Laser ablation is potentially important for nanofabrication but can suffer from poor reproducibility, as it is highly sensitive to even small fluctuations in the laser energy. The authors exploit nonlinear effects in the propagation of high-intensity light through transparent media to control ablation of ultrathin (8 nm) polymer films, achieving subwavelength resolution and a tolerance to energy fluctuations that allows high reproducibility. They also show conversely how thin-film laser ablation can be used to profile laser beams undergoing self-focusing and filamentation.

Mass spectrometry is a key analytical tool in many disciplines, as it provides accurate identification of unknown chemical components in complex mixtures. The authors demonstrate that using laser cooling significantly increases the phase-space density of this assay, improving both mass resolution and detection limits by better than an order of magnitude.

Laser ablation is potentially important for nanofabrication but can suffer from poor reproducibility, as it is highly sensitive to even small fluctuations in the laser energy. The authors exploit nonlinear effects in the propagation of high-intensity light through transparent media to control ablation of ultrathin (8 nm) polymer films, achieving subwavelength resolution and a tolerance to energy fluctuations that allows high reproducibility. They also show conversely how thin-film laser ablation can be used to profile laser beams undergoing self-focusing and filamentation.

Multiphase flow in porous media is important in many technological and natural systems, including filtration, fuel cells, and microfluidics. Systems of interest often feature “mixed wettability”, with wetting domains distributed over many length scales, yet systematic studies of the effects of scale on flow are rare. Using capillary pressure saturation plus x-ray microtomography imaging to study model systems, the authors observe strong dissipation and smoothing of propagating liquid fronts due to heterogeneities smaller than the pores—a feature qualitatively missed in previous studies.

Yttrium iron garnet (Y${}_3$Fe${}_5$O${}_{12}$, YIG) seems to be a prime material for spintronics, but the threshold currents associated with its current-induced spin-wave excitation are not well understood. Meanwhile, spin-torque ferromagnetic resonance (ST-FMR) is known to be a noninvasive probe of the spin-orbit coupling between currents and magnetization in ferromagnet/normal-metal bilayers. The authors’ show that ST-FMR can be used to unveil the current-induced magnetization dynamics of magnetic insulators like YIG–a development that may pave the way for low-power devices using such materials.

Sulfur cathodes have much larger capacities than do the components in commercial lithium-ion batteries, but their long-term performance suffers due to diffusion of soluble polysulfides into the electrolyte. This first-principles molecular dynamics study reveals the formation at high Li/S ratios of large, $insoluble$ Li-S clusters that ultimately fuse into a network, and also predicts stabilization of soluble polysulfides by functionalized graphene-based materials incorporated into the cathode. These results offer a road map for progress in battery technology.

Although the traditional metal-on-semiconductor field-effect transistor (MOSFET) has been a workhorse in information processing for decades, we must now consider its successor. To make spintronics a reality, by analogy we need a “spin MOSFET”. The authors demonstrate room-temperature operation of just such a device, in which a flow of spin angular momentum in nondegenerate silicon is controlled by an external gate voltage.

Thermophotovoltaic devices convert heat to electricity, and are valuable for both solar applications and waste-heat recovery. In this work, the authors show that a graphene-on-silicon Schottky photodiode both dramatically increases radiative heat transfer due to the materials’ plasmonic properties, and bypasses the need for $p-n$ junctions as are used in traditional semiconductors, making the device cheap and simple.

It has been proposed that organic-inorganic perovskites may provide the “disruptive” technology needed to deliver widespread and affordable solar power. To reach this goal, a detailed understanding of their material properties and behavior in working devices is needed. The authors present a robust model that explains charge recombination in the presence of subgap trap states in these materials. This study provides concrete predictions regarding the most important material parameters for improved solar-cell performance of these perovskites.

The Weibull distribution is often used to predict the fracture of brittle materials, based on a “weakest link” hypothesis, but it may not be an apt description. This is especially true for so-called quasibrittle materials such as ceramics, in which subcritical cracking during loading is significant. The authors use analytical and numerical arguments to explain the shortcomings of the traditional approach, and demonstrate that several orders of magnitude improvement in failure prediction can be achieved by using a simple nonlinear transform.

Noise enhances the detection threshold of neural oscillators, thanks to a phenomenon known as stochastic resonance. Taking advantage of the stochastic magnetization fluctuations that emerge at the nanoscale, the authors apply the strategy of leveraging noise to achieve low-power, robust synchronization of magnetic oscillators. This work opens the path to spintronic bio-inspired computing applications.

Microscopic defects can degrade the spatially averaged carrier density—and so the performance—of solar cells and light emitters. The authors devise a technique to measure carrier lifetime at high spatial and temporal resolution, and use it to study cadmium telluride, one of the most technologically important materials for thin-film solar cells. They find that carrier depletion near certain defects profoundly influences the effective spatial extent of those defects.

A memristor is a resistor whose resistance depends on how much charge has flowed through it; thus it “remembers” its history, even if its power supply is cut, and is desirable for nonvolatile computer memory and other applications. The authors explain how a hybrid SQUID threaded by half a flux quantum should exhibit phase-dependent conductance, functioning as a memristor.

CuIn${}_{1-x}$Ga${}_x$Se${}_2$ (CIGS) is an important photovoltaic material, but variations in composition and nanoscale textures that form naturally during processing thwart accurate modeling. The authors develop a general formalism to simulate the charge carrier collection in complex multilayered systems, permitting the calculation of the external quantum efficiency of a thin-film solar cell. For a realistic complicated system they find that the collection efficiency in the CIGS layer is almost 100%, while the light absorption in the 1-$\mu$m-thick bottom region is negligible.

Mass spectrometry is a key analytical tool in many disciplines, as it provides accurate identification of unknown chemical components in complex mixtures. The authors demonstrate that using laser cooling significantly increases the phase-space density of this assay, improving both mass resolution and detection limits by better than an order of magnitude.