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Abstract Rising atmospheric CO₂levels place terrestrial ecosystems under novel environmental conditions, and research in field settings is key to understanding how real plant communities will respond. Despite decades of progress in elevated CO₂(eCO₂) experiments, major gaps persist in our knowledge of plant responses to interacting influences of climate change, especially in areas outside North America and Western Europe.With a goal to expand access to field‐based eCO₂research, we designed, built, and tested TinyCO₂, a low‐cost field experiment for climate change research on plants. TinyCO₂features sixteen 0.62‐m²plot areas, half with ambient and half with elevated (+200 ppm) CO₂concentrations, and is suitable for short‐stature plants (≤0.5 m in height).Using a proportional‐integral control algorithm and constant sampling of air within the plots, TinyCO₂achieves consistent elevation of [CO₂] averaging +196.9 ppm. During testing, 95.1% of measured CO₂concentrations fell within 20% of the setpoint (ambient CO₂ + 200 ppm). A streamlined design and efficient use of instrumentation reduced the cost of the system to roughly one‐fifth of the cost of similar experiments from the past 30 years ($13.68 vs. $64.65 ppm⁻¹ m⁻², adjusted to 2024 USD).Our results demonstrate a system capable of precise and accurate field‐based CO₂elevation for significantly reduced cost. We envision the TinyCO₂design being implemented in a multitude of field‐based eCO₂studies, perhaps as part of a globally distributed collaborative network experiment. 

Abstract Plants differ widely in how soil drying affects stomatal conductance (g_s) and leaf water potential (ψ_leaf), and in the underlying physiological controls. Efforts to breed crops for drought resilience would benefit from a better understanding of these mechanisms and their diversity. We grew 12 diverse genotypes of common bean (Phaseolus vulgarisL.) and four of tepary bean (P. acutifolius;a highly drought resilient species) in the field under irrigation and post‐flowering drought, and quantified responses ofg_sandψ_leaf, and their controls (soil water potential [ψ_soil], evaporative demand [Δw] and plant hydraulic conductance [K]). We hypothesised that (i) common beans would be more “isohydric” (i.e., exhibit strong stomatal closure in drought, minimisingψ_leafdecline) than tepary beans, and that genotypes with largerψ_leafdecline (more “anisohydric”) would exhibit (ii) smaller increases in Δw, due to less suppression of evaporative cooling by stomatal closure and hence less canopy warming, but (iii) largerKdeclines due toψ_leafdecline. Contrary to our hypotheses, we found that half of the common bean genotypes were similarly anisohydric to most tepary beans; canopy temperature was cooler in isohydric genotypes leading to smaller increases in Δwin drought; and that stomatal closure andKdecline were similar in isohydric and anisohydric genotypes.g_sandψ_leafwere virtually insensitive to drought in one tepary genotype (G40068). Our results highlight the potential importance of non‐stomatal mechanisms for leaf cooling, and the variability in drought resilience traits among closely related crop legumes. 

Abstract Two-dimensional van der Waals materials such as graphene present an opportunity for band structure engineering using custom superlattice potentials. In this study, we demonstrate how self-assemblies of magnetic iron-oxide (Fe₃O₄) nanospheres stacked on monolayer graphene generate a proximity-induced magnetic superlattice in graphene and modify its band structure. Interactions between the nanospheres and the graphene layer generate superlattice Dirac points in addition to a gapped energy spectrum near the K and K′ valleys, resulting in magnetic confinement of quasiparticles around the nanospheres. This is evidenced by gate-dependent resistance oscillations, observed in our low temperature transport measurements, and confirmed by self-consistent tight binding calculations. Furthermore, we show that an external magnetic field can tune the magnetic superlattice potential created by the nanospheres, and thus the transport characteristics of the system. This technique for magnetic-field-tuned band structure engineering using magnetic nanostructures can be extended to a broader class of 2D van der Waals and topological materials. 

Abstract Background Remote sensing instruments enable high-throughput phenotyping of plant traits and stress resilience across scale. Spatial (handheld devices, towers, drones, airborne, and satellites) and temporal (continuous or intermittent) tradeoffs can enable or constrain plant science applications. Here, we describe the technical details of TSWIFT (Tower Spectrometer on Wheels for Investigating Frequent Timeseries), a mobile tower-based hyperspectral remote sensing system for continuous monitoring of spectral reflectance across visible-near infrared regions with the capacity to resolve solar-induced fluorescence (SIF). Results We demonstrate potential applications for monitoring short-term (diurnal) and long-term (seasonal) variation of vegetation for high-throughput phenotyping applications. We deployed TSWIFT in a field experiment of 300 common bean genotypes in two treatments: control (irrigated) and drought (terminal drought). We evaluated the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), and SIF, as well as the coefficient of variation (CV) across the visible-near infrared spectral range (400 to 900 nm). NDVI tracked structural variation early in the growing season, following initial plant growth and development. PRI and SIF were more dynamic, exhibiting variation diurnally and seasonally, enabling quantification of genotypic variation in physiological response to drought conditions. Beyond vegetation indices, CV of hyperspectral reflectance showed the most variability across genotypes, treatment, and time in the visible and red-edge spectral regions. Conclusions TSWIFT enables continuous and automated monitoring of hyperspectral reflectance for assessing variation in plant structure and function at high spatial and temporal resolutions for high-throughput phenotyping. Mobile, tower-based systems like this can provide short- and long-term datasets to assess genotypic and/or management responses to the environment, and ultimately enable the spectral prediction of resource-use efficiency, stress resilience, productivity and yield. 

Abstract The confluence between high-energy physics and condensed matter has produced groundbreaking results via unexpected connections between the two traditionally disparate areas. In this work, we elucidate additional connectivity between high-energy and condensed matter physics by examining the interplay between spin-orbit interactions and local symmetry-breaking magnetic order in the magnetotransport of thin-film magnetic semimetal FeRh. We show that the change in sign of the normalized longitudinal magnetoresistance observed as a function of increasing in-plane magnetic field results from changes in the Fermi surface morphology. We demonstrate that the geometric distortions in the Fermi surface morphology are more clearly understood via the presence of pseudogravitational fields in the low-energy theory. The pseudogravitational connection provides additional insights into the origins of a ubiquitous phenomenon observed in many common magnetic materials and points to an alternative methodology for understanding phenomena in locally-ordered materials with strong spin-orbit interactions. 

Proximal remote sensing offers a powerful tool for high-throughput phenotyping of plants for assessing stress response. Bean plants, an important legume for human consumption, are often grown in regions with limited rainfall and irrigation and are therefore bred to further enhance drought tolerance. We assessed physiological (stomatal conductance and predawn and midday leaf water potential) and ground- and tower-based hyperspectral remote sensing (400 to 2,400 nm and 400 to 900 nm, respectively) measurements to evaluate drought response in 12 common bean and 4 tepary bean genotypes across 3 field campaigns (1 predrought and 2 post-drought). Hyperspectral data in partial least squares regression models predicted these physiological traits ( R 2 = 0.20 to 0.55; root mean square percent error 16% to 31%). Furthermore, ground-based partial least squares regression models successfully ranked genotypic drought responses similar to the physiologically based ranks. This study demonstrates applications of high-resolution hyperspectral remote sensing for predicting plant traits and phenotyping drought response across genotypes for vegetation monitoring and breeding population screening. 

Abstract Within the broad and deep field of topological materials, there are an ever-increasing number of materials that harbor topological phases. While condensed matter physics continues to probe the exotic physical properties resulting from the existence of topological phases in new materials, there exists a suite of “well-known” topological materials in which the physical properties are well-characterized, such as Bi 2 Se 3 and Bi 2 Te 3 . In this context, it is then appropriate to ask if the unique properties of well-explored topological materials may have a role to play in applications that form the basis of a new paradigm in information processing devices and architectures. To accomplish such a transition from physical novelty to application based material, the potential of topological materials must be disseminated beyond the reach of condensed matter to engender interest in diverse areas such as: electrical engineering, materials science, and applied physics. Accordingly, in this review, we assess the state of current electronic device applications and contemplate the future prospects of topological materials from an applied perspective. More specifically, we will review the application of topological materials to the general areas of electronic and magnetic device technologies with the goal of elucidating the potential utility of well-characterized topological materials in future information processing applications. 

Abstract Sap velocity measurements are useful in fields ranging from plant water relations to hydrology at a variety of scales. Techniques based on pulses of heat are among the most common methods to measure sap velocity, but most lack ability to measure velocities across a wide range, including very high, very low and negative velocities (reverse flow). We propose a new method, the double-ratio method (DRM), which is robust across an unprecedented range of sap velocities and provides real-time estimates of the thermal diffusivity of wood. The DRM employs one temperature sensor upstream (proximal) and two sensors downstream (distal) to the source of heat. This facilitates several theoretical, heat-based approaches to quantifying sap velocity. We tested the DRM using whole-tree lysimetry in Eucalyptus cypellocarpa L.A.S. Johnson and found strong agreement across a wide range of velocities.