic synthesis has been remaining limited to few reactions only. Cumulative Habilitation summarizes research work conducted by the group ‘Innovative Heterogeneous Photocatalysis’ between 2017-2023 in the field of carbon nitride organic photocatalysis, which is led by Dr. Oleksandr Savatieiev.
g-CN photocatalysts activate molecules, i.e. generate their more reactive open-shell intermediates, via three modes: i) Photoinduced electron transfer (PET); ii) Excited state proton-coupled electron transfer (ES-PCET) or direct hydrogen atom transfer (dHAT); iii) Energy transfer (EnT). The scope of reactions that proceed via oxidative PET, i.e. one-electron oxidation of a substrate to the corresponding radical cation, are represented by synthesis of sulfonylchlorides from S-acetylthiophenols. The scope of reactions that proceed via reductive PET, i.e. one-electron reduction of a substrate to the corresponding radical anion, are represented by synthesis of γ,γ-dichloroketones from the enones and chloroform.
Due to abundance of sp2-hybridized nitrogen atoms in the structure of g-CN materials, they are able to cleave X-H bonds in organic molecules and store temporary hydrogen atom. ES-PCET or dHAT mode of organic molecules activation to the corresponding radicals is implemented for substrates featuring relatively acidic X-H bonds and those that are characterized by low bond dissociation energy, such as C-H bond next to the heteroelements. On the other hand, reductively quenched g-CN carrying hydrogen atom reduces a carbonyl compound to the ketyl radical via PCET that is thermodynamically more favorable pathway compared to the electron transfer. The scope of these reactions is represented by cyclodimerization of α,β-unsaturated ketones to cyclopentanoles.
g-CN excited state demonstrates complex dynamics with the initial formation of singlet excited state, which upon intersystem crossing produces triplet excited state that is characterized by the lifetime > 2 μs. Due to long lifetime, g-CN activate organic molecules via EnT. For example, g-CN sensitizes singlet oxygen, which is the key intermediate in the dehydrogenation of aldoximes to nitrileoxides. The transient nitrileoxide undergoes [3+2]-cycloaddition to nitriles and gives oxadiazoles-1,2,4.
PET, ES-PCET and EnT are fundamental phenomena that are applied beyond organic photocatalysis. Hybrid composite is formed by combining conductive polymers, such as poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) with potassium poly(heptazine imide) (K-PHI). Upon PET, K-PHI modulated population of polarons and therefore conductivity of PEDOT:PSS. The initial state of PEDOT:PSS is recovered upon material exposure to O2. K-PHI:PEDOT:PSS may be applied in O2 sensing.
In the presence of electron donors, such as tertiary amines and alcohols, and irradiation with light, K-PHI undergoes photocharging – the g-CN material accumulates electrons and charge-compensating cations. Such photocharged state is stable under anaerobic conditions for weeks, but at the same time it is a strong reductant. This feature allows decoupling in time light harvesting and energy storage in the form of electron-proton couples from utilization in organic synthesis. The photocharged state of K-PHI reduces nitrobenzene to aniline, and enables dimerization of α,β-unsaturated ketones to hexadienones in dark.
This eye-tracking study establishes basic benchmarks of eye movements during reading in heritage language (HL) by Russian-speaking adults and adolescents of high (n = 21) and low proficiency (n = 27). Heritage speakers (HSs) read sentences in Cyrillic, and their eye movements were compared to those of Russian monolingual skilled adult readers, 8-year-old children and L2 learners. Reading patterns of HSs revealed longer mean fixation durations, lower skipping probabilities, and higher regressive saccade rates than in monolingual adults. High-proficient HSs were more similar to monolingual children, while low-proficient HSs performed on par with L2 learners. Low-proficient HSs differed from high-proficient HSs in exhibiting lower skipping probabilities, higher fixation counts, and larger frequency effects. Taken together, our findings are consistent with the weaker links account of bilingual language processing as well as the divergent attainment theory of HL.
This study examined the effect of 6 weeks of progressed and nonprogressed volume-based overload plyometric training (PT) on components of physical fitness and body composition measures in young male basketball players, compared with an active control group. Subjects were randomly assigned to a progressed PT (PPT, n = 7; age = 14.6 +/- 1.1 years), a non-PPT (NPPT, n = 8, age = 13.8 +/- 2.0 years), or a control group (CG, n = 7, age = 14.0 +/- 2.0 years). Before and after training, body composition measures (muscle mass and fat mass), countermovement jump with arms (CMJA) and countermovement jump without arms (CMJ), horizontal bilateral (HCMJ) and unilateral jump with right leg (RJ) and left leg (LJ), 20-cm drop jump (DJ20), sprint speed (10 m sprint), and change of direction speed (CODS [i.e., T-test]) were tested. Significant effects of time were observed for muscle and fat mass, all jump measures, and CODS (all p < 0.01; d = 0.37-0.83). Significant training group x time interactions were observed for all jump measures (all p < 0.05; d = 0.24-0.41). Post hoc analyses revealed significant pre-post performance improvements for the PPT (RJ and LJ: increment 18.6%, d = 0.8 and increment 22.7%, d = 0.9, respectively; HCMJ: increment 16.4%, d = 0.8; CMJ: increment 22.4%, d = 0.7; CMJA: increment 23.3%, d = 0.7; and DJ20: increment 39.7%, d = 1.1) and for the NPPT group (LJ: increment 14.1%, d = 0.4; DJ20: increment 32.9%, d = 0.8) with greater changes after PPT compared with NPPT for all jump measures (all p < 0.05; d = 0.21-0.81). The training efficiency was greater (p < 0.05; d = 0.22) after PPT (0.015% per jump) compared with NPPT (0.0053% per-jump). The PPT induced larger performance improvements on measures of physical fitness as compared to NPPT. Therefore, in-season progressive volume-based overload PT in young male basketball players is recommended.
Volatile supply and sales markets, coupled with increasing product individualization and complex production processes, present significant challenges for manufacturing companies. These must navigate and adapt to ever-shifting external and internal factors while ensuring robustness against process variabilities and unforeseen events. This has a pronounced impact on production control, which serves as the operational intersection between production planning and the shop- floor resources, and necessitates the capability to manage intricate process interdependencies effectively. Considering the increasing dynamics and product diversification, alongside the need to maintain constant production performances, the implementation of innovative control strategies becomes crucial.
In recent years, the integration of Industry 4.0 technologies and machine learning methods has gained prominence in addressing emerging challenges in production applications. Within this context, this cumulative thesis analyzes deep learning based production systems based on five publications. Particular attention is paid to the applications of deep reinforcement learning, aiming to explore its potential in dynamic control contexts. Analysis reveal that deep reinforcement learning excels in various applications, especially in dynamic production control tasks. Its efficacy can be attributed to its interactive learning and real-time operational model. However, despite its evident utility, there are notable structural, organizational, and algorithmic gaps in the prevailing research. A predominant portion of deep reinforcement learning based approaches is limited to specific job shop scenarios and often overlooks the potential synergies in combined resources. Furthermore, it highlights the rare implementation of multi-agent systems and semi-heterarchical systems in practical settings. A notable gap remains in the integration of deep reinforcement learning into a hyper-heuristic.
To bridge these research gaps, this thesis introduces a deep reinforcement learning based hyper- heuristic for the control of modular production systems, developed in accordance with the design science research methodology. Implemented within a semi-heterarchical multi-agent framework, this approach achieves a threefold reduction in control and optimisation complexity while ensuring high scalability, adaptability, and robustness of the system. In comparative benchmarks, this control methodology outperforms rule-based heuristics, reducing throughput times and tardiness, and effectively incorporates customer and order-centric metrics. The control artifact facilitates a rapid scenario generation, motivating for further research efforts and bridging the gap to real-world applications. The overarching goal is to foster a synergy between theoretical insights and practical solutions, thereby enriching scientific discourse and addressing current industrial challenges.
Do stereotypes strike twice?
(2019)
Stereotypes influence teachers' perception of and behaviour towards students, thus shaping students' learning opportunities. The present study investigated how 315 Australian pre-service teachers' stereotypes about giftedness and gender are related to their perception of students' intellectual ability, adjustment, and social-emotional ability, using an experimental vignette approach and controlling for social desirability in pre-service teachers' responses. Repeated-measures ANOVA showed that pre-service teachers associated giftedness with higher intellectual ability, but with less adjustment compared to average-ability students. Furthermore, pre-service teachers perceived male students as less socially and emotionally competent and less adjusted than female students. Additionally, pre-service teachers seemed to perceive female average-ability students' adjustment as most favourable compared to male average-ability students and gifted students. Findings point to discrepancies between actual characteristics of gifted female and male students and stereotypes in teachers' beliefs. Consequences of stereotyping and implications for teacher education are discussed.
Do stereotypes strike twice?
(2019)
Stereotypes influence teachers' perception of and behaviour towards students, thus shaping students' learning opportunities. The present study investigated how 315 Australian pre-service teachers' stereotypes about giftedness and gender are related to their perception of students' intellectual ability, adjustment, and social-emotional ability, using an experimental vignette approach and controlling for social desirability in pre-service teachers' responses. Repeated-measures ANOVA showed that pre-service teachers associated giftedness with higher intellectual ability, but with less adjustment compared to average-ability students. Furthermore, pre-service teachers perceived male students as less socially and emotionally competent and less adjusted than female students. Additionally, pre-service teachers seemed to perceive female average-ability students' adjustment as most favourable compared to male average-ability students and gifted students. Findings point to discrepancies between actual characteristics of gifted female and male students and stereotypes in teachers' beliefs. Consequences of stereotyping and implications for teacher education are discussed.
Making sense of the world
(2020)
For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.
Making sense of the world
(2020)
For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.
We are glad to introduce the Second Journal Club of Volume Five, Second Issue. This edition is focused on relevant studies published in the last few years in the field of resistance training, chosen by our Editorial Board members and their colleagues. We hope to stimulate your curiosity in this field and to share with you the passion for the sport, seen also from the scientific point of view. The Editorial Board members wish you an inspiring lecture.
We are glad to introduce the Second Journal Club of Volume Five, Second Issue. This edition is focused on relevant studies published in the last few years in the field of resistance training, chosen by our Editorial Board members and their colleagues. We hope to stimulate your curiosity in this field and to share with you the passion for the sport, seen also from the scientific point of view. The Editorial Board members wish you an inspiring lecture.