Autonomous Chemical Mechanistic Discovery through Agentic Reasoning and Validation

Introduction

• Existing tools automate predefined procedures, but open-ended mechanistic inquiry still requires competing hypotheses, discriminative calculations, iterative refinement, and integrated methodological checks (7–10, 25,26, 27–29).Generalist LLM agents have translated well-specified objectives into computational task loops, but typically execute fixed protocols rather than open-ended scientific reasoning (18–24).Source: Introduction · pp. 3–4
• ARCHE reconstructs stereocontrolling transition states and selectivity trends, refines competing radical hypotheses, and identifies an interpretable descriptor for ligand-controlled regioselectivity in nickel migratory cross-coupling.The scenarios cover a benchmark asymmetric organocatalytic reaction, a recently discovered but unpublished photochemical radical transformation, and nickel-catalyzed migratory cross-coupling.Source: Introduction · p. 5

ARCHE System Architecture

• ARCHE couples a generalist reasoning model, Gaussian-specialized ARCHE-Chem, and a tool registry in proposal–execution–reflection cycles that assess outputs and revise hypotheses or computational settings.ARCHE-Chem refines Gaussian settings, interprets outputs, diagnoses failures, and checks calculation validity, including transition-state verification through frequency and IRC analysis.Source: Introduction · pp. 4–5, ARCHE System Architecture · pp. 5–6

Role in ARCHE

• Within ARCHE's reasoning–validation loop, ARCHE-Chem refines Gaussian inputs, reviews outputs, and diagnoses errors; examples show valid keyword selection and correct attribution of SCF non-convergence.The comparison examples contrast ARCHE-Chem with GPT-o3-mini, which proposes an inappropriate method combination and misidentifies the failed process.Source: Figure 2 · p. 7, ARCHE-Chem: training and performance… · p. 8

Training data

• Its corpus drew on 105 textbooks and manuals and 432 expert forum discussions, curated into four task categories and expert-validated; evaluation tasks and case studies were excluded.The categories were computational chemistry and Gaussian basics, route generation, result analysis, and error handling.Source: ARCHE-Chem: training and performance… · p. 8

Training and inference

• Training combined continual pretraining of Qwen2.5-7B-Instruct with supervised fine-tuning and a Gemma-2-27B-IT reward model; inference ranks multiple candidates and selects the highest-scoring output.The reward model scores syntactic validity and chemical consistency.Source: Figure 2 · p. 7, ARCHE-Chem: training and performance… · p. 8

Performance

• ARCHE-Chem scored 70.65% CGB, 65.60% GRG, 80.30% GRA, and 87.60% GEH; GPT-5.5 led CGB at 82.71%, while ARCHE-Chem led the other categories.The benchmark compared ARCHE-Chem with 15 other models on held-out tasks.Source: Figure 2 · p. 7, ARCHE-Chem: training and performance… · p. 8
• ARCHE-Chem's GRG accuracy exceeded GPT-o3-mini's 44.80%; its GRA and GEH accuracies exceeded the next-highest scores by 1.30 and 3.90 percentage points, respectively.The remaining models scored 3.91–38.30% on GRG.Source: ARCHE-Chem: training and performance… · pp. 8–9

in a reported vicinal diamine-catalysed aldol reaction

• 1.9 kcal/mol was the computed activation-free-energy difference between enantiomeric pathways, close to 1.6 kcal/mol inferred from 88% ee at 303.15 K; TS-2a and TS-2b backbone RMSDs were 0.01 Å and 0.15 Å.The recovered structures corresponded to the competing enantiodetermining pathways reported by the Houk group (31).Source: Figure 3 · p. 10, in a reported vicinal… · p. 11
• ARCHE identified 12 transition states: the nine reported in the reference study and three additional, higher-energy, chemically reasonable candidates.The additional candidates indicate exploration of the stereochemical and conformational landscape, and were ranked as less favourable than the dominant pathways.Source: in a reported vicinal… · pp. 10–11, Figure 3 · p. 10
• ARCHE completed the aldol analysis within 24 hours without manual intervention, recovering the published mechanistic model from reaction-level input alone.The system was given reactants, product, catalyst, solvent, and temperature, while the reference study's selectivity, mechanism, transition states, protocols, and energetic results were withheld.Source: in a reported vicinal… · pp. 9, 11

iodoboronate C–I cleavage reaction

• Under 450 nm irradiation, α-iodoboronate 1 with HPPh2 and Cs2CO3 gave alkylboronate 2 in 83% yield; controls showed product formation required light, base, and phosphine and was suppressed by TEMPO.The control results indicated radical intermediates, while the activation mode and overall mechanism remained unresolved.Source: iodoboronate C–I cleavage reaction · p. 11
• ARCHE's evaluated pathways included concerted routes with 46.0 kcal·mol−1 Gibbs free-energy barriers; isolated 1 and its PPh2-associated counterpart had lowest singlet excitation energies of 102.8 and 75.8 kcal·mol−1, above 63.6 kcal·mol−1 from 450 nm light.These calculations excluded the concerted pathways as incompatible with room-temperature reactivity and the examined direct photoexcitation scenarios as energetically mismatched.Source: iodoboronate C–I cleavage reaction · pp. 11–12
• A reflective revision proposed favorable CsPPh2-complex formation and an approximately 64.0 kcal·mol−1 excitation, enabling photoinduced homolytic C–I cleavage and radical formation consistent with TEMPO inhibition.The revised excitation closely matched the energy supplied by 450 nm irradiation, and the activation mode emerged through iterative hypothesis generation, computation, and revision.Source: iodoboronate C–I cleavage reaction · p. 12

coupling reactions

• The Br–N–N–H dihedral torsional energy explains ligand-dependent selectivity: ortho-methyl substitution lowers the rotational penalty and favors hydride migration, while other variants favor original-site coupling.The descriptor reproduces the observed ligand-series trend and is consistent with prior transition-state analyses.Source: Figure 5 · p. 14, coupling reactions · pp. 15–16
• In the representative 2020 system [47], ortho-substituted N,N-bidentate ligands promote migratory coupling, whereas unsubstituted and meta- or para-substituted ligands favor original-site coupling.The underlying structural or electronic factor governing this experimentally established regioselectivity switch had not been discovered.Source: coupling reactions · p. 15
• ARCHE tested candidate structural hypotheses—including dihedral rotation, ligand bite angle, and Ni–H bond strength—using targeted calculations on a square-planar Ni(II)(bpy)–Br–H intermediate.The planner used relaxed dihedral scans and controlled geometric distortions after computational setup verification.Source: coupling reactions · p. 15

Discussion

• Across three scenarios, ARCHE reproduces stereocontrolling transition states, identifies a radical pathway consistent with experiments, and extracts a torsional descriptor for migratory selectivity.The authors attribute more reliable, chemically grounded analysis to integrating domain-specific computational expertise with general-purpose reasoning.Source: Discussion · pp. 16–17
• ARCHE currently uses a Gaussian-centric workflow, but its modular tool registry and dual-model architecture offer a blueprint for extending self-validating exploration to other scientific software and autonomous laboratories.The proposed laboratory extension would integrate robotic execution with real-time analytical feedback.Source: Discussion · p. 17

ARCHE system overview

• ARCHE retrieves relevant knowledge, generates and ranks competing mechanistic hypotheses, then translates prioritized hypotheses into computational workflows executed through external chemistry tools.Calculated results return in structured form for iterative assessment and revision.Source: ARCHE system overview · p. 18
• A generalist model supports mechanistic exploration, while the specialized ARCHE-Chem model provides methodological rigour and physical consistency in computational planning and evaluative reflection.Source: ARCHE system overview · p. 18
• A structured tool registry and execution interface connect reasoning components to external tools, enabling a reasoning–validation cycle grounded in calculated evidence.Source: ARCHE system overview · p. 18

Reasoning–validation circle

• ARCHE iteratively tests competing mechanistic hypotheses and refines them until reaching a chemically consistent conclusion.The cycle begins with relevant chemical knowledge retrieval, then formulates hypotheses and computational workflows targeting decisive evidence.Source: Reasoning–validation circle · pp. 18–19
• ARCHE-Chem supplies technical judgment for computational settings, failure diagnosis, and interpretation of computed outputs.Validated workflows are executed by a module that returns structured results for assessment.Source: Reasoning–validation circle · p. 18
• When calculations fail or evidence conflicts with hypotheses or observed reactivity, ARCHE revises the hypothesis, workflow, or both and evaluates again.Source: Reasoning–validation circle · p. 19

ARCHE-Chem training and inference

• ARCHE-Chem, derived from Qwen2.5-7B-Instruct, was continually pretrained and supervised fine-tuned for Gaussian input refinement, output interpretation, and error diagnosis.At inference, response selection is also reward-guided.Source: ARCHE-Chem training and inference · p. 19
• Continual pretraining used full-parameter optimization on a corpus of 105 textbooks and manuals, 432 expert discussions and articles, and approximately 286 MB of text.The corpus included computational chemistry literature, textbooks, official Gaussian manuals and documentation, and expert-level discussions and articles.Source: ARCHE-Chem training and inference · p. 19
• Supervised fine-tuning used approximately 50,000 question–answer pairs covering computational chemistry and Gaussian basics, result interpretation, route generation, output analysis, and error diagnosis.The stage was intended to turn domain knowledge into task-oriented expert behaviour.Source: ARCHE-Chem training and inference · p. 19
• The training data excluded evaluation-specific hypotheses, structures, procedures, energies, and benchmarks, so mechanistic conclusions came from explicit inference-time calculations rather than task-specific memorization.The exclusion applied to both the curated corpus and fine-tuning set.Source: ARCHE-Chem training and inference · p. 19
• At inference, a Gemma-2-27B-IT reward model trained on 28,000 preference pairs scored and ranked N=8 sampled responses, and the highest-scoring response was selected.This was the Best-of-N test-time scaling strategy.Source: ARCHE-Chem training and inference · p. 20

Benchmark scope

• ARCHE-Chem was evaluated on held-out benchmarks spanning computational chemistry and Gaussian basics, Gaussian route generation, result analysis, and error handling.The four categories distinguish descriptive methodological familiarity from execution-critical capabilities needed for practical computational chemistry support.Source: Benchmark design for ARCHE-Chem… · p. 20

Task examples

• Representative tasks included interpreting Gaussian keywords and method settings, generating executable route sections, analyzing Gaussian outputs, and diagnosing failed calculations.Full benchmark construction details, category definitions, and example tasks are provided in Supplementary Section A2.3.Source: Benchmark design for ARCHE-Chem… · p. 20

Tool registry and executable workflow construction

• The registry defines each operation’s computational function, required inputs, and expected outputs, covering basic utilities and recurring computational chemistry workflows.Examples include molecular structure conversion and Gaussian output parsing.Source: Tool registry and executable workflow… · p. 20
• During workflow construction, ARCHE assembles operations by their input–output relations and automatically inserts conversions when one step’s output cannot directly serve as the next step’s input.Conversions can transform molecular structures between file formats or coordinate representations.Source: Tool registry and executable workflow… · p. 20
• Conversion-aware composition makes multi-step workflows executable as complete procedures and provides a structured, traceable link between mechanistic reasoning and computational evaluation.Further registry details and representative tools are provided in Supplementary Section A3.Source: Tool registry and executable workflow… · p. 21

• At the system level, ARCHE was evaluated in three scenarios spanning established-mechanism reproduction, an unresolved mechanistic question, and descriptor extraction in a complex catalytic system.These value demonstrations assessed end-to-end reaction-mechanism elucidation.Source: Evaluation framework · p. 21
• ARCHE-Chem’s model-level benchmarks covered computational chemistry and Gaussian basics, Gaussian route generation, output analysis, and error handling.Source: Evaluation framework · p. 21
• Benchmark instances were manually reviewed for technical correctness, relevance, and reference-answer consistency, and kept separate from model-development training and preference data.The separation covered continual pretraining, supervised fine-tuning, and reward-model preference data.Source: Evaluation framework · p. 21
• For each system hypothesis, ARCHE generated a computational workflow; evaluation asked whether computed evidence supported the claim and whether reasoning-to-execution yielded chemically consistent conclusions.The three case studies were excluded from model-development data, and reported conclusions arose from calculations performed during inference.Source: Evaluation framework · p. 21
• Supplementary C provides the three demonstrations’ generated hypotheses, iterative refinements, and computational results extracted from Gaussian log files.Source: Evaluation framework · p. 22

Use of proprietary models

• GPT-5 via API supported the Retrieval, Hypothesis, and Planner Agents, and model availability or version changes may affect exact reproduction of some agent-level outputs.The authors report this limitation explicitly for transparency.Source: Use of proprietary models · p. 22

• Gaussian 16 was used for electronic-structure calculations, with RDKit, Open Babel, ASE, cclib, Multiwfn, and other tools assisting structure preparation, format conversion, and data analysis.Source: Computational chemistry protocols · p. 22
• Asymmetric-catalysis geometries and frequencies used B3LYP/6-31G(d) with IEFPCM acetone solvation; transition states were IRC-verified and energies refined at M06-2X/def2-TZVPP.Source: Computational chemistry protocols · p. 22
• Radical-system geometries and frequencies used B3LYP-D3(BJ)/def2-SVP with SMD ethyl acetate solvation, with TD-DFT used for excited states when required.Source: Computational chemistry protocols · p. 22
• The remaining system used a def2-SVP basis set and SMD solvation in dimethylacetamide, and stationary points were confirmed by vibrational frequency analysis.Source: Computational chemistry protocols · p. 22

Runtime environment and implementation

• ARCHE coordinated GPU-based language-model reasoning with CPU-based computational chemistry in a decoupled runtime environment.Model training and inference ran on GPU servers, while chemistry calculations ran on CPU resources; the tools stack included RDKit, Open Babel, ASE, cclib, Multiwfn, and related utilities for structure handling, workflow preparation, and output parsing.Source: Runtime environment and implementation · p. 23
• ARCHE-Chem training used eight NVIDIA A100 GPUs and took approximately 21 wall-clock hours, or 168 GPU-hours, for continual pretraining and supervised fine-tuning.The cluster ran Ubuntu 22.04 LTS with PyTorch 2.2 and DeepSpeed using mixed-precision FP16; both the generalist reasoning model and ARCHE-Chem were deployed on GPU servers for inference.Source: Runtime environment and implementation · p. 23
• Gaussian 16 (Revision B.01) ran the production chemistry studies on a dedicated node with dual Intel Xeon Platinum 8352Y CPUs and 512 GB RAM.Jobs used multicore CPU threads, and case-specific computational parameters are summarized in Supplementary Tab.S5.Source: Runtime environment and implementation · p. 23

A Supplementary Methods S4

• The methods outline ARCHE’s architecture and execution flow, including agent-level architecture, feedback routing, structured inter-agent communication, and cross-stage consistency.These topics are listed as sections A.1.1–A.1.4.Source: A Supplementary Methods S4 · p. 31
• The methods describe ARCHE-Chem development and evaluation, tool-registry specifications and workflow construction, and computational protocols for the value demonstrations.Listed topics include training data and configuration, reward-model training and Best-of-N inference, registry entries, and case-study protocols.Source: A Supplementary Methods S4 · p. 31
• The evaluation protocol covers validation through three value demonstrations, comparison with external models, and success criteria for the demonstrations.Source: A Supplementary Methods S4 · p. 32

B Supplementary Discussion S31

• The discussion covers autonomous reasoning and validation pipelines for three case studies, followed by supplementary results for each case study.The cases address asymmetric aldol chemistry, blue-light-driven deiodoborylation, and descriptor abstraction for migratory cross-coupling.Source: B Supplementary Discussion S31 · p. 32

C Supplementary Data S42

• The supplementary data include prompts for the retrieval, hypothesis, and planner agents and Gaussian expert model, plus problem formulations for three validations.The validations concern asymmetric catalysis, a photochemical radical reaction, and dihedral-based selectivity.Source: C Supplementary Data S42 · p. 32
• The data section lists example hypothesis objects for asymmetric catalysis, the radical reaction, and dihedral-based selectivity.Source: C Supplementary Data S42 · p. 32
• The data section also lists example workflows for the asymmetric-catalysis, photochemical-radical-reaction, and dihedral-based-selectivity validations.Source: C Supplementary Data S42 · pp. 32–33

C.10 Supplementary Information

• The supplementary information includes a section ending with a reference to quantum chemical calculations.Source: §C.10 · p. 33

A.1.1 Agent-level architecture

• ARCHE partitions retrieval, hypothesis generation, workflow planning, execution, and reflection into distinct components that iteratively test ranked hypotheses against computed evidence.The Hypothesis Agent prioritizes candidates for testing; reflection can refine or reject them based on computational results.Source: §A.1.1 · pp. 34–37

A.1.2 Execution flow and feedback routing

• Execution failures route workflow or setting problems to planning, defective starting structures to the user, and successful but contradictory results to the Hypothesis Agent for scientific revision.The system distinguishes technical correction from reconsideration of the mechanism under test.Source: §A.1.2 · p. 39

A.1.3 Structured inter-agent communication

• Structured hypothesis, workflow, execution, result, and reflection records coordinate distinct components while preserving traceability from each proposed mechanism through calculations to revisions.This record links calculations to their originating hypotheses and supports reconstruction of the reasoning and computational pathway.Source: §A.1.3 · pp. 40–41

A.1.4 Cross-stage consistency

• ARCHE links each conclusion to an upstream hypothesis and executed computational evidence, tracking why workflows or hypotheses change and recording incomplete or non-diagnostic results as limitations.Retrieved context and model priors guide hypothesis generation and planning but are not treated as evidence for final conclusions.Source: §A.1.4 · pp. 41–42

A.2.1 Training pipeline overview

• ARCHE-Chem was developed from Qwen2.5-7B-Instruct through continual pretraining, domain-specific supervised fine-tuning, and human-reviewed reward modeling, with reward-ranked Best-of-8 responses at inference.Its roles include auditing Gaussian settings, interpreting outputs, and supporting execution analysis and reflection.Source: §A.2.1 · pp. 42–43

A.2.2 Pretraining corpus composition

• The deduplicated pretraining corpus combines textbooks, official Gaussian documentation, and expert forum discussions to cover theory, software conventions, and practical troubleshooting.The sources were selected to support workflow evaluation, setting selection, failure diagnosis, and interpretation of computational results.Source: §A.2.2 · pp. 43–44

A.2.3 Instruction dataset composition

• The SFT dataset covers computational-chemistry and Gaussian basics, route generation, result analysis, and error handling, spanning foundational knowledge and execution-critical workflow support.Route-generation examples address tasks such as optimization, frequency analysis, transition-state search, IRC calculations, and single-point energies.Source: §A.2.3 · pp. 44–46

A.2.4 Data independence and contamination control

• ARCHE’s evaluation scenarios were excluded from ARCHE-Chem and reward-model training, and reported mechanistic conclusions came from quantum-chemical calculations performed during inference.External-model comparisons used identical input conditions.Source: §A.2.4 · p. 46

A.2.5 Training configuration

• ARCHE-Chem was trained with PyTorch mixed precision, while its Gemma-2-27B-IT reward model learned execution-oriented preferences from 28,000 expert-curated response pairs and selected outputs using Best-of-N ranking.The pairs favored chemical validity, appropriate Gaussian workflows, and executable, internally consistent responses; the reward model used AdamW, a cosine schedule, a 4096-token maximum sequence length, a 2 × 10−6 learning rate, a 0.03 warmup ratio, and three epochs.Source: §A.2.5 · p. 46, Table S3 · p. 47, §A.2.6 · pp. 47–48

A.3.1 Tool registry schema

• ARCHE’s registry defines atomic operations and standardized multi-step pipeline tools, with input, output, role, and constraint descriptions that support reliable tool selection and executable workflows.Examples include structure conversion, Gaussian input generation, job execution, output parsing, conformer preparation, and transition-state initialization.Source: §A.3.1 · pp. 49–50, §A.3.2 · p. 50, Table S5 · p. 51

A.3.3 Workflow construction mechanism

• The Planner Agent matches tools to hypothesis-derived objectives, checks data compatibility, inserts format conversions when needed, and represents workflows as directed graphs of tool calls and dependencies.The registry supplies the input-output specifications used for compatibility checks.Source: §A.3.3 · p. 51

Workflow of Case Study 1

• The Case Study 1 workflow links transition-state generation and optimization for both enantiomeric pathways to IRC connectivity checks, refined energies, and predicted enantiomeric excess.Its structured steps preserve execution order and data dependencies, supporting reproducible computational procedures.Source: Workflow of Case Study 1 · pp. 52–55

A.4 Computational protocols for value demonstrations

• ARCHE’s evaluation calculations use case-specific quantum-chemical protocols, with representative Gaussian settings provided for the value-demonstration scenarios.The supplied passage identifies Table S6 as the summary of representative settings but does not state its individual values.Source: §A.4 · pp. 55–56, Table S6 · p. 56

A.4.2 Asymmetric catalysis case study

• For asymmetric catalysis, ARCHE located and verified stereocontrolling transition states, refined their energies, and assessed agreement with the literature through geometric, energetic, and mechanistic comparisons.The assessments included structural similarity metrics such as RMSD where applicable, relative free-energy differences and selectivity trends, and consistency of hydrogen bonding and substrate–catalyst arrangement.Source: §A.4.2 · pp. 56–57

A.4.3 Photochemical reaction case study

• For the photochemical system, ARCHE assessed candidate intermediates and excited states against computed energetics, reported reaction conditions, and experimental control observations to eliminate unsupported pathways.Ground-state species were checked by geometry optimization and frequency analysis, while scenarios requiring photoexcitation were evaluated with TDDFT.Source: §A.4.3 · p. 57

B.1.3 Case Study 3: Descriptor abstraction for migratory cross-coupling

• For nickel-catalysed migratory coupling, ARCHE selected the Br–N–N–H dihedral as a direct, interpretable descriptor: ortho-substituted ligands incur the lowest penalty for migration-associated distortion.Bite-angle and Ni–H bonding descriptors were not retained because they were indirect or inconsistent; the dihedral tracked the distortion linked to hydride migration and the ligand-dependent selectivity trend.Source: §A.4.4 · p. 58, §B.1.3 · p. 66

A.5.3 Success criteria for the three value demonstrations

• The three demonstrations assess complementary capabilities: reconstructing a known mechanism, converging on an experimentally consistent explanation, and extracting a mechanistic principle from competing descriptors.Success required supported transition-state families and qualitative selectivity for the asymmetric case, evidence-consistent pathway selection for the photochemical case, and a compact, interpretable descriptor for the nickel case.Source: §A.5.1 · p. 59, §A.5.3 · pp. 60–61

A.5.2 Comparison with external models

• External-model comparisons controlled task inputs and scoring, while evaluating ARCHE-Chem with its Best-of-N configuration (N = 8) and without manual answer repair.GPT-4o scored responses against shared reference answers and fixed rubrics; external models used fixed prompting without human selection among retries unless stated otherwise.Source: §A.5.2 · pp. 59–60

B.1.1 Case Study 1: Asymmetric aldol reaction

• ARCHE identified 12 verified aldol transition states, recovering the reported stereocontrolling pathways with a 1.9 kcal·mol−1 free-energy difference and completing the analysis within 24h.The major and minor transition states matched reference structures with backbone RMSD values of 0.01˚A and 0.15˚A, respectively; three additional verified candidates were higher in energy.Source: §B.1.1 · pp. 62–63

B.1.2 Case Study 2: Blue-light-driven deiodoborylation

• For blue-light deiodoborylation, ARCHE rejected concerted cleavage and initial photoexcitation pathways because their calculated barriers or excitation energies were incompatible with the reaction conditions.The concerted barrier was 46.0 kcal·mol−1; isolated substrate and phosphine-adduct excitation energies were 102.8 and 75.8 kcal·mol−1, respectively, exceeding the 63.6 kcal·mol−1 energy of 450 nm light. The retained pathway was required to satisfy energetic and photophysical constraints as well as experimental evidence.Source: §A.4.3 · p. 57, §B.1.2 · p. 64
• After reassessing component interactions, ARCHE proposed a cesium–phosphide–substrate complex whose near-matched excitation energy supports radical initiation consistent with the experimental controls.Complex formation was favorable (ΔG = −3.0 kcal·mol−1), and its excitation energy was 64.0 kcal·mol−1 versus 63.6 kcal·mol−1 for 450 nm light; product formation required light, base, and phosphine and was suppressed by TEMPO.Source: §B.1.2 · pp. 64–65

B.2.1 Supplementary results for case study 1

• Figure S2 presents the enumerated and energetically ranked transition-state conformations, comparing newly identified structures with previously reported motifs and reporting activation-energy differences and RMSD.The caption describes crown, chair-boat, boat-chair, and twist-derived conformers, with relative activation free energies referenced to TS-2a.Source: Figure S2 · p. 67
• ARCHE recovered all reported low-energy transition states TS-2b through TS-2i and identified additional conformers across several motifs with energies near the lowest-energy structure.The conformers include crown, chair-boat, boat-chair, and twist-derived structures; relative activation free energies were referenced to the lowest-energy stereoisomeric transition structure.Source: §B.2.1 · p. 68
• RMSD comparisons confirm that ARCHE faithfully reproduced literature-reported transition-state geometries, while newly identified conformers extend the accessible conformational space.The new conformers were not included in the RMSD comparison.Source: §B.2.1 · p. 68
• The automated conformational exploration provides a comprehensive transition-state ensemble for stereoselectivity that is consistent with previously characterized mechanistic models.Source: §B.2.1 · p. 68

Closed-shell pathways

• Mechanism A’s 46.0 kcal·mol−1 activation barrier implied an extremely slow room-temperature reaction, excluding it as the dominant pathway.The hypothesis proposed closed-shell nucleophilic attack followed by C–I bond cleavage.Source: §B.2.2 · p. 68, Figure S3 · p. 69

Alternative pathways

• Mechanisms B–D received no computational support because transition-state searches failed to locate saddle points consistent with their proposed elementary steps.Optimization attempts either failed to converge to expected saddle points or relaxed to structures inconsistent with the hypotheses.Source: §B.2.2 · pp. 68–69, Figure S3 · p. 69

Photochemical radical-generation hypotheses

• Mechanisms E and F aligned with dark-control and radical-inhibitor results, but their predicted ultraviolet excitation conflicted with the experimental 450 nm irradiation.These S1-excitation pathways were therefore excluded as the validated mechanism.Source: §B.2.2 · pp. 69–70, Figure S3 · p. 69

Mechanism G

• Mechanism G was retained as most plausible: S2 excitation at 447 nm (f=0.0567), unlike inefficient S1 excitation at 649 nm (f=0.0044), matches 450 nm irradiation.Formation of the CsPPh2 complex lowers system free energy by 3.0 kcal·mol−1; the proposed initial activation complex involves Ph2P–/Cs+ ion pairing.Source: Figure S3 · p. 69, §B.2.2 · p. 70

B.2.3 Supplementary results for case study 3

• Bite-angle scans found the ortho-substituted ligand most flexible, but this indirect geometric effect does not track the out-of-plane distortion linked to hydride migration.The bite angle remains coordinated during migratory coupling, so its variation lacks a direct causal connection to selectivity; the dihedral scan probes the more relevant change.Source: §B.2.3 · pp. 70–71, Figure S4 · p. 71
• Ni–H metrics gave mixed evidence: the ortho-substituted ligand had the largest Wiberg bond index but somewhat easier bond dissociation, and neither directly captures the migration barrier.The Wiberg index is a local bonding measure, whereas bond dissociation energy describes cleavage thermochemistry rather than energy evolution along the operative reaction coordinate.Source: Figure S4 · p. 71, §B.2.3 · pp. 71–72

C.1 Prompt for Retrieval Agent

• The retrieval-agent prompts request 5–10 computational-chemistry keywords and a structured literature review emphasizing methods, protocols, software, and methodological benchmarks.The review is scoped to computational chemistry, including reaction mechanisms, transition-state searches, conformational sampling, solvation, and basis-set and functional choices.Source: §C.1 · pp. 72–74

C.2 Prompt for Hypothesis Agent

• The hypothesis-agent prompts call for distinct, testable computational hypotheses and strategies using quantum-chemical methods and Python-based chemistry tools.Examples include DFT, coupled-cluster or multireference methods, transition-state optimization, intrinsic reaction-coordinate analysis, solvation models, and dispersion corrections.Source: §C.2 · pp. 75–76
• The prompts direct hypothesis ranking by scientific soundness, feasibility, and chemical relevance, alongside novelty, supporting evidence, and logical clarity.They also describe comparing, merging, and resolving conflicts among hypotheses.Source: §C.2 · p. 78
• The Hypothesis Agent is instructed to rank competing strategies by scientific robustness and promise, explain its reasoning and weaknesses, and return assay analysis with a winner and loser in JSON.The assay comparison is framed as a decision based on evaluation criteria and provided evidence.Source: §C.2 · pp. 78–79

Automated Computational Protocol Formulation

• The computational protocol prompt requires ordered, tool-matched steps and explicit input/output compatibility checks, inserting format conversions when needed.It specifies a TS pipeline for initial structures, Gaussian input generation before TS optimization, and separate TS optimization and frequency analysis.Source: Automated Computational Protocol… · pp. 81–82

Gaussian Keyword Generation

• Gaussian Keyword Generation is prompted to produce a complete route section from a calculation description and set temperature when requested.The requested output is the route section alone, without explanation.Source: Gaussian Keyword Generation · p. 83

C.5 Problem formulation for the asymmetric catalysis validation

• The asymmetric-catalysis validation problem is framed as verifying a reaction mechanism, but the supplied passage gives no reaction details.The question text is incomplete in the supplied passage.Source: §C.5 · p. 84

C.6 Problem formulation for the photochemical radical reaction validation

• The photochemical case describes an 83% yield under 450 nm blue light and asks for computational tests of concerted, substitution, radical, ionic, or closed-shell pathways.The reaction uses Ph–CH2–CH2–CHI–BPin and HPPh2 with 2 equivalents of Cs2CO3 in EtOAc/CPME; the prompt notes possible C–I homolysis and HPPh2 as an H-atom donor.Source: §C.6 · pp. 84–85

C.7 Problem formulation for the dihedral-based selectivity validation

• In the nickel-catalyzed cross-coupling, ortho-methyl substitution on bipyridine favors the migratory product, whereas unsubstituted or meta-/para-methyl ligands favor the in situ product.The prompt states that TBAB and LiOH in DMA are required and that ligand structure strongly regulates selectivity with a Ni(II) catalyst.Source: §C.7 · p. 85
• For nickel selectivity, the proposed hypotheses link ortho-substitution effects to measurable geometric, electronic, or energetic indicators of the tetra-coordinate Ni(II) catalyst.The catalyst bears N–N, Br, and H ligands; the task asks for abstract explanations of selectivity reversal and minimal computational validation, without requiring explicit substrates or full transition states.Source: §C.7 · pp. 86–87
• The proposed nickel indicator should be computable with low-cost quantum-chemical methods and tested across ortho-, meta-, and para-substituted ligand patterns.The formulation calls for comparing indicator trends across substitutions, rather than relying on a single static value, and for consistency with experimental selectivity.Source: §C.7 · pp. 86–87

C.8.1 Hypothesis for the asymmetric catalysis validation

• An energetic-span hypothesis proposes calculating the full catalytic cycle and comparing diastereomeric pathways to relate turnover kinetics to enantioselectivity.It specifies turnover-frequency calculations, identifying rate-determining states, and including catalyst regeneration at 30 °C with SMD(acetone).Source: §C.8.1 · p. 89
• The asymmetric-catalysis hypothesis proposes comparing diastereomeric C–C bond-forming transition states and validating their structures and connectivity.It specifies M06-2X/6-31G* with SMD(acetone), relative Gibbs energies at 30 °C, frequency checks for one imaginary frequency, and IRC calculations connecting the transition states to the enol intermediate and aldol product.Source: §C.8.1 · p. 90
• A catalyst–substrate hypothesis proposes using conformational sampling, DFT optimization, and non-covalent interaction analysis to explain facial selectivity.The proposed comparisons include binding energies and geometries for diastereomeric complexes, with NCI analysis targeting steric repulsions and hydrogen bonding.Source: §C.8.1 · p. 90
• Additional hypotheses test how a Brønsted acid co-catalyst affects enolization barriers and how solvent polarity changes relative transition-state energies.The proposed tests compare barriers with and without acid and compare acetone solvation with gas-phase and alternative-solvent calculations.Source: §C.8.1 · pp. 90–91
• Compare competing enantiomeric transition states for key enolate–aldehyde bond formation, validating structures and using Gibbs free-energy differences at 30°C to predict enantiomeric excess.The proposed validation checks for a single imaginary frequency and connectivity to reactants and products.Source: §C.8.1 · p. 93
• Pair transition-state-based enantioselectivity prediction with energetic-span analysis of the catalytic cycle to assess turnover frequency, rate-determining states, and catalytic efficiency.The proposed workflow uses high-accuracy energies on optimized geometries and consistent solvation at 30°C, and includes catalyst regeneration.Source: §C.8.1 · p. 94
• Combine transition-state energy evaluation with conformational sampling and non-covalent interaction analysis of pre-reactive complexes to relate catalyst binding to enantiocontrol.The proposed analysis seeks to connect complex stability with transition-state energies.Source: §C.8.1 · p. 96
• An integrated transition-state strategy pairs Gibbs-energy-based enantioselectivity prediction with conformational sampling and noncovalent-interaction analysis to explain enantiocontrol.The proposed interactions include hydrogen bonding, steric effects, and dispersion.Source: §C.8.1 · p. 97
• The catalytic-cycle strategy computes intermediate and transition-state Gibbs energies at 30°C, uses energetic-span analysis to identify rate-determining states and turnover frequencies, and tests enantiomeric-excess predictions against experiments.Competing diastereomeric transition states are analyzed for the stereoselective bond-forming step.Source: §C.8.1 · p. 98
• The hybrid solvation strategy compares diastereomeric transition-state Gibbs energies at 30°C and uses solvation models to separate electrostatic from non-electrostatic contributions.The comparisons are intended to predict enantiomeric excess and clarify the origins of stereoselectivity.Source: §C.8.1 · p. 98
• A benchmarked screening strategy combines efficient geometry optimization with high-accuracy energy calculations, validation against higher-level methods and experimental enantiomeric excess, and routine screening efficiency.Source: §C.8.1 · p. 98

C.8.2 Hypothesis for the radical reaction validation

• The ionic alternative tests whether Cs2CO3 deprotonates HPPh2 to a phosphide that substitutes at the α-BPin carbon, evaluating the combined deprotonation and substitution free-energy cost.Source: §C.8.2 · pp. 99–100
• A ground-state concerted SN2 displacement by HPPh2 was proposed, with a DFT transition state and IRC used to assess connectivity and whether its barrier permits reaction under mild photochemical conditions.The proposed test compares the barrier with a typical room-temperature thermal barrier of less than 25 kcal/mol; an unreasonably high barrier would disfavor this pathway.Source: §C.8.2 · p. 101
• A stepwise radical-chain proposal has HPPh2 transfer hydrogen to an α-boryl radical; an exergonic HAT step with a barrier below 10 kcal/mol would support propagation.The proposal identifies P–I bond formation as the chain-terminating step.Source: §C.8.2 · p. 102
• A further initiation hypothesis considers electron transfer from HPPh2 to photoexcited substrate; a negative estimated SET free-energy change with driving force above approximately 0.1 eV would make it plausible.Source: §C.8.2 · p. 102
• An alternative radical pathway proposes 450 nm C–I homolysis to an α-boryl-stabilized radical, followed by H-atom transfer from HPPh2 and iodine recombination to form IPPh2.The proposed calculations compare excitation energies with the 450 nm photon energy of approximately 2.75 eV and assess the C–I bond dissociation energy.Source: §C.8.2 · p. 103
• A stepwise iodine-atom-transfer pathway proposes that a P-centered radical abstracts iodine from the substrate, yielding IPPh2 and an alkyl radical; a strongly exergonic, low-barrier transfer would support it.Source: §C.8.2 · p. 104
• A base-assisted SET alternative proposes that electron transfer to the α-iodoboronate forms a radical anion that fragments into an α-boryl radical and iodide.The proposed calculations compare substrate reduction and donor oxidation potentials and evaluate the radical-anion fragmentation barrier and reaction free energy.Source: §C.8.2 · p. 105
• A light-initiated radical pathway proposes C–I homolysis of the α-iodoboronate followed by HAT from HPPh2, producing the reduced alkyl product and a phosphorus-centered radical.The proposed tests assess 450 nm excitation, C–I bond dissociation in ground and excited states, and the energetics of P–H cleavage and P–I formation.Source: §C.8.2 · p. 107
• Nonradical alternatives considered include phosphide SN2 displacement and concerted P–H/C–I bond metathesis; an excited-state concerted HAT/IAT pathway was also proposed.The proposed computations examine transition-state barriers and connectivity for ionic pathways, and whether excited-state surfaces permit synchronous hydrogen- and iodine-atom transfer.Source: §C.8.2 · pp. 107–109
• An iodine-atom-transfer alternative proposes that a P-centered radical abstracts iodine from the substrate, generating an α-boryl radical for subsequent product formation.The proposed test calculates XAT thermodynamics and its activation barrier using open-shell DFT.Source: §C.8.2 · p. 108
• The proposed EDA/SRN1 radical chain discounts direct substrate excitation (∼102.5 kcal/mol versus ∼63.5 kcal/mol for 450 nm light) and invokes charge-transfer excitation, SET, C–I cleavage, and HAT.The proposed sequence generates a carbon radical, iodide, and a phosphorus-centered radical; the carbon radical abstracts hydrogen from HPPh2.Source: §C.8.2 · pp. 109–110
• Another proposal invokes a cesium-associated activation complex that polarizes the C–I bond and lowers excitation energy into reach of 450 nm light.After excitation, cleavage is proposed to generate a β-boryl radical that abstracts hydrogen from HPPh2; the phosphorus-derived radicals can dimerize.Source: §C.8.2 · p. 110
• A ground-state ionic substitution is considered a competing control, but visible-light dependence and formation of the phosphorus dimer make it unlikely to be the dominant pathway.The proposed calculation would test whether its thermal substitution barrier is prohibitive and whether it can explain those experimental features.Source: §C.8.2 · p. 111
• A proposed radical chain uses a phosphorus-centered radical for iodine-atom transfer, then hydrogen-atom transfer from HPPh2 forms product and regenerates the phosphorus radical.Coupling of phosphorus-centered radicals is proposed to yield Ph2P-PPh2 and terminate the chain; only initiation need be photochemical.Source: §C.8.2 · p. 111
• A distinct photochemical alternative proposes electron transfer from a phosphide/base aggregate, rather than a simple binary EDA complex, to the alkyl iodide.The resulting radical anion is proposed to fragment to a β-boryl carbon radical, which abstracts hydrogen from HPPh2; phosphorus-derived radicals ultimately dimerize.Source: §C.8.2 · p. 112
• The refined validation plan proposes comparing a concerted SN2-type pathway with a radical-polar crossover sequence to assess which is more feasible.The proposed SN2 test has HPPh2 attack as iodide departs, with proton transfer to the leaving group or a base.Source: §C.8.2 · p. 115
• For radical-chain propagation, the plans calculate HPPh2 P–H dissociation and HAT energetics; an exergonic transfer with a barrier ≤ 8 kcal/mol supports radical-polar crossover relevance.The HAT transition state is to be optimized and verified by IRC.Source: §C.8.2 · p. 115
• A concerted SN2-type pathway is assessed by locating an IRC-verified transition state and comparing its activation free energy with the ∼25 kcal/mol room-temperature feasibility threshold.A barrier substantially above that threshold would argue against a purely concerted pathway under mild photochemical conditions.Source: §C.8.2 · p. 116
• Photochemical radical formation is evaluated by comparing C–I excitation energies with 450 nm light and calculating the C–I bond dissociation energy; a BDE below ∼60 kcal/mol with accessible excited states supports plausibility.The proposed assessment uses TD-DFT for excitation energies and unrestricted DFT for radical stability.Source: §C.8.2 · p. 117
• The proposed workflow evaluates closed-shell concerted substitution alongside open-shell radical pathways under comparable computational conditions to identify which is feasible.The plans include comparing kinetic and thermodynamic profiles to distinguish concerted substitution from radical XAT or related radical routes.Source: §C.8.2 · pp. 118–119
• A complementary plan compares direct C–I homolysis with iodine-atom transfer from a P-centered radical, using excitation energies, bond dissociation energies, and XAT barriers to assess initiation.The proposed comparison relates the C–I dissociation free energy to 2.75 eV photons and evaluates iodine abstraction by the P-centered radical.Source: §C.8.2 · p. 121
• The proposed radical-chain assessment models hydrogen- and iodine-atom transfer and radical recombination, targeting propagation barriers below 10 kcal/mol.It also considers initiation by P–H or solvent C–H homolysis followed by iodine abstraction from the substrate.Source: §C.8.2 · p. 122
• The integrated model tests whether 450 nm photoexcitation, base-assisted SET, or both can generate the same α-boryl radical, potentially explaining reactivity under photoredox–base dual-initiation conditions.The proposed SET analysis evaluates redox feasibility and fragmentation of the radical anion to the α-boryl radical and I−.Source: §C.8.2 · p. 122
• A further workflow tests ground-state SN2-like substitution against radical pathways and probes whether BPin stabilizes anionic charge and lowers the substitution barrier.It proposes optimizing an HPPh2 attack transition state and comparing its barrier with the energy available from 450 nm photons.Source: §C.8.2 · pp. 124–125
• A parallel ionic-pathway test models base-assisted deprotonation of HPPh2 and an SN2 displacement of iodide, then compares its activation barrier with radical-pathway energetics.The proposed transition state is to be confirmed by IRC, with the comparison intended to identify a dominant or coexisting pathway.Source: §C.8.2 · p. 127
• A merged radical-chain proposal combines direct photoexcitation, propagation by P-centered radical iodine-atom transfer, and termination by H-atom recombination with α-boryl radicals.The proposed calculations assess C–I dissociation, P–H and P–I bond energetics, and iodine-atom-transfer energetics.Source: §C.8.2 · p. 128
• The integrated photochemical/SET strategy compares direct C–I photodissociation with photoinduced electron transfer as competing or complementary routes to α-boryl radicals.Its proposed tests include excitation energies for the substrate, HPPh2, and base–HPPh2 adducts, plus ionization potentials and substrate electron affinities to assess SET feasibility.Source: §C.8.2 · pp. 128–129
• An EDA/SRN1-type proposal attributes 450 nm initiation to charge-transfer excitation of a phosphide–substrate complex, followed by radical HAT and phosphine-radical dimerization.The proposal argues that direct substrate excitation requires more energy than the 450 nm photon and that two equivalents of HPPh2 supply the phosphide donor and hydrogen source.Source: §C.8.2 · p. 130
• A reflection-revised alternative proposes that photoexcited PPh2− activates C–I only under illumination, producing a rapidly reacting solvent-caged radical pair without a stable EDA complex or long chain.The proposal identifies PPh2− as the only component with appreciable 450 nm absorption, while allowing a tightly associated encounter complex.Source: §C.8.2 · p. 131
• A halogen-bonded phosphide–substrate exciplex is proposed to undergo photoinduced dissociative electron transfer, followed by cage-controlled hydrogen delivery and phosphorus-radical dimerization.This pathway is proposed to account for strict light dependence and lack of chain behavior through in-cage product formation.Source: §C.8.2 · p. 132
• A photogated PCET hypothesis proposes concerted electron and proton transfer from excited phosphide and an H-source, generating transient carbon-radical character while avoiding long-lived free radicals.It is proposed to explain the base requirement, TEMPO sensitivity, and strict light dependence without requiring a stable EDA band.Source: §C.8.2 · pp. 132–133
• An alternative proposal invokes iodine-assisted intersystem crossing in a photoexcited contact ion pair to reach a C-I-dissociative triplet or open-shell singlet radical-pair surface.The radical pair is hypothesized to remain caged and spin-correlated, suppressing chain propagation while allowing TEMPO interception.Source: §C.8.2 · p. 133
• A proposed boryl-assisted radical-polar crossover converts a transient carbon radical through back-electron transfer or capture and protonation, yielding hydrodeiodination without chain propagation.The hypothesis also links PPh2-PPh2 formation to P-centered radical coupling and associates UV-vis perturbation with ground-state association.Source: §C.8.2 · p. 134

Initial mechanistic hypotheses for the dihedral-based selectivity validation

• Initial nickel hypotheses propose that ortho substitution distorts the Ni coordination geometry or increases its flexibility, reducing the energetic penalty for hydride departure or migration.Proposed indicators include Ni-H out-of-plane dihedral scans, bite-angle energy profiles, and out-of-plane displacement maps.Source: Initial mechanistic hypotheses for the… · pp. 135–137
• Other initial nickel hypotheses suggest ortho substitution could facilitate migration by weakening the Ni-H bond or increasing Br-Ni bond lability.The proposed tests compare Ni-H bond dissociation energies and bond indices, and relaxed Br-Ni stretching energy profiles across ligand variants.Source: Initial mechanistic hypotheses for the… · pp. 136–137
• Other geometric hypotheses linked ortho substitution to greater tetrahedral Ni distortion or smaller bipyridine bite angles, each expected to favor migration over in situ product formation.The proposed indicators were the τ4 geometry index and N–Ni–N bite-angle measurements in optimized complexes.Source: Initial mechanistic hypotheses for the… · pp. 138, 141
• Electronic tests proposed that ortho-methyl donation weakens Ni–H bonding, assessed through NBO occupancy, Wiberg bond indices, and Ni–H bond dissociation free energies.Lower NBO occupancy and Wiberg bond index, and lower Ni–H BDFE, were predicted for ortho-methyl ligands.Source: Initial mechanistic hypotheses for the… · pp. 139, 141
• The leading hypothesis was that ortho-methyl bpy crowds the Ni plane, pre-displacing β-hydride out of plane and lowering its departure barrier, tested by relaxed dihedral scans.The predicted signature was a shallower energy increase for out-of-plane hydride displacement than with unsubstituted or meta-/para-substituted ligands.Source: Initial mechanistic hypotheses for the… · p. 140
• Other proposed explanations include weaker axial-ligand binding that preserves reactive four-coordinate Ni(II), and increased hydride-to-Ni donation in distorted geometries.The latter is proposed to lower migration barriers; the passages describe these as hypotheses and planned computational tests.Source: Initial mechanistic hypotheses for the… · pp. 144–145
• Ortho-substituted bpy is hypothesized to promote migration by making out-of-plane hydride displacement energetically more accessible.The proposed test scans the H-Ni-Br dihedral from planar to ±90° in 5° increments for ortho-, meta-, para-methyl, and unsubstituted bpy complexes, using B3LYP-D3/def2-TZVP with SMD(DMA).Source: Initial mechanistic hypotheses for the… · pp. 145–146

Refined mechanistic hypotheses for the dihedral-based selectivity validation

• The refined hypothesis proposes that ortho substitution changes bpy's natural bite angle, destabilizing ideal square-planar Ni(II) and easing rearrangement to the migratory intermediate.The proposed indicator is the energy change as the N-Ni-N bite angle is varied.Source: Refined mechanistic hypotheses for the… · p. 148
• The proposed mechanism is that ortho-methyl substitution combines steric distortion and increased nitrogen donation to weaken Ni–H bonding and lower the barrier for hydride departure.The proposed indicators are lower Ni–H bond dissociation energy and Wiberg bond index, associated with greater migratory product formation.Source: Refined mechanistic hypotheses for the… · pp. 151–152
• Matched ortho-, meta-, para-, and unsubstituted ligands would be compared using Ni–H dihedral and N–Ni–N bite-angle scans to test for easier hydride displacement and greater coordination flexibility.The predicted signature is a shallower dihedral energy rise and lower bite-angle curvature for ortho-substituted ligands.Source: Refined mechanistic hypotheses for the… · pp. 151–152
• A complementary hypothesis is that ortho-methyl groups increase Br–Ni lability, allowing bromide repositioning or dissociation to assist the migratory rearrangement.Relaxed Ni–H dihedral and Br–Ni elongation scans across substituted and unsubstituted ligands would test for shallower energy rises in both motions.Source: Refined mechanistic hypotheses for the… · p. 153
• A unified one- and two-dimensional scan of Ni–H and Ni–Br motions is proposed to test whether ortho-methyl substitution favors a more flexible, pseudo-tetrahedral coordination geometry.The energy maps would compare distortion penalties and cooperative motions across substituted and unsubstituted bipyridines.Source: Refined mechanistic hypotheses for the… · pp. 150, 153
• A complementary proposal links ortho-methyl-induced Ni–H displacement to altered N–Ni–N bite-angle flexibility, assessed with dihedral and bite-angle energy scans across ligand substitutions.The protocol compares ortho-, meta-, para-, and unsubstituted ligands; shallower dihedral curves and lower bite-angle curvature would indicate joint hydride propensity and angular tolerance.Source: Refined mechanistic hypotheses for the… · pp. 154–155
• A steric–electronic hypothesis proposes that ortho-methyl groups both reduce the penalty for Ni–H displacement and weaken Ni–H bonding, lowering the barrier to hydride departure.Proposed tests pair relaxed dihedral scans with Ni–H bond-dissociation-energy and NBO bond-order analyses.Source: Refined mechanistic hypotheses for the… · p. 155
• Another proposal adds bromide lability: ortho-methyl crowding could facilitate Br–Ni repositioning or dissociation while ligand distortion facilitates hydride departure during migration.Relaxed Ni–H dihedral and Br–Ni elongation scans across ortho-, meta-, para-, and unsubstituted ligands are proposed to test this synergy.Source: Refined mechanistic hypotheses for the… · p. 156
• Ortho-methyl substitution is proposed to distort the Ni complex toward pseudo-tetrahedral geometry, flattening the energy landscape and lowering the hydride-migration barrier.The proposed comparison is between substituted and unsubstituted bipyridines; the passages present this as a hypothesis, not a reported validation result.Source: Refined mechanistic hypotheses for the… · p. 156
• A complementary trans-influence hypothesis proposes that ortho-methyl-induced geometry more strongly elongates and destabilizes Ni–Br, suppressing the in situ pathway.The proposed tests include hydride-dihedral and Ni–H extension scans at B3LYP-D3(BJ)/def2-TZVP with CPCM(DMA) solvation.Source: Refined mechanistic hypotheses for the… · p. 159
• Ortho-methyl substitution is hypothesized to pre-distort Ni–H out of plane and increase cis Br–H repulsion, lowering the hydride-displacement penalty and disfavoring the in situ pathway.The proposed combined effects favor hydride migration; they are presented as a mechanistic hypothesis, not as a reported computational result.Source: Refined mechanistic hypotheses for the… · p. 159
• The refined validation strategy predicts that ortho-substituted ligands will show a shallower hydride-displacement energy profile and greater Br–H repulsion, consistent with migratory-product preference.The proposed comparison uses unsubstituted, ortho-, and control-substituted ligands, relaxed dihedral scans, and BSSE-corrected Br–H interaction calculations.Source: Refined mechanistic hypotheses for the… · pp. 159–160

Refined computational workflow for the asymmetric catalysis validation

• For asymmetric catalysis, the workflow generates initial transition-state guesses for both enantiomeric C–C bond-forming pathways and converts the structures into Gaussian input files.The file-generation step assigns both pathways the same default charge and multiplicity.Source: Refined computational workflow for the… · pp. 163–164
• The workflow then performs Gaussian transition-state optimization and frequency calculations for both enantiomers using a generated high-accuracy composite DFT/coupled-cluster route.The initial guesses are treated as close to the true transition states, without detailed reorganization of the catalyst–substrate hydrogen-bonding network.Source: Refined computational workflow for the… · pp. 163–165
• IRC calculations validate a transition state when one trajectory reaches a chemically plausible minimum, even if the opposite side terminates prematurely or reaches a related hydrogen-bonded arrangement.The intended connectivity is to reactants and products; the opposite side need not reach the exact expected structure.Source: Refined computational workflow for the… · p. 166
• High-level single-point electronic energies rank the enantiomeric pathways, with entropic contributions assumed negligible because their transition states are structurally similar.The workflow proposes a more accurate single-point method after transition-state optimization and frequency calculations.Source: Refined computational workflow for the… · pp. 167–168
• At 30°C, Gibbs free-energy barriers are calculated from frequency data and single-point energies, and their difference is used to compute the predicted enantiomeric excess.The calculation compares the competing transition-state pathways.Source: Refined computational workflow for the… · p. 168
• Initial transition-state guesses are generated for both enantiomeric C-C bond-forming pathways, then optimized and frequency-checked; acceptable structures converge cleanly and may have one small or no imaginary frequency.Flat regions of the asymmetric catalytic surface can make a transition state numerically resemble a minimum.Source: Refined computational workflow for the… · pp. 165, 169
• The refined asymmetric-catalysis workflow reports ΔG‡ values for both enantiomeric pathways and predicted ee%.The supplied passages identify these as workflow outputs, not computed results.Source: Refined computational workflow for the… · p. 172

Initial Workflow for the photochemical radical reaction validation

• The initial radical workflow treated the lowest-energy contact-ion-pair conformer as most reactive, without considering alternative ion-pair arrangements.Initial complexes included Cs2CO3 or Ph2P− species and HPPh2 hydrogen-bonding motifs.Source: Initial Workflow for the photochemical… · pp. 172–173
• The initial workflow generated transition-state guesses by linear interpolation and accepted structures based on zero or one small imaginary frequency and partial C-I bond involvement.The interpolated guess did not explicitly account for radical spin density or charge separation.Source: Initial Workflow for the photochemical… · pp. 176–177

Refined Workflow for the photochemical radical reaction validation

• The refined radical workflow preserves ion-pair contacts through atom mapping, then calculates binding energies and excited-state properties for optimized complexes.It uses quasi-RRHO thermochemical corrections for binding energies and examines excitation energies, oscillator strengths, and state-dependent dipole moments for possible exciplex states.Source: Refined Workflow for the photochemical… · pp. 179–180
• The refined workflow generates simulated UV-Vis spectra from TD-DFT results and compares them with experiment to identify bleaching and non-additive spectral behavior.The initial workflow instead treated a match in the lowest excitation energy as sufficient evidence for a reactive excited state, without considering state character or orbital contributions.Source: Initial Workflow for the photochemical… · p. 175, Refined Workflow for the photochemical… · p. 181
• The radical workflow generates transition-state guesses by interpolating mapped C–I cleavage and P–H transfer coordinates, then checks optimized structures for convergence, one imaginary frequency, and the target mode.Source: Refined Workflow for the photochemical… · p. 182
• Forward and reverse IRC calculations, endpoint optimization, and thermochemical corrections establish connected reactant- and product-side minima and Gibbs energies.Source: Refined Workflow for the photochemical… · pp. 183–184

Initial workflow for the dihedral-based selectivity validation

• The Ni(II) series covers unsubstituted and ortho-, meta-, and para-methyl bipyridines, assuming square-planar complexes and a neutral singlet state without further spin-state or coordination validation.Source: Initial workflow for the… · p. 185
• Relaxed H–N–N–Br scans use ωB97XD/def2-SVP with SMD(DMA), but accept any SCF solution and compare raw curves despite unchecked state or minimum equivalence and differing basins.Source: Initial workflow for the… · pp. 186–188
• The initial workflow treated the energy-rise slope in dihedral scans as a proxy for product ratio, hypothesizing that ortho-methyl ligands favor migratory products through a shallower rise.The passage notes that this proxy was used without additional transition-state or full-pathway validation.Source: Initial workflow for the… · p. 189

Refined workflow for the dihedral-based selectivity validation

• The refined workflow proposed relaxed Ni-H dihedral scans from 0° to 60° with SMD(DMA) solvation, comparing unsubstituted and ortho-, meta-, and para-methyl bipyridines.The workflow analyzes energy-rise rates against experimental selectivity to test whether ortho-methyl ligands favor migratory products.Source: Refined workflow for the… · pp. 190, 191, 193

C.10 Supplementary Information for Quantum Chemical Calculations

• Three machine-readable JSON files, case1.json through case3.json, contain Gaussian-log data parsed with cclib for transparent inspection and downstream reanalysis.The parsed molecular objects include geometry, electronic energies, thermochemical quantities, and excited-state properties.Source: §C.10 · pp. 193–194