School of Materials Science and Engineering (MSE)

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1 to 10 of 8,029 Results

Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting May 4, 2026 - TAN Li Yi Tan, Li Yi, 2026, "Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting", https://doi.org/10.21979/N9/0EBMNO, DR-NTU (Data), V1, UNF:6:BFfoThAzHZSoffSc35HA7Q== [fileUNF] Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting
Ridges-Statistical Data-2026-05-04 L.Y. Tan et al..tab May 4, 2026 - Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting Tabular Data - 181.6 KB - 12 Variables, 3605 Observations - UNF:6:BFfoThAzHZSoffSc35HA7Q== Data
TAN Li Yi (Nanyang Technological University) May 4, 2026
Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations Apr 9, 2026 - Rafika RAHMAWATI Rahmawati, Rafika; Li, Shuzhou, 2026, "Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations", https://doi.org/10.21979/N9/LDPUKT, DR-NTU (Data), V2 The provided data includes the general source code and its computational results.
Benchmark-1-UCCSD-Tier1-ipynb-09042026.ipynb Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations Jupyter Notebook - 305.7 KB - MD5: 7efad5b4a45371e7b05eaf26fc37879e Benchmark VQE using UCCSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer
Benchmark-2-HE-Tier1-ipynb-09042026.ipynb Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations Jupyter Notebook - 599.4 KB - MD5: f7601afba1cea436f8cf9ab71e3ecc8a Benchmark VQE using Hardware Efficient ansatz with Gradient Descent and Quantum Natural Gradient Optimizer
Benchmark-3-kUpCCGSD-Tier1-ipynb-09042026.ipynb Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations Jupyter Notebook - 119.9 KB - MD5: 1ba8e13a293df80fb017384f82d11fd3 Benchmark VQE using kUpCCGSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer
Noiseless-comp-cost-Tier1-png-08042026 Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations PNG Image - 215.3 KB - MD5: d2d913e58a411cf2e2a1cf75a966b23e Noiseless computation cost of min energy calculated using VQE
Rafika RAHMAWATI (Nanyang Technological University) Apr 8, 2026 Data for Tier 1 Project
Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they? Nov 19, 2025 - Darrell Jun Jie TAY Tay, Darrell Jun Jie, 2025, "Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?", https://doi.org/10.21979/N9/HBVMXK, DR-NTU (Data), V1, UNF:6:/L/2QMEJnyiRabOOgRwOoA== [fileUNF] Raw Data

Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting

May 4, 2026 - TAN Li Yi

Tan, Li Yi, 2026, "Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting", https://doi.org/10.21979/N9/0EBMNO, DR-NTU (Data), V1, UNF:6:BFfoThAzHZSoffSc35HA7Q== [fileUNF]

Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting

Ridges-Statistical Data-2026-05-04 L.Y. Tan et al..tab

May 4, 2026 - Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting

Tabular Data - 181.6 KB - 12 Variables, 3605 Observations -

Data

TAN Li Yi (Nanyang Technological University)

May 4, 2026

Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations

Apr 9, 2026 - Rafika RAHMAWATI

Rahmawati, Rafika; Li, Shuzhou, 2026, "Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations", https://doi.org/10.21979/N9/LDPUKT, DR-NTU (Data), V2

The provided data includes the general source code and its computational results.

Benchmark-1-UCCSD-Tier1-ipynb-09042026.ipynb

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations

Jupyter Notebook - 305.7 KB -

Benchmark VQE using UCCSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer

Benchmark-2-HE-Tier1-ipynb-09042026.ipynb

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations

Jupyter Notebook - 599.4 KB -

Benchmark VQE using Hardware Efficient ansatz with Gradient Descent and Quantum Natural Gradient Optimizer

Benchmark-3-kUpCCGSD-Tier1-ipynb-09042026.ipynb

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations

Jupyter Notebook - 119.9 KB -

Benchmark VQE using kUpCCGSD ansatz with Gradient Descent and Quantum Natural Gradient Optimizer

Noiseless-comp-cost-Tier1-png-08042026

Apr 9, 2026 - Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations

PNG Image - 215.3 KB -

Noiseless computation cost of min energy calculated using VQE

Rafika RAHMAWATI (Nanyang Technological University)

Apr 8, 2026

Data for Tier 1 Project

Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?

Nov 19, 2025 - Darrell Jun Jie TAY

Tay, Darrell Jun Jie, 2025, "Related Data for: CsPbI3 and DMA-incorporated CsPbI3: How stable are they?", https://doi.org/10.21979/N9/HBVMXK, DR-NTU (Data), V1, UNF:6:/L/2QMEJnyiRabOOgRwOoA== [fileUNF]

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