arXiv subjects

John Robertson

Publications and source records attributed to John Robertson.

At least 19 recordsLinked to original sources

arXiv2026

Automated Generation of Commensurate Magnetic Structures based on Spin Space Groups and Graph Theory

Magnetic structures with symmetry constraints are candidates for energetically favorable configurations. Enumerating these structures is essential for identifying experimental observations and provides unbiased, linearly stable, and optimally sampled reference configurations for energy fitting when extracting spin interactions. We present SpinGraph, an automated workflow generating symmetry-distinct magnetic configurations. SpinGraph is not only compatible with the more general spin space groups, but also allows precise control of the prescribed single- or multi-Q states superposition. For finite groups, we enumerate compatible subgroups directly. For spin space groups with a continuous or special spin-only part, the finite component is enumerated first and then combined with the compatible exact spin-only constraints. These actions are translated into graph constraints in real or Fourier space. The symmetry of every generated structure is re-evaluated after construction. Finally, we integrate SpinGraph with the magnetic analysis code AMATIS to perform a thorough calculation for the spin interactions of the insulating monolayer CrI3. SpinGraph complements the last part of AMATIS and realizes the fully automated workflow for the spin Hamiltonian construction, which is essential for studying phase transitions, spin textures, magnons, and spin dynamics.

cond-mat.mtrl-sci↗

arXiv2026

Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems

Long-lived AI agents are increasingly deployed as persistent operational systems, yet they are still evaluated like freshly initialized models. Day-one benchmarks miss a basic systems question: how long does an agent remain reliable after deployment? Even when model weights are frozen, an agent's effective state keeps changing as it compresses interaction history, retrieves from a growing memory store, revises facts after updates, and undergoes routine maintenance. Reliability therefore becomes a lifespan property of the full agent harness, not only a snapshot property of the base model. We introduce AgingBench, a longitudinal reliability benchmark for agent lifespan engineering: measuring not only whether deployed agents degrade, but what form the degradation takes and where repair should target. AgingBench organizes agent aging into four mechanisms: compression aging, interference aging, revision aging, and maintenance aging. To diagnose these failures, AgingBench uses temporal dependency graphs and paired counterfactual probes that produce diagnostic profiles for the write, retrieval, and utilization stages of the memory pipeline. Across 7 scenarios, 14 models, multiple memory policies, and both runner-controlled and autonomous agents, over ~400 runs spanning 8 - 200 sessions show that agent aging is not one-dimensional: behavioral tests can remain clean while factual precision decays; derived-state tracking can collapse sharply within a single model; and the same wrong answer can require different repairs depending on what the diagnostic profile points to. These results suggest that reliable agent deployment requires lifespan evaluation, mechanism-level diagnosis, and stage-targeted repair, not only stronger day-one models.

cs.AI↗

arXiv2025

How to Identify Suitable Gate Dielectrics for Transistors based on Two-Dimensional Semiconductors

The recent progress in nanosheet transistors has established two-dimensional (2D) semiconductors as viable candidates for future ultra-scaled electronic devices. Next to reducing contact resistance, identifying good gate dielectrics is a fundamental challenge, as the dielectric/channel interface dramatically impacts virtually all performance parameters. While several promising gate dielectrics have recently been reported, the evaluation of their quality and suitability is often fragmentary and focused on selected important performance metrics of the gate stack, such as the capacitive gate control, leakage currents, reliability, and ease of fabrication and integration. However, identifying a suitable gate stack is a complex problem that has not yet been approached systematically. In this perspective, we aim to formulate general criteria for good gate dielectrics.

physics.app-ph↗

arXiv2023

Automatic Calculation of the Transition Temperatures for two-dimensional Heisenberg type Magnets

Theoretical prediction of the 2nd-order magnetic transition temperature (TM) used to be arduous. Here, we develop a first principle-based, fully automatic structure-to-TM method for two-dimensional (2D) magnets whose effective Hamiltonians follow the Heisenberg model. The Heisenberg exchanges, which can be calculated to an arbitrary shell, are transferred into the Monte Carlo calculation. Using Cr-based magnets as the showcases, we show that our method is a powerful tool to study the 2D magnets in two aspects. First, considering long-range exchanges enables us to identify the spin frustration in the suspended CrTe2 monolayer, whereas the heterostructure calculations reveal that the ferromagnetism can be recovered if the monolayer CrTe2 is grown onto various 2D substrates. Second, we realize a high-throughput screening of novel magnets discovered by random structure searches. Six 2D Cr chalcogenides are selected to have high TM. Our work provides a new insight for the study of 2D magnets and helps accelerate the pace of magnetic materials data-mining.

cond-mat.mtrl-sci↗

arXiv2023

XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples

It is estimated that approximately 15% of cancers worldwide can be linked to viral infections. The viruses that can cause or increase the risk of cancer include human papillomavirus, hepatitis B and C viruses, Epstein-Barr virus, and human immunodeficiency virus, to name a few. The computational analysis of the massive amounts of tumor DNA data, whose collection is enabled by the recent advancements in sequencing technologies, have allowed studies of the potential association between cancers and viral pathogens. However, the high diversity of oncoviral families makes reliable detection of viral DNA difficult and thus, renders such analysis challenging. In this paper, we introduce XVir, a data pipeline that relies on a transformer-based deep learning architecture to reliably identify viral DNA present in human tumors. In particular, XVir is trained on genomic sequencing reads from viral and human genomes and may be used with tumor sequence information to find evidence of viral DNA in human cancers. Results on semi-experimental data demonstrate that XVir is capable of achieving high detection accuracy, generally outperforming state-of-the-art competing methods while being more compact and less computationally demanding.

q-bio.GN↗

arXiv2021

Insights into Cold Source MOSFETs with Sub-60 mV/decade and Negative Differential Resistance Effect

To extend the Moores law in the 5 nm node, a large number of two dimensional (2D) materials and devices have been thoroughly researched, among which the cold metals 2H MS2 (M = Nb, Ta) with unique band structures are expected to achieve the sub-60 mV/dec subthreshold swing (SS). The studied cold metal field-effect transistors (CM-FETs) based on the cold metals are capable to fulfill the high-performance (HP) and low-dissipation (LP) goals simultaneously, as required by the International Technology Roadmap for Semiconductors (ITRS). Moreover, gaps of cold metals also enable the CM-FETs to realize negative differential resistance (NDR) effect. Owing to the wide transmission path in the broken gap structure of NbS2/MoS2 heterojunction, the recording 4110 A/m peak current, several orders of magnitude higher than the tunneling current of the Esaki diode, is achieved by NbS2/MoS2 CM-FET. The largest peak-valley ratio (PVR) is obtained by TaS2/MoS2 CM-FET with VGS = -1V at room temperature. Our results claim that the superior on-state current, SS, cut-off frequency and NDR effect can be obtained by CM-FETs simultaneously. The study of CM-FETs provides a practicable solution for state-of-the-art logic device in sub 5 nm node for both more Moore roadmap and more than Moore roadmap applications.

physics.app-ph↗

arXiv2021

Native point defects of semiconducting layered Bi2O2Se

Bi2O2Se is an emerging semiconducting, air-stable layered material (Nat. Nanotechnol. 2017, 12, 530; Nano Lett. 2017, 17, 3021), potentially exceeding MoS2 and phosphorene in electron mobility and rivalling typical Van der Waals stacked layered materials in the next-generation high-speed and low-power electronics. Holding the promise of functional versatility, it is arousing rapidly growing interest from various disciplines, including optoelectronics, thermoelectronics and piezoelectronics. In this work, we comprehensively study the electrical properties of the native point defects in Bi2O2Se, as an essential step toward understanding the fundamentals of this material. The defect landscapes dependent on both Fermi energy and the chemical potentials of atomic constituents are investigated. Along with the bulk defect analysis, a complementary inspection of the surface properties, within the simple context of charge neutrality level model, elucidates the observed n-type characteristics of Bi2O2Se based FETs. This work provides important guide to engineer the defects of Bi2O2Se for desired properties, which is key to the successful application of this emerging layered material.

cond-mat.mtrl-sci↗

arXiv2021

Sparse logistic regression on functional data

Motivated by a hemodialysis monitoring study, we propose a logistic model with a functional predictor, called the Sparse Functional Logistic Regression (SFLR), where the corresponding coefficient function is {\it locally sparse}, that is, it is completely zero on some subregions of its domain. The coefficient function, together with the intercept parameter, are estimated through a doubly-penalized likelihood approach with a B-splines expansion. One penalty is for controlling the roughness of the coefficient function estimate and the other penalty, in the form of the $L_1$ norm, enforces the local sparsity. A Newton-Raphson procedure is designed for the optimization of the penalized likelihood. Our simulations show that SFLR is capable of generating a smooth and reasonably good estimate of the coefficient function on the non-null region(s) while recognizing the null region(s). Application of the method to the Raman spectral data generated from the heomdialysis study pinpoint the wavenumber regions for identifying key chemicals contributing to the dialysis progress.

stat.ME↗

arXiv2021

Schottky Barrier Heights of Defect-free Metal/ZnO, CdO, MgO and SrO Interfaces

The Schottky barrier heights (SBHs) of defect-free interfaces of ZnO, CdO, MgO and SrO with various metals and different terminations are investigated by density functional supercell calculations. The oxide bands are corrected for their density functional band gap error by applying U-type treatment to their metal-d and O-p states where necessary. The p-type SBHs are found to decrease linearly with increasing metal work function. The pinning factor S of the non-polar and polar interfaces are similar for each oxide. S is found to be 0.26, 0.56, 0.74 and 0.96 for CdO, ZnO, MgO and SrO, respectively, with S increasing for increased oxide ionicity. The calculated pinning factors are generally consistent with the metal-induced gap states (MIGS) model in terms of variation with ionicity and dielectric constant. A significant shift of SBHs from the non-polar to the polar interfaces of 0.4 eV, 1 eV and 0.5 eV for ZnO, MgO and SrO, respectively, can be explained by an interfacial dipole. Our results are also useful to describe Co,Fe|MgO interfaces in magnetic tunnel junctions.

cond-mat.mtrl-sci↗

arXiv2020

Halide perovskites: third generation photovoltaic materials empowered by metavalent bonding

Third-generation photovoltaic (PV) materials combine many advantageous properties, including a high optical absorption together with a large charge carrier mobility, facilitated by small effective masses. Halide perovskites (ABX3, where X is I, Br or Cl) appear to be the most promising third-generation PV materials at present. Their opto-electronic properties are governed by the B-X bond. A quantum-chemical bond analysis reveals that this bond differs significantly from ionic, metallic or covalent bonds. Instead, it is better regarded as metavalent, since it shares approximately one p-electron between adjacent atoms. The resulting sigma-bond is half-filled, which causes pronounced optical absorption. Electron transfer and lattice distortions open a moderate band gap, resulting in charge carriers with small effective masses. Hence metavalent bonding explains the favorable PV properties of halide perovskites. This is summarized in a map for different bond types, which provides a blueprint to design third-generation PV materials.

cond-mat.mtrl-sci↗

arXiv2020

Coupled VO2 oscillators circuit as analog first layer filter in convolutional neural networks

In this work we present an in-memory computing platform based on coupled VO2 oscillators fabricated in a crossbar configuration on silicon. Compared to existing platforms, the crossbar configuration promises significant improvements in terms of area density and oscillation frequency. Further, the crossbar devices exhibit low variability and extended reliability, hence, enabling experiments on 4-coupled oscillator. We demonstrate the neuromorphic computing capabilities using the phase relation of the oscillators. As a application, we propose to replace digital filtering operation in a convolutional neural network with oscillating circuits. The concept is tested with a VGG13 architecture on the MNIST dataset, achieving performances of 95% in the recognition task.

cs.ET↗

arXiv2020

Electronic Structure of Amorphous Copper Iodide: A p-type Transparent Semiconductor

The atomic and electronic structure of the p-type transparent amorphous semiconductor CuI is calculated by ab-initio molecular dynamics. It is found to consist of a random tetrahedrally bonded network. The hole effective mass is found to be quite low, as in the crystal. The valence band maximum (VBM) state has a mixed I(p)-Cu(t2g)-I(p) character, and its energy is relatively insensitive to disorder. An iodine excess creates holes that move the Fermi level into the valence band, but it does not pin the Fermi level above the VBM mobility edge. Thus the Fermi level can easily enter the valence band if p-doped, similar to the behavior of electrons in In-Ga-Zn oxide semiconductors but opposite to that of electrons in a-Si:H. This suggests that amorphous CuI could make an effective p-type transparent semiconductor.

cond-mat.mtrl-sci↗

arXiv2017

Transfer doping of Graphene by Species of Extreme Work Function

Density functional calculations are used to explain the charge transfer doping mechanism by which species physisorptively bonded to graphene can increase its free hole or electron density, without giving rise to defects, and thus maintain a high carrier mobility. Typical dopants studied are FeCl3, AuCl3, SbF5, HNO3, MoO3, Cs2O and O2. These systems do not break the π bonding of the basal plane are particularly important as these do not degrade the carrier mobility. In contrast, more reactive radicals like -OH cause a puckering of the basal plane and thereby act as defects.

cond-mat.mtrl-sci↗

arXiv2017

Band Structure, Band Offsets, Substitutional Doping, and Schottky Barriers in InSe

We present a comprehensive study of the electronic structure of the layered semiconductor InSe using density functional theory. We calculate the band structure of the monolayer and bulk material with the band gap corrected using hybrid functionals. The band gap of the monolayer is 2.4 eV. The band edge states are surprising isotropic. The electron affinities and band offsets are then calculated for heterostructures as would be used in tunnel field effect transistors (TFETs). The ionization potential of InSe is quite large, similar to that of HfSe2 or SnSe2, and so InSe is suitable to act as the drain in the TFET. The intrinsic defects are then calculated. For Se-rich layers, the Se adatom is the lowest energy defect, whereas for In-rich layers, the In adatom is most stable for Fermi energies across most of the gap. Both substitutional donors and acceptors are calculated to be shallow, and not reconstructed. Finally, the Schottky barriers of metals are found to be strongly pinned, with the Fermi level pinned by metal induced gap states about 0.5 eV above the valence band edge.

cond-mat.mtrl-sci↗

arXiv2016

Darknet and Deepnet Mining for Proactive Cybersecurity Threat Intelligence

In this paper, we present an operational system for cyber threat intelligence gathering from various social platforms on the Internet particularly sites on the darknet and deepnet. We focus our attention to collecting information from hacker forum discussions and marketplaces offering products and services focusing on malicious hacking. We have developed an operational system for obtaining information from these sites for the purposes of identifying emerging cyber threats. Currently, this system collects on average 305 high-quality cyber threat warnings each week. These threat warnings include information on newly developed malware and exploits that have not yet been deployed in a cyber-attack. This provides a significant service to cyber-defenders. The system is significantly augmented through the use of various data mining and machine learning techniques. With the use of machine learning models, we are able to recall 92% of products in marketplaces and 80% of discussions on forums relating to malicious hacking with high precision. We perform preliminary analysis on the data collected, demonstrating its application to aid a security expert for better threat analysis.

cs.CR↗

arXiv2016

Insights into ultrafast Ge-Te bond dynamics in a phase-change superlattice

A long-standing question for avant-grade data storage technology concerns the nature of the ultrafast photoinduced phase transformations in the wide class of chalcogenide phase-change materials (PCMs). Overall, a comprehensive understanding of the microstructural evolution and the relevant kinetics mechanisms accompanying the out-of-equilibrium phases is still missing. Here, after overheating a phase-change chalcogenide superlattice by an ultrafast laser pulse, we indirectly track the lattice relaxation by time resolved X-ray absorption spectroscopy (tr-XAS) with a sub-ns time resolution. The novel approach to the tr-XAS experimental results reported in this work provides an atomistic insight of the mechanism that takes place during the cooling process, meanwhile a first-principles model mimicking the microscopic distortions accounts for a straightforward representation of the observed dynamics. Finally, we envisage that our approach can be applied in future studies addressing the role of dynamical structural strain in phase-change materials.

cond-mat.mtrl-sci↗

arXiv2015

Fast Transfer-free Synthesis of High-quality Monolayer Graphene on Insulating Substrates by Simple Rapid Thermal Treatment

The transfer-free synthesis of high-quality, large-area graphene on a given dielectric substrate, which is highly desirable for device applications, remains a significant challenge. In this paper, we report on a simple rapid thermal treatment method for the fast and direct growth of high-quality, large-scale monolayer graphene on a SiO2/Si substrate from solid carbon sources. The stack structure of solid carbon layer/copper film/SiO2 is adopted in the RTT process. The inserted copper film does not only act as an active catalyst for the carbon precursor but also serves as a "filter" that prevents premature carbon dissolution, and thus, contributes to monolayer graphene growth on SiO2/Si. The produced monolayer graphene exhibits high carrier mobility of up to 3000 cm2 V-1s-1 at room temperature and standard half-integer quantum oscillations.

cond-mat.mtrl-sci↗

arXiv2014

Graphene-Passivated Nickel as an Oxidation-Resistant Electrode for Spintronics

We report on graphene-passivated ferromagnetic electrodes (GPFE) for spin devices. GPFE are shown to act as spin-polarized oxidation-resistant electrodes. The direct coating of nickel with few layer graphene through a readily scalable chemical vapour deposition (CVD) process allows the preservation of an unoxidized nickel surface upon air exposure. Fabrication and measurement of complete reference tunneling spin valve structures demonstrates that the GPFE is maintained as a spin polarizer and also that the presence of the graphene coating leads to a specific sign reversal of the magneto-resistance. Hence, this work highlights a novel oxidation-resistant spin source which further unlocks low cost wet chemistry processes for spintronics devices.

cond-mat.mtrl-sci↗