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Electroadsorption analysis enables the determination of reaction intermediates to accelerate the design of next generation electrocatalysts. 

ABSTRACT Bacterial biofilms are complex, multi‐component structures consisting primarily of four key elements: polysaccharides, metal ions, proteins, and extracellular DNA. In our research, we specifically focus on the polysaccharide and metal ion components, which play a crucial role in determining the biofilm's mechanical properties. Polysaccharides provide the structural matrix, although metal ions, particularly divalent cations like calcium and cobalt, cross‐link with the polysaccharides, thereby modulating the biofilm's rigidity and viscoelastic behavior. By introducing divalent cations into nanocellulose, we can replicate this natural cross‐linking process, allowing us to finely tune the material's mechanical properties to more closely resemble those of bacterial biofilms. This approach not only enhances the accuracy of synthetic biofilm models over alginate hydrogels but also provides valuable insights into how biofilms maintain their structural integrity in various environments. Our findings indicate that nanocellulose exhibits mechanical properties closer to biofilms than alginate analogs, making it a suitable non‐living control for biofilm studies. Furthermore, divalent nickel, followed by calcium and magnesium, demonstrate a closer mechanical mimicry to biofilms. In conclusion, this research shows the potential of nanocellulose as a versatile material for bacterial biofilm mimicry. 

Abstract We prove well‐posedness of a class ofkinetic‐typemean field games (MFGs), which typically arise when agents control their acceleration. Such systems include independent variables representing the spatial position as well as velocity. We consider non‐separable Hamiltonians without any structural conditions, which depend locally on the density variable. Our analysis is based on two main ingredients: an energy method for the forward–backward system in Sobolev spaces, on the one hand, and on a suitablevector field methodto control derivatives with respect to the velocity variable, on the other hand. The careful combination of these two techniques reveals interesting phenomena applicable for MFGs involving general classes of drift‐diffusion operators and non‐linearities. While many prior existence theories for general MFGs systems take the final datum function to be smoothing, we can allow this function to be non‐smoothing, that is, also depending locally on the final measure. Our well‐posedness results hold under an appropriate smallness condition, assumed jointly on the data. 

We report a Liquid Crystal Display (LCD) structure employing cellulose nanocrystals (CNC) as a recyclable, non‐toxic alignment layer in a twisted nematic configuration The CNC alignment layer, fabricated via spin coating and mechanical rubbing, demonstrated comparable performance to polyimide in transparency, threshold voltage, response speed, and liquid crystal alignment This work demonstrates the viability of CNC alignment layers, advancing LCD technology toward circular economy principles. 

Abstract Over the past decades, missions at the L1 point have been providing solar wind and interplanetary magnetic field measurements that are necessary for forecasting space weather at Earth with high accuracy and a lead time of a few tens of minutes. Improving the lead time, while maintaining a relatively high level of accuracy, can be achieved with missions sunward of L1, so‐called sub‐L1 monitors. However, too much is unknown to plan for sub‐L1 monitors as operational missions: both the orbital requirements of such missions, and the achievable accuracy of forecasts based on their measurements have not been quantitatively defined. We review here some proposed mission concepts and explain the knowledge gaps related to coronal mass ejections (CMEs) that require a space weather research or science mission. We first show how STEREO‐A measurements in 2023 can be used as a proof of concept of the use of sub‐L1 monitor slightly off the Sun‐Earth line to forecast the Dst index. We then highlight that separations of are needed to ensure that CMEs measured by a sub‐L1 monitor impact Earth. Next, we show that measurements with angular separations of have negligible errors but separations of a few degrees can result in significant errors in lead time and in the forecasted magnetic field strength of CMEs. We also discuss how CME evolution over the last 0.05–0.2 au before impacting Earth is strongly under‐constrained and needs to be better understood before using measurements of sub‐L1 monitors for real‐time space weather forecasting. 

ABSTRACT Machine‐learning models have been surprisingly successful at predicting stream solute concentrations, even for solutes without dedicated sensors. It would be extremely valuable if these models could predict solute concentrations in streams beyond the one in which they were trained. We assessed the generalisability of random forest models by training them in one or more streams and testing them in another. Models were made using grab sample and sensor data from 10 New Hampshire streams and rivers. As observed in previous studies, models trained in one stream were capable of accurately predicting solute concentrations in that stream. However, models trained on one stream produced inaccurate predictions of solute concentrations in other streams, with the exception of solutes measured by dedicated sensors (i.e., nitrate and dissolved organic carbon). Using data from multiple watersheds improved model results, but model performance was still worse than using the mean of the training dataset (Nash–Sutcliffe Efficiency < 0). Our results demonstrate that machine‐learning models thus far reliably predict solute concentrations only where trained, as differences in solute concentration patterns and sensor‐solute relationships limit their broader applicability. 

ABSTRACT It is unclear how environmental change influences standing genetic variation in wild populations. Here, we characterised environmental conditions that protect versus erode polymorphic chemical defences inBoechera stricta(Brassicaceae), a short‐lived perennial wildflower. By manipulating drought and herbivory in a 4‐year field experiment, we measured the effects of driver variation on vital rates of genotypes varying in defence chemistry and then assessed interacting driver effects on total fitness (estimated as each genotype's lineage growth rate,λ) using demographic models. Drought and herbivory interacted to shape vital rates, but contrasting defence genotypes had equivalent total fitness in many environments. Defence polymorphism thus may persist under a range of conditions; however, ambient field conditions fall close to the boundary of putatively polymorphic environment space, and increasing aridity may drive populations to monomorphism. Consequently, elevated intensity and/or frequency of drought under climate change may erode genetic variation for defence chemistry inB. stricta.