Hermawan Kresno Dipojono
YOU?
Author Swipe
View article: Theoretical Study of CO <sub>2</sub> Hydrogenation to HCOOH on Subnanometer PdZn Cluster
Theoretical Study of CO <sub>2</sub> Hydrogenation to HCOOH on Subnanometer PdZn Cluster Open
PdZn alloys have been used as catalysts in various hydrogenation reactions, where Pd and Zn atoms exhibit a significant role in binding hydrogen and CO 2 molecules, respectively. In this work, we utilize density functional theory (DFT) cal…
View article: Acceptable noise level of quantum circuit for encrypting plaintext
Acceptable noise level of quantum circuit for encrypting plaintext Open
This study investigates quantum cryptography using quantum circuits for encrypting and decrypting plaintext data. Various quantum gates were combined to form encryption and decryption circuits, demonstrating the potential of quantum crypto…
View article: Shot-Efficient ADAPT-VQE via Reused Pauli Measurements and Variance-Based Shot Allocation
Shot-Efficient ADAPT-VQE via Reused Pauli Measurements and Variance-Based Shot Allocation Open
The Adaptive Variational Quantum Eigensolver (ADAPT-VQE) is a promising approach for quantum algorithms in the Noisy Intermediate-Scale Quantum (NISQ) era, offering advantages over traditional VQE methods by reducing circuit depth and miti…
View article: Synergistic interaction between a corrugated surface and hydrogen bonding affects selectivity in bond cleaving reaction: A case of coadsorbed hydrazine-OH on Ni(211) system
Synergistic interaction between a corrugated surface and hydrogen bonding affects selectivity in bond cleaving reaction: A case of coadsorbed hydrazine-OH on Ni(211) system Open
View article: Predicting CO2 adsorption in metal-organic frameworks: Integrating machine learning with virtual sample generation
Predicting CO2 adsorption in metal-organic frameworks: Integrating machine learning with virtual sample generation Open
View article: DFT Study of H<sub>2</sub> Adsorption and Dissociation on Supported PdZn Clusters
DFT Study of H<sub>2</sub> Adsorption and Dissociation on Supported PdZn Clusters Open
The adsorption and dissociation of hydrogen molecules are essential for various hydrogenation reactions and utilization in hydrogen storage. Herein, by utilizing Density Functional Theory (DFT), we introduce Zn atoms to a Pd subnanometer c…
View article: Comprehensive Prediction of Abx3 Perovskite Formation Energy Via Quantum Circuit Learning
Comprehensive Prediction of Abx3 Perovskite Formation Energy Via Quantum Circuit Learning Open
View article: Synergistic Interaction between a Corrugated Surface and Hydrogen Bonding Affects Selectivity in Bond Cleaving Reaction: A Case of Coadsorbed Hydrazine-Oh on Ni(211) System
Synergistic Interaction between a Corrugated Surface and Hydrogen Bonding Affects Selectivity in Bond Cleaving Reaction: A Case of Coadsorbed Hydrazine-Oh on Ni(211) System Open
View article: Quantum Circuit Learning for Predicting Nature of Band Gap of Perovskite Oxides
Quantum Circuit Learning for Predicting Nature of Band Gap of Perovskite Oxides Open
View article: Stacking classical-quantum hybrid learning approach for corrosion inhibition efficiency of N-heterocyclic compounds
Stacking classical-quantum hybrid learning approach for corrosion inhibition efficiency of N-heterocyclic compounds Open
This study introduces the stacking classical-quantum model (SCQM) as a novel approach to predicting N-heterocyclic compounds' corrosion inhibition efficiency (CIE). SCQM integrates classical models such as Multi-Layer Perceptron Neural Net…
View article: A Machine Learning Approach for Forecasting the Efficacy of Pyridazine Corrosion Inhibitors
A Machine Learning Approach for Forecasting the Efficacy of Pyridazine Corrosion Inhibitors Open
This paper presents a machine learning (ML) methodology grounded in quantitative structure-property relationship (QSPR) principles for the prediction of corrosion inhibition efficiency (CIE) values, specifically focusing on pyridazine inhi…
View article: Quantum machine learning for corrosion resistance in stainless steel
Quantum machine learning for corrosion resistance in stainless steel Open
This study evaluates the efficacy of quantum machine learning (QML) models in predicting stainless steel corrosion behaviour. Using two datasets, the quantum support vector classifier (QSVC) outperformed classical models, achieving accurac…
View article: A feature restoration for machine learning on anti-corrosion materials
A feature restoration for machine learning on anti-corrosion materials Open
Materials informatics often struggles with small datasets. Our study introduces the Gaussian Mixture Model Virtual Sample Generation (GMM-VSG) approach to enhance feature correlation by generating virtual samples. Applied to six small and …
View article: A comprehensive approach utilizing quantum machine learning in the study of corrosion inhibition on quinoxaline compounds
A comprehensive approach utilizing quantum machine learning in the study of corrosion inhibition on quinoxaline compounds Open
In this investigation, a quantitative structure-property relationship (QSPR) model coupled with a quantum neural network (QNN) was used to explore the corrosion inhibition efficiency (CIE) of quinoxaline compounds. Integrating quantum chem…
View article: Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds
Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds Open
This work used a variational quantum circuit (VQC) in conjunction with a quantitative structure-property relationship (QSPR) model to completely investigate the corrosion inhibition efficiency (CIE) displayed by pyridine-quinoline compound…
View article: A Simulation of Hydrazine Molecule’s Potential Energy Surface using Variational Quantum Eigensolver Algorithm
A Simulation of Hydrazine Molecule’s Potential Energy Surface using Variational Quantum Eigensolver Algorithm Open
Quantum computing is a technology that utilizes the principles of quantum mechanics to perform complex computational processes. In this work, we use Qiskit Module from IBM to do quantum computational calculation using Variational Quantum E…
View article: Theoretical Insights into the Carbon Linker Length Effects on the Radical Scavenging Activity of Curcumin
Theoretical Insights into the Carbon Linker Length Effects on the Radical Scavenging Activity of Curcumin Open
Linker length is one crucial factor affecting the free radical scavenging activity of curcumin. However, identifying an optimal linker length that maintains the desired activity remains challenging. This study offers a thermodynamic evalua…
View article: Broad Learning System for Investigating Corrosion Inhibition Efficiency of Heterocyclic Compounds
Broad Learning System for Investigating Corrosion Inhibition Efficiency of Heterocyclic Compounds Open
View article: Effects of Cr Atom Adsorption Configurations on Anatase Tio2(101) Toward Methane-to-Methanol Conversion Mechanism
Effects of Cr Atom Adsorption Configurations on Anatase Tio2(101) Toward Methane-to-Methanol Conversion Mechanism Open
View article: Co2 Hydrogenation to Hcooh on Pdzn Surface and Supported Pdzn Cluster: A Comparative Dft Study
Co2 Hydrogenation to Hcooh on Pdzn Surface and Supported Pdzn Cluster: A Comparative Dft Study Open
View article: Predicting Co2 Adsorption in Metal-Organic Frameworks: Integrating Machine Learning with Virtual Sample Generation
Predicting Co2 Adsorption in Metal-Organic Frameworks: Integrating Machine Learning with Virtual Sample Generation Open
View article: A Feature Restoration for Machine Learning on Anti-Corrosion Materials
A Feature Restoration for Machine Learning on Anti-Corrosion Materials Open
View article: Investigation of Best QSPR-Based Machine Learning Model to Predict Corrosion Inhibition Performance of Pyridine-Quinoline Compounds
Investigation of Best QSPR-Based Machine Learning Model to Predict Corrosion Inhibition Performance of Pyridine-Quinoline Compounds Open
Corrosion is a major concern for the industrial and academic sectors because it causes significant losses in many fields. Currently, there is a great deal of interest in the topic of material damage control using organic chemicals. Pyridin…
View article: General quantum correlation from nonreal values of Kirkwood–Dirac quasiprobability over orthonormal product bases
General quantum correlation from nonreal values of Kirkwood–Dirac quasiprobability over orthonormal product bases Open
We propose a characterization and a quantification of the general quantum correlation which is exhibited even by a separable (unentangled) mixed bipartite state in terms of the nonclassical values of the associated Kirkwood–Dirac (KD) quas…
View article: Machine learning investigation to predict corrosion inhibition capacity of new amino acid compounds as corrosion inhibitors
Machine learning investigation to predict corrosion inhibition capacity of new amino acid compounds as corrosion inhibitors Open
This scientific paper aims to investigate the best machine learning (ML) for predicting the corrosion inhibition efficiency (CIE) value of amino acid compounds. The study applied a quantitative structure–property relationship (QSPR) model …
View article: Selectivity of CO2 reduction reaction to CO on the graphitic edge active sites of Fe-single-atom and dual-atom catalysts: A combined DFT and microkinetic modeling
Selectivity of CO2 reduction reaction to CO on the graphitic edge active sites of Fe-single-atom and dual-atom catalysts: A combined DFT and microkinetic modeling Open
We study the carbon dioxide reduction reaction (CO2RR) activity and selectivity of Fe single-atom catalyst (Fe-SAC) and Fe dual-atom catalyst (Fe-DAC) active sites at the interior of graphene and the edges of graphitic nanopore by using a …
View article: Quantum coherence as asymmetry from complex weak values
Quantum coherence as asymmetry from complex weak values Open
Quantum coherence as an asymmetry relative to a translation group generated by a Hermitian operator, is a necessary resource for the quantum parameter estimation. On the other hand, the sensitivity of the parameter estimation is known to b…
View article: Combination of ozone-based advanced oxidation process and nanobubbles generation toward textile wastewater recovery
Combination of ozone-based advanced oxidation process and nanobubbles generation toward textile wastewater recovery Open
The intricate nature of various textile manufacturing processes introduces colored dyes, surfactants, and toxic chemicals that have been harmful to ecosystems in recent years. Here, a combination ozone-based advanced oxidation process (AOP…
View article: A machine learning approach for corrosion small datasets
A machine learning approach for corrosion small datasets Open
In this work, we developed a QSAR model using the K-Nearest Neighbor (KNN) algorithm to predict the corrosion inhibition performance of the inhibitor compound. To overcome the small dataset problems, virtual samples are generated and added…
View article: Quantifying quantum coherence via Kirkwood-Dirac quasiprobability
Quantifying quantum coherence via Kirkwood-Dirac quasiprobability Open
Kirkwood-Dirac (KD) quasiprobability is a quantum analog of phase space probability of classical statistical mechanics, allowing negative or/and nonreal values. It gives an informationally complete representation of a quantum state. Recent…