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Wang et al. Energy Mater. 2026, 6, 600064 Page 19 of 34

passivate defects and modulate electronic properties. Liu et al. [152] introduced 3-(2-aminoethyl)pyridine
(3-PyEA) as an additive, whose terminal amino groups react with V on the perovskite surface while the
FA
nitrogen atoms in the pyridine ring coordinate with undercoordinated Pb ions, effectively eliminating
2+
surface deep-level traps responsible for the p-type tendency. This dual-functional passivation restores and
amplifies the n-type characteristics of the film, inducing an upward shift of the Fermi level (E ) by 160 meV
F
toward the CBM, thereby achieving near-optimal energy-level alignment with [6,6]-phenyl-C -butyric acid
61
methyl ester (PCBM) and significantly improving charge extraction efficiency.

Energy cascade engineering
Constructing gradient or cascade energy steps through ultrathin interlayers represents an effective strategy
for optimizing interfacial energy levels. The introduction of the hydroxylated non-fullerene acceptor NFA
(IT-DOH) at the perovskite/ETL interface effectively suppresses non-radiative recombination via the specific
interaction between the hydroxyl groups and undercoordinated Pb , thereby enabling inverted PSCs to
2+
achieve superior Voc . Crucially, intermolecular hydrogen bonding induces an expansion of the IT-DOH
[153]
conjugated plane, which facilitates the formation of long-range ordered molecular packing and a preferred
face-on orientation. This structural refinement provides auxiliary pathways for dissociated electrons to
migrate from the perovskite to the PCBM layer, effectively minimizing energy loss during charge transport
and enhancing the short-circuit current density (J ). While the vast majority of current additive engineering
SC
research focuses exclusively on improving the Voc, the IT-DOH strategy provides a dual enhancement of
both the Voc and Jsc [154,155] . This hydroxylated non-fullerene acceptor paradigm establishes a useful
foundation for future ML-guided molecular screening. On unmodified interfaces, a substantial energetic
offset frequently exists between the VBM of the perovskite and the HOMO of conventional HTLs such as
2,2′,7,7′-tetrakis[N,N-di(4-methoxyphenyl)amino]-9,9′-spirobifluorene (Spiro-OMeTAD) . To overcome
[156]
this interfacial barrier, Shen et al. [157] introduced an ultrathin p-type polymeric interlayer of
PDTBT2T-FTBDT (D18), which possesses a deeply situated HOMO level. By strategically positioning the
D18 energy level between the perovskite valence band and the HTL, a continuous energy cascade was
established. This tailored alignment enables photogenerated holes to transition smoothly along the potential
gradient with negligible energy loss. Precise regulation of the D18 thickness to approximately 7 nm ensures
both optimal surface coverage and effective energy-level modulation without incurring the parasitic series
resistance typical of thicker polymeric films. Operating at the perovskite/HTL junction, this methodology
represents a conceptual counterpart to the IT-DOH strategy employed at electron transport interfaces,
further underscoring the universal efficacy of energy cascade engineering in high-performance photovoltaics.
The molecular bridge strategies previously discussed in the context of interfacial defect passivation prove
equally effective in facilitating superior energy-level alignment [32,76] . Although the precise mechanistic details
have been discussed in the preceding sections, this dual functionality underscores a critical overarching
principle in perovskite research, namely that the enhancements provided by additive engineering are not
isolated but rather function through a multifaceted approach to synergistically improve the collective
photovoltaic characteristics of PSCs.

In summary, achieving favorable interfacial energetics is not a standalone objective but rather a synergistic
component of comprehensive defect and interface management. As evidenced by the diverse molecular
interventions discussed, simultaneously addressing energy-level offsets and chemical vulnerabilities through
multifunctional additives represents an effective paradigm for minimizing non-radiative losses and
maximizing charge extraction in perovskite photovoltaics. Looking forward, the integration of ML with
additive engineering is poised to advance the rational design of these interfacial modifiers. By systematically
extracting quantum descriptors from DFT calculations, such as molecular dipole moments and binding
affinities, ML algorithms can utilize these physical parameters as core input features alongside
high-throughput experimental datasets [158,159] . This integration enables computational models to accurately