@article{13235, abstract = {AgSbSe2 is a promising thermoelectric (TE) p-type material for applications in the middle-temperature range. AgSbSe2 is characterized by relatively low thermal conductivities and high Seebeck coefficients, but its main limitation is moderate electrical conductivity. Herein, we detail an efficient and scalable hot-injection synthesis route to produce AgSbSe2 nanocrystals (NCs). To increase the carrier concentration and improve the electrical conductivity, these NCs are doped with Sn2+ on Sb3+ sites. Upon processing, the Sn2+ chemical state is conserved using a reducing NaBH4 solution to displace the organic ligand and anneal the material under a forming gas flow. The TE properties of the dense materials obtained from the consolidation of the NCs using a hot pressing are then characterized. The presence of Sn2+ ions replacing Sb3+ significantly increases the charge carrier concentration and, consequently, the electrical conductivity. Opportunely, the measured Seebeck coefficient varied within a small range upon Sn doping. The excellent performance obtained when Sn2+ ions are prevented from oxidation is rationalized by modeling the system. Calculated band structures disclosed that Sn doping induces convergence of the AgSbSe2 valence bands, accounting for an enhanced electronic effective mass. The dramatically enhanced carrier transport leads to a maximized power factor for AgSb0.98Sn0.02Se2 of 0.63 mW m–1 K–2 at 640 K. Thermally, phonon scattering is significantly enhanced in the NC-based materials, yielding an ultralow thermal conductivity of 0.3 W mK–1 at 666 K. Overall, a record-high figure of merit (zT) is obtained at 666 K for AgSb0.98Sn0.02Se2 at zT = 1.37, well above the values obtained for undoped AgSbSe2, at zT = 0.58 and state-of-art Pb- and Te-free materials, which makes AgSb0.98Sn0.02Se2 an excellent p-type candidate for medium-temperature TE applications.}, author = {Liu, Yu and Li, Mingquan and Wan, Shanhong and Lim, Khak Ho and Zhang, Yu and Li, Mengyao and Li, Junshan and Ibáñez, Maria and Hong, Min and Cabot, Andreu}, issn = {1936-086X}, journal = {ACS Nano}, number = {12}, pages = {11923–11934}, publisher = {American Chemical Society}, title = {{Surface chemistry and band engineering in AgSbSe₂: Toward high thermoelectric performance}}, doi = {10.1021/acsnano.3c03541}, volume = {17}, year = {2023}, } @article{13231, abstract = {We study ab initio approaches for calculating x-ray Thomson scattering spectra from density functional theory molecular dynamics simulations based on a modified Chihara formula that expresses the inelastic contribution in terms of the dielectric function. We study the electronic dynamic structure factor computed from the Mermin dielectric function using an ab initio electron-ion collision frequency in comparison to computations using a linear-response time-dependent density functional theory (LR-TDDFT) framework for hydrogen and beryllium and investigate the dispersion of free-free and bound-free contributions to the scattering signal. A separate treatment of these contributions, where only the free-free part follows the Mermin dispersion, shows good agreement with LR-TDDFT results for ambient-density beryllium, but breaks down for highly compressed matter where the bound states become pressure ionized. LR-TDDFT is used to reanalyze x-ray Thomson scattering experiments on beryllium demonstrating strong deviations from the plasma conditions inferred with traditional analytic models at small scattering angles.}, author = {Schörner, Maximilian and Bethkenhagen, Mandy and Döppner, Tilo and Kraus, Dominik and Fletcher, Luke B. and Glenzer, Siegfried H. and Redmer, Ronald}, issn = {2470-0053}, journal = {Physical Review E}, number = {6}, publisher = {American Physical Society}, title = {{X-ray Thomson scattering spectra from density functional theory molecular dynamics simulations based on a modified Chihara formula}}, doi = {10.1103/PhysRevE.107.065207}, volume = {107}, year = {2023}, } @article{13233, abstract = {We study the impact of finite-range physics on the zero-range-model analysis of three-body recombination in ultracold atoms. We find that temperature dependence of the zero-range parameters can vary from one set of measurements to another as it may be driven by the distribution of error bars in the experiment, and not by the underlying three-body physics. To study finite-temperature effects in three-body recombination beyond the zero-range physics, we introduce and examine a finite-range model based upon a hyperspherical formalism. The systematic error discussed in this Letter may provide a significant contribution to the error bars of measured three-body parameters.}, author = {Agafonova, Sofya and Lemeshko, Mikhail and Volosniev, Artem}, issn = {2469-9934}, journal = {Physical Review A}, number = {6}, publisher = {American Physical Society}, title = {{Finite-range bias in fitting three-body loss to the zero-range model}}, doi = {10.1103/PhysRevA.107.L061304}, volume = {107}, year = {2023}, } @article{13256, abstract = {The El Niño-Southern Oscillation (ENSO) and the Indian summer monsoon (ISM, or monsoon) are two giants of tropical climate. Here we assess the future evolution of the ENSO-monsoon teleconnection in climate simulations with idealized forcing of CO2 increment at a rate of 1% year-1 starting from a present-day condition (367 p.p.m.) until quadrupling. We find a monotonous weakening of the ENSO-monsoon teleconnection with the increase in CO2. Increased co-occurrences of El Niño and positive Indian Ocean Dipoles (pIODs) in a warmer climate weaken the teleconnection. Co-occurrences of El Niño and pIOD are attributable to mean sea surface temperature (SST) warming that resembles a pIOD-type warming pattern in the Indian Ocean and an El Niño-type warming in the Pacific. Since ENSO is a critical precursor of the strength of the Indian monsoon, a weakening of this relation may mean a less predictable Indian monsoon in a warmer climate.}, author = {Goswami, Bidyut B and An, Soon Il}, issn = {2397-3722}, journal = {npj Climate and Atmospheric Science}, publisher = {Springer Nature}, title = {{An assessment of the ENSO-monsoon teleconnection in a warming climate}}, doi = {10.1038/s41612-023-00411-5}, volume = {6}, year = {2023}, } @article{13260, abstract = {Experimental evolution studies are powerful approaches to examine the evolutionary history of lab populations. Such studies have shed light on how selection changes phenotypes and genotypes. Most of these studies have not examined the time course of adaptation under sexual selection manipulation, by resequencing the populations’ genomes at multiple time points. Here, we analyze allele frequency trajectories in Drosophila pseudoobscura where we altered their sexual selection regime for 200 generations and sequenced pooled populations at 5 time points. The intensity of sexual selection was either relaxed in monogamous populations (M) or elevated in polyandrous lines (E). We present a comprehensive study of how selection alters population genetics parameters at the chromosome and gene level. We investigate differences in the effective population size—Ne—between the treatments, and perform a genome-wide scan to identify signatures of selection from the time-series data. We found genomic signatures of adaptation to both regimes in D. pseudoobscura. There are more significant variants in E lines as expected from stronger sexual selection. However, we found that the response on the X chromosome was substantial in both treatments, more pronounced in E and restricted to the more recently sex-linked chromosome arm XR in M. In the first generations of experimental evolution, we estimate Ne to be lower on the X in E lines, which might indicate a swift adaptive response at the onset of selection. Additionally, the third chromosome was affected by elevated polyandry whereby its distal end harbors a region showing a strong signal of adaptive evolution especially in E lines.}, author = {De Castro Barbosa Rodrigues Barata, Carolina and Snook, Rhonda R. and Ritchie, Michael G. and Kosiol, Carolin}, issn = {1759-6653}, journal = {Genome biology and evolution}, number = {7}, publisher = {Oxford Academic}, title = {{Selection on the fly: Short-term adaptation to an altered sexual selection regime in Drosophila pseudoobscura}}, doi = {10.1093/gbe/evad113}, volume = {15}, year = {2023}, } @unpublished{13447, abstract = {Asteroseismology has transformed stellar astrophysics. Red giant asteroseismology is a prime example, with oscillation periods and amplitudes that are readily detectable with time-domain space-based telescopes. These oscillations can be used to infer masses, ages and radii for large numbers of stars, providing unique constraints on stellar populations in our galaxy. The cadence, duration, and spatial resolution of the Roman galactic bulge time-domain survey (GBTDS) are well-suited for asteroseismology and will probe an important population not studied by prior missions. We identify photometric precision as a key requirement for realizing the potential of asteroseismology with Roman. A precision of 1 mmag per 15-min cadence or better for saturated stars will enable detections of the populous red clump star population in the Galactic bulge. If the survey efficiency is better than expected, we argue for repeat observations of the same fields to improve photometric precision, or covering additional fields to expand the stellar population reach if the photometric precision for saturated stars is better than 1 mmag. Asteroseismology is relatively insensitive to the timing of the observations during the mission, and the prime red clump targets can be observed in a single 70 day campaign in any given field. Complementary stellar characterization, particularly astrometry tied to the Gaia system, will also dramatically expand the diagnostic power of asteroseismology. We also highlight synergies to Roman GBTDS exoplanet science using transits and microlensing.}, author = {Huber, Daniel and Pinsonneault, Marc and Beck, Paul and Bedding, Timothy R. and Joss Bland-Hawthorn, Joss Bland-Hawthorn and Breton, Sylvain N. and Bugnet, Lisa Annabelle and Chaplin, William J. and Garcia, Rafael A. and Grunblatt, Samuel K. and Guzik, Joyce A. and Hekker, Saskia and Kawaler, Steven D. and Mathis, Stephane and Mathur, Savita and Metcalfe, Travis and Mosser, Benoit and Ness, Melissa K. and Piro, Anthony L. and Serenelli, Aldo and Sharma, Sanjib and Soderblom, David R. and Stassun, Keivan G. and Stello, Dennis and Tayar, Jamie and Belle, Gerard T. van and Zinn, Joel C.}, booktitle = {arXiv}, title = {{Asteroseismology with the Roman galactic bulge time-domain survey}}, doi = {10.48550/arXiv.2307.03237}, year = {2023}, } @phdthesis{12781, abstract = {Most energy in humans is produced in form of ATP by the mitochondrial respiratory chain consisting of several protein assemblies embedded into lipid membrane (complexes I-V). Complex I is the first and the largest enzyme of the respiratory chain which is essential for energy production. It couples the transfer of two electrons from NADH to ubiquinone with proton translocation across bacterial or inner mitochondrial membrane. The coupling mechanism between electron transfer and proton translocation is one of the biggest enigma in bioenergetics and structural biology. Even though the enzyme has been studied for decades, only recent technological advances in cryo-EM allowed its extensive structural investigation. Complex I from E.coli appears to be of special importance because it is a perfect model system with a rich mutant library, however the structure of the entire complex was unknown. In this thesis I have resolved structures of the minimal complex I version from E. coli in different states including reduced, inhibited, under reaction turnover and several others. Extensive structural analyses of these structures and comparison to structures from other species allowed to derive general features of conformational dynamics and propose a universal coupling mechanism. The mechanism is straightforward, robust and consistent with decades of experimental data available for complex I from different species. Cyanobacterial NDH (cyanobacterial complex I) is a part of broad complex I superfamily and was studied as well in this thesis. It plays an important role in cyclic electron transfer (CET), during which electrons are cycled within PSI through ferredoxin and plastoquinone to generate proton gradient without NADPH production. Here, I solved structure of NDH and revealed additional state, which was not observed before. The novel “resting” state allowed to propose the mechanism of CET regulation. Moreover, conformational dynamics of NDH resembles one in complex I which suggest more broad universality of the proposed coupling mechanism. In summary, results presented here helped to interpret decades of experimental data for complex I and contributed to fundamental mechanistic understanding of protein function. }, author = {Kravchuk, Vladyslav}, isbn = {978-3-99078-029-9}, issn = {2663-337X}, pages = {127}, publisher = {Institute of Science and Technology Austria}, title = {{Structural and mechanistic study of bacterial complex I and its cyanobacterial ortholog}}, doi = {10.15479/at:ista:12781}, year = {2023}, } @phdthesis{13074, abstract = {Deep learning has become an integral part of a large number of important applications, and many of the recent breakthroughs have been enabled by the ability to train very large models, capable to capture complex patterns and relationships from the data. At the same time, the massive sizes of modern deep learning models have made their deployment to smaller devices more challenging; this is particularly important, as in many applications the users rely on accurate deep learning predictions, but they only have access to devices with limited memory and compute power. One solution to this problem is to prune neural networks, by setting as many of their parameters as possible to zero, to obtain accurate sparse models with lower memory footprint. Despite the great research progress in obtaining sparse models that preserve accuracy, while satisfying memory and computational constraints, there are still many challenges associated with efficiently training sparse models, as well as understanding their generalization properties. The focus of this thesis is to investigate how the training process of sparse models can be made more efficient, and to understand the differences between sparse and dense models in terms of how well they can generalize to changes in the data distribution. We first study a method for co-training sparse and dense models, at a lower cost compared to regular training. With our method we can obtain very accurate sparse networks, and dense models that can recover the baseline accuracy. Furthermore, we are able to more easily analyze the differences, at prediction level, between the sparse-dense model pairs. Next, we investigate the generalization properties of sparse neural networks in more detail, by studying how well different sparse models trained on a larger task can adapt to smaller, more specialized tasks, in a transfer learning scenario. Our analysis across multiple pruning methods and sparsity levels reveals that sparse models provide features that can transfer similarly to or better than the dense baseline. However, the choice of the pruning method plays an important role, and can influence the results when the features are fixed (linear finetuning), or when they are allowed to adapt to the new task (full finetuning). Using sparse models with fixed masks for finetuning on new tasks has an important practical advantage, as it enables training neural networks on smaller devices. However, one drawback of current pruning methods is that the entire training cycle has to be repeated to obtain the initial sparse model, for every sparsity target; in consequence, the entire training process is costly and also multiple models need to be stored. In the last part of the thesis we propose a method that can train accurate dense models that are compressible in a single step, to multiple sparsity levels, without additional finetuning. Our method results in sparse models that can be competitive with existing pruning methods, and which can also successfully generalize to new tasks.}, author = {Peste, Elena-Alexandra}, issn = {2663-337X}, pages = {147}, publisher = {Institute of Science and Technology Austria}, title = {{Efficiency and generalization of sparse neural networks}}, doi = {10.15479/at:ista:13074}, year = {2023}, } @phdthesis{12964, abstract = {Pattern formation is of great importance for its contribution across different biological behaviours. During developmental processes for example, patterns of chemical gradients are established to determine cell fate and complex tissue patterns emerge to define structures such as limbs and vascular networks. Patterns are also seen in collectively migrating groups, for instance traveling waves of density emerging in moving animal flocks as well as collectively migrating cells and tissues. To what extent these biological patterns arise spontaneously through the local interaction of individual constituents or are dictated by higher level instructions is still an open question however there is evidence for the involvement of both types of process. Where patterns arise spontaneously there is a long standing interest in how far the interplay of mechanics, e.g. force generation and deformation, and chemistry, e.g. gene regulation and signaling, contributes to the behaviour. This is because many systems are able to both chemically regulate mechanical force production and chemically sense mechanical deformation, forming mechano-chemical feedback loops which can potentially become unstable towards spatio and/or temporal patterning. We work with experimental collaborators to investigate the possibility that this type of interaction drives pattern formation in biological systems at different scales. We focus first on tissue-level ERK-density waves observed during the wound healing response across different systems where many previous studies have proposed that patterns depend on polarized cell migration and arise from a mechanical flocking-like mechanism. By combining theory with mechanical and optogenetic perturbation experiments on in vitro monolayers we instead find evidence for mechanochemical pattern formation involving only scalar bilateral feedbacks between ERK signaling and cell contraction. We perform further modeling and experiment to study how this instability couples with polar cell migration in order to produce a robust and efficient wound healing response. In a following chapter we implement ERK-density coupling and cell migration in a 2D active vertex model to investigate the interaction of ERK-density patterning with different tissue rheologies and find that the spatio-temporal dynamics are able to both locally and globally fluidize a tissue across the solid-fluid glass transition. In a last chapter we move towards lower spatial scales in the context of subcellular patterning of the cell cytoskeleton where we investigate the transition between phases of spatially homogeneous temporal oscillations and chaotic spatio-temporal patterning in the dynamics of myosin and ROCK activities (a motor component of the actomyosin cytoskeleton and its activator). Experimental evidence supports an intrinsic chemical oscillator which we encode in a reaction model and couple to a contractile active gel description of the cell cortex. The model exhibits phases of chemical oscillations and contractile spatial patterning which reproduce many features of the dynamics seen in Drosophila oocyte epithelia in vivo. However, additional pharmacological perturbations to inhibit myosin contractility leaves the role of contractile instability unclear. We discuss alternative hypotheses and investigate the possibility of reaction-diffusion instability.}, author = {Boocock, Daniel R}, isbn = {978-3-99078-032-9}, issn = {2663-337X}, pages = {146}, publisher = {Institute of Science and Technology Austria}, title = {{Mechanochemical pattern formation across biological scales}}, doi = {10.15479/at:ista:12964}, year = {2023}, } @article{13963, abstract = {The many-body localization (MBL) proximity effect is an intriguing phenomenon where a thermal bath localizes due to the interaction with a disordered system. The interplay of thermal and nonergodic behavior in these systems gives rise to a rich phase diagram, whose exploration is an active field of research. In this paper, we study a bosonic Hubbard model featuring two particle species representing the bath and the disordered system. Using state-of-the-art numerical techniques, we investigate the dynamics of the model in different regimes, based on which we obtain a tentative phase diagram as a function of coupling strength and bath size. When the bath is composed of a single particle, we observe clear signatures of a transition from an MBL proximity effect to a delocalized phase. Increasing the bath size, however, its thermalizing effect becomes stronger and eventually the whole system delocalizes in the range of moderate interaction strengths studied. In this regime, we characterize particle transport, revealing diffusive behavior of the originally localized bosons.}, author = {Brighi, Pietro and Ljubotina, Marko and Abanin, Dmitry A. and Serbyn, Maksym}, issn = {2469-9969}, journal = {Physical Review B}, number = {5}, publisher = {American Physical Society}, title = {{Many-body localization proximity effect in a two-species bosonic Hubbard model}}, doi = {10.1103/physrevb.108.054201}, volume = {108}, year = {2023}, }