arXiv subjects
Publications and source records attributed to Michele Pizzochero.
An influential argument for scientific realism posits that, if scientific theories were not true, their empirical success would be a coincidence. Here, I show that the false Drude's theory succeeds in explaining the Wiedemann-Franz law by coincidence--a fortuitous compensation of errors.
Inspired by the Turing test, we present a novel methodological framework to assess the extent to which a population of machines mirrors the philosophical views of a population of humans. The framework consists of three steps: (i) instructing machines to impersonate each human in the population, reflecting their backgrounds and beliefs, (ii) administering a questionnaire covering various philosophical positions to both humans and machines, and (iii) statistically analyzing the resulting responses. We apply this methodology to the debate on scientific realism, a long-standing philosophical inquiry exploring the relationship between science and reality. By considering the outcome of a survey of over 500 human participants, including both physicists and philosophers of science, we generate their machine personas using an artificial intelligence engine based on a large language model. We reveal that the philosophical views of a population of machines are, on average, similar to those endorsed by a population of humans, irrespective of whether they are physicists or philosophers of science. As compared to humans, however, machines exhibit a weaker inclination toward scientific realism and a stronger coherence in their philosophical positions. Given the observed similarities between the populations of humans and machines, this methodological framework may offer unprecedented opportunities for advancing research in the empirical social sciences by complementing human participants with their machine-impersonated counterparts.
We demonstrate that higher-order electric susceptibilities in crystals can be enhanced and understood through nontrivial topological invariants and quantum geometry, using one-dimensional $π$-conjugated chains as representative model systems. First, we show that the crystalline-symmetry-protected topology of these chains imposes a lower bound on their quantum metric and hyperpolarizabilities. Second, we employ numerical simulations to reveal the tunability of nonlinear, quantum geometry-driven optical responses in various one-dimensional crystals in which band topology can be externally controlled. Third, we develop a semiclassical picture to deliver an intuitive understanding of these effects. Our findings offer a firm interpretation of otherwise elusive experimental observations of colossal hyperpolarizabilities and establish guidelines for designing topological materials of any dimensionality with enhanced nonlinear optical properties.
We design antiferromagnetic spin-1/2 chains in fullerene nanoribbons by introducing extra C$_{60}$ cages at one of their edges. The resulting odd number of intermolecular bonds induces an unpaired $π$-electron and hence a quantised magnetic moment in otherwise non-magnetic nanoribbons. We further reveal the formation of an antiferromagnetic ground state upon the linear arrangement of spin-1/2 C$_{60}$ cages that is insensitive to the specific structural motifs. Compared with graphene nanoribbons, Janus fullerene nanoribbons may offer an experimentally more accessible route to magnetic edge states with atomic precision in low-dimensional carbon nanostructures, possibly serving as a versatile nanoarchitecture for scalable spin-based devices and the exploration of many-body quantum phases.
As AI becomes increasingly embedded in daily life, ascertaining whether an agent is human is critical. We systematically benchmark AI's ability to imitate humans in three language tasks (image captioning, word association, conversation) and three vision tasks (color estimation, object detection, attention prediction), collecting data from 636 humans and 37 AI agents. Next, we conducted 72,191 Turing-like tests with 1,916 human judges and 10 AI judges. Current AIs are approaching the ability to convincingly impersonate humans and deceive human judges in both language and vision. Even simple AI judges outperformed humans in distinguishing AI from human responses. Imitation ability showed minimal correlation with conventional AI performance metrics, suggesting that passing as human is an important independent evaluation criterion. The large-scale Turing datasets and metrics introduced here offer valuable benchmarks for assessing human-likeness in AI and highlight the importance of rigorous, quantitative imitation tests for AI development.
Graphene nanoribbons support a range of electronic phases that can be controlled via external stimuli. Zigzag-edged graphene nanoribbons (ZGNRs), in particular, exhibit an antiferromagnetic insulating ground state that transitions to a half-metallic phase under a transverse electric field or when embedded inside hexagonal Boron Nitride. Here, we consider a simple model of a heterostructure of a ZGNR with an Ising superconductor and show that, the Ising superconductor with a parent s-wave spin-singlet pairing can induce spin-triplet odd-parity pairing in the half-metallic phase of the ZGNR. The resulting superconducting phase is topologically nontrivial, with gate-tunable transitions that enable the emergence of Majorana zero modes.
Monolayer fullerene (C$_{60}$) networks combine molecular-level rigidity with crystalline connectivity, offering a promising platform for numerous applications. In this Feature article, we review the physical and chemical properties of fullerene monolayers, focusing on first-principles studies. We first explore the structural stability of monolayer phases and investigate their thermal expansion behaviours. We then outline criteria for photocatalytic water splitting and introduce theoretical predictions which are supported by recent experimental verification. Finally, we show how interlayer stacking, molecular size, and dimensional tuning (from 2D monolayers into 3D crystals, 1D chains, or nanoribbons) offer versatile approaches to modulate their chemical functionality. Together, these insights establish fullerene networks as a novel class of carbon-based materials with tailored properties for catalysis, photovoltaics, and flexible electronics.
Using first-principles calculations, we examine the electronic structure of quasi-one-dimensional fullerene nanoribbons derived from two-dimensional fullerene networks. Depending on the edge geometry and width, these nanoribbons exhibit a rich variety of properties, including direct and indirect band gaps, positive and negative effective masses, as well as dispersive and flat bands. Our findings establish a comprehensive understanding of the electronic properties of fullerene nanoribbons, with potential implications for the design of future nanoscale devices.
Atomically thin crystals hosting flat electronic bands have been recently identified as a rich playground for exploring and engineering strongly correlated phases. Yet, their variety remains limited, primarily to two-dimensional moiré superlattices. Here, we predict the formation of reversible, electrically-induced ultra-flat bands and $π$-electron magnetism in one-dimensional chevron graphene nanoribbons. Our $ab$ $initio$ calculations show that the application of a transverse electric field to these nanoribbons generates a pair of isolated, nearly perfectly flat bands with widths of approximately 1 meV around the Fermi level. Upon charge doping, these flat bands undergo a Stoner-like electronic instability, resulting in the spontaneous emergence of local magnetic moments at the edges of the otherwise non-magnetic nanoribbon, akin to a one-dimensional spin-$\frac{1}{2}$ chain. Our findings expand the class of carbon-based nanostructures exhibiting flat bands and establish a novel route for inducing correlated electronic phases in chevron graphene nanoribbons.
First-principles density functional theory (DFT) codes which employ a localized basis offer advantages over those which use plane-wave bases, such as better scaling with system size and better suitability to low-dimensional systems. The trade-off is that care must be taken in order to generate a good localized basis set which is efficient and accurate in a variety of environments. Here we develop and make freely available optimized local basis sets for two common two-dimensional (2D) materials, graphene and hexagonal boron nitride, for the \siesta DFT code. Each basis set is benchmarked against the \abinit plane-wave code, using the same pseudopotentials and exchange-correlation functionals. We find that a significant improvement is obtained by including the $l+2$ polarization orbitals ($4f$) to the basis set, which greatly improves angular flexibility. The optimized basis sets yield much better agreement with plane-wave calculations for key features of the physical system, including total energy, lattice constant and cohesive energy. The optimized basis sets also result in a speedup of the calculations with respect to the non-optimized, native choices.
Two-dimensional (2D) semiconductors are likely to dominate next-generation electronics due to their advantages in compactness and low power consumption. However, challenges such as high contact resistance and inefficient doping hinder their applicability. Here, we investigate workfunction-mediated charge transfer (modulation doping) as a pathway for achieving high-performance p-type 2D transistors. Focusing on type-III band alignment, we explore the doping capabilities of 27 candidate materials, including transition metal oxides, oxyhalides, and α-RuCl3, on channel materials such as transition metal dichalcogenides (TMDs) and group-III nitrides. Our extensive first-principles density functional theory (DFT) reveal p-type doping capabilities of high electron affinity materials, including α-RuCl3, MoO3, and V2O5. We predict significant reductions in contact resistance and enhanced channel mobility through efficient hole transfer without introducing detrimental defects. We analyze transistor geometries and identify promising material combinations beyond the current focus on WSe2 doping, suggesting new avenues for hBN, AlN, GaN, and MoS2. This comprehensive investigation provides a roadmap for developing high-performance p-type monolayer transistors toward the realization of 2D electronics.
We examine the electronic structure of recently fabricated in-plane heterojunctions of zigzag graphene nanoribbons embedded in hexagonal boron nitride. We focus on hitherto unexplored interface configurations in which both edges of the nanoribbon are bonded to the same chemical species, either boron or nitrogen atoms. Using ab initio and mean-field Hubbard model calculations, we reveal the emergence of one-dimensional magnetic conducting channels at these interfaces. These channels originate from the energy shift of the magnetic interface states that is induced by charge transfer between the nanoribbon and hexagonal boron nitride. We further address the response of these heterojunctions to external electric and magnetic fields, demonstrating the tunability of energy and spin splittings in the electronic structure. Our findings establish that zigzag graphene nanoribbon/hexagonal boron nitride heterojunctions are a suitable platform for exploring and engineering spin transport in the atomically thin limit, with potential applications in integrated spintronic devices
Ultra-wide bandgap (UWBG) semiconductors are poised to transform power electronics by surpassing the capabilities of established wide bandgap materials, such as GaN and SiC, owing to their capability to operate at higher voltage, frequency, and temperature ranges. While bulk group-III nitrides and their alloys have been extensively studied in the UWBG realm, their two-dimensional counterparts remain unexplored. Here, we examine the stability and electronic properties of monolayers of ordered boron-based group-III nitride alloys with general formula BxM1-xN, where M = Al, Ga. On the basis of ab initio calculations we identify a number of energetically and dynamically stable structures. Instrumental to their stability is a previously overlooked out-of-plane displacement (puckering) of atoms, which induces a polar ordering and antiferroelectric ground state. Our findings reveal the energy barrier between metastable ferroelectric states is lowered by successive switching of out-of-plane displacements through an antiferroelectric state.
Twisted bilayer graphene (tBLG) has emerged as a promising platform to explore exotic electronic phases. However, the formation of moiré patterns in tBLG has thus far been confined to the introduction of twist angles between the layers. Here, we propose heterostrained bilayer graphene (hBLG), as an alternative avenue to access twist-angle-free moiré physics via lattice mismatch. Using atomistic and first-principles calculations, we demonstrate that uniaxial heterostrain can promote isolated flat electronic bands around the Fermi level. Furthermore, the heterostrain-induced out-of-plane lattice relaxation may lead to a spatially modulated reactivity of the surface layer, paving the way for the moiré-driven chemistry and magnetism. We anticipate that our findings can be readily generalized to other layered materials.
Thermoelectrics are a promising class of materials for renewable energy owing to their capability to generate electricity from waste heat, with their performance being governed by a competition between charge and thermal transport. A detailed understanding of energy transport at the nanoscale is thus of paramount importance for developing efficient thermoelectrics. Here, we provide a comprehensive overview of the methodologies adopted for the computational design and optimization of thermoelectric materials from first-principles calculations. First, we introduce density-functional theory, the fundamental tool to describe the electronic and vibrational properties of solids. Next, we review charge and thermal transport in the semiclassical framework of the Boltzmann transport equation, with a particular emphasis on the various scattering mechanisms between phonons, electrons, and impurities. Finally, we illustrate how these approaches can be deployed in determining the figure of merit of tin and germanium selenides, an emerging family of layered thermoelectrics that exhibits a promising figure of merit. Overall, this review article offers practical guidelines to achieve an accurate assessment of the thermoelectric properties of materials by means of computer simulations.
Half-metals have been envisioned as active components in spintronic devices by virtue of their completely spin-polarized electrical currents. Actual materials hosting half-metallic phases, however, remain scarce. Here, we predict that recently fabricated heterojunctions of zigzag nanoribbons embedded in two-dimensional hexagonal boron nitride are half-semimetallic, featuring fully spin-polarized Dirac points at the Fermi level. The half-semimetallicity originates from the transfer of charges from hexagonal boron nitride to the embedded graphene nanoribbon. These charges give rise to opposite energy shifts of the states residing at the two edges while preserving their intrinsic antiferromagnetic exchange coupling. Upon doping, an antiferromagnetic-to-ferrimagnetic phase transition occurs in these heterojunctions, with the sign of the excess charge controlling the spatial localization of the net magnetic moments. Our findings demonstrate that such heterojunctions realize tunable one-dimensional conducting channels of spin-polarized Dirac fermions that are seamlessly integrated into a two-dimensional insulator, thus holding promise for the development of carbon-based spintronics.
Twisted van der Waals multilayers are widely regarded as a rich platform to access novel electronic phases, thanks to the multiple degrees of freedom such as layer thickness and twist angle that allow control of their electronic and chemical properties. Here, we propose that the stacking domains that form naturally due to the relative twist between successive layers act as an additional "knob" for controlling the behavior of these systems, and report the emergence and engineering of stacking domain-dependent surface chemistry in twisted few-layer graphene. Using mid-infrared near-field optical microscopy and atomic force microscopy, we observe a selective adhesion of metallic nanoparticles and liquid water at the domains with rhombohedral stacking configurations of minimally twisted double bi- and tri-layer graphene. Furthermore, we demonstrate that the manipulation of nanoparticles located at certain stacking domains can locally reconfigure the moiré superlattice in their vicinity at the μm-scale. In addition, we report first-principles simulations of the energetics of adhesion of metal atoms and water molecules on the stacking domains in an attempt to elucidate the origin of the observed selective adhesion. Our findings establish a new approach to controlling moiré-assisted chemistry and nanoengineering.
Armchair graphene nanoribbons are a highly promising class of semiconductors for all-carbon nanocircuitry. Here, we present a new perspective on their electronic structure from simple model Hamiltonians and $\textit{ab initio}$ calculations. We focus on a specific set of nanoribbons of width $n = 3p+2$, where $n$ is the number of carbon atoms across the nanoribbon axis and $p$ is a positive integer. We demonstrate that the energy-gap opening in these nanoribbons originates from the breaking of a previously unidentified hidden symmetry by long-ranged hopping of $π$-electrons and structural distortions occurring at the edges. This hidden symmetry can be restored or manipulated through the application of in-plane lattice strain, which enables continuous energy-gap tuning, the emergence of Dirac points at the Fermi level, and topological quantum phase transitions. Our work establishes an original interpretation of the semiconducting character of armchair graphene nanoribbons and offers guidelines for rationally designing their electronic structure.