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Barocaloric effects─solid-state thermal changes induced by the application and removal of hydrostatic pressure─offer the potential for energy-efficient heating and cooling without relying on volatile refrigerants. Here, we report that dialkylammonium halides─organic salts featuring bilayers of alkyl chains templated through hydrogen bonds to halide anions─display large, reversible, and tunable barocaloric effects near ambient temperature. The conformational flexibility and soft nature of the weakly confined hydrocarbons give rise to order–disorder phase transitions in the solid state that are associated with substantial entropy changes (>200 J kg–1 K–1) and high sensitivity to pressure (>24 K kbar–1), the combination of which drives strong barocaloric effects at relatively low pressures. Through high-pressure calorimetry, X-ray diffraction, and Raman spectroscopy, we investigate the structural factors that influence pressure-induced phase transitions of select dialkylammonium halides and evaluate the magnitude and reversibility of their barocaloric effects. Furthermore, we characterize the cyclability of thin-film samples under aggressive conditions (heating rate of 3500 K s–1 and over 11,000 cycles) using nanocalorimetry. Taken together, these results establish dialkylammonium halides as a promising class of pressure-responsive thermal materials. 

Soft, tip-extending "vine" robots offer a unique mode of inspection and manipulation in highly constrained environments. For practicality, it is desirable that the distal end of the robot can be manipulated freely, while the body remains stationary. However, in previous vine robots, either the shape of the body was fixed after growth with no ability to manipulate the distal end, or the whole body moved together with the tip. Here, we present a concept for shape-locking that enables a vine robot to move only its distal tip, while the body is locked in place. This is achieved using two inextensible, pressurized, tip-extending, chambers that "grow" along the sides of the robot body, preserving curvature in the section where they have been deployed. The length of the locked and free sections can be varied by controlling the extension and retraction of these chambers. We present models describing this shape-locking mechanism and workspace of the robot in both free and constrained environments. We experimentally validate these models, showing an increased dexterous workspace compared to previous vine robots. Our shape-locking concept allows improved performance for vine robots, advancing the field of soft robotics for inspection and manipulation in highly constrained environments. 

Controlling diamond structures with nanometer precision is fundamentally challenging owing to their extreme and far‐from‐equilibrium synthetic conditions. State‐of‐the‐art techniques, including detonation, chemical vapor deposition, mechanical grinding, and high‐pressure‐high‐temperature synthesis, yield nanodiamond particles with a broad distribution of sizes. Despite many efforts, the direct synthesis of nanodiamonds with precisely controlled diameters remains elusive. Here the geochemistry‐inspired synthesis of sub‐5 nm nanodiamonds with sub‐nanometer size deviation is described. High‐pressure‐high‐temperature treatment of uniform iron carbide nanoparticles embedded in iron oxide matrices yields nanodiamonds with tunable diameters down to 2.13 and 0.22 nm standard deviation. A self‐limiting, redox‐driven, and diffusion‐controlled solid‐state reaction mechanism is proposed and supported by in situ X‐ray diffraction, ex situ characterizations, and computational modeling. This work provides a unique mechanism for the precise control of nanostructured diamonds under extreme conditions and paves the road for the full realization of their potential in emerging technologies.

 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.