IMEC

Unifying Nanosecond Electrical and Optical Excitations in Perovskite Light‐Emitting Diodes

ABSTRACT Metal halide perovskites offer a promising pathway toward solution‐processable monolithic lasers. In the pursuit of direct electrical pumping, optical excitation is widely employed as the primary route for investigating the gain potential at the device level. However, th...

Monolithic Intrinsic-Capacitance Bootstrapped Inverter in E-Mode GaN-on-SOI: Design, Analysis, and Electro-Thermal Characterization

This paper presents, analyzes, and experimentally validates a bootstrapped inverter implemented via low-voltage enhancement-mode HEMTs offered by a 200-V E-mode GaN-on-SOI monolithic platform. Unlike conventional resistor–transistor logic (RTL), the proposed topology exploits int...

Photonic integrated recurrent spectrum slicer enabling low complexity direct detection over 200 GBaud dispersive links

Abstract The rising demand for data-intensive workloads in the network is driving the development of scalable and energy-efficient optical communication infrastructure. Intensity modulation with direct detection (IM/DD) remains the preferred choice for cost-sensitive systems but...

Stoichiometric Epitaxial Strontium Titanate Thin Films on Silicon by High-Temperature Sr Segregation

Abstract Thin-film strontium titanate (SrTiO3, STO) layers grown on silicon require accurate stoichiometry and single-crystalline order to exploit their functional properties optimally. Oxide molecular beam epitaxy can provide an epitaxial interface, but suffers from source oxida...

Primary school pre-service teachers' ability to understand and use dashboard data and associations with their data literacy knowledge, beliefs and experience

Teacher dashboards can support instructional decision-making, but teachers often struggle to interpret dashboard data. This study examines pre-service teachers' situation-specific skills for using dashboards, including perceiving relevant data, interpreting information, and makin...

Discrete time survival analysis machine learning models for IVF prognosis across multiple cycles

Abstract STUDY QUESTION Can discrete time survival analysis machine learning (ML) methods provide reliable and accurate predictions of cumulative live birth rate (CLBR) for patients both at diagnosis (pre-treatment) and after the first cycle of treatment (post-treatment)? SUMMARY...

Vertical Compressive Stress in Fab-Integrated WS2 FETs: An In Situ Electrical and Nanoindentation-Based Study

Abstract Two-dimensional (2D) semiconductors are sensitive to mechanical stress due to their atomic thickness, weak van der Waals interfaces, and ultra-high sensitivity to the surrounding dielectric environment. While the effects of in-plane strain in transition-metal dichalcogen...

Dissecting the transition metal dichalcogenides-based metal-oxide-semiconductor structures charge components

Abstract Different variable charges such as interface traps, oxide border traps, and mobile carriers can contribute to the total capacitance in metal oxide semiconductor (MOS) field-effect devices. This study aims to quantify these charge components using multi-frequency, multi-t...

Three‐Dimensional Optical and Computational Reconstruction of Colloidal Electrokinetic Flows via Multiplane Imaging and Multiscale Modeling

ABSTRACT Sorting, filtering, and controlling colloidal particles is crucial in many fields, ranging from chemistry to biology and physics. Dielectrophoresis (DEP) enables selective manipulation of colloids by non‐uniform AC electric fields, yet the associated three‐dimensional na...

Micro-CT radiomics reveals the microcalcification-surrounding tissue interface as the diagnostic epicenter of breast microcalcifications

In clinical breast imaging, microcalcifications (MCs) are routinely interpreted as small radiological signs, typically analyzed in clusters. They guide radiologists in assessing breast lesions and determining the likelihood of malignancy. Yet, increasing biological evidence indic...

Data-driven identification of modifiable risk factors for colorectal cancer in Palestine using machine learning methods

Colorectal cancer (CRC) is a growing public health concern in Palestine, yet limited evidence is available on locally relevant behavioral, dietary, socioeconomic, and contextual predictors. Machine learning (ML) may support prevention-oriented risk stratification by identifying c...