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At least 739 records · Page 41

Accuracy of hourly energy predictions for demand flexibility applications

Decarbonization goals in the United States electricity sector are increasing the levels of renewable energy generation in the electricity supply system, and are driving increased attention to building electrification, which will increase the magnitude and shift the timing of the electricity system peak. These changes are motivating new approaches to coordinate building electricity demand with low-carbon renewable generation, elevating the importance of demand flexibility (DF) in buildings and the need to quantify the temporal impacts of DF. In this paper, we first characterize the hourly predictive accuracy of six commonly used baseline models in an application context of quantifying building-level load shift. Our analysis revealed insights such as hours of the day (afternoons), periods of the week (weekends), and seasons (summer) that were predicted with more accuracy than other time periods. In addition, the analysis showed tendencies toward overprediction or underprediction of load. Secondly, we provide the first published investigation of baseline erosion from repeated dispatch of building load shifting. We observed that as the baseline period is pushed back further from the prediction day, the distribution of errors across baseline model predictions increases, with notable inflection points near the three-week erosion point for two of the three models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Double-Pronged Sword: XJB-5-131 Is a Suppressor of Somatic Instability and Toxicity in Huntington’s Disease

Due to large increases in the elderly populations across the world, age-related diseases are expected to expand dramatically in the coming years. Among these, neurodegenerative diseases will be among the most devastating in terms of their emotional and economic impact on patients, their families, and associated subsidized health costs. There is no currently available cure or rescue for dying brain cells. Viable therapeutics for any of these disorders would be a breakthrough and provide relief for the large number of affected patients and their families. Neurodegeneration is accompanied by elevated oxidative damage and inflammation. While natural antioxidants have largely failed in clinical trials, preclinical phenotyping of the unnatural, mitochondrial targeted nitroxide, XJB-5-131, bodes well for further translational development in advanced animal models or in humans. Here we consider the usefulness of synthetic antioxidants for the treatment of Huntington’s disease. The mitochondrial targeting properties of XJB-5-131 have great promise. It is both an electron scavenger and an antioxidant, reducing both somatic expansion and toxicity simultaneously through the same redox mechanism. By quenching reactive oxygen species, XJB-5-131 breaks the cycle between the rise in oxidative damage during disease progression and the somatic growth of the CAG repeat which depends on oxidation.

59 BASIC BIOLOGICAL SCIENCES↗

Renewable Thermal Energy Systems Designed for Industrial Process Solutions in Multiple Industries

Industrial decarbonization is a key area that must be accelerated, to foster the removal of fossil fuels from the provision of heat, especially at low temperatures less than 300 degrees C. This paper looks at the results of two case studies for understanding the economics and potential for renewable thermal energy systems (RTES), particularly in hybrid configurations to provide industrial process heat (IPH). The first case study looks at heat pumps for district heating, and the second, the use of linear Fresnel collectors (LFCs) coupled with phase change material (PCM) thermal energy storage (TES) for direct steam generation (DSG). Using district heat as an input for the heat pump, three cases were run harvesting energy from ambient water (5 degrees C), sewage water (20 degrees C), and a solar collector (35 degrees C). Accounting for elevated costs of infrastructure for each heat source, the levelized cost of heat (LCOH) of the first case study ranged from $4-$15 per million British Thermal Units (MMBTU). For the second case study modeling LFCs with PCM and TES, the results show that a LCOH of $9-$15 per MMBTU is possible, depending on the direct normal irradiance.

concentrated solar thermal↗

Renewable Thermal Energy Systems Designed for Industrial Process Solutions in Multiple Industries: Preprint

Industrial decarbonization is a key area that must be accelerated, to foster the removal of fossil fuels from the provision of heat, especially at low temperatures less than 300 degrees C. This paper looks at the results of two case studies for understanding the economics and potential for renewable thermal energy systems (RTES), particularly in hybrid configurations to provide industrial process heat (IPH). The first case study looks at heat pumps for district heating, and the second, the use of linear Fresnel collectors (LFCs) coupled with phase change material (PCM) thermal energy storage (TES) for direct steam generation (DSG). Using district heat as an input for the heat pump, three cases were run harvesting energy from ambient water (5 degrees C), sewage water (20 degrees C), and a solar collector (35 degrees C). Accounting for elevated costs of infrastructure for each heat source, the levelized cost of heat (LCOH) of the first case study ranged from $4-$10 per million British Thermal Units (MMBTU). For the second case study modeling LFCs with PCM and TES, the results show that a LCOH of $9-$15 per MMBTU is possible, depending on the direct normal irradiance.

concentrated solar thermal↗

High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning

Abstract The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high‐resolution (∼37 km 2 ) differentiable models (a type of hybrid model): one with implicit, unit‐hydrograph‐style routing and another with explicit Muskingum‐Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process‐based equations to provide a structural backbone, which were trained simultaneously (“end‐to‐end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash‐Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long‐standing modeling challenge. The Muskingum‐Cunge version further improved performance for basins >10,000 km 2 . Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. We also provide a CONUS‐scale hydrologic data set for further evaluation and use.

Song, Yalan [Civil and Environmental Engineering T↗

Band Energy Dependence of Defect Formation in the Topological Semimetal Cd3As2

Cadmium Arsenide (Cd3As2) is a prototypical Dirac semimetal that manifests topological properties in a 3D bulk material. In defect-free Cd3As2, the Fermi level lies at a minimum in the density of states at the Dirac point, but experimentally it forms with excess electron carriers and an elevated EF, thereby masking the topological features. To computationally study the self-doping of Cd3As2, we combine density functional theory (DFT) calculations for defect formation energies with quasi-particle self-consistent GW (QSGW) electronic structure calculations. We demonstrate an innate dependence of the point defect formation energies on carrier concentrations and use the QSGW calculated density of states to extrapolate formation energies to arbitrary electron concentrations. This approach allows the quantitative modeling of thermodynamic defect equilibria in topological semimetals and is used to predict how Cd3As2 growth conditions affect the position of EF relative to the Dirac point.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗

Temperature and Water Levels Collectively Regulate Methane Emissions From Subtropical Freshwater Wetlands

Abstract Wetlands are the largest and most climate‐sensitive natural sources of methane. Accurately estimating wetland methane emissions involves reconciling inversion (“top‐down”) and process‐based (“bottom‐up”) models within the global methane budget. However, estimates from these two model types are inherently interdependent and often reveal substantial discrepancies. To enhance the reliability of both approaches, we need a comprehensive understanding of wetland methane emissions and an independent high‐resolution long‐term flux data set. Here, we employed a data‐driven random forest approach to identify key variables influencing methane emissions from subtropical freshwater wetlands in the Southeastern United States. The model‐estimated monthly mean methane fluxes fit well with measured methane fluxes ( R 2 = 0.67) at four representative FLUXNET‐CH4 wetland sites across the region. Variable importance analysis highlighted the sensitivity of subtropical freshwater wetland methane emissions to variations in both temperature and water levels. High temperatures facilitate methanogenesis by enhancing microbial activities, while elevated water levels maintain anaerobic conditions necessary for methane production. Notably, the response of methane emissions to water level fluctuations is contingent on temperature conditions, and vice versa. Moreover, we constructed the first high‐spatial‐resolution (∼1 km × 1 km) and long‐term (1982–2010) gridded regional wetland methane flux product for the Southeastern United States, estimating annual methane emissions from subtropical freshwater wetlands in the region at 4.93 ± 0.11 Tg CH 4 yr −1 for 1982–2010. This new benchmark product holds promise for validating and parameterizing uncertain wetland methane emission processes in bottom‐up models and provides improved prior information for top‐down models.

He, Keqi [Earth and Climate Sciences Nicholas Scho↗

Additively manufactured Al-Ce-Ni-Mn alloy with improved elevated-temperature fatigue resistance

Here, the high cycle fatigue behavior of an additively manufactured (AM) Al-10.5Ce-3.1Ni-1.2Mn wt% alloy was evaluated at 350 °C. The measured fatigue strength of 50 MPa at this temperature is comparable to the most fatigue resistant wrought Al alloys (2618-T6 and 7079-T6) at 315 °C. Refinement of pore populations through advanced AM processing in the examined alloy led to oxide inclusions becoming dominant fatigue crack initiation sites. The distribution of microstructural features that determine crack initiation was measured by X-ray computed tomography and served as input to make fatigue strength model predictions with various methodologies. A Monte-Carlo based approach that was previously applied to predict the fatigue strength of cast aluminum alloys through pore size distributions yielded accurate predictions for the fatigue strength of this AM alloy. Given the tunability of defect distributions in AM alloys, the sensitivity of the Al-Ce-Ni-Mn alloy fatigue behavior to defect distributions and outstanding elevated-temperature fatigue resistance of this alloy; the results together suggest the possibility of a new generation of fatigue-resistant alloys produced by the additive manufacturing route.

36 MATERIALS SCIENCE↗

Mapping the global distribution of C 4 vegetation using observations and optimality theory

Plants with the C 4 photosynthesis pathway typically respond to climate change differently from more common C 3 -type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C 4 and C 3 vegetation distributions. However, current C 4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C 4 vegetation. We find that global C 4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C 4 natural grass cover due to elevated CO 2 favoring C 3 -type photosynthesis, and an increase in C 4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C 4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18–23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C 4 plants in the contemporary global carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

Correspondence: Bill of Materials Variation and Module Degradation in Utility-Scale PV Systems

We report photovoltaic (PV) modules of the same make and model are often assembled with different bills of materials (BOMs). In this correspondence, we revisit two case studies of utility-scale silicon PV systems in which these differing BOMs were associated with faster-than-expected degradation. In one of the sites, we found that different metallization paste had been used for grid lines in some cells leading to loss of contact to the cell and severe series resistance degradation. We provide details on the observation of this mechanism at two additional sites not described in the original article. In a second case study, we found that two different types of cell had been used, and that they could be distinguished by their back contact. Cells with uniform back contacts suffered from light and elevated temperature induced degradation (LeTID), while those with local back contacts did not. We also briefly describe BOM variations observed at other sites to illustrate the extent of the challenge. Our results from both sites underscore that variations in BOM, even among modules of the same make and model can lead to reliability challenges.

14 SOLAR ENERGY↗

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗

Noise Optimization for MKIDs with Different Design Geometries and Material Selections

The separation and optimization of noise components is critical to microwave-kinetic inductance detector (MKID) development. We analyze the effect of several changes to the lumped-element inductor and interdigitated capacitor geometry on the noise performance of a series of MKIDs intended for millimeter-wavelength experiments. We extract the contributions from two-level system noise in the dielectric layer, the generation-recombination noise intrinsic to the superconducting thin-film, and system white noise from each detector noise power spectrum and characterize how these noise components depend on detector geometry, material, and measurement conditions such as driving power and temperature. We observe a reduction in the amplitude of two-level system noise with both an elevated sample temperature and an increased gap between the fingers within the interdigitated capacitors for both aluminum and niobium detectors. We also verify the expected reduction of the generation-recombination noise and associated quasiparticle lifetime with reduced inductor volume. This study also iterates over different materials, including aluminum, niobium, and aluminum manganese, and compares the results with an underlying physical model.

generation-recombination noise↗

Phase evolution and mechanical performance of an ettringite-based binder during hydrothermal aging

Little is known about the performance of ettringite-based binders in hydrothermal conditions. This investigation aims to gain insights into the phase evolution and corresponding mechanical performance of an ettringite-based binder considering crystallization pressure caused by late-reaction products. Additionally, the role of fiber reinforcement on the strength retention of the binder was investigated. When aged at an elevated temperature under water-saturated conditions, hard-burned MgO hydrated to form brucite. The precipitation and growth of the brucite crystals led to a crystallization pressure of approximately 200 MPa calculated using thermodynamic modelling. Damage was observed after 4 months of aging with cracks in the microstructure and eventually a failure at the macro scale. Ettringite remained stable at 60 °C due to the water-saturated conditions. Polypropylene fiber delayed crack propagation and thus reduced the damage caused by crystallization pressure. The fiber improved the flexural performance of composite attaining deflection-hardening behavior regardless of aging conditions.

36 MATERIALS SCIENCE↗

High temperature mechanical properties of fluorite crystal structured materials (CeO 2 , ThO 2 , and UO 2 ) and advanced accident tolerant fuels (U 3 Si 2 , UN, and UB 2 )

The mechanical interaction between the fuel and cladding that occurs during operation of a nuclear reactor is important to understand as it can lead to cladding failures and release of radioactive material into the coolant. Additionally, in order to develop better models of the pellet-clad mechanical interactions, the mechanical properties of the fuel at relevant operating temperatures, like the elastic moduli, are needed for current and advanced accident tolerant fuels (ATFs). In this work, elevated temperature nanoindentation and resonant ultrasound spectroscopy were used to measure the moduli and hardness of several fluorite materials (CeO 2 , ThO 2 , UO 2 ) and several ATF candidates (ATF) (U 3 Si 2 , UN, UB 2 ). In addition, a comparison of the two techniques was performed in this study to independently validate the mechanical properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Convergent use of phosphatidic acid for hepatitis C virus and SARS-CoV-2 replication organelle formation

Double membrane vesicles (DMVs) serve as replication organelles of plus-strand RNA viruses such as hepatitis C virus (HCV) and SARS-CoV-2. Viral DMVs are morphologically analogous to DMVs formed during autophagy, but lipids driving their biogenesis are largely unknown. Here we show that production of the lipid phosphatidic acid (PA) by acylglycerolphosphate acyltransferase (AGPAT) 1 and 2 in the ER is important for DMV biogenesis in viral replication and autophagy. Using DMVs in HCV-replicating cells as model, we found that AGPATs are recruited to and critically contribute to HCV and SARS-CoV-2 replication and proper DMV formation. An intracellular PA sensor accumulated at viral DMV formation sites, consistent with elevated levels of PA in fractions of purified DMVs analyzed by lipidomics. Apart from AGPATs, PA is generated by alternative pathways and their pharmacological inhibition also impaired HCV and SARS-CoV-2 replication as well as formation of autophagosome-like DMVs. These data identify PA as host cell lipid involved in proper replication organelle formation by HCV and SARS-CoV-2, two phylogenetically disparate viruses causing very different diseases, i.e. chronic liver disease and COVID-19, respectively. Host-targeting therapy aiming at PA synthesis pathways might be suitable to attenuate replication of these viruses.

60 APPLIED LIFE SCIENCES↗

Familial Associations of Prevalence and Cause-Specific Mortality for Thoracic Aortic Disease and Bicuspid Aortic Valve in a Large-Population Database

Thoracic aortic disease and bicuspid aortic valve (BAV) likely have a heritable component, but large population-based studies are lacking. This study characterizes familial associations of thoracic aortic disease and BAV, as well as cardiovascular and aortic-specific mortality, among relatives of these individuals in a large-population database. In this observational case-control study of the Utah Population Database, we identified probands with a diagnosis of BAV, thoracic aortic aneurysm, or thoracic aortic dissection. Age- and sex-matched controls (10:1 ratio) were identified for each proband. First-degree relatives, second-degree relatives, and first cousins of probands and controls were identified through linked genealogical information. Cox proportional hazard models were used to quantify the familial associations for each diagnosis. We used a competing-risk model to determine the risk of cardiovascular-specific and aortic-specific mortality for relatives of probands. The study population included 3,812,588 unique individuals. Familial hazard risk of a concordant diagnosis was elevated in the following populations compared with controls: first-degree relatives of patients with BAV (hazard ratio [HR], 6.88 [95% CI, 5.62–8.43]); first-degree relatives of patients with thoracic aortic aneurysm (HR, 5.09 [95% CI, 3.80–6.82]); and first-degree relatives of patients with thoracic aortic dissection (HR, 4.15 [95% CI, 3.25–5.31]). In addition, the risk of aortic dissection was higher in first-degree relatives of patients with BAV (HR, 3.63 [95% CI, 2.68–4.91]) and in first-degree relatives of patients with thoracic aneurysm (HR, 3.89 [95% CI, 2.93–5.18]) compared with controls. Dissection risk was highest in first-degree relatives of patients who carried a diagnosis of both BAV and aneurysm (HR, 6.13 [95% CI, 2.82–13.33]). First-degree relatives of patients with BAV, thoracic aneurysm, or aortic dissection had a higher risk of aortic-specific mortality (HR, 2.83 [95% CI, 2.44–3.29]) compared with controls. Our results indicate that BAV and thoracic aortic disease carry a significant familial association for concordant disease and aortic dissection. The pattern of familiality is consistent with a genetic cause of disease. Furthermore, we observed higher risk of aortic-specific mortality in relatives of individuals with these diagnoses. In conclusion, this study provides supportive evidence for screening in relatives of patients with BAV, thoracic aneurysm, or dissection.

60 APPLIED LIFE SCIENCES↗

Less Common Topological Phenomena in Bulk Materials

"Prediction and subsequent discovery of topological insulators is considered to be one of the main results in condensed matter physics in the last decades. Not surprisingly, it has received major attention of both researchers and funding agencies. This attention is well-deserved; yet, one cannot but note that nearly all this research revolves about essentially the same concept: electronic excitations with linear dispersion, covering, of course, such diverse and intriguing phenomena as topological insulator, bulk Dirac states (or Weyl, if not spin degenerate), Mayorana fermions. In this project, we will address, mainly, other topological phenomena, such as topologically nontrivial magnetic patterns (as, for instance, topological Hall and related phenomena). Specifically, we propose three interrelated trusts: (1) Time-reversal symmetry breaking nonrelativistic antiferromagnets, called altermagnets. These are materials that break Kramers degeneracy of electronic bands, despite having zero net magnetization by symmetry and being fully collinear, and not necessarily non-centrosymmetric. The corresponding band structure is very similar to the band structure in non-centrosymmetric spin-orbital materials, but materials that we propose to study are distinctly different, first and foremost in the sense that despite sharing many aspects of their electronic properties with the latter, they break the time-reversal symmetry without either spin-orbit coupling or lack of inversion symmetry. (2) Topologically nontrivial magnetic spirals. The PI has been engaged with the experimental group of Dr. Ghimire at GMU investigating Dirac materials with helical magnetism, based on stacked magnetic Kagome layers, with a generic formula of RMn6Sn6. In particular, Y Mn6Sn6 demonstrates a component of the Hall effect that is naturally interpreted in terms of a topological spin texture, as well as linear magnetoresistance. Our calculation identify Dirac states that are robust with respect to the spiral formation, and let us derive an advance mean-field model explaining the observed phase diagram. This model predicted four distinct phases, with very distinct properties, which have now been seen in neutron experiments. The same compound is known to demonstrate topological Hall effect in a particular magnetic phase, and only at elevated temperature. Based on our understanding of the phase diagram, we have worked out a phenomenological theory of a chiral (skyrmionic) response to an external magnetic field, similar to the nematic response to external strain in Fe-based superconductors, which is possible in a centrosymmetric lattice and without interplanar Dzyaloshinskii-Moriya interaction. This phenomenological theory agrees quantitatively with the experiment. It is in our plans to research other similar materials for this effect. (3) Search for 3D analogues of Fe-based superconductors. We want to investigate materials that can be viewed as 3D analogues of FeSe. Specifically, we want materials that are good metals and host antiferromagnetism, which can be suppressed by pressure and generate an s-wave superconductivity, as in Fe-based superconductors. We have in mind some candidates already. This work will proceed in close collaboration with the experimental group of Prof. Nirmal Ghimire in the same department, whose expertise lies in sample making, magnetometry and transport measurements of materials with complex magnetic structures."

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗