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Reversible phenotypic flexibility allows organisms to better match phenotypes to prevailing environmental conditions and may produce fitness benefits. Costs and constraints of phenotypic flexibility may limit the capacity for flexible responses but are not well understood nor documented. Costs could include expenses associated with maintaining the flexible system or with generating the flexible response. One potential cost of maintaining a flexible system is an energetic cost reflected in the basal metabolic rate (BMR), with elevated BMR in individuals with more flexible metabolic responses. We accessed data from thermal acclimation studies of birds where BMR and/or M_sum(maximum cold-induced metabolic rate) were measured before and after acclimation, as a measure of metabolic flexibility, to test the hypothesis that flexibility in BMR (ΔBMR), M_sum(ΔM_sum), or metabolic scope (M_sum − BMR; ΔScope) is positively correlated with BMR. When temperature treatments lasted at least three weeks, three of six species showed significant positive correlations between ΔBMR and BMR, one species showed a significant negative correlation, and two species showed no significant correlation. ΔM_sumand BMR were not significantly correlated for any species and ΔScope and BMR were significantly positively correlated for only one species. These data suggest that support costs exist for maintaining high BMR flexibility formore »some bird species, but high flexibility in M_sumor metabolic scope does not generally incur elevated maintenance costs.

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Quantum simulation is a prominent application of quantum computers. While there is extensive previous work on simulating finite-dimensional systems, less is known about quantum algorithms for real-space dynamics. We conduct a systematic study of such algorithms. In particular, we show that the dynamics of a d -dimensional Schrödinger equation with η particles can be simulated with gate complexity O ~ ( η d F poly ( log ⁡ ( g ′ / ϵ ) ) ) , where ϵ is the discretization error, g ′ controls the higher-order derivatives of the wave function, and F measures the time-integrated strength of the potential. Compared to the best previous results, this exponentially improves the dependence on ϵ and g ′ from poly ( g ′ / ϵ ) to poly ( log ⁡ ( g ′ / ϵ ) ) and polynomially improves the dependence on T and d , while maintaining best known performance with respect to η . For the case of Coulomb interactions, we give an algorithm using η 3 ( d + η ) T poly ( log ⁡ ( η d T g ′ / ( Δ ϵ ) ) ) / Δ one- and two-qubit gates,more »and another using η 3 ( 4 d ) d / 2 T poly ( log ⁡ ( η d T g ′ / ( Δ ϵ ) ) ) / Δ one- and two-qubit gates and QRAM operations, where T is the evolution time and the parameter Δ regulates the unbounded Coulomb interaction. We give applications to several computational problems, including faster real-space simulation of quantum chemistry, rigorous analysis of discretization error for simulation of a uniform electron gas, and a quadratic improvement to a quantum algorithm for escaping saddle points in nonconvex optimization.« less

Despite numerous reported lithium metal batteries (LMBs) with excellent cycling performance achieved in labs, transferring the high performing LMBs from lab-scale to industrial-production remains challenging. Therefore, via imitating the stand-still process in battery production, a conventional but important procedure, to investigate the formation and evolution of a solid electrolyte interface (SEI) is particularly important for LMBs. Our previous studies indicate that zein (corn protein)-modified carbonate-ester electrolyte (the most commercialized) effectively improves the performance of LMBs through guiding Li- ions and repairing cracked SEI. Herein, we investigate the formation and evolution of the protein-modified SEIs on Li anodes by imitating the stand-still temperature and duration. A simulation study on the protein denaturation in the electrolyte under different temperatures demonstrates a highly unfolded configuration at elevated temperatures. The experiments show that this heat-treated-zein (H-zein) modified SEI forms quickly and becomes stable after a stand-still process of less than 100 min. Moreover, the H-zein SEI exhibits excellent wetting behavior with the electrolyte due to the highly unfolded protein structures with more functional groups exposed. The Li|Li cell with the H-zein SEI achieves prolonged cycling performance (>360 h vs.
260 h of the cell with the untreated-zein (U-zein) modified SEI). The LiFePO4|Li cell withmore »the H-zein SEI shows much stable long-term cycling performance of capacity retention (70% vs. 42% of the cell with U-zein SEI) after 200 cycles. This study confirms that the appropriately treated protein is able to effectively improve the performance of LMBs, and will inspire future studies for the production process of LMBs toward their commercialization.« less

Suffering from critical instability of lithium (Li) anode, the most commercial electrolytes, carbonate-ester electrolytes, have been restrictedly used in high-energy Li metal batteries (LMBs) despite of their broad implementation in lithium-ion batteries. Here, abundant, natural corn protein, zein, is exploited as a novel additive to stabilize Li anode and effectively prolong the cycling life of LMBs based on carbonate-ester electrolyte. It is discovered that the denatured zein is involved in the formation of solid electrolyte interphase (SEI), guides Li+ deposition and repairs the cracked SEI. In specific, the zein-rich SEI benefits the anion immobilization, enabling uniform Li+ deposition to diminish dendrite growth; the preferential zein-Li reaction effectively repairs the cracked SEI, protecting Li from parasite reactions. The resulting symmetrical Li cell exhibits a prolonged cycling life to over 350 h from <200 h for pristine cell at 1 mA cm􀀀 2 with a capacity of 1 mAh cm^ 2. Paired with LiFePO4 cathode, zein additive markedly improves the electrochemical performance including a higher capacity of 130.1 mAh g^ 1 and a higher capacity retention of ~ 80 % after 200 cycles at 1 C. This study demonstrates a natural protein to be an effective additive for the most commercial electrolytesmore »for advancing performance of LMBs.« less

Quantum computers can produce a quantum encoding of the solution of a system of differential equations exponentially faster than a classical algorithm can produce an explicit description. However, while high-precision quantum algorithms for linear ordinary differential equations are well established, the best previous quantum algorithms for linear partial differential equations (PDEs) have complexity p o l y ( 1 / ϵ ) , where ϵ is the error tolerance. By developing quantum algorithms based on adaptive-order finite difference methods and spectral methods, we improve the complexity of quantum algorithms for linear PDEs to be p o l y ( d , log ⁡ ( 1 / ϵ ) ) , where d is the spatial dimension. Our algorithms apply high-precision quantum linear system algorithms to systems whose condition numbers and approximation errors we bound. We develop a finite difference algorithm for the Poisson equation and a spectral algorithm for more general second-order elliptic equations.