Chapter Four · failure evidence
What Surface Plasmon Resonance got wrong, from 24 dissertations
The records describe various experimental and analytical breakdowns encountered when applying surface plasmon resonance and related plasmonic biosensing techniques. Across these investigations, researchers experienced failures in surface functionalization, kinetic modeling, background scattering suppression, plasmonic coupling, and assay stability. These records come from PhD theses at 10 institutions, 2021 to 2026. Each links to its thesis. They were extracted by language models reading the full text, so treat each as a lead to read, not a verdict.
Ineffective surface functionalization and ligand attachment prevent optical resonance signal generation
Direct physisorption or sensing without specific capture ligands failed to accumulate target analytes and generate measurable optical resonance shifts. In addition, recombinant proteins failed to immobilize under standard buffer conditions, and responsive polymer shell coatings produced no concentration-dependent spectral shifts.
Tried and failed
direct protein physisorption onto sensor surface applied to optical biosensing transducers. Outcome: no signal. Reason: insufficient surface binding density or low refractive index contrast prevents measurable optical resonance shifts
All-Dielectric Nanophotonic via Glass Fluid Instabilities · EPFL
Tried and failed
responsive polymer shell coating for plasmonic biosensing applied to protein detection via LSPR shifts. Outcome: no signal. Reason: Target protein binding caused no concentration-dependent localized surface plasmon resonance wavelength shifts across various polymerizations
Tried and failed
plasmonic biosensing without specific capture ligands applied to single-cell secretion detection. Outcome: no signal. Reason: lack of affinity capture ligands prevents target analyte accumulation on the sensor surface
Tried and failed
amine coupling surface plasmon resonance immobilisation applied to recombinant protein on sensor chip. Reason: protein failed to immobilise under standard low pH sodium acetate buffer conditions
Rapid kinetics, multi-site binding, and analyte heterogeneity prevent accurate kinetic fitting
Interaction rates were too fast to be resolved within instrument temporal limits, and large heterogeneous analytes produced unreliable kinetic measurements. Furthermore, complex multi-site binding combined with solubility limits prevented reaching the surface saturation required for kinetic modeling.
Considered and rejected
Considered and rejected: Rejected surface plasmon resonance (SPR) for determining LO1 and LO1Fab binding kinetics because the large size and heterogeneity of MDA-LDL yielded unreliable and inaccurate data; adopted microfluidic diffusional sizing instead.
Tried and failed
surface plasmon resonance binding affinity modeling applied to fragment library screening on structured RNA. Outcome: did not converge. Reason: complex multi-site binding and solubility limits prevented reaching surface saturation needed for kinetic fitting
Tried and failed
surface plasmon resonance kinetic fitting applied to fast-exchanging protein-protein interactions. Reason: association and dissociation rates were too fast to be resolved within instrument temporal limits
CHARACTERIZING THE STRUCTURE AND DYNAMICS OF ADAPTIVE IMMUNE PROTEINS TO INFORM IMMUNOTHERAPY DESIGN · Penn
Background scattering and optical distortions undermine single-particle plasmonic sensing
Substrate surface roughness scattering equaled or exceeded single-particle signals, creating unrealistic sub-angstrom surface smoothness requirements for dark-field detection. Coherent interference and antenna scattering also distorted point spread functions, causing severe localization errors during standard fitting.
Tried and failed
dark-field plasmonic scattering detection applied to single biological nanoparticle sensing. Outcome: no signal. Reason: Substrate surface roughness scattering background equals or exceeds the scattering intensity of single nanoparticles.
Random scattering of surface plasmons for sensing and tracking · Imperial
Considered and rejected
Considered and rejected: Rejected dark-field plasmonic single-particle sensing due to requirement of unrealistic sub-angstrom (<0.1 nm) surface roughness to suppress background scattering below particle scattering.
Random scattering of surface plasmons for sensing and tracking · Imperial
Considered and rejected
Considered and rejected: Rejected standard 2D Gaussian fitting for plasmon-coupled single-molecule localization because coherent interference and antenna scattering distort PSFs, causing severe mislocalization errors.
Modeling the diffraction-limited images of interacting emitters and plasmonic nanoantennas · ResearchWorks
Polarization misalignment, spectral mismatch, and modal overlap degrade plasmonic coupling
Direct energy transfer failed when spectral overlap between nanoparticle localized plasmons and partner resonances was poor. In addition, orthogonal polarization excitation eliminated field enhancement on nanorods, and overlapping localized modes prevented geometric deconvolution of nanoparticle morphology.
Lost to a baseline
AuNP@CuFeS2 showed negligible direct energy transfer compared to AgNP@CuFeS2 due to poor spectral overlap with CuFeS2 quasistatic resonance (460-510 nm vs Au LSPR at ~530-550 nm)
Tried and failed
Orthogonal polarization excitation in surface-enhanced infrared spectroscopy applied to protein monolayer absorption detection. Outcome: no signal. Reason: Lack of plasmonic resonance enhancement when electric field polarization is perpendicular to nanorod long axis
Tried and failed
spectral peak broadening for geometric deconvolution applied to branched nanoparticle morphology characterisation. Outcome: no signal. Reason: overlapping localized surface plasmon resonance modes prevented distinguishing independent geometric sources of broadness
Non-specific surface aggregation and pipeline instability prevent reproducible binding assays
Severe protein aggregation and irreversible non-specific deposition formed thick layers across the sensor surface during kinetic runs. Consequently, researchers were unable to establish robust and reproducible binding assay pipelines across target protein panels.
Tried and failed
surface plasmon resonance validation screening applied to RNA-binding protein small molecule interactions. Outcome: unstable. Reason: could not establish robust and reproducible binding assay pipelines for the protein panel
High Throughput Screening for Small Molecule Interactions with Nucleic Acid Binding Proteins · MIT
Tried and failed
surface plasmon resonance and quartz crystal microbalance applied to protein binding and unbinding kinetics. Reason: severe protein aggregation and irreversible non-specific deposition formed thick layers on the sensor surface
Biophysical Dynamics Of Rgs-Lov Proteins As Systems For Light-Induced Membrane Recruitment · Penn
Left open by the authors
Problems the authors named and did not get to.
Left open
Optimize surface plasmon resonance (SPR) assay conditions, including buffer systems and regeneration protocols, to measure KD values for small-molecule PD-L1 candidates. Blocker: Requires a wet biochemistry lab and an SPR instrument (e.g., Biacore) with access to PD-L1 protein and small-molecule compounds.
The development and evaluation of PET imaging agents targeting PD-L1 · Imperial
Left open
Identify additional hits from antibody libraries and characterize full IgG binding affinity using surface plasmon resonance. Blocker: Requires wet lab facilities, surface plasmon resonance equipment, and physical antibody libraries/samples
ENGINEERING THE HUMORAL RESPONSE TO GENERATE ANTIGEN-SPECIFIC ANTIBODIES · Cornell
Left open
Assess antibody affinity and somatically hypermutated clones using surface plasmon resonance and B-cell sequencing instead of ELISA titers. Blocker: Requires a wet lab, animal/patient samples, surface plasmon resonance apparatus, and B-cell sequencing facilities.
Mesoporous Silica Rods Scaffolds for the generation of adaptive immune responses · Harvard
Left open
Validate binding affinity of ambiguous or fluorescence-quenching MST hit compounds against G9a using surface plasmon resonance assays. Blocker: Requires a wet lab, surface plasmon resonance instrumentation, purified recombinant G9a protein, and physical compound samples
Left open
Develop an s-SNOM simulation model incorporating direct tip-sample dipole interactions to reproduce near-field phase maps of coupled plasmonic resonators. Blocker: None
Enhanced infrared sensing with plasmonic metasurfaces and undetected light · Imperial
Left open
Develop surface functionalization and capping strategies for plasmonic metal nitride nanoparticles to improve colloidal stability and solvent dispersion. Blocker: Requires wet-lab chemical synthesis, specialized reagents, and experimental characterization apparatus.
SYNTHESIS, CHARACTERIZATION, AND PHOTOTHERMAL PROPERTIES OF PLASMONIC METAL NITRIDE NANOPARTICLES · DalSpace
Left open
Measure binding kinetics of FP-specific monoclonal antibodies to pre-fusion versus post-fusion spike conformations using surface plasmon resonance or biolayer interferometry. Blocker: Requires a wet lab, recombinant spike proteins (pre- and post-fusion), physical mAb samples, and biophysical instrumentation.
Fantastic B-Cells and Where to Find Them · Harvard
Left open
Optimize and repeat surface plasmon resonance (SPR) binding kinetics measurements between knuckle peptides and BMP receptors. Blocker: Requires wet lab access, an SPR instrument, synthesized knuckle peptides, and purified BMP receptors
Left open
Separate nonreorientable SHE-like torques from interface-driven spin-orbit precession effects having identical angular signatures in STFMR trilayer measurements. Blocker: Requires nanofabrication facilities, spin-torque ferromagnetic resonance (STFMR) hardware, and physical experimental samples
GENERATION OF SPIN CURRENTS IN FERROMAGNETIC MATERIALS · Cornell
Left open
Simulate and compute hybridized states and electron transfer modes for gold nanostar plasmon-induced chemistry. Blocker: Lacks specific computational methodology, target models, and precise parameters
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