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Revising the dynamic energy budget theory with a new reserve mobilization rule and three example applications to bacterial growth
Dynamic energy budget (DEB) theory has been applied to model a wide range of organisms, including microbes. In the standard DEB model, biomass is partitioned into reserve and structural compartments, where reserve biomass is mobilized in a pseudolinear manner (while the reserve biomass density, defined as the ratio between reserve and structural biomass, decays linearly) to drive maintenance and the growth of structural biomass (and extracellular enzyme production if it is considered). However, the linear dynamics of the reserve biomass density makes the standard DEB model incapable of explaining the slowdown of microbial growth at high reserve density that is caused by macromolecular crowding effect which reduces biochemical reaction rates (a typical situation occurs when microbes are experiencing severe moisture stress) and is inconsistent with the observation that intracellular enzymatic reactions generally follow non-linear kinetics. By partitioning biomass into reserve, kinetic, and structural compartments, we show here that the Equilibrium Chemistry Approximation (ECA) kinetics can be used to represent enzymatically catalyzed reserve biomass mobilization that can then drive the kinetic and structural biomass synthesis. This revised DEB model better represents the tradeoff in ribosome allocation for structural growth and internal enzyme production, is structurally compatible with metabolic models of cell individuals, and includes the standard DEB model and the popular compromise model as special cases for representing population growth. We then applied the revised DEB model to interpret components of bacterial respiration, their dependence on substrate availability, and emergent microbial carbon use efficiency dynamics for an exponentially growing population. We found that the revised DEB model enables a better understanding of bacterial substrates use (carbon in our examples) than that can be derived from a few other models in the literature. In particular, the revised DEB model explains why carbon use efficiency may first increase, then plateau, and finally decrease with growth rate (and substrate uptake rate), as a function of proteomics. Additionally, the revised DEB model explains why the kinetic biomass compartment needs to be divided to reasonably incorporate proteomic control of microbial growth.
Toward High-Voltage Cathodes for Zinc-Ion Batteries: Discovery Pipeline and Material Design Rules
Efficient energy storage systems are crucial to address the intermittency of renewable energy sources. As multivalent batteries, Zn-ion batteries (ZIBs), while inherently low voltage, offer a promising low-cost alternative to Li-ion batteries due to the viable use of zinc as the anode. However, to maximize the potential impact of ZIBs, rechargeable cathodes with improved Zn diffusion are needed. To better understand the chemical and structural factors influencing Zn-ion mobility within battery electrode materials, we employ a high-throughput computational screening approach to systematically evaluate candidate intercalation hosts for ZIB cathodes, expanding the chemical search space on empty intercalation hosts that do not contain Zn. We leverage a high-throughput screening funnel to identify promising cathodes in ZIBs, integrating screening criteria with density functional theory (DFT)-based calculations of Zn2+ intercalation and diffusion inside the host materials. Using these data, we identify the design principles that favor Zn-ion mobility in candidate cathode materials. Building on previous work on divalent-ion cathodes, this study broadens the chemical space for next-generation multivalent energy storage systems.
Learning Chemistry of Complex Reaction Systems via a Python First-Principles Reaction Rule Stencil (pReSt) Generator
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New Design Rules for Developing Potent Cell-Active Inhibitors of the Nucleosome Remodeling Factor (N
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General Design Rules for Bimetallic Platinum(II) Complexes
A series of platinum(II) bimetallic complexes were studied to investigate the effects of ligands on both the geometric and electronic structure. Modulating the Pt-Pt distance through the bridging ligand architecture was found to dictate the nature of the lowest energy electronic transitions, localized in one-half of the molecule or delocalized across the entire molecule. By reducing the separation between the platinum atoms, the lowest energy electronic transitions will be dominated by the metal-metal-to-ligand charge transfer transition. Conversely, by increasing the distance between the platinum atoms, the lowest electronic transition will be largely localized metal-to-ligand charge transfer or ligand centered in nature. Additionally, the cyclometalating ligands were observed to have a noticeable stabilizing effect on the triplet excited states as the conjugation increased, arising from geometric reorientation and increased electron delocalization of the ligands. Furthermore, such stabilization of the triplet state energy has been shown to alter the excited state potential energy landscape as well as the excited state trajectory.
Design Rules for Selecting Fluorinated Linear Organic Solvents for Li Metal Batteries
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Topogivity: A Machine-Learned Chemical Rule for Discovering Topological Materials
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Elucidating Design Rules toward Enhanced Solid-State Charge Transport in Oligoether-Functionalized Dioxythiophene-Based Alternating Copolymers
This study investigates the solid-state charge transport properties of the oxidized forms of dioxythiophene-based alternating copolymers consisting of an oligoether-functionalized 3,4-propylenedioxythiophene (ProDOT) copolymerized with different aryl groups, dimethyl ProDOT (DMP), 3,4-ethylenedioxythiophene (EDOT), and 3,4-phenylenedioxythiophene (PheDOT), respectively, to yield copolymers P(OE3)-D, P(OE3)-E, and P(OE3)-Ph. At a dopant concentration of 5 mM FeTos 3 , the electrical conductivities of these copolymers vary significantly (ranging between 9 and 195 S cm –1 ) with the EDOT copolymer, P(OE3)-E, achieving the highest electrical conductivity. UV–vis–NIR and X-ray spectroscopies show differences in both susceptibility to oxidative doping and extent of oxidation for the P(OE3) series, with P(OE3)-E being the most doped. Wide-angle X-ray scattering measurements indicate that P(OE3)-E generally demonstrates the lowest paracrystallinity values in the series, as well as relatively small π–π stacking distances. The significant (i.e., order of magnitude) increase in electrical conductivity of doped P(OE3)-E films versus doped P(OE3)-D or P(OE3)-Ph films can therefore be attributed to P(OE3)-E exhibiting both the highest carrier ratios in the P(OE3) series, along with good π–π overlap and local ordering (low paracrystallinity values). Furthermore, these trends in the extent of doping and paracrystallinity are consistent with the reduced Fermi energy level and transport function prefactor parameters calculated using the semilocalized transport (SLoT) model. Observed differences in carrier ratios at the transport edge (c t ) and reduced Fermi energies [η(c)] suggest a broader electronic band (better overlap and more delocalization) for the EDOT-incorporating P(OE3)-E polymer relative to P(OE3)-D and P(OE3)-Ph. Ultimately, we rationalize improvements in electrical conductivity due to microstructural and doping enhancements caused by EDOT incorporation, a structure–property relationship worth considering in the future design of highly electrically conductive systems.
Why Conventional Design Rules for C–H Activation Fail for Open-Shell Transition-Metal Catalysts
The design of selective and active C–H activation catalysts for direct methane-to-methanol conversion is challenging. Bioinspired complexes that form high-valent metal–oxo intermediates capable of hydrogen abstraction and rebound hydroxylation are promising candidates. This promise has made them a target for computational high-throughput screening, typically simplified through the use of linear free energy relationships (LFERs). However, their mid-row transition-metal centers have numerous accessible spin and oxidation states that increase the combinatorial scale of design efforts. Here, we carry out a computational design screen of over 2500 mid-row 3d transition-metal complexes with four metals in numerous spin and oxidation states. We demonstrate the importance of spin/oxidation state in dictating design principles, limiting the generalization of strategies derived for widely studied high-spin Fe(II) catalysts to other metals or spin/oxidation states. Combined assessment of the effect of ligand-field tuning on reaction step energetics and on the identity of the ground state allows us to propose refined design strategies for spin-allowed methane-to-methanol catalysis. We observe weak coupling of energetics and design principles between reaction steps (e.g., oxo formation vs methanol release), meaning that LFERs do not generalize across our larger catalyst set. To rationalize relative reactivity in known catalysts, we instead compute independent reaction energies and propose strategies for further improvements in catalyst design.
Acidity-Governed Rules in the Electrochemical Performance of Fluorinated Benzenes for High-Voltage Lithium Metal Batteries
Judicious selection of the optimal fluorobenzene (FB) as a nonsolvating cosolvent for lithium metal batteries (LMBs) is reported. For this work, we found the key correlation between FB structures and cycling stabilities of cells: increased fluorine substitution of FBs results in higher anodic stability but at the expense of reduced reductive stability, and FBs containing three or more fluorine atoms exhibit insufficient anodic stability in the electrolyte system comprised of fluoroethylene carbonate (FEC) and ethyl methyl carbonate (EMC). More importantly, FBs with higher acidity (lower pK a ) due to protons located between two adjacent fluorine atoms tend to be more susceptible to side reactions during cycling. Our results indicate that difluorobenzenes with no “acidic” proton (DFB2 and DFB4) have emerged as the optimal choice with the desired redox stability in high-voltage LMBs. Nuclear magnetic resonance and X-ray photoelectron spectroscopy confirmed these findings, providing guidance for selecting the most suitable FB variants as nonsolvating cosolvents for high-voltage LMBs.
Tuning the Redox Activity of Metal–Organic Frameworks for Enhanced, Selective O 2 Binding: Design Rules and Ambient Temperature O 2 Chemisorption in a Cobalt–Triazolate Framework
Metal–organic frameworks (MOFs) with coordinatively unsaturated metal sites are appealing as adsorbent materials due to their tunable functionality and ability to selectively bind small molecules. Through the use of computational screening methods based on periodic density functional theory, we investigate O 2 and N 2 adsorption at the coordinatively unsaturated metal sites of several MOF families. A variety of design handles are identified that can be used to modify the redox activity of the metal centers, including changing the functionalization of the linkers (replacing oxido donors with sulfido donors), anion exchange of bridging ligands (considering μ-Br – , μ-Cl – , μ-F – , μ-SH – , or μ-OH – groups), and altering the formal oxidation state of the metal. As a result, we show that it is possible to tune the O 2 affinity at the open metal sites of MOFs for applications involving the strong and/or selective binding of O 2 . In contrast with O 2 adsorption, N 2 adsorption at open metal sites is predicted to be relatively weak across the MOF dataset, with the exception of MOFs containing synthetically elusive V 2+ open metal sites. As one example from the screening study, we predicted that exchanging the μ-Cl – ligands of M 2 Cl 2 (BBTA) (H 2 BBTA = 1H,5H-benzo(1,2-d:4,5-d')bistriazole) with μ-OH – groups would significantly enhance the strength of O 2 adsorption at the open metal sites without a corresponding increase in the N 2 affinity. Experimental investigation of Co 2 Cl 2 (BBTA) and Co 2 (OH) 2 (BBTA) confirms that the former exhibits weak physisorption of both N 2 and O 2 , whereas the latter is capable of chemisorbing O 2 at room temperature in a highly selective manner. The O 2 chemisorption behavior is attributed to the greater electron-donating character of the μ-OH – ligands and the presence of H-bonding interactions between the μ-OH – bridging ligands and the reduced O 2 adsorbate.
Topology-Informed Design Rules for Deconstructable Thermoset Copolymer Networks
Existing models of thermoset deconstruction facilitated by incorporating cleavable comonomers rely on a mean-field reverse gel point paradigm, which predicts network dissolution once cleavable bonds reach a critical stoichiometric threshold, but does not account for where those bonds reside within the network architecture. Using reactive coarse-grained molecular dynamics simulations coupled with graph-theoretic analysis, we extend this stoichiometric picture to show that deconstructability is governed by the curing-imprinted network topology rather than stoichiometry alone. This topological organization is hierarchical: at the local scale, the elastic effectiveness of cross-link junctions determines which cross-links constitute the load-bearing scaffold; at the mesoscale, the cross-linking rate kinetically templates that scaffold into topologically modular communities─densely cross-linked clusters connected by sparse bridging strands that sustain network connectivity. Using betweenness centrality to identify nodes that disproportionately lie on intercommunity shortest paths, we demonstrate that effective deconstruction of the network into macromolecular fragments requires cleavable comonomers to intercept these high-centrality bridging strands. We further find that under uniform, disassortative comonomer incorporation, this topological requirement provides a mechanistic basis for extending the reverse gel point to incorporate network topology. We also show that modularity imposes a fundamental limit on fragment uniformity that persists even when the centrality requirement is met. Finally, we demonstrate that chain stiffness provides a nearly independent lever to suppress mechanically redundant cross-links and raise the glass transition temperature without significantly altering the deconstruction outcome. Together, these findings reframe the thermoset design space around network topology and provide actionable guidelines for engineering thermoset copolymers with predictable deconstructability and targeted thermomechanical performance.
One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models
Abstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr −1 . We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.
Anomalous metal segregation in lithium-rich material provides design rules for stable cathode in lithium-ion battery
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