Artificial Intelligence (AI) has reached memory studies in earnest. This partly reflects the hype around recent developments in generative AI (genAI), machine learning, and large language models (LLMs). But how can memory studies scholars handle this hype? Focusing on genAI applications, in particular so-called ‘chatbots’ (transformer-based instruction-tuned text generators), this commentary highlights five areas of critique that can help memory scholars to critically interrogate AI’s implications for their field. These are: (1) historical critiques that complicate AI’s common historical narrative and historicize genAI; (2) technical critiques that highlight how genAI applications are designed and function; (3) praxis critiques that centre on how people use genAI; (4) geopolitical critiques that recognize how international power dynamics shape the uneven global distribution of genAI and its consequences; and (5) environmental critiques that foreground genAI’s ecological impact. For each area, we highlight debates and themes that we argue should be central to the ongoing study of genAI and memory. We do this from an interdisciplinary perspective that combines our knowledge of digital sociology, media studies, literary and cultural studies, cognitive psychology, and communication and computer science. We conclude with a methodological provocation and by reflecting on our own role in the hype we are seeking to dispel.

The breakup and coalescence of particle aggregates confined at the interface of turbulent liquid layers are investigated experimentally and theoretically. In particular, we consider conductive fluid layers driven by Lorentz forces and laden with millimetre-scale floating particles. These form aggregates held together by capillary attraction and disrupted by the turbulent motion. The process is fully characterised by imaging at high spatio-temporal resolution. The breakup frequency $\varOmega$ is proportional to the mean strain rate and follows a power-law scaling $\varOmega \sim D^{3\text{/}2}$, where $D$ is the size of the aggregate, attributed to the juxtaposition of particle-scale strain cells. The daughter aggregate size distribution exhibits a robust U-shape, which implies erosion of small fragments as opposed to even splitting. The coalescence kernel $\varGamma$ between pairs of aggregates of size $D_{1}$ and $D_{2}$ scales as $\varGamma \sim ( D_{1} + D_{2} )^{2}$, which is consistent with gas-kinetic dynamics. These relations, which apply to regimes dominated both by capillary-driven aggregation and by drag-driven breakup, are implemented into the population balance equation for the evolution of the aggregate number density. Comparison with the experiments shows that the framework captures the observed distribution for aggregates smaller than the forcing length scale.

Perfluorinated compounds (PFCs) are synthetic chemicals commonly used in various industries for their water-, grease-, and stain-repellent properties. These compounds are highly persistent in the environment and can be absorbed by farm animals, subsequently contaminating animal-derived products. This contamination poses a significant health risk to humans who consume these products. Previous studies have identified cow's milk as one of the primary animal products contaminated with PFCs. However, it remains unclear which specific PFCs increase in concentrations over time. In this study, we analysed data on the concentrations of 24 PFCs in cow's milk sourced from a milk processing plant in Taiyuan, Shanxi Province, China, over a three-year period, as provided by the National Agriculture Science Data Centre. Our analysis revealed that perfluoropentanoic acid (PFPeA) and perfluorobutanoic acid (PFBA) were the dominant PFCs that tended to accumulate in cow's milk over time. Consequently, consumers and milk producers should monitor the levels of PFPeA and PFBA in cow's milk to mitigate potential health risks associated with these pollutants.

In this paper, a wideband reconfigurable reflectarray antenna (RRA) using 1-bit resolution for beam scanning with two-dimensional (2D) capability is presented at Ku-band. A 1-bit RRA element with a rectangular patch embedded with slots is proposed for broadband operation. Each element is equipped with a single PIN diode, allowing for resonance tuning while ensuring low cost and minimal power consumption. According to the simulation results, the proposed element is capable of 1-bit phase resolution with a phase difference of ${180^\circ \pm 20^\circ}$ stability from 11.27 to 13.74 GHz, which corresponds to an approximate bandwidth of 19.75%. To demonstrate its capabilities, we developed, fabricated, and tested a wideband electronically RRA with ${14 \times 14}$ elements. The experimental results demonstrate that the realized maximum gain in the broadside direction is 21.1 dB with a peak aperture efficiency of 20.9%. 2D beam scanning within ${\pm50^\circ}$ angular range are obtained and the scan gain reduction is 1.88 dB for ${-50^\circ}$ scanned beam in E-plane while 2.21 dB for ${50^\circ}$ scanned beam in H-plane. The 1-dB gain bandwidth of the RRA is 15.1%.

Turbulence exhibits a striking duality: it drives concentrated substances apart, enhancing mixing and transport, while simultaneously drawing particles and bubbles into collisions. Little experimental data exist to clarify the latter process due to challenges in techniques for resolving bubble pairs from afar to coalescence via turbulent entrainment, film drainage and rupture. In this work, we tracked pairs of bubbles across nearly four orders of magnitude in spatial resolution, capturing the entire dynamics of collision and coalescence. The resulting statistics show that critical variables exhibit scalings with bubble size in ways that are different from some classical models, which were developed based on assumptions that bubble collision and coalescence only mirror the key scales of the surrounding turbulence. Furthermore, contrary to classical models which suggest that coalescence favours slow collision velocity, we find a ‘Goldilocks zone’ of relative velocities for bubble coalescence, where there is an optimal coalescence velocity that is neither too high nor too low. This zone arises from the competition between bubble–bubble and bubble–eddy interactions. Incorporating this zone into the new model yields excellent agreement with experimental results, laying a foundation for better predictions for many multiphase flow systems.