Abstract: The energy dependence of a pulsed-dielectric barrier discharge (DBD) plasma treatment on chemical species production and biological responses was investigated. We hypothesized that the total plasma energy delivered during treatment encompasses the influence of major application parameters. A microsecond-pulsed DBD system was used to treat three different cancer cell lines and cell viability was analyzed. The energy per pulse was measured and the total plasma treatment energy was controlled by adjusting the pulse frequency, treatment time, and application distance. Our data suggest that the delivered plasma energy plays a predominant role in stimulating a biological response in vitro. This study aids in developing steps toward defining a plasma treatment unit and treatment dose for biomedical and clinical research.

Abstract: Ever since the industrial revolution, the emission of greenhouse gasses dramatically increased, resulting in high CO2 concentration in the atmosphere. The electrochemical conversion of CO2 to value added products, such as carbon monoxide, formic acid, methane, ethylene and ethanol is a very promising strategy to inhibit CO2 emissions. Nevertheless, at the moment, the electrochemical CO2 reduction (eCO2R) is not yet industrially viable, mainly due to the lack of good electrocatalysts. On the other hand, core-shell nanoparticles (NPs) have emerged over the last couple of years as promising candidates. It is believed that bimetallic enhancement effects are behind the improved performance of these core-shell NPs when compared to the individual metals. Although widely investigated, there are still some remaining issues and/or open questions. Indeed, the development of a robust and straightforward synthesis method along with fundamental insight into their resistance towards electrochemical stress remains absent. A good control over morphology, size and composition is key in determining which properties are beneficial for the eCO2R. Since these catalysts are designed to be implemented in electrolyzers, they have to maintain long-term performance. This makes the design of a reproducible method, unveiling structure-performance relationships the effect of electrochemical stress, a crucial aspect. Exploring and modifying existing synthesis methods, have led to the acquisition of a robust and reproducible synthesis method where thermal decomposition of the Cu core is combined with the galvanic replacement of Ag in organic solvents. The implementation of this method has led to the design of a wide variety of Cu-Ag bimetallic NPs and enabled to investigate their composition-selectivity profile. Introducing Ag on Cu suppressed hydrogen and increased the CO formation. CO production was boosted by using Cu@Ag core-shells and was promoted even more by changing the type of electrolyte. As these nanoparticles suffered from degradation, the 3D mapping of the structural changes of Cu@Ag core-shells under operating conditions led to the hypothesis of a two-step degradation mechanism where initially Cu leaching was observed with the subsequent sintering of the Ag shells. One approach to avoid this electrochemical degradation, investigated in this research, was the application of an ultrathin carbon layer to protect the active layer. This ultrathin carbon layer operated as a protective layer, suppressing hydrogen production and increasing the stability of the electrocatalyst. In conclusion, the product selectivity can be tuned by using different Cu-Ag bimetallic nanoparticles synthesized through a robust method. Their unique degradation pathway of Cu@Ag core-shell nanoparticles has led to the proposition of a more accurate stabilization strategy. These findings can contribute significantly in the quest for improved electrocatalysts for the eCO2R.

Abstract: The two-dimensional (2D) transition metal trihalide (TMX3, X = Cl, Br, I) family has attracted considerable attention in recent years due to the realization of CrCl3, CrBr3, and CrI3 monolayers. Up to now, the main focus of the theoretically predicted TMX3 monolayers has been on the Chern insulator states, which can realize the quantum anomalous Hall effect. Here, using first-principles calculations, we theoretically demonstrate that the stable OsCl3 monolayer has a ferromagnetic ground state and a spin-polarized Dirac point without spin-orbit coupling (SOC), which disappears in the band structure of a Janus OsBr1.5Cl1.5 monolayer. We find that OsCl3 exhibits in-plane magnetization when SOC is included. By manipulating the magnetization direction along the C-2 symmetry axis of the OsCl3 structure, a gapless half-Dirac semimetal state with SOC can be achieved, which is different from the gapped Chern insulator state. Both semimetal states of OsCl3 monolayer without and with SOC exhibit a linear half-Dirac point (twofold degenerate) with high Fermi velocities. The achievement of the 2D semimetal state with SOC is expected to be found in other TMX3 monolayers, and we confirm it in a TiCl3 monolayer. This provides a different perspective to study the band structure with SOC of the 2D TMX3 family.

Abstract: The increasing world population and living standards urgently necessitate the transition towards a sustainable food system. One solution is microbial protein, i.e. using microbial biomass as alternative protein source for human nutrition, particularly based on renewable electron and carbon sources that do not require arable land. Upcoming green electrification and carbon capture initiatives enable this, yielding new routes to H2, CO2 and CO2-derived compounds like methane, methanol, formic- and acetic acid. Aerobic hydrogenotrophs, methylotrophs, acetotrophs and microalgae are the usual suspects for nutritious and palatable biomass production on these compounds. Interestingly, these compounds are largely un(der)explored for purple non-sulfur bacteria, even though these microbes may be suitable for growing aerobically and phototrophically on these substrates. Currently, selecting the best strains, metabolisms and cultivation conditions for nutritious and palatable microbial food mainly starts from empirical growth experiments, and mostly does not stretch beyond bulk protein. We propose a more target-driven and efficient approach starting from the genome-embedded potential to tuning towards, for instance, essential amino- and fatty acids, vitamins, taste,... Genome-scale metabolic models combined with flux balance analysis will facilitate this, narrowing down experimental variations and enabling to get the most out of the 'best' combinations of strain and electron and carbon sources.

Abstract: This piece of work is twofold. First, the time evolution of wave-packets in 2D systems is analyzed by the Split-Operator technique in three different scenarios: in multilayer phosphorene, the transient oscillations in the time-dependent average of position and momentum were observed due to the zitterbewegung effect, and the wave packet propagates non-uniformly along the space deforming itself into an elliptical shape. These results were corroborated by the Green’s function formalism except for large values of the wave-vector and long times; in 2D semiconductor quantum wires (QWs) with anisotropic effective masses and different angle orientations with respect to the anisotropic axis. We have shown that the greater this angle, the smaller is the energy levels spacing implying in an increase of the accessible electronic states. Additionally, for non-null magnetic field, the quantum Hall edge states are significantly affected by the edge orientation. In the anisotropic case damped oscillations in the average values of velocity in both x and y directions where obtained. Theses oscillations are originated by the QW geometry but also from subwavepackets with different momentum orientations, whereas for isotropic QWs the wavepacket disperses without splitting; in the third scenario the split-operator technique was used to study the Landau levels, the wave packet trajectories and velocities of electrons in graphene at low-energy regime described by a modified Dirac equation where the momentum-operator is written in a generalized form as result of applying the position-dependent translation operator formalism (PDTO). In the second part of this thesis, the electronic and tunneling properties of α − T3 lattices were studied. Electrons in these lattices behave analogous to integer-spin Dirac Fermions. The presence of a third atomic site in the unit cell leads to a flat band in the energy spectrum, providing unique electronic and tunneling properties. The presence of a super-periodic potential and the inclusion of symmetry-breaking terms results in deviations of the atomic equivalence between the atomic sites affecting the Dirac points and the band-gap. Small deviations in the equivalence between the atomic sites and the number of barriers change the transmission properties in these lattices. Additionally, new tunneling regions are possible by adjusting the symmetry between the atomic sites and affect the omnidirectional total transmission called super-Klein tunneling observed in these lattices. We compare those results to the tunneling probabilities through regions where the energy spectrum changes from linear with a middle flat band to a hyperbolic dispersion.

Abstract: For oxygen conducting materials applied in solid oxide fuel cells and chemical-looping processes, the understanding of the oxygen diffusion mechanism and the materials’ crystal structure at different stages of the redox reactions is a key parameter to control their performance. In this paper we report the first ever in situ 3D ED experiment in a gas environment and with it uncover the structure evolution of SrFeO2.5 as notably different from that reported from in situ X-ray and in situ neutron powder diffraction studies in gas environments. Using in situ 3D ED on submicron sized single crystals obtained from a high quality monodomain SrFeO2.5 single crystal , we observe the transformation under O2 flow of SrFeO2.5 with an intra- and interlayer ordering of the left and right twisted (FeO4) tetrahedral chains (space group Pcmb) into consecutively SrFeO2.75 with space group Cmmm (at 350°C, 33% O2) and SrFeO3-δ with space group Pm3 ̅m (at 400°C, 100% O2). Upon reduction in H2 flow, the crystals return to the brownmillerite structure with intralayer order, but without regaining the interlayer order of the pristine crystals. Therefore, redox cycling of SrFeO2.5 crystals in O2 and H2 introduces stacking faults into the structure, resulting in an I2/m(0βγ)0s symmetry with variable β.

Abstract: In this work, the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) submitted to an external magnetic field are studied using a Metropolis algorithm. The influence on the M(B) curves of the size distribution of the nanoparticles, of uniaxial anisotropy, and of dipolar interaction between the cores are examined, as well as the influence of drying the samples under a zero or non-zero magnetic field. It is shown that the anisotropy impacts the shape of the magnetization curves, which then deviate from a pure Langevin behaviour, whereas the dipolar interaction has no influence on the curves at 300 K for small particles (with a radius of 3 nm). The fitting of the magnetization curves of particles with magnetic anisotropy to a Langevin model (including a size distribution of the particles) can then lead to erroneous values of the distribution parameters. The simulation results are qualitatively compared to experimental results obtained for iron oxide nanoparticles (with a 3.21 nm median radius).

Abstract: We explorethepotentialofmicrowave(MW)-plasma-based in situ
utilizationoftheMartianatmospherewithafocusonthenovelpos-
sibilityoffixingN2 forfertilizerproduction. Conversioninasimulant
plasma (i.e.,
96% CO2,
2% N2, and
2% Ar),performedunderen-
ergyconditionssimilartothoseoftheMarsOxygen In Situ Resource
UtilizationExperiment(MOXIE),currentlyonboardNASA’sPerse-
verancerover,demonstratesthatO/O2 formedthroughCO2 dissociation
facilitatesthefixationoftheN2 fractionviaoxidationtoNOx.
PromisingproductionratesforO2, CO,andNOx of 47.0,76.1,and
1.25g/h,respectively,arerecordedwithcorrespondingenergy
costs of0.021,0.013,and0.79kWh/g,respectively.Notably,O2
productionratesare
30 timeshigherthanthosedemonstrated
by MOXIE,whiletheNOx production raterepresentsan
7% fixa-
tionoftheN2 fraction presentintheMartian atmosphere.MW-
plasma-basedconversionthereforeshowsgreatpotentialasan in
situ resourceutilization(ISRU)technologyonMarsinthatitsimulta-
neouslyfixesN2 and producesO2.

Abstract: Sustainable management of industrial plastic waste is crucial in the transition to a circular economy. Today, most industrial plastic waste is incinerated, whereas it could be recycled. As a consequence, governments increasingly make use of incineration taxes to improve current waste management practices. This paper presents an econometric panel analysis that studies the effects of an incineration tax on industrial plastic waste in Flanders (Belgium). Not only is this study the first econometric analysis on industrial plastic waste management in which firm heterogeneity is explicitly taken into account by including firm-specific characteristics, but this study also provides policymakers with insights into the effectiveness of an incineration tax to change current waste management practices. Empirical estimates imply that heterogeneous firms generate industrial plastic waste in different ways and that heterogeneous firms reduce their waste generation in different ways after the incineration tax rate increases. The estimates also show that the unique decrease of the incineration tax in 2007, did not change waste management practices. These estimates show that firms do not disinvest or indicate that loss aversion theory, i.e. a preference for avoiding losses over acquiring equivalent gains, might apply to firms that are faced with environmental taxation in a waste management context.

Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.

Abstract: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: Advances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the object of interest. If the materials and their spectral responses are known a priori, the image reconstruction step is rather straightforward. If they are not known, however, the maps as well as the responses need to be estimated jointly. A conventional workflow in spectral CT involves performing volume reconstruction followed by material decomposition, or vice versa. However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem. To resolve this issue, we propose 'A Dictionary-based Joint reconstruction and Unmixing method for Spectral Tomography' (ADJUST). Our formulation relies on forming a dictionary of spectral signatures of materials common in CT and prior knowledge of the number of materials present in an object. In particular, we decompose the spectral volume linearly in terms of spatial material maps, a spectral dictionary, and the indicator of materials for the dictionary elements. We propose a memory-efficient accelerated alternating proximal gradient method to find an approximate solution to the resulting bi-convex problem. From numerical demonstrations on several synthetic phantoms, we observe that ADJUST performs exceedingly well compared to other state-of-the-art methods. Additionally, we address the robustness of ADJUST against limited and noisy measurement patterns. The demonstration of the proposed approach on a spectral micro-CT dataset shows its potential for real-world applications. Code is available at https://github.com/mzeegers/ADJUST.

Abstract: Using a particle-based model, we examine the collective dynamics of skyrmions interacting with a funnel potential under dc driving as the skyrmion density and relative strength of the Magnus and damping terms are varied. For driving in the easy direction, we find that increasing the skyrmion density reduces the average skyrmion velocity due to jamming of skyrmions near the funnel opening, while the Magnus force causes skyrmions to accumulate on one side of the funnel array. For driving in the hard direction, there is a critical skyrmion density below which the skyrmions become trapped. Above this critical value, a clogging effect appears with multiple depinning and repinning states where the skyrmions can rearrange into different clogged configurations, while at higher drives, the velocity-force curves become continuous. When skyrmions pile up near the funnel opening, the effective size of the opening is reduced and the passage of other skyrmions is blocked by the repulsive skyrmion-skyrmion interactions. We observe a strong diode effect in which the critical depinning force is higher and the velocity response is smaller for hard direction driving. As the ratio of Magnus force to dissipative term is varied, the skyrmion velocity varies in a non-linear and non-monotonic way due to the pile up of skyrmions on one side of the funnels. At high Magnus forces, the clogging effect for hard direction driving is diminished.

Abstract: Bamboo is an important component in subtropical and tropical forest communities. The plant has characteristic long lanceolate leaves with parallel venation. Prior studies have shown that the leaf shapes of this plant group can be well described by a simplified version (referred to as SGE-1) of the Gielis equation, a polar coordinate equation extended from the superellipse equation. SGE-1 with only two model parameters is less complex than the original Gielis equation with six parameters. Previous studies have seldom tested whether other simplified versions of the Gielis equation are superior to SGE-1 in fitting empirical leaf shape data. In the present study, we compared a three-parameter Gielis equation (referred to as SGE-2) with the two-parameter SGE-1 using the leaf boundary coordinate data of six bamboo species within the same genus that have representative long lanceolate leaves, with >300 leaves for each species. We sampled 2000 data points at approximately equidistant locations on the boundary of each leaf, and estimated the parameters for the two models. The root–mean–square error (RMSE) between the observed and predicted radii from the polar point to data points on the boundary of each leaf was used as a measure of the model goodness of fit, and the mean percent error between the RMSEs from fitting SGE-1 and SGE-2 was used to examine whether the introduction of an additional parameter in SGE-1 remarkably improves the model’s fitting. We found that the RMSE value of SGE-2 was always smaller than that of SGE-1. The mean percent errors among the two models ranged from 7.5% to 20% across the six species. These results indicate that SGE-2 is superior to SGE-1 and should be used in fitting leaf shapes. We argue that the results of the current study can be potentially extended to other lanceolate leaf shapes.