interpret-uv-vis-spectrum
关于
This skill analyzes UV-Vis spectra to identify chromophores, classify electronic transitions, and predict absorption maxima using Woodward-Fieser rules. It also performs quantitative analysis via the Beer-Lambert law. Use it for interpreting spectroscopic data from conjugated systems and determining concentrations.
快速安装
Claude Code
推荐npx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/interpret-uv-vis-spectrum在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
Interpret UV-Vis Spectrum
Analyze ultraviolet-visible absorption spectra to identify chromophores, classify electronic transitions, predict absorption maxima for conjugated systems, and apply the Beer-Lambert law for quantitative determination.
When to Use
- Identifying chromophores and the extent of conjugation in an organic compound
- Confirming the presence of aromatic rings, conjugated dienes, or enones
- Performing quantitative analysis (determining concentration from absorbance)
- Monitoring reaction kinetics by tracking absorbance changes over time
- Characterizing metal-ligand complexes via d-d and charge-transfer transitions
- Assessing solvent effects on electronic transitions (solvatochromism)
Inputs
- Required: UV-Vis spectrum data (wavelength in nm vs. absorbance or molar absorptivity)
- Required: Solvent used for measurement
- Optional: Concentration and path length (for Beer-Lambert calculations)
- Optional: Molar absorptivity (epsilon) values at lambda-max
- Optional: Spectra in multiple solvents (for solvatochromism analysis)
- Optional: Structural information from other spectroscopic methods
Procedure
Step 1: Verify Instrument Parameters and Spectrum Quality
Ensure the data is reliable before interpreting absorption bands:
- Wavelength range: Confirm the spectrum covers the relevant range. Standard UV-Vis spans 190--800 nm. Solvents impose low-wavelength cutoffs:
| Solvent | UV Cutoff (nm) | Notes |
|---|---|---|
| Water | 190 | Excellent UV transparency |
| Hexane | 195 | Non-polar, minimal solvent effects |
| Methanol | 205 | Protic, may cause blue shifts |
| Acetonitrile | 190 | Good general-purpose UV solvent |
| Dichloromethane | 230 | Absorbs below 230 nm |
| Chloroform | 245 | Absorbs below 245 nm |
| Acetone | 330 | Absorbs strongly, poor UV solvent |
- Absorbance range: Reliable measurements require absorbance between 0.1 and 1.0. Below 0.1, noise dominates; above 1.0, stray light causes non-linear response. Flag any lambda-max values outside this range.
- Baseline and blank: Verify that a solvent blank was subtracted. Residual solvent absorption or cuvette artifacts appear as a rising baseline at short wavelengths.
- Slit width: Narrow slit widths give better resolution but lower signal-to-noise. If fine structure is expected (vibrational progression on electronic bands), confirm the slit width is appropriate (1--2 nm).
Got: Instrument parameters documented, solvent cutoff respected, absorbance values within the linear range, and baseline confirmed clean.
If fail: If absorbance exceeds 1.0 at lambda-max, the sample must be diluted and remeasured. If the solvent absorbs in the region of interest, recommend re-acquisition in a more transparent solvent.
Step 2: Identify Lambda-Max and Band Characteristics
Locate and characterize all absorption bands:
- Locate lambda-max values: Identify each absorption maximum (lambda-max) and record its wavelength (nm) and absorbance (or molar absorptivity epsilon if known).
- Measure band shape: Note whether each band is broad and featureless (typical of solution-phase electronic transitions) or shows vibrational fine structure (typical of rigid chromophores like polycyclic aromatics).
- Record shoulders: Absorption shoulders indicate overlapping transitions. Note their approximate wavelength and intensity.
- Classify by molar absorptivity:
| epsilon (L mol-1 cm-1) | Transition Type | Example |
|---|---|---|
| < 100 | Forbidden (n -> pi*) | Ketone ~280 nm |
| 100--10,000 | Weakly allowed | Aromatic 250--270 nm |
| 10,000--100,000 | Fully allowed (pi -> pi*) | Conjugated diene ~220 nm |
| > 100,000 | Charge transfer | Metal complexes, dyes |
Got: All absorption maxima and shoulders tabulated with wavelength, absorbance/epsilon, and qualitative band shape.
If fail: If the spectrum shows no distinct maxima (monotonic rise), the compound may lack a chromophore in the measured range, or the concentration may be too low. Increase concentration or extend the wavelength range.
Step 3: Classify Electronic Transitions
Assign each absorption band to a specific electronic transition type:
- sigma -> sigma transitions* (< 200 nm): Observed only in vacuum UV. Relevant for saturated hydrocarbons and C-C/C-H bonds. Not measured in standard UV-Vis.
- n -> sigma transitions* (150--250 nm): Lone pair to sigma antibonding. Observed for heteroatoms (O, N, S, halogens). Saturated amines absorb near 190--200 nm; alcohols/ethers near 175--185 nm.
- pi -> pi transitions* (200--500 nm): Bonding pi to antibonding pi*. These are the strongest absorptions for organic compounds. Intensity and wavelength increase with extended conjugation.
- n -> pi transitions* (250--400 nm): Lone pair to pi antibonding. Formally forbidden (low epsilon, 10--100). Characteristic of C=O (270--280 nm for simple ketones), N=O, and C=S groups.
- Charge-transfer transitions: Electron transfer between donor and acceptor groups, or between metal and ligand. Typically very intense (epsilon > 10,000) and broad. Found in metal complexes and donor-acceptor organic molecules.
- d-d transitions (for transition metal complexes): Weak, broad bands in the visible region arising from crystal field or ligand field splitting.
Got: Each absorption band assigned to a transition type with supporting rationale (position, intensity, solvent sensitivity).
If fail: If a band cannot be assigned to a standard transition type, consider charge-transfer character or the possibility of impurity absorption. Multiple overlapping transitions may require deconvolution.
Step 4: Apply Woodward-Fieser Rules for Conjugated Systems
Predict lambda-max for conjugated dienes and enones and compare with observed values:
- Conjugated dienes (Woodward rules):
| Component | Increment (nm) |
|---|---|
| Base value (heteroannular diene) | 214 |
| Base value (homoannular diene) | 253 |
| Each additional conjugated C=C | +30 |
| Each exocyclic C=C | +5 |
| Each alkyl substituent on C=C | +5 |
| -OAcyl substituent | +0 |
| -OR substituent | +6 |
| -SR substituent | +30 |
| -Cl, -Br substituent | +5 |
| -NR2 substituent | +5 |
- Alpha-beta unsaturated carbonyls (Woodward-Fieser rules):
| Component | Increment (nm) |
|---|---|
| Base value (alpha-beta unsat. ketone, 6-ring or acyclic) | 215 |
| Base value (alpha-beta unsat. aldehyde) | 208 |
| Each additional conjugated C=C | +30 |
| Each exocyclic C=C | +5 |
| Homoannular diene component | +39 |
| Alpha substituent (alkyl) | +10 |
| Beta substituent (alkyl) | +12 |
| Gamma and higher substituent (alkyl) | +18 |
| -OH (alpha) | +35 |
| -OH (beta) | +30 |
| -OAc (alpha, beta, gamma) | +6 |
| -OR (alpha) | +35 |
| -OR (beta) | +30 |
| -Cl (alpha) | +15 |
| -Cl (beta) | +12 |
| -Br (beta) | +25 |
| -NR2 (beta) | +95 |
- Calculate predicted lambda-max: Sum the base value and all applicable increments.
- Compare with observed: Agreement within +/- 5 nm supports the proposed chromophore. Deviations > 10 nm suggest an incorrect structural assignment or strong solvent/steric effects.
Got: Predicted lambda-max calculated and compared with observed value, supporting or refuting the proposed chromophore structure.
If fail: If the predicted and observed values disagree significantly, re-examine the assumed chromophore structure. Common errors: miscounting substituents, overlooking an exocyclic double bond, or applying the wrong base value (homoannular vs. heteroannular).
Step 5: Apply Beer-Lambert Law for Quantitative Analysis
Use absorbance data for concentration determination or molar absorptivity characterization:
- Beer-Lambert equation: A = epsilon * b * c, where A = absorbance (dimensionless), epsilon = molar absorptivity (L mol-1 cm-1), b = path length (cm), c = concentration (mol L-1).
- Determine molar absorptivity: If concentration and path length are known, calculate epsilon from the measured absorbance at lambda-max.
- Determine concentration: If epsilon is known (from literature or a calibration curve), calculate the concentration from the measured absorbance.
- Check linearity: Beer-Lambert law is valid only in the linear range (A = 0.1--1.0). At higher absorbances, deviations occur due to stray light, molecular interactions, and instrumental limitations.
- Assess solvent effects: Compare spectra in polar vs. non-polar solvents:
- Bathochromic (red) shift: lambda-max moves to longer wavelength. pi -> pi* transitions red-shift in more polar solvents; n -> pi* transitions red-shift in less polar solvents.
- Hypsochromic (blue) shift: lambda-max moves to shorter wavelength. n -> pi* transitions blue-shift in more polar/protic solvents (hydrogen bonding stabilizes the lone pair ground state).
- Hyperchromic/hypochromic effects: Increase or decrease in epsilon without wavelength change.
Got: Quantitative results calculated with appropriate significant figures, linearity verified, and solvent effects documented if spectra in multiple solvents are available.
If fail: If Beer-Lambert linearity fails, check for sample degradation, aggregation at high concentration, or fluorescence interference. Dilute the sample and remeasure to confirm.
Validation
- Solvent cutoff respected and absorbance within the linear range (0.1--1.0)
- All lambda-max values and shoulders tabulated with wavelength, absorbance, and epsilon
- Each absorption band assigned to an electronic transition type
- Woodward-Fieser calculation performed where applicable and compared with observed lambda-max
- Beer-Lambert law applied correctly with verified linearity
- Solvent effects characterized if multi-solvent data is available
- Chromophore assignment consistent with molecular structure from other spectroscopic methods
Pitfalls
- Measuring above A = 1.0: High absorbance values are unreliable due to stray light effects. Always dilute and remeasure if lambda-max absorbance exceeds 1.0.
- Ignoring the solvent cutoff: Attempting to interpret absorptions below the solvent cutoff wavelength produces artifacts, not real sample data.
- Confusing transition types by intensity alone: A weak band near 280 nm could be an n -> pi* transition of a carbonyl or a forbidden pi -> pi* of an aromatic. Context and solvent effects are needed to distinguish them.
- Misapplying Woodward-Fieser rules: These empirical rules apply only to conjugated dienes and alpha-beta unsaturated carbonyls. They cannot be used for aromatic systems, isolated chromophores, or metal complexes.
- Neglecting impurity absorption: Even small amounts of a strongly absorbing impurity can dominate the spectrum. If lambda-max does not match expectations, consider impurity contributions.
- Assuming one band = one transition: Broad UV-Vis bands often contain multiple overlapping transitions. Band deconvolution may be necessary for accurate assignment.
Related Skills
interpret-nmr-spectrum-- determine molecular connectivity to support chromophore identificationinterpret-ir-spectrum-- identify functional groups that contribute to the chromophoreinterpret-mass-spectrum-- establish molecular formula and detect conjugation via fragmentationinterpret-raman-spectrum-- complementary vibrational data for symmetric chromophoresplan-spectroscopic-analysis-- select and sequence spectroscopic techniques before data acquisition
GitHub 仓库
相关推荐技能
llamaguard
其他LlamaGuard是Meta推出的7-8B参数内容审核模型,专门用于过滤LLM的输入和输出内容。它能检测六大安全风险类别(暴力/仇恨、性内容、武器、违禁品、自残、犯罪计划),准确率达94-95%。开发者可通过HuggingFace、vLLM或Sagemaker快速部署,并能与NeMo Guardrails集成实现自动化安全防护。
cost-optimization
其他这个Claude Skill帮助开发者优化云成本,通过资源调整、标记策略和预留实例来降低AWS、Azure和GCP的开支。它适用于减少云支出、分析基础设施成本或实施成本治理策略的场景。关键功能包括提供成本可视化、资源规模调整指导和定价模型优化建议。
quantizing-models-bitsandbytes
其他这个Skill使用bitsandbytes库量化大语言模型,能在GPU内存有限时通过8位或4位量化减少50-75%内存占用,同时保持精度损失最小。它支持INT8、NF4、FP4等多种量化格式,可与HuggingFace Transformers无缝集成,适用于需要部署更大模型或加速推理的场景。还提供QLoRA训练和8位优化器支持,让开发者能轻松实现高效模型压缩。
dispatching-parallel-agents
其他该Skill用于并行处理3个以上无依赖关系的独立故障,可为每个问题域分派专属Claude代理同时执行调查修复。它通过并发处理多个独立问题显著提升故障排查效率,特别适用于测试文件、子系统等无共享状态的场景。
