Iron-doped nickel layered double hydroxides (LDHs) are among the most active heterogeneous water oxidation catalysts. Due to inter-spin interactions, however, the high density of magnetic centers results in line-broadening in magnetic resonance spectra. As a result, gaining atomic-level insight into the catalytic mechanism via electron paramagnetic resonance (EPR) is not generally possible. To circumvent spin-spin broadening, iron and nickel atoms were doped into non-magnetic [ZnAl]-LDH materials and the coordination environments of the isolated Fe(III) and Ni(II) sites were characterized. Multifrequency EPR spectroscopy identified two distinct Fe(III) sites (S = 5/2) in [Fe:ZnAl]-LDH. Changes in zero field splitting (ZFS) were induced by dehydration of the material, revealing that one of the Fe(III) sites is solvent-exposed (i.e. at an edge, corner, or defect site). These solvent-exposed sites feature an axial ZFS of 0.21 cm-1 when hydrated. The ZFS increases dramatically upon dehydration (to -1.5 cm-1), owing to lower symmetry and a decrease in the coordination number of iron. The ZFS of the other (“inert”) Fe(III) site maintains an axial ZFS of 0.19-0.20 cm-1 under both hydrated and dehydrated conditions. We observed a similar effect in [Ni:ZnAl]-LDH materials; notably, Ni(II) (S = 1) atoms displayed a single, small ZFS (±0.30 cm-1) in hydrated material, whereas two distinct Ni(II) ZFS values (±0.30 and ±1.1 cm-1) were observed in the dehydrated samples. Although the magnetically-dilute materials were not active catalysts, the identification of model sites in which the coordination environments of iron and nickel were particularly labile (e.g. by simple vacuum drying) is an important step towards identifying sites in which the coordination number may drop spontaneously in water, a probable mechanism of water oxidation in functional materials.
The brain has persistent internal states that can modulate every aspect of an animal’s mental experience1,2,3,4. In complex tasks such as foraging, the internal state is dynamic5,6,7,8. Caenorhabditis elegans alternate between local search and global dispersal5. Rodents and primates exhibit trade-offs between exploitation and exploration6,7. However, fundamental questions remain about how persistent states are maintained in the brain, which upstream networks drive state transitions and how state-encoding neurons exert neuromodulatory effects on sensory perception and decision-making to govern appropriate behaviour. Here, using tracking microscopy to monitor whole-brain neuronal activity at cellular resolution in freely moving zebrafish larvae9, we show that zebrafish spontaneously alternate between two persistent internal states during foraging for live prey (Paramecia). In the exploitation state, the animal inhibits locomotion and promotes hunting, generating small, localized trajectories. In the exploration state, the animal promotes locomotion and suppresses hunting, generating long-ranging trajectories that enhance spatial dispersion. We uncover a dorsal raphe subpopulation with persistent activity that robustly encodes the exploitation state. The exploitation-state-encoding neurons, together with a multimodal trigger network that is associated with state transitions, form a stochastically activated nonlinear dynamical system. The activity of this oscillatory network correlates with a global retuning of sensorimotor transformations during foraging that leads to marked changes in both the motivation to hunt for prey and the accuracy of motor sequences during hunting. This work reveals an important hidden variable that shapes the temporal structure of motivation and decision-making.
Optical upconversion is a net process by which two low energy photons are converted into one higher energy photon. There is vast potential to exploit upconversion in applications ranging from solar energy and biological imaging to data storage and photocatalysis. Here, we link two upconverting chromophores together to synthesize a series of novel tetracene dimers for use as annihilators. When compared with the monomer annihilator, TIPS–tetracene, the dimers yield a strong enhancement in the triplet fusion process, also known as triplet–triplet annihilation, as demonstrated via a large increase in upconversion efficiency and an order of magnitude reduction of the threshold power for maximum yield. Along with the ongoing rapid improvements to sensitizer materials, the dimerization improvements demonstrated here open the way to a wide variety of emerging upconversion applications.
Triplet fusion upconversion, the conversion of two low-energy photons into one higher-energy photon via excitonic intermediates, has the potential to revolutionize fields as diverse as biological imaging, photovoltaics, and optogenetics. However, important hurdles to widespread application still exist; for example, the vast majority of demonstrations are in nonpolar solvents, limiting applications. Furthermore, the necessary high concentrations of dyes limit optical penetration depth. Efforts toward aqueous solutions utilizing micelles and other nanoencapsulants have been limited by poor efficiencies or scatter from the nanoparticles. Here, we demonstrate a facile micellular fabrication method that drives a high boiling point solvent into the core of a block copolymer micelle, greatly reducing molecular aggregation. We show that this simple preparation is scalable and provides benefits across five different colors of photon upconversion. We expect this simple, user-friendly, and high-performance system to aid a multitude of photon upconversion applications, in particular, for optogenetics, photodynamic therapy, and photochemistry.
Noninvasive behavioral tracking of animals during experiments is critical to many scientific pursuits. Extracting the poses of animals without using markers is often essential to measuring behavioral effects in biomechanics, genetics, ethology, and neuroscience. However, extracting detailed poses without markers in dynamically changing backgrounds has been challenging. We recently introduced an open-source toolbox called DeepLabCut that builds on a state-of-the-art human pose-estimation algorithm to allow a user to train a deep neural network with limited training data to precisely track user-defined features that match human labeling accuracy. Here, we provide an updated toolbox, developed as a Python package, that includes new features such as graphical user interfaces (GUIs), performance improvements, and active-learning-based network refinement. We provide a step-by-step procedure for using DeepLabCut that guides the user in creating a tailored, reusable analysis pipeline with a graphical processing unit (GPU) in 1–12 h (depending on frame size). Additionally, we provide Docker environments and Jupyter Notebooks that can be run on cloud resources such as Google Colaboratory.
Interest in organic–inorganic hybrid perovskite (ABX3) LEDs has exploded over the past several years, yet significant gains in stability, efficiency, and brightness are required before commercialization is possible, particularly for blue devices. The perovskite composition has been shown to play a crucial role in its performance, yet to date nearly all existing reports focus on tuning the A-site composition. Here, we find that doping the B-site with manganese allows us to achieve bright, efficient, and stable LEDs regardless of A or X composition. By doping with Mn, we demonstrate ultrabright sky-blue, green, and red perovskite LEDs with a maximum brightness of 11800, 97000, and 1470 cd/m2 and quantum efficiencies of 0.58%, 3.2%, and 5.1%, respectively. Crucially, these devices show excellent operational stability, with the sky-blue devices lasting for 20 min and red devices over 5 h with strong spectral stability. Moreover, the green devices showed over 1% efficiency even at higher current densities, ∼2000 mA/cm2. Mn doping allows for universal improvement in perovskite performance and stability, opening the door to a huge number of applications.
Optical upconversion based on triplet fusion (TF), also known as triplet–triplet annihilation, is a process by which two or more low-energy photons are converted to one higher energy photon. This process requires two components, a sensitizer which absorbs the incident low-energy photons and an annihilator which emits the higher energy photons. While much attention has been given to the investigation of new types of sensitizers, very little work has been done on the exploration of new annihilators. In this work, we show that the singlet energy of diketopyrrolopyrroles (DPPs) can be altered by modifying the pendant aryl substituents to the core. This allows us to meet the energetic requirements necessary for TF upconversion and demonstrates DPPs as a new class of annihilator molecules. Using this new DPP platform, the output wavelength from upconversion can easily be tuned, which will greatly diversify the number of applications of DPPs in upconversion technologies.
Recent advances in photoredox catalysis have made it possible to achieve various challenging synthetic transformations, polymerizations and surface modifications1,2,3. All of these reactions require ultraviolet- or visible-light stimuli; however, the use of visible-light irradiation has intrinsic challenges. For example, the penetration of visible light through most reaction media is very low, leading to problems in large-scale reactions. Moreover, reactants can compete with photocatalysts for the absorption of incident light, limiting the scope of the reactions. These problems can be overcome by the use of near-infrared light, which has a much higher penetration depth through various media, notably biological tissue4. Here we demonstrate various photoredox transformations under infrared radiation by utilizing the photophysical process of triplet fusion upconversion, a mechanism by which two low-energy photons are converted into a higher-energy photon. We show that this is a general strategy applicable to a wide range of photoredox reactions. We tune the upconversion components to adjust the output light, accessing both orange light and blue light from low-energy infrared light, by pairwise manipulation of the sensitizer and annihilator. We further demonstrate that the annihilator itself can be used as a photocatalyst, thus simplifying the reaction. This approach enables catalysis of high-energy transformations through several opaque barriers using low-energy infrared light.
Scaling up electrochemical water splitting is nowadays in high demand for hydrogen economy implementation. Tremendous eff orts over the past decade have been focused on exploring alternative catalytic materials, including a variety of earth-abundant transitionmetal-based catalysts, to replace traditional noble metals such as Pt, Ir, or Ru. Nevertheless, few eff orts have been carried out for (1) scalable catalyst synthesis on current collectors and (2) practical device design toward large-scale H2 generation. Herein, we designed a modular alkaline water-splitting electrolyzer system with scaled-up metal foam electrodes covered by low-cost NiMo alloy and Ni3 Fe oxide for efficient hydrogen evolution and oxygen evolution, respectively. An electrolyte circulation system facilitates the mass transport and thus can further boost the H2 generation particularly under large currents. As a result, the overall water-splitting performance of one-unit cell with a dimension of 10 Å~ 10 cm2 under room temperature presents an early onset voltage of 1.54 V and delivered practical currents of 20 and 55 A (9.1 and 25.0 L/h H2 generation) under 2.2 and 2.9 V without iR compensations, respectively. This demonstration could stimulate new focuses in water splitting toward more practical applications.