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DOE OSTI2025

Bulk Anion Recognition Kinetically Holds Back Interfacial Adsorption

The competition between bulk and interfacial phenomena underlies many key processes in complex chemical phenomena and transport. While competitive processes are often framed in a thermodynamic context, opportunities to leverage transient species found away from equilibrium can provide a kinetic handle to achieve unconventional reaction outcomes. In this work, we outfit an iminoguanidinium headgroup capable of selective SO 4 2– complexation with alkyl tails of varying complexity to probe competitive bulk and interfacial reaction pathways and tune kinetic pathways for selective chemical separations. Using sum frequency generation (SFG) vibrational spectroscopy we unexpectedly find that adsorption of ligands to the air–aqueous interface was dramatically slowed down for species with increasingly hydrophobic tails. Underlying this phenomenon, we show that the formation of bulk colloidal species with differing propensities for SO 4 2– inhibited surface adsorption via a kinetic bottleneck in the exchange of molecular extractants with colloidal aggregates. This kinetic effect could open up avenues to access unconventional selectivity via complexation of strongly coordinating species in the bulk phase, allowing for more weakly coordinating species to transport via interfacial mechanisms. Furthermore, this work broadly probes nonequilibrium phenomena in chemical separations that arise through unexpected interfacial events that are neglected in traditional equilibrium descriptions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites

Molecular simulations demonstrate that the enthalpic softening of elastomeric nanocomposites upon heating can arise naturally from a Poisson’s ratio mismatch between elastomer and nanoparticle networks, providing a more parsimonious explanation for this phenomenon than the widely accepted interpretation based on glassy interparticle bridging. Despite a century of use, the mechanism of nanoparticle-driven mechanical reinforcement of elastomers is unresolved. Here, a major hypothesis attributes it to glassy interparticle bridges, supported by an observed inversion of the variation of the modulus E(T) on heating – from entropic stiffening in elastomers to enthalpic softening in nanocomposites. Here, molecular simulations reveal that elastomer enthalpic softening can instead emerge from a competition over the preferred volumes between elastomer and nanoparticulate networks. A theory for this competition accounting for softening of the bulk modulus on heating predicts the simulated E(T) inversion, suggesting that reinforcement is driven by a volume-competition mechanism unique to cocontinuous systems of soft and rigid networks.

Biopolymers↗

DOE OSTI2018

Effects of Fulvic Acid on Uranium(VI) Sorption Kinetics

Many studies by Dr. James A. Davis and others have demonstrated the influence of natural organic matter (NOM) on metal sorption and transport behavior in subsurface environments. Overall, NOM effects on metal sorption have been ascribed to: (1) different sorption affinities of metal-ligand solution complexes compared to ‘free’ metals in solution, and (2) NOM sorption onto minerals leading to competitive sorption behavior and/or changes in mineral surface characteristics. All of these processes have the potential to decrease metal sorption onto mineral surfaces, and alter the pH-dependence of metal sorption characteristics. Maybe even more importantly, a change in metal sorption mechanisms in the presence of NOM may lead to differences in metal surface speciation and affect the potential for later metal desorption and remobilization. Furthermore, it is well-known that overall reaction rates change if the series of elemental reactions comprising a reaction pathway has been altered. In the presence of NOM, metal-ligand dissociation reactions occurring prior to the sorption of ‘free’ metal ions may slow down overall metal sorption kinetics. In addition, a competition between metals and organic ligands binding to the same reactive surface sites may potentially decrease metal sorption rates based on mass action principles. Last, the sorption kinetics of metal-ligand solution complexes may be controlled by the rates of NOM surface reactions, which could be either faster or slower than ‘free’ metal sorption depending on ligand sorption mechanisms. In this presentation, we will use a uranium(VI)-fulvic acid-silica sand system to demonstrate how kinetic sorption experiments – combined with modeling strategies – can provide a powerful tool to study changes in metal sorption mechanisms as a function of organic ligand concentrations. Based on our kinetic sorption data and modeling-based data interpretation, U(VI) sorption onto silica sand can be either faster or slower in the presence of fulvic acid compared to a ligand-free system, depending on the relative concentrations of metals, organic ligands and mineral surface sites. Supporting simulations of U(VI) solution speciation and mineral surface characterization data further allowed us to conclude that a shift occurred from competitive sorption behavior to strong influences of uranium(VI)-fulvic acid complexes with increasing ligand concentrations in this system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Ecological trade-offs drive phenotypic and genetic differentiation of Arabidopsis thaliana in Europe

Plant diversity is shaped by trade-offs between traits related to competitive ability, propagule dispersal, and stress resistance. However, we still lack a clear understanding of how these trade-offs influence species distribution and population dynamics. In Arabidopsis thaliana , recent genetic analyses revealed a group of cosmopolitan genotypes that successfully recolonized Europe from its center after the last glaciation, excluding older (relict) lineages from the distribution except for their north and south margins. Here, we tested the hypothesis that cosmopolitans expanded due to higher colonization ability, while relicts persisted at the margins due to higher tolerance to competition and/or stress. We compared the phenotypic and genetic differentiation between 71 European genotypes originating from the center, and the south and north margins. We showed that a trade-off between plant fecundity and seed mass shapes the differentiation of A. thaliana in Europe, suggesting that the success of the cosmopolitan groups could be explained by their high dispersal ability. However, at both north and south margins, we found evidence of selection for alleles conferring low dispersal but highly competitive and stress-resistance abilities. This study sheds light on the role of ecological trade-offs as evolutionary drivers of the distribution and dynamics of plant populations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Spin density wave instability in a ferromagnet

Due to its cooperative nature, magnetic ordering involves a complex interplay between spin, charge, and lattice degrees of freedom, which can lead to strong competition between magnetic states. Binary Fe 3 Ga 4 is one such material that exhibits competing orders having a ferromagnetic (FM) ground state, an antiferromagnetic (AFM) behavior at intermediate temperatures, and a conspicuous re-entrance of the FM state at high temperature. Through a combination of neutron diffraction experiments and simulations, we have discovered that the AFM state is an incommensurate spin-density wave (ISDW) ordering generated by nesting in the spin polarized Fermi surface. These two magnetic states, FM and ISDW, are seldom observed in the same material without application of a polarizing magnetic field. To date, this unusual mechanism has never been observed and its elemental origins could have far reaching implications in many other magnetic systems that contain strong competition between these types of magnetic order. Furthermore, the competition between magnetic states results in a susceptibility to external perturbations allowing the magnetic transitions in Fe 3 Ga 4 to be controlled via temperature, magnetic field, disorder, and pressure. Thus, Fe 3 Ga 4 has potential for application in novel magnetic memory devices, such as the magnetic components of tunneling magnetoresistance spintronics devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Optimal thermodynamic conditions to minimize kinetic by-products in aqueous materials synthesis

Abstract Phase diagrams offer substantial predictive power for materials synthesis by identifying the stability regions of target phases. However, thermodynamic phase diagrams do not offer explicit information regarding the kinetic competitiveness of undesired by-product phases. Here we propose a quantitative and computable thermodynamic metric to identify synthesis conditions under which the propensity to form kinetically competing by-products is minimized. We hypothesize that thermodynamic competition is minimized when the difference in free energy between a target phase and the minimal energy of all other competing phases is maximized. We validate this hypothesis for aqueous materials synthesis through two empirical approaches: first, by analysing 331 aqueous synthesis recipes text-mined from the literature; and second, by systematic experimental synthesis of LiIn(IO 3 ) 4 and LiFePO 4 across a wide range of aqueous electrochemical conditions. Our results show that even for synthesis conditions that are within the stability region of a thermodynamic Pourbaix diagram, phase-pure synthesis occurs only when thermodynamic competition with undesired phases is minimized.

Wang, Zheren (ORCID:0000000227429451)↗

DOE OSTI2014

Nonlinear luminescence response of CaF{sub 2}:Eu and YAlO{sub 3}:Ce to single-ion excitation

Understanding scintillation physics and nonproportionality is essential to accelerate materials discovery that has been restricted due to the difficulties inherent to large crystal growth and complex nature of gamma-solid interaction. Taking advantage of less restrictive growth and deposition techniques for smaller crystal sizes or thin films and better fundamental understanding of ion-solid interactions, a unique ion approach is demonstrated to effectively screen candidate scintillators with relatively small size and evaluate their nonlinear scintillation response. Response of CaF{sub 2}:Eu and YAlO{sub 3}:Ce scintillators to single ions of H{sup +}, He{sup +}, and O{sup 3+} are measured by the corresponding pulse height over a continuous energy range using a time-of-flight–scintillator–photoelectric multiplier tube apparatus. Nonlinear response of the scintillators under ionizing ion irradiation is quantitatively evaluated by considering the energy partitioning process. In a differential energy deposition region with negligible displacement damage, the low, medium and high excitation energy deposition density (D{sub exci}) can be produced by energetic H{sup +}, He{sup +} and O{sup 3+} ions, respectively, and significantly different impacts on the response characteristics of these two benchmark scintillators are observed. For CaF{sub 2}:Eu, the scintillation efficiency under ion irradiation monotonically decreases with increasing excitation-energy density. In contrast, the response efficiency of YAlO{sub 3}:Ce scintillation initially increases with excitation-energy density at low excitation-energy densities, goes through a maximum, and then decreases with further increasing excitation-energy density. The fundamental mechanism causing these different response behaviours in the scintillators is based on the competition between the scintillation response and the nonradiative quenching process under different excitation densities, which is also the main origin of the nonlinear response of the scintillators to irradiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Electrostatically driven pattern formation in mixed charged–neutral multicomponent elastic membranes

Multicomponent crystalline and amorphous elastic shells exhibit heterogeneous surface patterns that provide distinctive functionalities in cellular environments. Such patterning typically arises from the competition between short-range attractive and long-range repulsive interactions in membranes. Here, we demonstrate that the intrinsic competition between electrostatic repulsion and elastic deformation is sufficient to drive spontaneous surface patterning in elastic shells, requiring no additional attractive interactions. Using numerical simulations, we demonstrate pattern formation in mechanically homogeneous membranes with heterogeneous surface charge composition across different topologies, including spheres, discs, and flat periodic membranes. We also examine patterns in crystalline and amorphous shells of coassembled charged and neutral components with different bending rigidities. At low charge fraction, discrete charged surface domains form. At intermediate charge fraction, the competition between electrostatics and elasticity leads to elongated domains (rods) of the charged component, which results in lamellar patterns at nearly equal fraction of the charged and neutral components. At high charge fraction, nanodomains of the neutral component form. Amorphous shells exhibit similar progressions but with disordered structures rather than ordered lamellar patterns. These pattern morphologies are observed in both the closed shells and flat membranes. As salt concentration increases, all patterns coarsen due to the screening of electrostatic interactions.

charge heterogeneity↗

DOE OSTI2018

Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market

This study analyzes the potential resource distribution in global competitive feedstock markets for industrial grade wood pellets. Based on historic trade patterns and expected future production and demand structures, a set of potential buyers and sellers of industrial grade wood pellets are simulated for 2022, 2030, and 2040. In contrast to previous trade modeling efforts, this study assumes a fully competitive market, i.e., excluding long-term contract arrangements, to show resource distributions under a potential future commodity market. This is done via a non-cooperative bi-level Stackelberg leader-follower game model. Of particular interest is the potential impact of international feedstock competition on the availability of US feedstock resources. The model results show that the main destinations for US wood pellet exports typically pay 10-20% more per tonne than the domestic market. The results show that domestic wood pellets are available to US industry at prices higher than the expected $88 per tonne delivered.

09 BIOMASS FUELS↗

DOE OSTI2021

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Abstract Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil–plant–atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Why is the winner the best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multi- center study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), im- age preprocessing (97%), data curation (79%), and post- processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

Eisenmann, Matthias↗

DOE OSTI2023

An Assessment of Additively Manufactured Bonded Permanent Magnets for a Distributed Wind Generator

In this paper, we examine and compare the performance of a generator design optimized using additively manufactured NdFeB-SmFeN in nylon-polymer-bonded permanent magnets (PMs) against a generator design with conventional NdFeB sintered PMs. To realize this, a commercially available 15-kW wind generator's rotor is re-optimized using both additively manufactured and sintered NdFeB magnets using simple geometric parameterization that allowed for two specific magnet shapes, namely, arc-shaped and crown-shaped designs. Results showed that for a similar generator performance, the designs with additively manufactured bonded PMs are more cost-competitive in terms of the estimated PM material cost and also have negligible eddy current magnet losses.

additive manufacturing↗

DOE OSTI2016

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERC region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Resource Adequacy in Electricity Markets With Renewable Energy

This paper presents a market-based resource adequacy assessment framework to analyze the system generation portfolio that results in a competitive market environment. In particular, we apply the modeling framework to investigate the impact of high penetration levels of variable renewable energy resources and different market designs on achieving resource adequacy. The model captures the strategic capacity investment and retirement decision-making of profit-maximizing generation companies. In contrast to many previous studies, this paper considers markets for capacity, energy, and reserve products in detail; thus, the modeling framework allows improved analysis of generation expansion and revenue sufficiency in a competitive market environment. The modeling framework is based on Stackelberg leader-follower games and is formulated as a bi-level optimization problem, which is then transformed into a mathematical program with equilibrium constraints. Furthermore, we employ a Lagrangian decomposition algorithm to enhance computational performance. In a case study of the electric reliability council of texas (ERCOT) system, we compare the results from the proposed model with those obtained from a traditional centralized least-cost planning model. Finally, the results demonstrate the effectiveness of the proposed modeling framework and highlight the importance of considering strategic behavior in a competitive market framework when assessing resource adequacy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Online peak-aware energy scheduling with untrusted advice

This paper studies the online energy scheduling problem in a hybrid model where the cost of energy is proportional to both the volume and peak usage, and where energy can be either locally generated or drawn from the grid. Inspired by recent advances in online algorithms with Machine Learned (ML) advice, we develop parameterized deterministic and randomized algorithms for this problem such that the level of reliance on the advice can be adjusted by a trust parameter. We then analyze the performance of the proposed algorithms using two performance metrics: robustness that measures the competitive ratio as a function of the trust parameter when the advice is inaccurate, and consistency for competitive ratio when the advice is accurate. Since the competitive ratio is analyzed in two different regimes, we further investigate the Pareto optimality of the proposed algorithms. Our results show that the proposed deterministic algorithm is Pareto-optimal, in the sense that no other online deterministic algorithms can dominate the robustness and consistency of our algorithm. Furthermore, we show that the proposed randomized algorithm dominates the Pareto-optimal deterministic algorithm. Our large-scale empirical evaluations using real traces of energy demand, energy prices, and renewable energy generations highlight that the proposed algorithms outperform worst-case optimized algorithms and fully data-driven algorithms.

Lee, Russell↗

DOE OSTI2025

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗

DOE OSTI2019

Orally Bioavailable Androgen Receptor Degrader, Potential Next-Generation Therapeutic for Enzalutamide-Resistant Prostate Cancer

Androgen receptor (AR)-targeting prostate cancer drugs, which are predominantly competitive ligand-binding domain (LBD)-binding antagonists, are inactivated by common resistance mechanisms. It is important to develop next-generation mechanistically distinct drugs to treat castration- and drug-resistant prostate cancers. Second-generation AR pan antagonist UT-34 was selected from a library of compounds and tested in competitive AR binding and transactivation assays. In this study, UT-34 was tested using biophysical methods for binding to the AR activation function-1 (AF-1) domain. Western blot, gene expression, and proliferation assays were performed in various AR-positive enzalutamide-sensitive and -resistant prostate cancer cell lines. Pharmacokinetic and xenograft studies were performed in immunocompromised rats and mice. UT-34 inhibits the wild-type and LBD-mutant ARs comparably and inhibits the in vitro proliferation and in vivo growth of enzalutamide-sensitive and -resistant prostate cancer xenografts. In preclinical models, UT-34 induced the regression of enzalutamide-resistant tumors at doses when the AR is degraded; but, at lower doses, when the AR is just antagonized, it inhibits, without shrinking, the tumors. This indicates that degradation might be a prerequisite for tumor regression. Mechanistically, UT-34 promotes a conformation that is distinct from the LBD-binding competitive antagonist enzalutamide and degrades the AR through the ubiquitin proteasome mechanism. UT-34 has a broad safety margin and exhibits no cross-reactivity with G-protein–coupled receptor kinase and nuclear receptor family members. Collectively, UT-34 exhibits the properties necessary for a next-generation prostate cancer drug.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Single and Dual Targeting of Mutant EGFR with an Allosteric Inhibitor

Allosteric kinase inhibitors offer a potentially complementary therapeutic strategy to ATP-competitive kinase inhibitors due to their distinct sites of target binding. Here, we identify and study a mutant-selective EGFR allosteric inhibitor, JBJ-04-125-02, which as a single agent can inhibit cell proliferation and EGFR L858R/T790M/C797S signaling in vitro and in vivo. However, increased EGFR dimer formation limits treatment efficacy and leads to drug resistance. Remarkably, osimertinib, an ATP-competitive covalent EGFR inhibitor, uniquely and significantly enhances the binding of JBJ-04-125-02 for mutant EGFR. The combination of osimertinib and JBJ-04-125-02 results in an increase in apoptosis, a more effective inhibition of cellular growth, and an increased efficacy in vitro and in vivo compared with either single agent alone. Collectively, our findings suggest that the combination of a covalent mutant–selective ATP-competitive inhibitor and an allosteric EGFR inhibitor may be an effective therapeutic approach for patients with EGFR-mutant lung cancer. Significance: The clinical efficacy of EGFR tyrosine kinase inhibitors (TKI) in EGFR-mutant lung cancer is limited by acquired drug resistance, thus highlighting the need for alternative strategies to inhibit EGFR. Here, we identify a mutant EGFR allosteric inhibitor that is effective as a single agent and in combination with the EGFR TKI osimertinib.

60 APPLIED LIFE SCIENCES↗