arXiv subjects

Giuseppe Romano

Publications and source records attributed to Giuseppe Romano.

33 records · Page 2Linked to original sources

arXiv2020

Thermal transport in nanoporous holey silicon membranes investigated with optically-induced transient thermal gratings

In this study, we use the transient thermal grating optical technique \textemdash a non-contact, laser-based thermal metrology technique with intrinsically high accuracy \textemdash to investigate room-temperature phonon-mediated thermal transport in two nanoporous holey silicon membranes with limiting dimensions of 100 nm and 250 nm respectively. We compare the experimental results to ab initio calculations of phonon-mediated thermal transport according to the phonon Boltzmann transport equation (BTE) using two different computational techniques. We find that the calculations conducted within the Casimir framework, i.e. based on the BTE with the bulk phonon dispersion and diffuse scattering from surfaces, are in quantitative agreement with the experimental data, and thus conclude that this framework is adequate for describing phonon-mediated thermal transport through holey silicon membranes with feature sizes on the order of 100 nm.

cond-mat.mes-hall↗

arXiv2020

Quantum multifractality in thermal conduction across random interfaces

Self-affine morphology of random interfaces governs their functionalities across tribological, geological, (opto-)electrical and biological applications. However, the knowledge of how energy carriers or generally classical/quantum waves interact with structural irregularity is still incomplete. In this work, we study vibrational energy transport through random interfaces exhibiting different correlation functions on the two-dimensional hexagonal lattice. We show that random interfaces at the atomic scale are Cantor composites populated on geometrical fractals, thus multifractals, and calculate their quantized conductance using atomistic approaches. We obtain a universal scaling law, which contains self-similarity for mass perturbation, and exponential scaling of structural irregularity quantified by fractal dimension. The multifractal nature and Cantor-composite picture may also be extendable to charge and photon transport across random interfaces.

cond-mat.mes-hall↗

arXiv2020

Phonon Transport in Patterned Two-Dimensional Materials from First Principles

Phonon size effects induce ballistic transport in nanomaterials, challenging Fourier's law. Nondiffusive heat transport is captured by the Peierls-Boltzmann transport equation (BTE), commonly solved under the relaxation time approximation (RTA), which assumes diagonal scattering operator. Although the RTA is accurate for many relevant materials over a wide range of temperatures, such as silicon, it underpredicts thermal transport in most two-dimensional (2D) systems, notoriously graphene. Here we present a formalism, based on the BTE with the full collision matrix, for computing the effective thermal conductivity of arbitrarily patterned 2D materials. We apply our approach to porous graphene and find strong heat transport suppression in configurations with feature sizes of the order of micrometers; this result, which is rooted in the large generalized phonon MFPs in graphene, corroborates the possibility of strong thermal transport tunability by relatively coarse patterning. Lastly, we present a promising material configuration with low thermal conductivity. Our method enables the parameter-free design of 2D materials for thermoelectric and thermal routing applications.

cond-mat.mes-hall↗

arXiv2019

Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks

X-ray diffraction (XRD) data acquisition and analysis is among the most time-consuming steps in the development cycle of novel thin-film materials. We propose a machine-learning-enabled approach to predict crystallographic dimensionality and space group from a limited number of thin-film XRD patterns. We overcome the scarce-data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data. As a test case, 115 thin-film metal halides spanning 3 dimensionalities and 7 space-groups are synthesized and classified. After testing various algorithms, we develop and implement an all convolutional neural network, with cross validated accuracies for dimensionality and space-group classification of 93% and 89%, respectively. We propose average class activation maps, computed from a global average pooling layer, to allow high model interpretability by human experimentalists, elucidating the root causes of misclassification. Finally, we systematically evaluate the maximum XRD pattern step size (data acquisition rate) before loss of predictive accuracy occurs, and determine it to be 0.16°, which enables an XRD pattern to be obtained and classified in 5.5 minutes or less.

physics.data-an↗

arXiv2018

Bayesim: a tool for adaptive grid model fitting with Bayesian inference

Bayesian inference is a widely used and powerful analytical technique in fields such as astronomy and particle physics but has historically been underutilized in some other disciplines including semiconductor devices. In this work, we introduce Bayesim, a Python package that utilizes adaptive grid sampling to efficiently generate a probability distribution over multiple input parameters to a forward model using a collection of experimental measurements. We discuss the implementation choices made in the code, showcase two examples in photovoltaics, and discuss general prerequisites for the approach to apply to other systems.

physics.data-an↗

arXiv2018

High-Throughput Calculations of Thermal Conductivity in Nanoporous Materials: The Case of Half-Heusler Compounds

Achieving low thermal conductivity and good electrical properties is a crucial condition for thermal energy harvesting materials. Nanostructuring offers a very powerful tool to address both requirements: in nanostructured materials, boundaries preferentially scatter phonons compared to electrons. The search for low-thermal-conductivity nanostructures is typically limited to materials with simple crystal structures, such as silicon, because of the complexity arising from modeling branch- and wave vector- dependent nanoscale heat transport. Using the phonon mean-free-path (MFP) dependent Boltzmann transport equation, a model that overcomes this limitation, we compute thermal transport in 75 nanoporous half-Heusler compounds for different pore sizes. We demonstrate that the optimization of thermal transport in nanostructures should take into account both bulk thermal properties and geometry-dependent phonon suppression, two aspects that are typically engineered separately. In fact, our work predicts that, given a set of bulk materials and a system geometry, the ordering of the thermal conductivity of the nanostructure does not necessarily align with that of the bulk: We show that what dictates thermal transport is the interplay between the bulk MFP distribution and the nanostructuring length scale of the material. Finally, we derive a thermal transport model that enables fast systems screening within large bulk material repositories and a given geometry. Our study motivates the need for a holistic approach to engineering thermal transport and provides a method for high-throughput materials discovery.

cond-mat.mes-hall↗

arXiv2017

Diffusive Phonons in Nongray Nanostructures

Nanostructured semiconducting materials are promising candidates for thermoelectrics due to their potential to suppress phonon transport while preserving electrical properties. Modeling phonon-boundary scattering in complex geometries is crucial for predicting materials with high conversion efficiency. However, the simultaneous presence of ballistic and diffusive phonons challenges the development of models that are both accurate and computationally tractable. Using the recently developed first-principles Boltzmann transport equation (BTE) approach, we investigate diffusive phonons in nanomaterials with wide mean-free-path (MFP) distributions. First, we derive the short MFP limit of the suppression function, showing that it does not necessarily recover the value predicted by standard diffusive transport, challenging previous assumptions. Second, we identify a Robin type boundary condition describing diffuse surfaces within Fourier's law, extending the validity of diffusive heat transport in terms of Knudsen numbers. Finally, we use this result to develop a hybrid Fourier/BTE approach to model realistic materials, obtaining excellent agreement with experiments. These results provide insight on thermal transport in materials that are within experimental reach and open opportunities for large-scale screening of nanostructured thermoelectric materials.

cond-mat.mtrl-sci↗

arXiv2017

Phonon Bottleneck Identification in Disordered Nanoporous Materials

Nanoporous materials are a promising platform for thermoelectrics in that they offer high thermal conductivity tunability while preserving good electrical properties, a crucial requirement for high- effciency thermal energy conversion. Understanding the impact of the pore arrangement on thermal transport is pivotal to engineering realistic materials, where pore disorder is unavoidable. Although there has been considerable progress in modeling thermal size effects in nanostructures, it has remained a challenge to screen such materials over a large phase space due to the slow simulation time required for accurate results. We use density functional theory in connection with the Boltzmann transport equation, to perform calculations of thermal conductivity in disordered porous materials. By leveraging graph theory and regressive analysis, we identify the set of pores representing the phonon bottleneck and obtain a descriptor for thermal transport, based on the sum of the pore-pore distances between such pores. This approach provides a simple tool to estimate phonon suppression in realistic porous materials for thermoelectric applications and enhance our understanding of heat transport in disordered materials.

cond-mat.mtrl-sci↗

arXiv2017

Thermal Anisotropy Enhanced by Phonon Size Effects in Nanoporous Materials

While thermal anisotropicity is a desirable materials property for many applications, including transverse thermoelectrics and thermal management in electronic devices, it remains elusive in practical natural compounds. In this work, we show how nanoporous materials with anisotropic pore lattices can be used as a platform for inducing strong heat transport directionality in isotropic materials. Using density functional theory and the phonon Boltzmann transport equation, we calculate the phonon-size effects and thermal conductivity of nanoporous silicon with different anisotropicpore lattices. Our calculations predict a strong directionality in the thermal conductivity, dictated by the difference in the pore-pore distances along the two Cartesian axes. As the space between pores along the direction of the applied temperature gradient represents the phonon bottleneck, an anisotropic pores lattice distortion induces directionality in heat transport. Using Fourier's law, we also compute diffusive heat transport for the same geometries obtaining significantly smaller anisotropicity, revealing the crucial role of phonon-size effects in tuning thermal transport directionality. Besides enhancing our understanding of nanoscale heat transport, our results demonstrate the promise of nanoporous materials for modulating anisotropy in thermal conductivity.

cond-mat.mtrl-sci↗

arXiv2016

Directional Phonon Suppression Function as a Tool for the Identification of Ultralow Thermal Conductivity Materials

Boundary-engineering in nanostructures has the potential to dramatically impact the development of materials for high-efficiency conversion of thermal energy directly into electricity. In particular, nanostructuring of semiconductors can lead to strong suppression of heat transport with little degradation of electrical conductivity. Although this combination of material properties is promising for thermoelectric materials, it remains largely unexplored. In this work, we introduce a novel concept, the directional phonon suppression function, to unravel boundary-dominated heat transport in unprecedented detail. Using a combination of density functional theory and the Boltzmann transport equation, we compute this quantity for nanoporous silicon materials. We first compute the thermal conductivity for the case with aligned circular pores, confirming a significant thermal transport degradation with respect to the bulk. Then, by analyzing the information on the directionality of phonon suppression in this system, we identify a new structure of rectangular pores with the same porosity that enables a four-fold decrease in thermal transport with respect to the circular pores. Our results illustrate the utility of the directional phonon suppression function, enabling new avenues for systematic thermal conductivity minimization and potentially accelerating the engineering of next-generation thermoelectric devices.

cond-mat.mtrl-sci↗

arXiv2015

Single-molecule Electronics: Cooling Individual Vibrational Modes by the Tunneling Current

Electronic devices composed of single molecules constitute the ultimate limit in the continued downscaling of electronic components. A key challenge for single-molecule electronics is to control the temperature of these junctions. Controlling heating and cooling effects in individual vibrational modes, can in principle, be utilized to increase stability of single-molecule junctions under bias, to pump energy into particular vibrational modes to perform current-induced reactions or to increase the resolution in inelastic electron tunneling spectroscopy by controlling the life-times of phonons in a molecule by suppressing absorption and external dissipation processes. Under bias the current and the molecule exchange energy, which typically results in heating of the molecule. However, the opposite process is also possible, where energy is extracted from the molecule by the tunneling current. Designing a molecular 'heat sink' where a particular vibrational mode funnels heat out of the molecule and into the leads would be very desirable. It is even possible to imagine how the vibrational energy of the other vibrational modes could be funneled into the 'cooling mode', given the right molecular design. Previous efforts to understand heating and cooling mechanisms in single molecule junctions, have primarily been concerned with small models, where it is unclear which molecular systems they correspond to. In this paper, our focus is on suppressing heating and obtaining current-induced cooling in certain vibrational modes. Strategies for cooling vibrational modes in single-molecule junctions are presented, together with atomistic calculations based on those strategies. Cooling and reduced heating are observed for two different cooling schemes in calculations of atomistic single-molecule junctions.

cond-mat.mes-hall↗

arXiv2015

Simulating nanoscale heat transport

In this book chapter we provide the definition of "Simulating Nanoscale Heat Transport", broadly regarded as modeling heat conduction beyond Fourier's law. We primarely focus on incoherent transport, which is dominated by scattering between phonons and the boundaries of a given material. After introducing the Boltzmann Transport Equation (BTE) for phonons, we elaborate on different numerical techniques for solving nanoscale heat transport includind deterministic and Monte Carlo based method. A discussion on the need for multiscale modeling concludes the chapter.

cond-mat.mtrl-sci↗

arXiv2015

Temperature-dependent thermal conductivity in nanoporous materials studied by the Boltzmann Transport Equation

Nanostructured materials exhibit low thermal conductivity because of the additional scattering due to phonon-boundary interactions. As these interactions are highly sensitive to the mean free path (MFP) of a given phonon mode, MFP distributions in nanostructures can be dramatically distorted relative to bulk. Here we calculate the MFP distribution in periodic nanoporous Si for different temperatures, using the recently developed MFP-dependent Boltzmann Transport Equation. After analyzing the relative contribution of each phonon branch to thermal transport in nanoporous Si, we find that at room temperature optical phonons contribute 18 % to heat transport, compared to 5% in bulk Si. Interestingly, we observe a steady thermal conductivity in the nanoporous materials over a temperature range 200 K < T < 300 K, which we attribute to the ballistic transport of acoustic phonons with long intrinsic MFP. These results, which are also consistent with a recent experimental study, shed light on the origin of the reduction of thermal conductivity in nanostructured materials, and could contribute to multiscale heat transport engineering, in which the bulk material and geometry are optimized concurrently.

cond-mat.mtrl-sci↗

arXiv2014

Multiscale Phonon Conduction in Nanostructured Materials Predicted by Bulk Thermal Conductivity Accumulation Function

We develop a computational framework, based on the Boltzmann transport equation, with the ability to compute the thermal transport in nanostructured materials of any geometry using as the only input the bulk thermal conductivity accumulation function. The main advantage of our method is twofold. First, while the scattering times and dispersion curves are unknown for most materials, the phonon mean free path distribution can be directly obtained by experiments. As a consequence, a wider range of materials can be simulated than with a frequency-dependent approach. Second, when phonon dispersions are available from first principles calculations, our approach allows one to include easily the whole Brillouen zone in the calculations without discretizing the phonon frequencies for all polarizations, reducing considerably the computational effort. Furthermore, after deriving the ballistic and diffusive limits of our model, we develop a multi-scale scheme that couples phonon transport across different scales, enabling efficient simulations of materials with wide phonon mean free path distributions. After we validate our model against the frequency-dependent approach, we apply the method to porous silicon membranes and find good agreement with experiments on mesoscale pores. By enabling the investigation of thermal transport in unexplored nanostructured materials, our method has potential to advance high-efficiency thermoelectric devices.

cond-mat.mes-hall↗

arXiv2014

Toward phonon-boundary engineering in nanoporous materials

Tuning thermal transport in nanostructured materials is a powerful approach to develop high-efficiency thermoelectric materials. Using a recently developed approach based on the phonon mean free path dependent Boltzmann transport equation, we compute the effective thermal conductivity of nanoporous materials with pores of various shapes and arrangements. We assess the importance of pore-pore distance in suppressing thermal transport, and identify the pore arrangement that minimizes the thermal conductivity, composed of a periodic arrangement of two misaligned rows of triangular pores. Such a configuration yields a reduction in the thermal conductivity of more than $60 \%$ with respect the simple circular aligned case with the same porosity.

cond-mat.mes-hall↗