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DOE OSTI2024

Assessment of Accelerated Stress Testing Data for Silicon Photovoltaics Using Tensor Decomposition Methods

In this work, we examine the use of high-order tensor decompositions to analyze degradation pathways emerging from accelerated stress testing of silicon photovoltaic (PV) modules. Matrix-based decompositions are powerful tools for studying two-dimensional data arrays and form the foundation of a host of classical data analysis techniques. Tensors are high-order extrapolations of matrices that are able to account for more parameter dimensions, and a variety of tensor decomposition methods have been developed that similarly seek to extend insights from matrix decompositions to higher dimensions. Applying and interpreting tensor decomposition methods to sequences of PV module image data, we seek to uncover and isolate different degradation modes occurring from accelerated stress testing procedures. Further, we consider the contributions of different modes to PV module performance degradations.

data analysis↗

DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗

DOE OSTI2024

Discovering Innovations in Stress Tolerance through Comparative Gene Regulatory Network Analysis and Cell-Type Specific Expression Maps (Final Technical Report with Cover Page)

Through this grant, we developed a comparative framework to elucidate the mechanisms behind variations in environmental stress responses among a diverse group of species within the Brassicaceae family. Our focus was on the differences in physiological and transcriptomic responses to abscisic acid (ABA), a hormone associated with water stress. We examined the differential growth responses of four Brassicaceae species, finding that most exhibited reduced root growth correlated with smaller meristem size. In contrast, Schrenkiella parvula showed accelerated growth due to increased root cell elongation. We employed RNA sequencing to analyze the transcriptional responses to ABA across these species, and innovative bioinformatics techniques were used to pinpoint biological pathways with significant divergence. Additionally, we utilized DAP-seq to map the gene regulatory networks associated with ABAresponsive transcription factors, revealing that variations in the regulation of growth hormone biosynthesis play a critical role in the distinct ABA effects on root growth among the species. This research sets a new standard for comparative physiology by integrating comparative genomics and transcriptomics to uncover pathway divergences.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Exploratory Studies of Mechanical Properties, Residual Stress, and Grain Evolution at the Local Regions near Pores in Additively Manufactured Metals

Directed energy deposition (DED) is gaining widespread acceptance in various industrial applications since its unique manufacturing features allow the DED to print metallic parts with very complex geometries. However, DED inevitably generates a lot of internal pores which can limit the widespread applications of the DED technique. The current studies on DED porosity are mostly focused on analyzing pores’ bulk-scale influences on mechanical properties and performances. Since DED pores have a micro-scale existence, with dimensions ranging from a few microns to several hundred microns, it is fundamental to explore the pores’ influences on the micro-scale, including local mechanical properties, residual stress, and grains near pores. However, this important research direction has been neglected. The objective of this work is to fill the above gap in DED porosity research and acquire a fundamental understanding of the role of porosity on a microscopic scale. The authors used nanoindentation approaches to investigate internal pores’ effects on mechanical properties and residual stress in local regions surrounding the pores. In addition, the grains near pores were observed through EBSD, and simulated with the Kinetic Monte Carlo model. The research findings can be provided for DED researchers and industrial practitioners as technical guidance. Most importantly, the research results can work as a good reference for tracing the source of bulk-scale mechanical performances and properties of DED parts with internal pores.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Electrical Resistivity Tomography based monitoring of stress perturbations to optimize placement of high-precision strain meters

The Center for Understanding Subsurface Signals and Permeability is a new U.S. Department of Energy Earthshot Center focused on understanding and predicting the long-term evolution of permeability in enhanced geothermal systems. The center will use a highly instrumented testbed within the Sanford Underground Research Facility to conduct field scale experiments that elucidate and test capabilities to simulate geochemical-geomechanical interactions and permeability evolution. Here we demonstrate initial developments using previously collected electrical resistivity tomography (ERT) monitoring data with high-performance multi-physics modelling advancements to inform the optimal location of two new monitoring boreholes. Specifically, ERT monitoring data collected during shear stimulation testing shows marked responses to changes in stress during borehole pressurization. We demonstrate how the same response is being simulated, ultimately to train a machine-learning algorithm to estimate rock properties and enable enhanced prediction of stress and strain responses anticipated during future testing campaigns.

Stress, EGS, CUSSP, 3D Electrical Imaging↗

DOE OSTI2025

IM3 Data Center Driven Grid Stress Dataset for the U.S. Western Interconnection

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from an open-source grid operations modeling framework - GO), for the Integrated Multisector, Multiscale Modeling (IM3) project, under varying levels of data center demand growth between 2025 and 2035 in the U.S. Western Interconnection. The scenarios and sensitivity experiments are combinations of different data center demand growth rates and energy, weather, population and economic pathways. Data center demand growth projections were sourced from the Electric Power Research Institute (EPRI). The data center demand growth projection names are: Low (3.71% annual data center demand growth) Moderate (5% annual data center demand growth) High (10% annual data center demand growth) Higher (15% annual data center demand growth) Energy, weather, population and economic pathways are informed by two Shared Socioeconomic Pathways (SSP3 and SSP5) and two Representative Concentration Pathways (RCP4.5 and RCP8.5) following the hotter general circulation model (GCM) forcing group from a set of perturbed thermodynamics simulations. The resulting pathway names are: rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 The main scenarios and sensitivity experiments are detailed below. Reference scenario: The projected grid stress and reliability results for the U.S. Western Interconnection from a previous study. This scenario does not consider data center demand growth explicitly. Data center scenario: Building on the reference scenario, this scenario considers various data center growth rates and how they impact the U.S. Western Interconnection. Data center loads are modeled as flat 8760-hr profiles. This scenario does not consider new generation and transmission capacities specifically designed to meet the new data center demands. The related folder is named "flat". Delayed generator retirements sensitivity experiment: Building on the data center scenario, this experiment explores the impact of different levels of natural gas and nuclear generator retirement delays. The resulting scenario names are: (1) postponing 100% nuclear retirements; (2) postponing 100% nuclear and 25% natural gas retirements; (3) postponing only 50% natural gas retirements; (4) postponing 100% nuclear and 50% natural gas retirements; (5) postponing 100% nuclear and 75% natural gas retirements; and (6) postponing 100% nuclear and 100% natural gas retirements. The related folder names are: no_gen_retire_0_gas, no_gen_retire_25_gas, no_gen_retire_50_gas, no_gen_retire_50_gas_only, no_gen_retire_75_gas, and no_gen_retire_100_gas. Demand response through curtailment sensitivity experiment: Building on the data center scenario, this experiment explores the impact of different participation and compensation levels of data center demand response. The resulting scenario names are: (1) 5% demand available for curtailment with 750 $/MWh compensation; (2) 5% demand available for curtailment with 500 $/MWh compensation; (3) 5% demand available for curtailment with 250 $/MWh compensation; (4) 15% demand available for curtailment with 750 $/MWh compensation; (5) 15% demand available for curtailment with 500 $/MWh compensation; and (6) 15% demand available for curtailment with 250 $/MWh compensation. The related folder names are: dr_cost_250_drup_0_drdown_5, dr_cost_250_drup_0_drdown_15, dr_cost_500_drup_0_drdown_5, dr_cost_500_drup_0_drdown_15, dr_cost_750_drup_0_drdown_5, and dr_cost_750_drup_0_drdown_15. Combination of delayed generator retirements and demand response through curtailment sensitivity experiment: The impact of combining postponing 100% nuclear and 25% natural gas retirements with 5% demand available for curtailment with 750 $/MWh compensation is simulated. The related folder is named "dr_cost_750_drup_0_drdown_5_nuc_100_gas_25". Please refer to the README file for a detailed description of the dataset including individual files and references.

Artificial Intelligence↗

DOE OSTI2025

Zymomonas mobilis oxidative stress transcriptomics

Zymomonas mobilis is an important bioenergy organism that has potential to produce biofuels, including ethanol, in high volumes. Here we examined the response of Zymomonas mobilis to various oxidative stresses using genome-scale transcriptomics data. We first examined the transcrpit abundance in WT aerobic growth compared to aerobic grown in paraquat, which forms superoxide. Under anaerobic growth conditions we compared WT Zymomonas mobilis with strains grown in media lacking iron as well as strains lacking iron that were treated with the iron chelator DIP before collection. Finally we examined transcript abundance in cells lacking ZMO_0422 (Rrf2 family transcription factor homolog) and ZMO_1411 (Fur homolog) grown under anaerobic conditions. Overall design: Transcriptomic analysis of WT, a deletion of ZMO_0422, and a deletion of ZMO_1411 in Zymomonas mobilis ZM4 under aerobic and anaerobic growth conditions along with various oxidative stresses: Paraquate addition, No Iron, and hydrogen peroxide addition.

aerobic↗

DOE OSTI2024

Assessment of Accelerated Stress Testing Data for Silicon Photovoltaics Using Tensor Decomposition Methods

The photovoltaic (PV) industry is simultaneously targeting long warranties and new materials/designs for high-energy-yield modules, requiring an advanced methodology to forecast long-term durability of products with un-proven materials combinations. Extended, sequential, and combined stress testing methods are gaining popularity for assessing durability of PV modules/materials beyond the early-stage mortalities. Importantly, multiple degradation mechanisms can proceed simultaneously, and their separate contributions to the overall power loss should ideally be quantified. This work examines the use of data-driven tools towards developing a strategy for faster learning cycles in accelerated stress testing.

accelerated stress testing↗

DOE OSTI2025

Increased inflammation as well as decreased endoplasmic reticulum stress and translation differentiate pancreatic islets from donors with pre-symptomatic stage 1 type 1 diabetes and non-diabetic donors

Aims/hypothesis Progression to type 1 diabetes is associated with genetic factors, the presence of autoantibodies and a decline in beta cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting beta cells prior to the onset of type 1 diabetes. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet-autoantibody-positive organ donors with pre-symptomatic stage 1 type 1 diabetes (HbA1c ≤42 mmol/mol [6.0%]). We aimed to identify pathways in islets that are indicative of beta cell dysfunction. Methods Multiple islet sections were collected through laser microdissection of frozen pancreatic tissues from organ donors positive for single or multiple islet autoantibodies (AAb + , n=5), and age (±2 years)- and sex-matched non-diabetic (ND) control donors (n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to MS-based proteomics and analysed with label-free quantification followed by pathway and functional annotations. Results Analyses resulted in ~4500 proteins identified with low false discovery rate (<1%), with 2165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on only the donors with stage 1 type 1 diabetes who were positive for multiple autoantibodies (mAAb + , n=3) and genetic risk compared with their matched ND controls (n=3) for the final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different (unadjusted p<0.025, q<0.15) for mAAb + vs ND donor islets. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including a proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single-cell RNA-seq datasets from AAb + individuals. Conclusions/interpretation In situ human islet proteome alterations in stage 1 type 1 diabetes centred around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation/HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on beta cell changes during type 1 diabetes progression and pathogenesis. Data availability The LC-MS raw datasets that support the findings of this study have been deposited in the online repository: MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) with accession no. MSV000090212.

Autoantibody-positive↗

DOE OSTI2024

Prediction of residual stresses in additively manufactured parts using lumped capacitance and classical lamination theory

Several industries are interested in Laser Powder Bed Fusion (L-PBF) Additively Manufactured (AM) metal parts because their designs can be made arbitrarily complex while retaining bulk-type material properties. However, the residual stresses (RS) and distortions caused by the heat gradients inherent to L-PBF processes are detrimental to the structural integrity of the parts and must be taken into consideration during the part design cycle. Predicting the state of stresses in as-built 3D printed parts is a difficult problem that is typically approached with the use of transient thermomechanical Finite Element Models (FEMs). However, the nonlinearities associated with AM processes are difficult to capture in these FEMs without increasing the computational cost of the simulation, limiting their ability to be incorporated into practical design cycles. This work presents a novel analytical framework that combines lumped capacitance nonlinear heat transfer with time dependent classical lamination theory to efficiently and accurately predict RS in as-built L-PBF parts without the need of FEMs. The simulation was compared to Neutron Diffraction (ND) residual strain measurements taken at Oak Ridge National Laboratories (ORNL) as well as Synchrotron X-ray Diffraction (XRD) strain data published by the National Institute of Standards and Technology (NIST). The simulation predictions and the experimental data showed excellent agreement for the in-plane strain directions, and general agreement for the out of plane strain component, highlighting an area where further development can be implemented.

42 ENGINEERING↗

DOE OSTI2024

Impacts of irregularly-distributed acidified brine flow on geo-chemo-mechanical alteration in an artificial shale fracture under differential stress

The efficacy of geological carbon sequestration is reliant on the integrity of the caprock and its resistance to physical and chemical alteration. Caprocks with high abundance of reactive carbonates like calcite are susceptible to acid-promoted dissolution and can result in structural weakening. This work investigates the effect of acidified brine flow through an artificially fractured, high-carbonate (30 % by XRD) shale under differential compressive stress. Cylindrical samples were cut in half vertically and milled to create an artificial fracture with interlocking asperities and open channels. Samples were sheared with a single applied stress in a custom flow cell housed within an industrial CT scanner. Further, either acidic (pH 4) or reservoir-simulated (pH 9.5) brine was flowed through the artificial fracture for 7–8 days under reservoir pressure and room temperature. Model simulations indicate flow mainly occurred in open channels, with limited flow between overlapping asperities. Analysis of fracture surfaces by optical and scanning electron microscopy show increased surface alteration and roughness after exposure to pH 4 versus pH 9.5 brine indicating mineral dissolution/loss, and this effect is greater in areas that receive the highest brine flows. Similarly, surface analysis by scratch testing shows fracture toughness decreases more after exposure to acidic versus reservoir-simulated brine, with the greatest alteration in areas of highest acidic brine flows. Despite weakening, no shear slip occurred. Overall, the results indicate that acidified brine can result in significant physical and geomechanical alteration of irregular fracture surfaces in shale caprock, with greatest effects in preferential flow regions.

58 GEOSCIENCES↗

DOE OSTI2024

Water acidification aggravates lithium-induced toxicity represented by energy supply, oxidative stress, and cell fate in Daphnia magna neonates

Lithium is extensively utilized in industrial energy production, particularly in lithium-ion batteries, and in pharmaceuticals for the treating clinical mood disorders. Consequently, lithium is frequently detected in various environmental matrices. It has been reported to cause a range of toxic effects on aquatic organisms including oxidative stress, neurological disorders, and reproductive suppression. Water acidification is a global issue with numerous negative impacts on aquatic organisms. It can alter the physio-chemical properties and bioavailability of metal ions. The acidic leaching process during lithium battery treatment and global water acidification both suggest that lithium contamination often occurs in acidic environments. In the present study, Daphnia magna neonates were exposed to four treatments (control, lithium alone, low pH, and combined) to investigate whether an acidic environment exacerbates the toxic effects of lithium on aquatic organisms and to explore potential toxic action mechanisms. The results indicated that low pH posed a significant threat to the growth and reproduction of D. magna. When exposed to both lithium and low pH, there was increased lithium accumulation and an energy trade-off response, leading to increased energy allocation to reproduction and reduced energy for growth. Lithium exposure stimulated D. magna activity, while low pH inhibited it, suggesting that an imbalance in energy consumption and supply. Combined exposure to lithium and low pH resulted in severe oxidative stress due to mitochondrial dysfunction, under-utilization of energy substances, and increased ionic homeostasis disturbances. Consequently, the exposed organism altered apoptosis and autophagy processes to maintain homeostasis. In conclusion, the present study demonstrated that lithium and water acidification posed a population-level threat to D. magna, and their combined exposure significantly largely exacerbated the toxic effects.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2025

Photo-oxidation of semicrystalline polymers: Effect of stress triaxiality on ductility

The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60∘, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned ex situ using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Reparameterizing a Lipid Force Field Using Small-Angle X-ray Scattering to Improve Predictions of Multicomponent Membranes under Organic Solvent Stress

Understanding and predicting properties of lipid-bilayer membranes are essential to elucidating organismal physiology and pathophysiology. Therefore, substantial efforts have been undertaken to derive accurate molecular-mechanics force fields (FF) to allow simulation of their properties; however, much of these past efforts focused on tuning force fields to accurately reproduce the properties of model single-component membranes and not multicomponent or stressed membranes. Here, we tuned the CHARMM36 FF for a simple 2-component model of a Gram-positive bacterium. This updated force field is parametrized against a single condensed-phase property, the small-angle X-ray scattering (SAXS) intensities of the 2-component lipid system, using a version of ForceBalance implemented previously (named ForceBalance-SAS) with SAXS and small-angle neutron scattering (SANS) intensities as optimization targets. After tuning, we observe improved agreement with the experimental SAXS of the membrane under 1-butanol and tetrahydrofuran solvent stresses, with a factor of 10.0 and 7.5 reduction, respectively, in χ 2 , the measure of the discrepancy between experimental and computed SAXS intensities. Furthermore, this reparametrized force field yielded improved agreement between experimental and simulated membrane thicknesses for the pure lipid systems. However, we note limitations in transferability and diagnose the source of such limitations, particularly the need for SANS in addition to SAXS.

Demerdash, Omar N. A. [Oak Ridge National Laborato↗

DOE OSTI2025

Unlocking the Dynamics of Ion Migration and Voltage Bias Stress Effects through Crystallite Engineering in Metal Halide Perovskites

Understanding the interplay between crystal engineering and the coupled electronic-ionic charge transport properties of metal halide perovskites remains a critical issue in the field. In this work, we developed an experimental approach to tune the crystallite orientation of methylammonium lead iodide (CH 3 NH 3 PbI 3 ) while maintaining their overall crystal structure. This approach allows us to selectively manipulate crystallite orientations to control out-ofplane ion migration and mitigate voltage bias stress effects in CH 3 NH 3 PbI 3 thin films. By employing advanced diffraction and spectroscopic techniques, we achieved a comprehensive characterization of the anisotropic crystallite properties in CH 3 NH 3 PbI 3 thin films with distinct preferred orientations. Our findings reveal that specific crystallite orientations, particularly those that limit halide ion migration pathways along the (200) crystallographic plane, significantly suppress out-of-plane ion migration. This suppression reduces hysteresis and alleviates voltage bias stress effects in CH 3 NH 3 PbI 3 solar cells, ultimately enhancing device stability and performance. These insights not only deepen our understanding of the relationship between crystallite orientation and device functionality but also highlight a promising strategy for regulating ion migration in MHP-based devices. This approach holds significant potential for advancing the stability and efficiency of perovskite solar cells and extending its applicability to other optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A stress-induced source of phonon bursts and quasiparticle poisoning

Abstract The performance of superconducting qubits is degraded by a poorly characterized set of energy sources breaking the Cooper pairs responsible for superconductivity, creating a condition often called “quasiparticle poisoning”. Both superconducting qubits and low threshold dark matter calorimeters have observed excess bursts of quasiparticles or phonons that decrease in rate with time. Here, we show that a silicon crystal glued to its holder exhibits a rate of low-energy phonon events that is more than two orders of magnitude larger than in a functionally identical crystal suspended from its holder in a low-stress state. The excess phonon event rate in the glued crystal decreases with time since cooldown, consistent with a source of phonon bursts which contributes to quasiparticle poisoning in quantum circuits and the low-energy events observed in cryogenic calorimeters. We argue that relaxation of thermally induced stress between the glue and crystal is the source of these events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Eco-evolutionary strategies for relieving carbon limitation under salt stress differ across microbial clades

With the continuous expansion of saline soils under climate change, understanding the eco-evolutionary tradeoff between the microbial mitigation of carbon limitation and the maintenance of functional traits in saline soils represents a significant knowledge gap in predicting future soil health and ecological function. Through shotgun metagenomic sequencing of coastal soils along a salinity gradient, we show contrasting eco-evolutionary directions of soil bacteria and archaea that manifest in changes to genome size and the functional potential of the soil microbiome. In salt environments with high carbon requirements, bacteria exhibit reduced genome sizes associated with a depletion of metabolic genes, while archaea display larger genomes and enrichment of salt-resistance, metabolic, and carbon-acquisition genes. This suggests that bacteria conserve energy through genome streamlining when facing salt stress, while archaea invest in carbon-acquisition pathways to broaden their resource usage. These findings suggest divergent directions in eco-evolutionary adaptations to soil saline stress amongst microbial clades and serve as a foundation for understanding the response of soil microbiomes to escalating climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Small molecule BLVRB redox inhibitor promotes megakaryocytopoiesis and stress thrombopoiesis in vivo

Biliverdin IXβ reductase (BLVRB) is an NADPH-dependent enzyme previously implicated in a redox-regulated mechanism of thrombopoiesis distinct from the thrombopoietin (TPO)/c-MPL axis. Here, we apply computational modeling to inform molecule design, followed by de novo syntheses and screening of unique small molecules retaining the capacity for selective BLVRB inhibition as a novel platelet-enhancing strategy. Two distinct classes of molecules are identified, and NMR spectroscopy and co-crystallization studies confirm binding modes within the BLVRB active site and ring stacking between the nicotinamide moiety of the NADP+ cofactor. A diazabicyclo derivative displaying minimal off-target promiscuity and excellent bioavailability characteristics promotes megakaryocyte speciation in biphenotypic (erythro/megakaryocyte) cellular models and synergizes with TPO-dependent megakaryocyte formation in hematopoietic stem cells. Upon oral delivery into mice, this inhibitor expands platelet recovery in stress thrombopoietic models with no adverse effects. In this work, we identify and validate a cellular redox inhibitor retaining the potential to selectively promote megakaryocytopoiesis and enhance stress-associated platelet formation in vivo distinct from TPO receptor agonists.

36 MATERIALS SCIENCE↗