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At least 1,261 records · Page 70

How Might the May 2015 Flood in the U.S. Southern Great Plains Induced by Clustered MCSs Unfold in the Future?

Abstract The historic 22–26 May 2015 flood event in Texas and Oklahoma was caused by anomalous clustered mesoscale convective systems (MCSs) that produced record‐breaking rainfall and $3 billion of damage in the region. A month‐long regional convection‐permitting simulation is conducted to reconstruct multiple clustered MCSs that lead to this flood event. We further use the pseudo global warming approach to examine how a similar event may unfold in a warmer climate and the driving physical factors for the changes. Tracking of MCSs in observations and simulations shows that the historical simulation reproduces the salient characteristics of the observed MCSs. In a warmer climate under a high‐emission (SSP5‐8.5) scenario, the Southern Great Plains is projected to experience a near surface warming of 4–6 K, accompanied by enhanced moisture transport by the strengthened Great Plains low‐level jet. A warmer and moister lower troposphere leads to 36%–59% larger convective available potential energy, supporting wider and more intense convective updrafts and rainfall production. Consistently, MCSs have wider convective areas and stronger rainfall intensities, producing 50% larger rain volumes during the mature stage. Extreme (99.5%) MCS rainfall frequency and amount will increase by threefold. However, MCS stratiform rain area decreases as a result of elevated stratiform cloud bases that lead to stronger sublimation and evaporation of precipitation in response to warming, resulting in reduced weak‐to‐moderate surface precipitation. Results suggest that global warming greatly increases precipitation intensity of clustered MCS events under strong synoptic influence, with much higher potential to produce serious floods without additional climate adaptation.

54 ENVIRONMENTAL SCIENCES↗

Implementation of Sub‐Grid Scale Temperature Perturbations Induced by Non‐Orographic Gravity Waves in WACCM6

Abstract Atmospheric gravity waves can play a significant role on atmospheric chemistry through temperature fluctuations. A recent modeling study introduced a method to implement subgrid‐scale orographic gravity‐wave‐induced temperature perturbations in the Whole Atmosphere Community Climate Model (WACCM). The model with a wave‐induced temperature parameterization was able to reproduce for example, the influence of mountain wave events on atmospheric chemistry, as highlighted in previous literature. Here we extend the subgrid‐scale wave‐induced temperature parameterization to also include non‐orographic gravity waves arising from frontal activity and convection. We explore the impact of these waves on middle atmosphere chemistry, particularly focusing on reactions that are strongly sensitive to temperature. The non‐orographic gravity waves increase the variability of chemical reaction rates, especially in the lower mesosphere. As an example, we show that this, in turn, leads to increases in the daytime ozone variability. To demonstrate another impact, we briefly investigate the role of non‐orographic gravity waves in cirrus cloud formation in this model. Consistent with findings from the previous study focusing on orographic gravity waves, non‐orographic waves also enhance homogeneous nucleation and increase cirrus clouds. The updated method used enables the global chemistry‐climate model to account for both orographic and non‐orographic gravity‐wave‐induced subgrid‐scale dynamical perturbations in a consistent manner.

Yook, Simchan [Department of Earth Atmospheric and↗

Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

An interatomic potential for the Al–Tb alloy around the composition of Al 90 Tb 10 is developed using the deep neural network (DNN) learning method. The atomic configurations and the corresponding total potential energies and forces on each atom obtained from ab initio molecular dynamics (AIMD) simulations are collected to train a DNN model to construct the interatomic potential for the Al–Tb alloy. Here we show that the obtained DNN model can well reproduce the energies and forces calculated by AIMD simulations. Molecular dynamics (MD) simulations using the DNN interatomic potential also accurately describe the structural properties of the Al 90 Tb 10 liquid, such as partial pair correlation functions (PPCFs) and bond angle distributions, in comparison with the results from AIMD simulations. Furthermore, the developed DNN interatomic potential predicts the formation energies of the crystalline phases of the Al–Tb system with an accuracy comparable to ab initio calculations. The structure factors of the Al 90 Tb 10 metallic liquid and glass obtained by MD simulations using the developed DNN interatomic potential are also in good agreement with the experimental X-ray diffraction data. The development of short-range order (SRO) in the Al 90 Tb 10 liquid and the undercooled liquid is also analyzed and three dominant SROs, i.e., Al-centered distorted icosahedron (DISICO) and Tb-centered ‘3661’ and ‘15551’ clusters, respectively, are identified.

36 MATERIALS SCIENCE↗

Reproducible growth of Brachypodium in EcoFAB 2.0 reveals that nitrogen form and starvation modulate root exudation

Understanding plant-microbe interactions requires examination of root exudation under nutrient stress using standardized and reproducible experimental systems. We grew Brachypodium distachyon hydroponically in fabricated ecosystem devices (EcoFAB 2.0) under three inorganic nitrogen forms (nitrate, ammonium, and ammonium nitrate), followed by nitrogen starvation. Analyses of exudates with liquid chromatography–tandem mass spectrometry, biomass, medium pH, and nitrogen uptake showed EcoFAB 2.0’s low intratreatment data variability. Furthermore, the three inorganic nitrogen forms caused differential exudation, generalized by abundant amino acids–peptides and alkaloids. Comparatively, nitrogen deficiency decreased nitrogen-containing compounds but increased shikimates-phenylpropanoids. Subsequent bioassays with two shikimates-phenylpropanoids (shikimic and p-coumaric acids) on soil bacteria or Brachypodium seedlings revealed their distinct capacity to regulate both bacterial and plant growth. Our results suggest that (i) Brachypodium alters exudation in response to nitrogen status, which can affect rhizobacterial growth, and (ii) EcoFAB 2.0 is a valuable standardized plant research tool.

59 BASIC BIOLOGICAL SCIENCES↗

The potential role of organics in new particle formation and initial growth in the remote tropical upper troposphere

Abstract. Global observations and model studies indicate that new particle formation (NPF) in the upper troposphere (UT) and subsequent particles supply 40 %–60 % of cloud condensation nuclei (CCN) in the lower troposphere, thus affecting the Earth's radiative budget. There are several plausible nucleation mechanisms and precursor species in this atmospheric region, which, in the absence of observational constraints, lead to uncertainties in modeled aerosols. In particular, the type of nucleation mechanism and concentrations of nucleation precursors, in part, determine the spatial distribution of new particles and resulting spatial distribution of CCN from this source. Although substantial advances in understanding NPF have been made in recent years, NPF processes in the UT in pristine marine regions are still poorly understood and are inadequately represented in global models. Here, we evaluate commonly used and state-of-the-art NPF schemes in a Lagrangian box model to assess which schemes and precursor concentrations best reproduce detailed in situ observations. Using measurements of aerosol size distributions (0.003 < Dp < 4.8 µm) in the remote marine troposphere between ∼0.18 and 13 km altitude obtained during the NASA Atmospheric Tomography (ATom) mission, we show that high concentrations of newly formed particles in the tropical UT over both the Atlantic and Pacific oceans are associated with outflow regions of deep convective clouds. We focus analysis on observations over the remote Pacific Ocean, which is a region less perturbed by continental emissions than the Atlantic. Comparing aerosol size distribution measurements over the remote Pacific with box model simulations for 32 cases shows that none of the NPF schemes most commonly used in global models, including binary nucleation of sulfuric acid and water (neutral and ion-assisted) and ternary involving sulfuric acid, water, and ammonia, are consistent with observations, regardless of precursor concentrations. Through sensitivity studies, we find that the nucleation scheme among those tested that is able to explain most consistently (21 of 32 cases) the observed size distributions is that of Riccobono et al. (2014), which involves both organic species and sulfuric acid. The method of Dunne et al. (2016), involving charged sulfuric acid–water–ammonia nucleation, when coupled with organic growth of the nucleated particles, was most consistent with the observations for 5 of 32 cases. Similarly, the neutral sulfuric acid–water–ammonia method of Napari (2002), when scaled with a tuning factor and with organic growth added, was most consistent for 6 of 32 cases. We find that to best reproduce both nucleation and growth rates, the mixing ratios of gas-phase organic precursors generally need to be at least twice that of SO2, a proxy for dimethyl sulfide (DMS). Unfortunately, we have no information on the nature of oxidized organic species that participated in NPF in this region. Global models rarely include organic-driven nucleation and growth pathways in UT conditions where globally significant NPF takes place, which may result in poor estimates of NPF and CCN abundance and contribute to uncertainties in aerosol–cloud–radiation effects. Furthermore, our results indicate that the organic aerosol precursor vapors may be important in the tropical UT above marine regions, a finding that should guide future observational efforts.

54 ENVIRONMENTAL SCIENCES↗

Dispersity-Driven Stabilization of Coexisting Morphologies in Asymmetric Diblock Copolymer Thin Films

Despite decades of research, characterization of the effects of polymer chain dispersity on the structural properties of block copolymer thin films remains challenging. Here we present an integrated experimental and modeling approach to characterize the morphology of thin films containing asymmetric diblock copolymers. Specifically, we used synergistic neutron reflectivity (NR) and self-consistent field theory (SCFT)-based modeling to realize unexpected morphology of thin films containing asymmetric copolymers. Using NR, a highly stable and reproducible mixed phase of coexisting cylinders and lamellar domains was discovered in asymmetric poly(deuterated-styrene-b-n butyl methacrylate) (dPS-PBMA) copolymer thin films containing 34% volume fraction of dPS. SCFT reveals how to obtain such a thermodynamically stable morphology in the presence of disperse majority block and asymmetric interactions of polymer species with surfaces. Stabilization of the coexisting domains is a consequence of the depth segregation based on chain-length distribution. The asymmetric chains microphase-separate into cylindrical domains close to the substrate and near-symmetric chains form lamellar domains at the air interface. In the absence of dispersity, the coexistence of cylindrical and lamellar domains is thermodynamically unstable because of the absence of depth segregation. Overall, such an effect of dispersity on diblock copolymer thin-film morphology reveals a unique and powerful strategy to create coexisting nanoscale domains and tailor properties of thin films.

36 MATERIALS SCIENCE↗

Simulating Observations of Southern Ocean Clouds and Implications for Climate

Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds.

54 ENVIRONMENTAL SCIENCES↗

Thermal energy mitigation and toroidal peaking effects in JET disruptions

Previous investigations on JET suggest half or less of plasma stored thermal energy W th is radiated (f rad,th ≲ 0.5) using either massive gas injection (MGI) or shattered pellet injection (SPI) disruption mitigation. We investigate whether the apparent incomplete f rad,th is explained by radiation peaking near the injection plume. High toroidal peaking throughout the pre-thermal quench is found in argon–deuterium MGI on JET, with typically >3× higher radiation near the injector than toroidally distant. Previously unexplained toroidal bolometry measurements in neon–deuterium SPI are reproduced with similar peaking using the Emis3D radiation analysis code. These observations align with results from Alcator C-Mod and KSTAR. This peaking is not captured by previous JET studies that found poor thermal mitigation. Two sets of neon–deuterium SPI and two sets of argon–deuterium MGI are analyzed using Emis3D. In SPI, f rad,th rises from no-plume estimates of 0.31 and 0.66 to lower bounds of 0.84 and 0.92, respectively, and f rad,th ∼ 1 is possible. In MGI, the toroidal spread of the peaking feature is poorly constrained. f rad,th up to 0.85 and 0.65 are possible using the largest possible spread, increasing from 0.42 and 0.28, although f rad,th ∼ 1 does not appear to be reached. Revised mitigation estimates on JET suggest a lower melt risk to the divertor in mitigated disruptions on ITER and SPARC than previously thought. However, peaking near injectors could increase flash melting risk on nearby plasma facing components.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Are 100 Ensemble Members Enough to Capture the Remote Atmospheric Response to +2°C Arctic Sea Ice Loss?

This study presents results from the Polar Amplification Multimodel Intercomparison Project (PAMIP) single-year time-slice experiments that aim to isolate the atmospheric response to Arctic sea ice loss at global warming levels of +2°C. Using two general circulation models (GCMs), the ensemble size is increased up to 300 ensemble members, beyond the recommended 100 members. After partitioning the response in groups of 100 ensemble members, the reproducibility of the results is evaluated, with a focus on the response of the midlatitude jet streams in the North Atlantic and North Pacific. Both atmosphere-only and coupled ocean–atmosphere PAMIP experiments are analyzed. Substantial differences in the midlatitude response are found among the different experiment subsets, suggesting that 100-member ensembles are still significantly influenced by internal variability, which can mislead conclusions. Despite an overall stronger response, the coupled ocean–atmosphere runs exhibit greater spread due to additional ENSO-related internal variability when the ocean is interactive. The lack of consistency in the response is true for anomalies that are statistically significant according to Student’s t and false discovery rate tests. This is problematic for the multimodel assessment of the response, as some of the spread may be attributed to different model sensitivities whereas it is due to internal variability. Here, we propose a method to overcome this consistency issue that allows for more robust conclusions when only 100 ensemble members are used.

58 GEOSCIENCES↗

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗

Findings of the African Combustion Aerosol Collaborative Intercomparison Analysis (ACACIA) Pilot Project to Understand the Optical Properties of Biomass Burning Smoke

Africa is a critical source of biomass burning (BB) aerosols, and its importance is increasing. The African Combustion Aerosol Collaborative Intercomparison Analysis (ACACIA) Pilot Project set to optically characterize BB aerosol generated from sub-Saharan African fuels. We used a photoacoustic spectrometer as a reference instrument to determine the multiple-scattering correction factor C λ for an AE33 aethalometer at three wavelengths, which produced weighted mean values of C 370 =3.69, C 470 =5.65, and C 520 =6.39. C λ increased with wavelength and C 370 was statistically independent of the others, suggesting a single C λ is insufficient, especially in BB scenarios. While a dependence of C λ on burning state was not found, C λ was shown to strongly relate to particle single scattering albedo (SSA, ω). When Cλ was plotted against SSA, values slowly rose at low SSA values, followed by a sharp rise around an SSA of ∼ 0.9; indicating a larger correction needed for less absorbing aerosol. A number of functions operating on either SSA or C λ were explored and the best function was -C λ /(1-C λ )=Aω+B. This is an important parametrization of C λ specifically geared towards BB aerosol from African fuels under different aging states, and is of particular importance for future field work in that continent. An Ångström matrix plot shows that African BB aerosol can have values more akin to dust, which demonstrates that these fuels are distinct in their wavelength dependence from more typical BB aerosol. Lastly, we examined the mass extinction and absorbance cross sections for BB aerosol generated for the same fuels with two different tube furnace setups. Not only is this combustion method flexible, it was found to be reproducible between labs.

47 OTHER INSTRUMENTATION↗

Toward a Unified Kinetic Model of Nitrogenase Catalysis

The microbial enzyme nitrogenase catalyzes the MgATP-dependent reduction of N 2 to 2NH 3 , a transformation central to the global nitrogen cycle. While the canonical Thorneley−Lowe (TL) kinetic model has long served as a mechanistic framework, it does not incorporate several recent insights. Here, we present an updated kinetic model for Monitrogenase that incorporates these new findings. A significant insight is that electron transfer (ET) from the reduced Fe protein to the FeMo-cofactor is gated by MgATP-dependent conformational transitions and can be described as a probabilistic event that is dependent on the ligand bound to the active-site metallocofactor. The updated kinetic model quantitatively reproduces steady-state product formation rates across a broad range of experimental conditions, yielding revised estimates for key rate constants. It is demonstrated that under N 2 turnover, the probability of productive ET to the active site decreases by ∼60%, resulting in a significant fraction of Fe protein cycles that are unproductive for electron delivery. This mechanistic feature explains the observed rate limitation in N 2 reduction and implies a revised minimum energetic cost of approximately 25 MgATP per N 2 reduced. Integrating these new features into the revised kinetic model provides a more complete and usable foundation for understanding nitrogenase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure and properties of densified silica glass: characterizing the order within disorder

The broken symmetry in the atomic-scale ordering of glassy versus crystalline solids leads to a daunting challenge to provide suitable metrics for describing the order within disorder, especially on length scales beyond the nearest neighbor that are characterized by rich structural complexity. Here, we address this challenge for silica, a canonical network-forming glass, by using hot versus cold compression to (i) systematically increase the structural ordering after densification and (ii) prepare two glasses with the same high-density but contrasting structures. The structure was measured by high-energy X-ray and neutron diffraction, and atomistic models were generated that reproduce the experimental results. The vibrational and thermodynamic properties of the glasses were probed by using inelastic neutron scattering and calorimetry, respectively. Traditional measures of amorphous structures show relatively subtle changes upon compacting the glass. The method of persistent homology identifies, however, distinct features in the network topology that change as the initially open structure of the glass is collapsed. The results for the same high-density glasses show that the nature of structural disorder does impact the heat capacity and boson peak in the low-frequency dynamical spectra. Densification is discussed in terms of the loss of locally favored tetrahedral structures comprising oxygen-decorated SiSi 4<:sub> tetrahedra.

36 MATERIALS SCIENCE↗

Microgravity effects on nonequilibrium melt processing of neodymium titanate: thermophysical properties, atomic structure, glass formation and crystallization

The relationships between materials processing and structure can vary between terrestrial and reduced gravity environments. As one case study, we compare the nonequilibrium melt processing of a rare-earth titanate, nominally 83TiO 2 -17Nd 2 O 3 , and the structure of its glassy and crystalline products. Density and thermal expansion for the liquid, supercooled liquid, and glass are measured over 300–1850 °C using the Electrostatic Levitation Furnace (ELF) in microgravity, and two replicate density measurements were reproducible to within 0.4%. Cooling rates in ELF are 40–110 °C s -1 lower than those in a terrestrial aerodynamic levitator due to the absence of forced convection. X-ray/neutron total scattering and Raman spectroscopy indicate that glasses processed on Earth and in microgravity exhibit similar atomic structures, with only subtle differences that are consistent with compositional variations of ~2 mol. % Nd 2 O 3 . The glass atomic network contains a mixture of corner- and edge-sharing Ti-O polyhedra, and the fraction of edge-sharing arrangements decreases with increasing Nd 2 O 3 content. X-ray tomography and electron microscopy of crystalline products reveal substantial differences in microstructure, grain size, and crystalline phases, which arise from differences in the melt processes.

36 MATERIALS SCIENCE↗

Evidence of ordering in Cu-Ni alloys from experimental electronic entropy measurements

Phase diagrams exhibiting extended solid-solution and lenslike melting are often reproduced using ideal solutions, where ideal mixing considers a fully random configurational entropy of mixing. In the field of irreversible thermodynamics, experimental measurements of the composition variation of high-temperature electronic transport and molten-state properties suggest, however, a strong role for short-range atomic ordering in these systems. Herein, measurements of the thermopower and resistivity are reported for Cu-Ni solid solutions as a function of temperature and composition. The electronic transport properties were interpreted with an irreversible thermodynamic framework, revealing a large electronic contribution to the entropy of mixing. By considering a cluster model for the configurational entropy that uses the electronic contribution to inform the existence of ordered associates, we rationalize such a contribution of the electronic entropy with the ideal entropy of mixing commonly used to model such systems. In conclusion, these results suggest that the short-range order of the atoms plays a significant role in both solid and liquid states, even when there are no dominant intermetallic compounds in these alloys.

36 MATERIALS SCIENCE↗

Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region

Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. Here, we conduct an intercomparison between statistically and dynamically downscaled GCMs simulations using the hybrid delta (HD) and the Weather Research and Forecast (WRF) Model, respectively, over the Midwest and Great Lakes region to 1) validate their performance in reproducing extreme daily precipitation (P) and daily maximum temperature (T max ) for summer and winter and 2) evaluate projections of extremes in the future. Our results show the HD statistical downscaling approach, which includes large-scale bias correction of GCM inputs, can reproduce observed extreme P and T max reasonably well for both summer and winter. However, raw historical WRF simulations show significant bias in both extreme P and T max for both seasons. Interestingly, the convection-permitting WRF simulation at 4-km grid spacing does not produce better results for seasonal extremes than the WRF simulation at 12 km using a parameterized convection scheme. Despite a broad similarity for winter extreme P projections, the projected changes in the future summer storms are quite different between downscaling methods; WRF simulations show substantial increases in summer extreme precipitation, while the changes projected by the HD approach exhibit moderate decreases overall. The WRF simulations at 4 km also show a pronounced decoupling effect between seasonal totals and extreme daily P for summer, which suggests that there could be more intense summer extremes at two different time scales, with more severe individual convective storms combined with longer summer droughts at the end of the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗

Many-Body Effects in FeN4 Center Embedded in Graphene

We introduce a computational approach to study porphyrin-like transition metal complexes, bridging density functional theory and exact many-body techniques, such as the density matrix renormalization group (DMRG). We first derive a multi-orbital Anderson impurity Hamiltonian starting from first principles considerations that qualitatively reproduce generalized gradient approximation (GGA)+U results when ignoring inter-orbital Coulomb repulsion U ′ and Hund exchange J. An exact canonical transformation is used to reduce the dimensionality of the problem and make it amenable to DMRG calculations, including all many-body terms (both intra- and inter-orbital), which are treated in a numerically exact way. We apply this technique to FeN 4 centers in graphene and show that the inclusion of these terms has dramatic effects: as the iron orbitals become single occupied due to the Coulomb repulsion, the inter-orbital interaction further reduces the occupation, yielding a non-monotonic behavior of the magnetic moment as a function of the interactions, with maximum polarization only in a small window at intermediate values of the parameters. Furthermore, U ′ changes the relative position of the peaks in the density of states, particularly on the iron d z 2 orbital, which is expected to affect the binding of ligands greatly.

36 MATERIALS SCIENCE↗

Calibration and Validation of a Mechanistic COVID-19 Model for Translational Quantitative Systems Pharmacology – A Proof-of-Concept Model Development for Remdesivir

With the ongoing global pandemic of coronavirus disease 2019 (COVID-19), there is an urgent need to accelerate the traditional drug development process. Many studies identified potential COVID-19 therapies based on promising nonclinical data. However, the poor translatability from nonclinical to clinical settings has led to failures of many of these drug candidates in the clinical phase. In this study, we propose a mechanism-based, quantitative framework to translate nonclinical findings to clinical outcome. Adopting a modularized approach, this framework includes an in silico disease model for COVID-19 (virus infection and human immune responses) and a pharmacological component for COVID-19 therapies. Here, the disease model was able to reproduce important longitudinal clinical data for patients with mild and severe COVID-19, including viral titer, key immunological cytokines, antibody responses, and time courses of lymphopenia. Using remdesivir as a proof-of-concept example of model development for the pharmacological component, we developed a pharmacological model that describes the conversion of intravenously administered remdesivir as a prodrug to its active metabolite nucleoside triphosphate through intracellular metabolism and connected it to the COVID-19 disease model. After being calibrated with the placebo arm data, our model was independently and quantitatively able to predict the primary endpoint (time to recovery) of the remdesivir clinical study, Adaptive Covid-19 Clinical Trial (ACTT). Our work demonstrates the possibility of quantitatively predicting clinical outcome based on nonclinical data and mechanistic understanding of the disease and provides a modularized framework to aid in candidate drug selection and clinical trial design for COVID-19 therapeutics.

60 APPLIED LIFE SCIENCES↗