arXiv subjects

Heena

Publications and source records attributed to Heena.

5 recordsLinked to original sources

arXiv2026

Distorted polyhedral architecture enabled high thermoelectric performance of columnar double halide perovskites Cs2AgPdCl5 and Cs2AgPtCl5

We investigate the thermoelectric properties of two newly synthesized columnar double halide perovskites Cs$_2$AgPdCl$_5$ and Cs$_2$AgPtCl$_5$. These materials accommodate a distorted local polyhedral architecture with tetrahedral symmetry compared to traditional double halide perovskites. By employing density functional theory along with the semiclassical transport model, we have analyzed the electronic and transport properties of these materials. Our results show that at 800 K, the largest figure of merit ($zT$) is 1.30 (0.86) for p-type (n-type) Cs$_2$AgPdCl$_5$ and 0.87 for n-type Cs$_2$AgPtCl$_5$ at doping concentrations of $1.94 \times 10^{20}$ ($3.76 \times 10^{19}$) cm$^{-3}$ and $3.52 \times 10^{19}$ cm$^{-3}$, respectively. Remarkably, a very low doping concentration is required to achieve a high $zT$, setting these materials apart from others in this field. Our calculations demonstrate that Cs$_2$AgPdCl$_5$ benefits from the presence of conduction and valence band valleys near the band edges; however, the flat bands present in the valence band of Cs$_2$AgPtCl$_5$ do not improve its thermoelectric performance. Among these systems, hole doping in Cs$_2$AgPdCl$_5$ has shown remarkable thermoelectric performance. Interestingly, the local octahedral distortions present in these perovskites contribute to a marked reduction in the lattice thermal conductivity to 0.27 W/mK in Cs$_2$AgPtCl$_5$ and 0.20 W/mK in Cs$_2$AgPdCl$_5$ by causing enhanced phonon scattering, further improving the thermoelectric figure of merit. This drop in thermal conductivity, combined with the favorable electronic properties, underscores the potential use of these materials for applications in highly efficient thermoelectric devices.

cond-mat.mtrl-sci↗

arXiv2026

Synergistic effect of the electronic band delocalization and bond anharmonicity on the thermoelectric performance of Cs2TeX6(X=Cl, Br, I)

We investigate the structural, mechanical, and thermoelectric properties of lead-free double halide perovskites Cs2TeX6 (X = Cl, Br, I) using first-principles calculations and semiclassical Boltzmann transport theory. The HSE06 band gap is incorporated using the scissor correction method along with PBE calculated electronic band structures including spin orbit coupling to accurately predict transport properties. The band gap values are 3.27, 2.50, and 1.55 eV for Cs2TeX6 (X = Cl, Br, I), respectively. The coexistence of heavy and light bands in the Cs2TeI6 band structure helps mitigate the trade-off between the Seebeck coefficient and electrical conductivity. Among these systems, Cs2TeI6 exhibits superior performance with a ZT of 1.97 at 800 K and an electronic concentration of 3.35 x 10^19 cm^-3. Such a high ZT at relatively low carrier concentration arises from high electrical conductivity combined with low lattice thermal conductivity. The lattice thermal conductivity of Cs2TeI6 is found to be 0.41 W m^-1 K^-1 at room temperature. This low lattice thermal conductivity is attributed to weak Te-I bonding and non-uniform out-of-phase displacement of Cs atoms. The presence of local TeX6 units together with weak bonds strongly resists heat conduction, leading to significant suppression of lattice thermal conductivity. In particular, transverse acoustic phonons and optical phonons play a key role in limiting lattice thermal conductivity. These results identify Cs2TeI6 as a promising candidate for high performance thermoelectric applications.

cond-mat.mtrl-sci↗

arXiv2025

Nanoparticles and Quantum Dots as Emerging Optical Sensing Platforms for $\mathrm{Ni}^{2+}$ Detection: Recent Approaches and Perspectives

Over the preceding years, nickel (Ni) and its compounds have been increasingly employed in various aspects of human social life, metallurgical/industrial manufactures, healthcare, and chemical processes. Although Ni is considered an essential trace element in biological systems, excessive intake or metabolic deficiency of $\mathrm{Ni}^{2+}$ ions may cause detrimental health effects to living organisms. Therefore, a facile and accurate detection of $\mathrm{Ni}^{2+}$, especially in environmental and biological settings, is of huge significance. As an efficient detection method, assaying $\mathrm{Ni}^{2+}$ using optical (colorimetric and/or fluorogenic) sensors has experienced quite a vigorous growth period, with a large number of excellent research contributions. Nanomaterial-based optical sensors, including metal nanoparticles (MNPs), quantum dots (QDs), and carbon dots (CDs), offer distinct advantages over conventional small-molecule organic and inorganic sensors. This study mainly provides an overview of the recent advancements and challenges related to the design strategies of various optical nanosensors to selectively detect the $\mathrm{Ni}^{2+}$ ion. Emphasis has also been placed on comparing the sensing performance of various nanosensors, along with exploring future perspectives.

physics.app-ph↗

arXiv2023

A Systematic Study Of Various Fingertip Detection Techniques For Air Writing Using Machine Learning

The recent advancement in technology breaks the barriers to communication between users and computers. The communication between humans and computers includes emotion and gesture recognition. Emotions can be recognized on the face of humans whereas gesture recognition includes hand and body gesture recognition. Fingertip detection is also part of it. Gesture recognition is the way of interaction that is used in air writing. Users can control the devices with simple gestures without touching them. It is how computers can understand human language which will reduce the interaction barriers between them. This paper discusses the different techniques that can be used for fingertip detection in air writing using machine learning

cs.HC↗

arXiv2021

Advances In Malware Detection- An Overview

Malware has become a widely used means in cyber attacks in recent decades because of various new obfuscation techniques used by malwares. In order to protect the systems, data and information, detection of malware is needed as early as possible. There are various studies on malware detection techniques that have been done but there is no method which can detect the malware completely and make malware detection problematic. Static Malware analysis is very effective for known malwares but it does not work for zero day malware which leads to the need of dynamic malware detection and the behaviour based malware detection is comparatively good among all detection techniques like signature based, deep learning based, mobile/IOT and cloud based detection but still it is not able to detect all zero day malware which shows the malware detection is very challenging task and need more techniques for malware detection. This paper describes a literature review of various methods of malware detection. A short description of each method is provided and discusses various studies already done in the advanced malware detection field and their comparison based on the detection method used, accuracy and other parameters. Apart from this we will discuss various malware detection tools, dataset and their sources which can be used in further study. This paper gives you the detailed knowledge of advanced malwares, its detection methods, how you can protect your devices and data from malware attacks and it gives the comparison of different studies on malware detection.

cs.CR↗