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At least 721 records · Page 40

Polarization and domains in wurtzite ferroelectrics: Fundamentals and applications

The 2019 report of ferroelectricity in (Al,Sc)N [Fichtner et al., J. Appl. Phys. 125, 114103 (2019)] broke a long-standing tradition of considering AlN the textbook example of a polar but non-ferroelectric material. Combined with the recent emergence of ferroelectricity in HfO2-based fluorites [Böscke et al., Appl. Phys. Lett. 99, 102903 (2011)], these unexpected discoveries have reinvigorated studies of integrated ferroelectrics, with teams racing to understand the fundamentals and/or deploy these new materials—or, more correctly, attractive new capabilities of old materials—in commercial devices. The five years since the seminal report of ferroelectric (Al,Sc)N [Fichtner et al., J. Appl. Phys. 125, 114103 (2019)] have been particularly exciting, and several aspects of recent advances have already been covered in recent review articles [Jena et al., Jpn. J. Appl. Phys. 58, SC0801 (2019); Wang et al., Appl. Phys. Lett. 124, 150501 (2024); Kim et al., Nat. Nanotechnol. 18, 422–441 (2023); and F. Yang, Adv. Electron. Mater. 11, 2400279 (2024)]. We focus here on how the ferroelectric wurtzites have made the field rethink domain walls and the polarization reversal process—including the very character of spontaneous polarization itself—beyond the classic understanding that was based primarily around perovskite oxides and extended to other chemistries with various caveats. The tetrahedral and highly covalent bonding of AlN along with the correspondingly large bandgap lead to fundamental differences in doping/alloying, defect compensation, and charge distribution when compared to the classic ferroelectric systems; combined with the unipolar symmetry of the wurtzite structure, the result is a class of ferroelectrics that are both familiar and puzzling, with characteristics that seem to be perfectly enabling and simultaneously nonstarters for modern integrated devices. The goal of this review is to (relatively) quickly bring the reader up to speed on the current—at least as of early 2025—understanding of domains and defects in wurtzite ferroelectrics, covering the most relevant work on the fundamental science of these materials as well as some of the most exciting work in early demonstrations of device structures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Preventing ash from poisoning proton–boron 11 fusion plasmas

Proton–boron 11 (pB11) fusion is safe and clean, but also difficult to harness for breakeven power production. Particularly deleterious are fusion-born alpha particles, which massively increase both plasma pressure and bremsstrahlung losses unless they are pulled promptly from the plasma. We show that even if one cannot extract the alphas quickly, one can still achieve net power production, by separating the plasma into two regions: a fusion region, accessible to all species, and an alpha storage region, accessible only to alphas and electrons. This new demixing strategy could make pB11 fusion much easier to achieve.

Ochs, Ian E. (ORCID:0000000260029169)↗

Bremsstrahlung constraints on proton-boron 11 inertial fusion

Proton-boron 11 (pB11) fusion is relatively safe and clean, but difficult to use for net power production, since bremsstrahlung radiation tends to radiate away power more quickly than it can be generated by fusion power, particularly once poisoning by alpha particles is taken into account. While in magnetic confinement fusion, this problem can be addressed by deconfining the alphas, in inertial confinement fusion (ICF), the alphas that heat the plasma linger for the duration of the reaction. Thus, it becomes essential to trap the bremsstrahlung radiation in the hotspot. Through burn simulations incorporating bremsstrahlung emission and reabsorption, we infer the necessary conditions to capture enough radiation to produce scientific breakeven in a pB11 ICF plasma. We find that breakeven requires a stagnation areal density roughly two orders of magnitude higher than the current state-of-the-art, at pressures three orders of magnitude higher.

Alpha particles↗

Analytic rate theory of polariton relaxation that explains long polariton lifetime

Hybridization of a molecular exciton with a quantized photon creates a polariton. Despite extensive experimental investigations, the apparent lifetime of the exciton–polariton is not well-understood. For this work, we examined the steady-state population dynamics for a Holstein–Tavis–Cumming Hamiltonian to illuminate the long-term polaritonic dynamics and lifetime of the exciton–polariton in an optical cavity. For a realistic description of polariton relaxation, cavity loss and various exciton decay channels are included in the model. We found that in the presence of weak but finite exciton loss, the apparent lifetime of the lower polariton coincides with the out-of-cavity exciton lifetime and is independent of cavity-matter detuning. This is a simple explanation for the experimentally observed lifetimes for exciton polaritons and theoretically justifies the dark state reservoir hypothesis. Furthermore, if the upper polariton is initially populated, the system reaches the steady state very quickly, leading to single-exponential polariton relaxation. Starting from the lower polariton leads to a longer pre-steady-state time period, leading to double-exponential relaxation. Finally, we considered the effect of site orientational disorders and the exciton frequency disorderers. Under the collective limit, the effects of this disorder can be included in Fermi’s golden rule population dynamics without explicit sampling. For the exciton energy disorders, numerical calculations are needed. Our theoretical framework is applicable to interpret exciton–polariton experiments, especially related to the measured apparent lifetime of polaritons.

Chemical dynamics↗

Robustness of inertial fusion energy relevant implosions to low-mode asymmetries

Inertial confinement fusion implosions for power production need to be robust. Degradation sources need to be understood and considered for an economic power plant. In this work, the impact of low-mode asymmetries on yield is studied using 2D radiation hydrodynamics simulations for inertial fusion energy relevant implosions. First, a high-gain indirectly driven capsule design is developed. This design is subsequently degraded with low-mode drive asymmetries. The results show that yield is constant with increasing amounts of asymmetry until a cliff is reached where the yield quickly drops below ignition. Robustness arises because the degraded hotspot still has enough time to get to ignition before capsule decompression. This robustness occurs even though the asymmetry couples less energy to the hotspot and causes decompression to occur sooner. The robustness is linked to the generalized Lawson parameter, χ⁠. The value of χ steadily decreases with increasing asymmetry. Once χ is close to one, the hotspot is no longer able to ignite before the capsule decompresses. A simple piston model is used to predict where the robustness cliff is for any design. The trade-off between yield and robustness is also demonstrated.

Physics - Plasma physics↗

High-throughput, combinatorial synthesis of multimetallic nanoclusters

Significance Multielement nanomaterials hold great promise for various applications due to their widely tunable surface chemistry, yet it remains challenging to efficiently study this multidimensional space. Conventional approaches are typically slow and depend on serendipity, while a robust and general synthesis is still lacking among increasingly complex compositions. We report a high-throughput technique for combinatorial compositional design (formulation in solution phases) and rapid synthesis (within seconds) of ultrafine multimetallic nanoclusters with a homogeneous alloy structure. We synthesized and screened the PtPdRhRuIrFeCoNi compositional space using scanning droplet cell electrochemistry, with two promising catalysts quickly identified and further verified in a rotating disk setup. The reported high-throughput approach establishes a facile and reliable pipeline to significantly accelerate material discovery in multimetallic nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty

Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria with national coverage. These gridded population estimates and areal population totals derived from them are accompanied by estimates of uncertainty based on Bayesian posterior probabilities. The model had an overall error rate of 67 people per hectare (mean of absolute residuals) or 43% (using scaled residuals) for predictions in out-of-sample survey areas (approximately 3 ha each), with increased precision expected for aggregated population totals in larger areas. This statistical approach represents a significant step toward estimating populations at high resolution with national coverage in the absence of a complete and recent census, while also providing reliable estimates of uncertainty to support informed decision making.

99 GENERAL AND MISCELLANEOUS↗

The myosin interacting-heads motif present in live tarantula muscle explains tetanic and posttetanic phosphorylation mechanisms

Striated muscle contraction involves sliding of actin thin filaments along myosin thick filaments, controlled by calcium through thin filament activation. In relaxed muscle, the two heads of myosin interact with each other on the filament surface to form the interacting-heads motif (IHM). A key question is how both heads are released from the surface to approach actin and produce force. Here we used time-resolved synchrotron X-ray diffraction to study tarantula muscle before and after tetani. The patterns showed that the IHM is present in live relaxed muscle. Tetanic contraction produced only a very small backbone elongation, implying that mechanosensing—proposed in vertebrate muscle—is not of primary importance in tarantula. Rather, thick filament activation results from increases in myosin phosphorylation that release a fraction of heads to produce force, with the remainder staying in the ordered IHM configuration. After the tetanus, the released heads slowly recover toward the resting, helically ordered state. During this time the released heads remain close to actin and can quickly rebind, enhancing the force produced by posttetanic twitches, structurally explaining posttetanic potentiation. Taken together, these results suggest that, in addition to stretch activation in insects, two other mechanisms for thick filament activation have evolved to disrupt the interactions that establish the relaxed helices of IHMs: one in invertebrates, by either regulatory light-chain phosphorylation (as in arthropods) or Ca 2+ -binding (in mollusks, lacking phosphorylation), and another in vertebrates, by mechanosensing.

59 BASIC BIOLOGICAL SCIENCES↗

Peatland warming strongly increases fine-root growth

Belowground climate change responses remain a key unknown in the Earth system. Plant fine-root response is especially important to understand because fine roots respond quickly to environmental change, are responsible for nutrient and water uptake, and influence carbon cycling. However, fine-root responses to climate change are poorly constrained, especially in northern peatlands, which contain up to two-thirds of the world’s soil carbon. We present fine-root responses to warming between +2 °C and 9 °C above ambient conditions in a whole-ecosystem peatland experiment. Warming strongly increased fine-root growth by over an order of magnitude in the warmest treatment, with stronger responses in shrubs than in trees or graminoids. In the first year of treatment, the control (+0 °C) shrub fine-root growth of 0.9 km m -2 y -1 increased linearly by 1.2 km m -2 y -1 (130%) for every degree increase in soil temperature. An extended belowground growing season accounted for 20% of this dramatic increase. In the second growing season of treatment, the shrub warming response rate increased to 2.54 km m -2 °C -1 . Soil moisture was negatively correlated with fine-root growth, highlighting that drying of these typically water-saturated ecosystems can fuel a surprising burst in shrub belowground productivity, one possible mechanism explaining the “shrubification” of northern peatlands in response to global change. This previously unrecognized mechanism sheds light on how peatland fine-root response to warming and drying could be strong and rapid, with consequences for the belowground growing season duration, microtopography, vegetation composition, and ultimately, carbon function of these globally relevant carbon sinks.

54 ENVIRONMENTAL SCIENCES↗

Reinforcement learning for bluff body active flow control in experiments and simulations

Significance Reinforcement learning (RL) has been applied effectively in games and robotic manipulation. We demonstrate the effectiveness of RL in experimental fluid mechanics by applying it to reduce the drag of circular cylinders in turbulent flow, a canonical fluid–structure interaction problem. Although physics agnostic, RL managed to reduce the drag by 30 % or reach another specified optimum point very quickly. Following this discovery, we used high-fidelity simulations to probe the underlying physical mechanisms so that the discovered control techniques can be generalized to other similar flow problems. More broadly, RL-guided active control can lead to efficient exploration of additional flow-control strategies in experimental fluid mechanics, potentially paving the way for accelerating scientific discovery and different designs in flow-related engineering problems.

42 ENGINEERING↗

Structural relaxation and crystallization in supercooled water from 170 to 260 K

The structural relaxation and crystallization of deeply supercooled water are investigated in transiently-heated nanoscale water films using infrared spectroscopy for temperatures between 170 and 260 K. For temperatures above ~230 K, the relaxation kinetics can be fit with a simple exponential decay which is characteristic of normal liquids. At lower temperatures, increasingly non-exponential decay is observed indicating the onset of heterogeneous dynamics. Water’s relaxation rate depends on its initial structure with hyper-quenched glassy water (HQW) typically relaxing more quickly than low-density amorphous solid water (LDA). At all temperatures, the relaxation time, trel is faster than the crystallization time, txtal. For HQW, the ratio, txtal/trel, goes through a minimum at ~198 K where it is about 60. The research was designed and supervised by GAK and BDK. LK and WAT conducted the experiments and analyzed the data. LK and GAK wrote the manuscript, with input from all authors.

Kringle, Loni M.↗

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures

Significance The efficient utilization of electrical energy is an increasingly important challenge, especially as renewable energy sources become cheaper and demand increases. Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy. Their commercial viability and ultimate adoption hinge on attaining high current densities to drive cost competitiveness. There are limited opportunities for engineering FTE materials, as these are often random, disordered media. Alternatively, three-dimensional (3D)–printed FTEs provide the opportunity to quickly explore the impact of engineered electrode architectures on device performance. We demonstrate that 3D-printed FTEs have the potential to exceed the performance of conventional materials by using the expanded design freedom to engineer the internal flow.

30 DIRECT ENERGY CONVERSION↗

Efficient computation of N -point correlation functions in D dimensions

We present efficient algorithms for computing the N-point correlation functions (NPCFs) of random fields in arbitrary D-dimensional homogeneous and isotropic spaces. Such statistics appear throughout the physical sciences and provide a natural tool to describe stochastic processes. Typically, algorithms for computing the NPCF components have $\mathscr O$(n N ) complexity (for a dataset containing n particles); their application is thus computationally infeasible unless N is small. By projecting the statistic onto a suitably defined angular basis, we show that the estimators can be written in a separable form, with complexity $\mathscr O$(n 2 ) or $\mathscr O$(n g log n g ) if evaluated using a Fast Fourier Transform on a grid of size n g . Our decomposition is built upon the D-dimensional hyperspherical harmonics; these form a complete basis on the (D – 1) sphere and are intrinsically related to angular momentum operators. Concatenation of (N – 1) such harmonics gives states of definite combined angular momentum, forming a natural separable basis for the NPCF. As N and D grow, the number of basis components quickly becomes large, providing a practical limitation to this (and all other) approaches: However, the dimensionality is greatly reduced in the presence of symmetries; for example, isotropic correlation functions require only states of zero combined angular momentum. We provide a Julia package implementing our estimators and show how they can be applied to a variety of scenarios within cosmology and fluid dynamics. The efficiency of such estimators will allow higher-order correlators to become a standard tool in the analysis of random fields.

97 MATHEMATICS AND COMPUTING↗

Reimport of carbon from cytosolic and vacuolar sugar pools into the Calvin–Benson cycle explains photosynthesis labeling anomalies

Significance Photosynthesis metabolites are quickly labeled when 13 CO 2 is fed to leaves, but the time course of labeling reveals additional contributing processes involved in the metabolic dynamics of photosynthesis. The existence of three such processes is demonstrated, and a metabolic flux model is developed to explore and characterize them. The model is consistent with a slow return of carbon from cytosolic and vacuolar sugars into the Calvin–Benson cycle through the oxidative pentose phosphate pathway. Our results provide insight into how carbon assimilation is integrated into the metabolic network of photosynthetic cells with implications for global carbon fluxes.

59 BASIC BIOLOGICAL SCIENCES↗

Is stochastic thermodynamics the key to understanding the energy costs of computation?

The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has exploded. Importantly, real-world computers obey multiple physical constraints on how they work, which affects their thermodynamic properties. Moreover, many of these constraints apply to both naturally occurring computers, like brains or Eukaryotic cells, and digital systems. Most obviously, all such systems must finish their computation quickly, using as few degrees of freedom as possible. This means that they operate far from thermal equilibrium. Furthermore, many computers, both digital and biological, are modular, hierarchical systems with strong constraints on the connectivity among their subsystems. Yet another example is that to simplify their design, digital computers are required to be periodic processes governed by a global clock. None of these constraints were considered in 20th-century analyses of the thermodynamics of computation. The new field of stochastic thermodynamics provides formal tools for analyzing systems subject to all of these constraints. We argue here that these tools may help us understand at a far deeper level just how the fundamental thermodynamic properties of physical systems are related to the computation they perform.

computation↗

Stochastic machine learning via sigma profiles to build a digital chemical space

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Behavioral resilience via dynamic circuit firing homeostasis

Homeostatic regulation ensures stable neural circuit output under changing conditions. We find that in Drosophila larvae, either presynaptic weakening due to perturbation of transmitter release or postsynaptic weakening due to perturbation of glutamate receptors at synapses between motor neuron (MN) and muscle has little impact on locomotion, suggesting a nonsynaptic compensatory mechanism. In vivo imaging shows that five different forms of synaptic weakening increase the duration of activity bouts in type I MNs. Strikingly, this compensation is input selective: occurring only in the tonic type Ib MN, not the phasic type Is MN that innervates the same muscle. Moreover, an inhibitory class of central pre-MNs that innervates the tonic—but not phasic—input decreases in activity. The adjustment in activity occurs remarkably quickly: within minutes of synapse perturbation. We propose that MN firing is dynamically regulated by two coordinated mechanisms: a cell-autonomous adjustment of MN excitability and a circuit adjustment of inhibitory central drive. The input selectivity of this process suggests homeostatic adjustment to maintain tonic drive but hold constant the phasic drive that organizes locomotory wave patterns.

59 BASIC BIOLOGICAL SCIENCES↗

Acclimation to high and low diurnal light is flexible in Chlamydomonas reinhardtii

Chlamydomonas acclimates to repeated low (LL) or high light (HL) days by changing the abundance of photosynthetic complexes and the ultrastructure of its thylakoid membranes. These phenotypes persist through the night phases, suggesting a readiness for the daylight environment that is routinely experienced despite the intervening dark periods [S. Dupuis et al., Plant Cell 37, koaf086 (2025), 10.1093/plcell/koaf086]. Here, we investigate how prior acclimation impacts algal fitness upon a change in daylight intensity and how quickly Chlamydomonas can reprogram its photoprotective strategy in a diurnal context. We performed a systems analysis of synchronized populations acclimated to diurnal LL when subjected to HL days and of populations acclimated to diurnal HL when subjected to LL days. In the latter case, diurnal photoacclimation decreased fitness during the first day at a new light intensity: HL-acclimated cells barely increased in size over the first LL period, and they failed to complete a cell cycle. However, although LL-acclimated cells showed severe photodamage after 6 h of HL, they recovered chloroplast form and function later that afternoon and successfully divided at nightfall. These cells rapidly altered their thylakoid membrane ultrastructure, increased their photoprotective quenching capacity, and decreased their inventory of photosystem and antenna proteins by the end of the first HL day. Transcriptomic and proteomic analyses revealed rapid induction of thousands of genes, including those encoding proteases, chaperones, and other proteins involved in the chloroplast unfolded protein response. These results show that the alga is highly flexible and competent to rapidly acclimate to changes in diurnal light intensity.

Diel↗