Hasil untuk "Heat"

Nianbei Li, Jie Ren, Lei Wang et al.

The form of energy termed heat that typically derives from lattice vibrations, i.e., phonons, is usually considered as waste energy and, moreover, deleterious to information processing. However, in this Colloquium, an attempt is made to rebut this common view: By use of tailored models it is demonstrated that phonons can be manipulated similarly to electrons and photons, thus enabling controlled heat transport. Moreover, it is explained that phonons can be put to beneficial use to carry and process information. In the first part ways are presented to control heat transport and to process information for physical systems which are driven by a temperature bias. In particular, a toolkit of familiar electronic analogs for use of phononics is put forward, i.e., phononic devices are described which act as thermal diodes, thermal transistors, thermal logic gates, and thermal memories. These concepts are then put to work to transport, control, and rectify heat in physically realistic nanosystems by devising practical designs of hybrid nanostructures that permit the operation of functional phononic devices; the first experimental realizations are also reported. Next, richer possibilities to manipulate heat flow by use of time-varying thermal bath temperatures or various other external fields are discussed. These give rise to many intriguing phononic nonequilibrium phenomena such as, for example, the directed shuttling of heat, geometrical phase-induced heat pumping, or the phonon Hall effect, which may all find their way into operation with electronic analogs.

S. Sherwood, M. Huber

Jianguo Tan, Youfei Zheng, Xu Tang et al.

Lisan Yu, R. Weller

A. Govorov, H. Richardson

A. Bejan

W. Rohsenow, J. Hartnett, Young I. Cho

J. González-Alonso, C. Teller, Signe Lindgaard Andersen et al.

G. Grest, K. Kremer

Sreyashi Basu, R. Binder, T. Ramalingam et al.

D. Vassilevich

Abstract The heat kernel expansion is a very convenient tool for studying one-loop divergences, anomalies and various asymptotics of the effective action. The aim of this report is to collect useful information on the heat kernel coefficients scattered in mathematical and physical literature. We present explicit expressions for these coefficients on manifolds with and without boundaries, subject to local and non-local boundary conditions, in the presence of various types of singularities (e.g., domain walls). In each case the heat kernel coefficients are given in terms of several geometric invariants. These invariants are derived for scalar and spinor theories with various interactions, Yang–Mills fields, gravity, and open bosonic strings. We discuss the relations between the heat kernel coefficients and quantum anomalies, corresponding anomalous actions, and covariant perturbation expansions of the effective action (both “low-” and “high-energy” ones).

U. Jakob, M. Gaestel, K. Engel et al.

Small heat shock proteins (sHsp) with a molecular mass of 15-30 kDa are ubiquitous and conserved. Up to now their function has remained enigmatic. Increased expression under heat shock conditions and their protective effect on cell viability at elevated temperatures suggest that they may have a function in the formation or maintenance of the native conformation of cytosolic proteins. To test this hypothesis we studied the influence of murine Hsp25, human Hsp27, and bovine alpha-B-crystallin (an eye lens protein homologous to sHsps) on the unfolding and refolding of citrate synthase and alpha-glucosidase in vitro. Here we show that all sHsps investigated act as molecular chaperones in these folding reactions. At stoichiometric amounts they maximally prevent the aggregation of citrate synthase and alpha-glucosidase under heat shock conditions and stabilize the proteins. Furthermore, they promote the functional refolding of these proteins after urea denaturation similar to GroE and Hsp90. The interaction both with unfolding and refolding proteins seems to be ATP-independent.

I. S. Bowen

S. M. Hasnain

Dan Li, E. Bou‐Zeid

E. Teixeira, G. Fischer, H. Velthuizen et al.

S. Russo, A. Dosio, R. Graversen et al.

An extreme heat wave occurred in Russia in the summer of 2010. It had serious impacts on humans and natural ecosystems, it was the strongest recorded globally in recent decades and exceeded in amplitude and spatial extent the previous hottest European summer in 2003. Earlier studies have not succeeded in comparing the magnitude of heat waves across continents and in time. This study introduces a new Heat Wave Magnitude Index that can be compared over space and time. The index is based on the analysis of daily maximum temperature in order to classify the strongest heat waves that occurred worldwide during the three study periods 1980–1990, 1991–2001, and 2002–2012. In addition, multimodel ensemble outputs from the Coupled Model Intercomparison Project Phase 5 are used to project future occurrence and severity of heat waves, under different Representative Concentration Pathways, adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5). Results show that the percentage of global area affected by heat waves has increased in recent decades. Moreover, model predictions reveal an increase in the probability of occurrence of extreme and very extreme heat waves in the coming years, in particular, by the end of this century, under the most severe IPCC AR5 scenario, events of the same severity as that in Russia in the summer of 2010 will become the norm and are projected to occur as often as every 2 years for regions such as southern Europe, North America, South America, Africa, and Indonesia.

Nayeli A. Rodríguez-Briones, Daniel K. Park

This work introduces an approach rooted in quantum thermodynamics to enhance sampling efficiency in quantum machine learning (QML). We propose conceptualizing quantum supervised learning as a thermodynamic cooling process. Building on this concept, we develop a quantum refrigerator protocol that enhances sample efficiency during training and prediction without the need for Grover iterations or quantum phase estimation. Inspired by heat-bath algorithmic cooling protocols, our method alternates entropy compression and thermalization steps to decrease the entropy of qubits, increasing polarization toward the dominant bias. This technique minimizes the computational overhead associated with estimating classification scores and gradients, presenting a practical and efficient solution for QML algorithms compatible with noisy intermediate-scale quantum devices.

Sang‐Ki Lee, W. Park, M. Baringer et al.

T. Yan, Ruzhu Wang, Tingxian Li et al.