Molecular Electronics
Molecular Electronics — Single-Molecule Transport · Nanoelectronics
Compute with single molecules — predict and design the quantum conductance of a molecule wired between two electrodes.
📋 The problem
If single molecules could act as wires and transistors, electronics could shrink to the molecular scale. Predicting and designing the quantum conductance of a molecule wired between two electrodes is the central challenge.
🧗 Why it's a grand challenge
Transport depends on quantum interference, level alignment and the molecule–electrode contact — all sensitive and hard to measure; DFT+NEGF is expensive and approximate.
🧮 Governing model
G = (2e²/h)·T(E_F); T(E) = Tr[Γ_L G^r Γ_R G^a] (NEGF)Coherent quantum transport through a molecular junction: Landauer conductance G=(2e²/h)·T(E_F) with the transmission T(E) from non-equilibrium Green's functions (NEGF) of the molecule+leads.
Current best: DFT+NEGF transport + break-junction conductance measurements
🧭 Possible approaches
- ML / graph surrogates of NEGF transport
- Inverse design for target conductance / rectification
- Models of contact geometry and corona effects
🎯 Build the benchmark
Predict single-molecule conductance from structure (≲ 0.3 dex error); inverse-design for a target conductance.
Metric: conductance_logerr — log10 conductance error (lower better)
Datasets to start from: Single-molecule break-junction corpus, DFT+NEGF transmission set
🤖 Build an AI agent to solve it
An agent that designs molecular junctions for a target electrical behavior and predicts conductance.
Once a benchmark exists, an AI4Science agent can iterate solutions against it — every verified solution earns PWM.
This is a frontier framing page — an open problem, not yet benchmarked or verified, unlike PWM's mature computational-imaging benchmarks.